This application is related to U.S. patent application Ser. No. 10/190,805 filed Jul. 8, 2002, now U.S. Pat. No. 6,758,089, U.S. patent application Ser. No. 13/854,099 filed Mar. 31, 2013, and U.S. patent application Ser. No. 11/968,736, now U.S. Pat. No. 8,410,945, on the grounds that they include common subject matter.
All of the references, patents and patent applications that are referred to herein are incorporated by reference in their entirety as if they had each been set forth herein in full. Note that this application is one in a series of applications covering safety and other systems for vehicles and other uses. The disclosure herein goes beyond that needed to support the claims of the particular invention set forth herein. This is not to be construed that the inventor is thereby releasing the unclaimed disclosure and subject matter into the public domain. Rather, it is intended that patent applications have been or will be filed to cover all of the subject matter disclosed below and in the current assignee's granted and pending applications. Also please note that the terms frequently used below “the invention” or “this invention” is not meant to be construed that there is only one invention being discussed. Instead, when the terms “the invention” or “this invention” are used, it is referring to the particular invention being discussed in the paragraph where the term is used.
The present invention relates generally to monitoring arrangements and methods using vehicles.
A detailed background of the invention is found in the parent applications.
The definitions set forth in section 5.0 of the Background of the Invention section of the '139 application are also incorporated by reference herein.
All of the patents, patent applications, technical papers and other references referenced in the '139 application and herein are incorporated herein by reference in their entirety.
A monitoring arrangement and method including vehicles, a locating system in each vehicle that provides location data about the vehicle, a sensor system in each vehicle that detects presence of at least one chemical in the air at a location at which the vehicle is situated when the sensor system is analyzing air, and a monitoring facility. Each vehicle also includes a communication system that generates a signal based on data provided by the sensor system about the detected presence of at least one chemical in the air and a signal based on the location data and directs the signals to the monitoring facility. Data provided by the sensor systems and sent via the communication systems is analyzed at the monitoring facility in association with location data about the vehicles determined by the locating systems.
The following drawings are illustrative of embodiments of the systems developed or adapted using the teachings of these inventions and are not meant to limit the scope of the invention as encompassed by the claims.
The output of a diagnostic system is generally the present condition of the vehicle or component. However the vehicle operator wants to repair the vehicle or replace the component before it fails, but a diagnosis system in general does not specify when that will occur. Prognostics is the process of determining when the vehicle or a component will fail. At least one of the inventions disclosed herein in concerned with prognostics. Prognostics can be based on models of vehicle or component degradation and the effects of environment and usage. In this regard it is useful to have a quantitative formulation of how the component degradation depends on environment, usage and current component condition. This formulation may be obtained by monitoring condition, environment and usage level, and by modeling the relationships with statistical techniques or pattern recognition techniques such as neural networks, combination neural networks and fuzzy logic. In some cases, it can also be obtained by theoretical methods or from laboratory experiments.
A preferred embodiment of the vehicle diagnostic and prognostic unit described below performs the diagnosis and prognostics, i.e., processes the input from the various sensors, on the vehicle using, for example, a processor embodying a pattern recognition technique such as a neural network. The processor thus receives data or signals from the sensors and generates an output indicative or representative of the operating conditions of the vehicle or its component. A signal could thus be generated indicative of an under-inflated tire, or an overheating engine.
The term “component” as used herein generally refers to any part or assembly of parts which is mounted to or a part of a motor vehicle and which is capable of emitting a signal representative of its operating state.
The term “sensor” as used herein generally refers to any measuring, detecting or sensing device mounted on a vehicle or any of its components including new sensors mounted in conjunction with the diagnostic module in accordance with the invention.
The term “signal” as used herein generally refers to any time-varying output from a component including electrical, acoustic, thermal, electromagnetic radiation or mechanical vibration.
Sensors on a vehicle are generally designed to measure particular parameters of particular vehicle components. However, frequently these sensors also measure outputs from other vehicle components. For example, electronic airbag crash sensors currently in use contain one or more accelerometers for determining the accelerations of the vehicle structure so that the associated electronic circuitry of the airbag crash sensor can determine whether a vehicle is experiencing a crash of sufficient magnitude so as to require deployment of the airbag. This or these accelerometers continuously monitors the vibrations in the vehicle structure regardless of the source of these vibrations. If a wheel is out of balance, or if there is extensive wear of the parts of the front wheel mounting assembly, or wear in the shock absorbers, the resulting abnormal vibrations or accelerations can, in many cases, be sensed by a crash sensor accelerometer. There are other cases, however, where the sensitivity or location of an airbag crash sensor accelerometer is not appropriate and one or more additional accelerometers or gyroscopes may be mounted onto a vehicle for the purposes of this invention. Some airbag crash sensors are not sufficiently sensitive accelerometers or have sufficient dynamic range for the purposes herein.
For example, a technique for some implementations of an invention disclosed herein is the use of multiple accelerometers and/or microphones that will allow the system to locate the source of any measured vibrations based on the time of flight, time of arrival, direction of arrival and/or triangulation techniques. Once a distributed accelerometer installation, or one or more IMUs, has been implemented to permit this source location, the same sensors can be used for smarter crash sensing as it can permit the determination of the location of the impact on the vehicle. Once the impact location is known, a highly tailored algorithm can be used to accurately forecast the crash severity making use of knowledge of the force vs. crush properties of the vehicle at the impact location.
Every component of a vehicle can emit various signals during its life. These signals can take the form of electromagnetic radiation, acoustic radiation, thermal radiation, vibrations transmitted through the vehicle structure and voltage or current fluctuations, depending on the particular component. When a component is functioning normally, it may not emit a perceptible signal. In that case, the normal signal is no signal, i.e., the absence of a signal. In most cases, a component will emit signals that change over its life and it is these changes which typically contain information as to the state of the component, e.g., whether failure of the component is impending. Usually components do not fail without warning. However, most such warnings are either not perceived or if perceived, are not understood by the vehicle operator until the component actually fails and, in some cases, a breakdown of the vehicle occurs.
An important system and method as disclosed herein for acquiring data for performing the diagnostics, prognostics and health monitoring functions makes use of the acoustic transmissions from various components. This can involve the placement of one or more microphones, accelerometers, or other vibration sensors onto and/or at a variety of locations within the vehicle where the sound or vibrations are most effectively sensed. In addition to acquiring data relative to a particular component, the same sensors can also obtain data that permits analysis of the vehicle environment. A pothole, for example, can be sensed and located for possible notification to a road authority if a location determining apparatus is also resident on the vehicle.
In a few years, it is expected that various roadways will have systems for automatically guiding vehicles operating thereon. Such systems have been called “smart highways” and are part of the field of intelligent transportation systems (ITS). If a vehicle operating on such a smart highway were to breakdown due to the failure of a component, serious disruption of the system could result and the safety of other users of the smart highway could be endangered.
When a vehicle component begins to change its operating behavior, it is not always apparent from the particular sensors which are monitoring that component, if any. The output from any one of these sensors can be normal even though the component is failing. By analyzing the output of a variety of sensors, however, the pending failure can frequently be diagnosed. For example, the rate of temperature rise in the vehicle coolant, if it were monitored, might appear normal unless it were known that the vehicle was idling and not traveling down a highway at a high speed. Even the level of coolant temperature which is in the normal range could be in fact abnormal in some situations signifying a failing coolant pump, for example, but not detectable from the coolant thermometer alone.
The pending failure of some components is difficult to diagnose and sometimes the design of the component requires modification so that the diagnosis can be more readily made. A fan belt, for example, frequently begins failing as a result of a crack of the inner surface. The belt can be designed to provide a sonic or electrical signal when this cracking begins in a variety of ways. Similarly, coolant hoses can be designed with an intentional weak spot where failure will occur first in a controlled manner that can also cause a whistle sound as a small amount of steam exits from the hose. This whistle sound can then be sensed by a general purpose microphone, for example.
In
In addition, various other sensors 48, 49 measure other parameters of other components that in some manner provide information directly or indirectly on the operation of component 35. Each of the sensors illustrated in
The diagnostic module 51 will analyze the received data in light of the data values or patterns itself either statically or over time. In some cases, a pattern recognition algorithm as discussed below will be used and in others, a deterministic algorithm may also be used either alone or in combination with the pattern recognition algorithm. Additionally, when a new data value or sequence is discovered the information can be sent to an off-vehicle location, perhaps a dealer or manufacturer site, and a search can be made for other similar cases and the results reported back to the vehicle. Also additionally as more and more vehicles are reporting cases that perhaps are also examined by engineers or mechanics, the results can be sent to the subject vehicle or to all similar vehicles and the diagnostic software updated automatically. Thus, all vehicles can have the benefit from information relative to performing the diagnostic function. Similarly, the vehicle dealers and manufacturers can also have up-to-date information as to how a particular class or model of vehicle is performing. This telematics function is discussed in more detail elsewhere herein. By means of this system, a vehicle diagnostic system can predict component failures long before they occur and thus prevent on-road problems.
An important function that can be performed by the diagnostic system herein is to substantially diagnose the vehicle's own problems rather then, as is the case with the prior art, forwarding raw data to a central site for diagnosis. Eventually, a prediction as to the failure point of all significant components can be made and the owner can have a prediction that the fan belt will last another 20,000 miles, or that the tires should be rotated in 2,000 miles or replaced in 20,000 miles. This information can be displayed or reported orally or sent to the dealer who can then schedule a time for the customer to visit the dealership or for the dealer to visit the vehicle wherever it is located. If it is displayed, it can be automatically displayed periodically or when there is urgency or whenever the operator desires. The display can be located at any convenient place such as the dashboard or it can be a heads-up display. The display can be any convenient technology such as an LCD display or an OLED based display. This can permit the vehicle manufacturer to guarantee that the owner will never experience a vehicle breakdown provided he or she permits the dealer to service the vehicle at appropriate times based on the output of the prognostics system.
It is worth emphasizing that in many cases, it is the rate that a parameter is changing that can be as or more important than the actual value in predicting when a component is likely to fail. In a simple case when a tire is losing pressure, for example, it is a quite different situation if it is losing one psi per day or one psi per minute. Similarly for the tire case, if the tire is heating up at one degree per hour or 100 degrees per hour may be more important in predicting failure due to delamination or overloading than the particular temperature of the tire.
The diagnostic module, or other component, can also consider situation awareness factors such as the age or driving habits of the operator, the location of the vehicle (e.g., is it in the desert, in the arctic in winter), the season, the weather forecast, the length of a proposed trip, the number and location of occupants of the vehicle etc. The system may even put limits on the operation of the vehicle such as turning off unnecessary power consuming components if the alternator is failing or limiting the speed of the vehicle if the driver is an elderly woman sitting close to the steering wheel, for example. Furthermore, the system may change the operational parameters of the vehicle such as the engine RPM or the fuel mixture if doing so will prolong vehicle operation. In some cases where there is doubt whether a component is failing, the vehicle operating parameters may be temporarily varied by the system in order to accentuate the signal from the component to permit more accurate diagnosis.
In addition to the above discussion there are some diagnostic features already available on some vehicles some of which are related to the federally mandated OBD-II and can be included in the general diagnostics and health monitoring features of this invention. In typical applications, the set of diagnostic data includes at least one of the following: diagnostic trouble codes, vehicle speed, fuel level, fuel pressure, miles per gallon, engine RPM, mileage, oil pressure, oil temperature, tire pressure, tire temperature, engine coolant temperature, intake-manifold pressure, engine-performance tuning parameters, alarm status, accelerometer status, cruise-control status, fuel-injector performance, spark-plug timing, and a status of an anti-lock braking system.
The data parameters within the set describe a variety of electrical, mechanical, and emissions-related functions in the vehicle. Several of the more significant parameters from the set are:
Pending DTCs (Diagnostic Trouble Codes)
Ignition Timing Advance
Calculated Load Value
Air Flow Rate MAF Sensor
Engine RPM
Engine Coolant Temperature
Intake Air Temperature
Absolute Throttle Position Sensor
Vehicle Speed
Short-Term Fuel Trim
Long-Term Fuel Trim
MIL Light Status
Oxygen Sensor Voltage
Oxygen Sensor Location
Delta Pressure Feedback EGR Pressure Sensor
Evaporative Purge Solenoid Duty cycle
Fuel Level Input Sensor
Fuel Tank Pressure Voltage
Engine Load at the Time of Misfire
Engine RPM at the Time of Misfire
Throttle Position at the Time of Misfire
Vehicle Speed at the Time of Misfire
Number of Misfires
Transmission Fluid Temperature
PRNDL position (1, 2, 3, 4, 5=neutral, 6=reverse) Number of Completed OBDII Trips, and
Battery Voltage.
When the diagnostic system determines that the operator is operating the vehicle in such a manner that the failure of a component is accelerated, then a warning can be issued to the operator. For example, the driver may have inadvertently placed the automatic gear shift lever in a lower gear and be driving at a higher speed than he or she should for that gear. In such a case, the driver can be notified to change gears.
Managing the diagnostics and prognostics of a complex system has been termed “System Health Management” and has not been applied to over the road vehicles such as trucks and automobiles. Such systems are used for fault detection and identification, failure prediction (estimating the time to failure), tracking degradation, maintenance scheduling, error correction in the various measurements which have been corrupted and these same tasks are applicable here.
Various sensors, both wired and wireless, will be discussed below. Representative of such sensors are those available from Honeywell which are MEMS-based sensors for measuring temperature, pressure, acoustic emission, strain, and acceleration. The devices are based on resonant microbeam force sensing technology. Coupled with a precision silicon microstructure, the resonant microbeams provide a high sensitivity for measuring inertial acceleration, inclination, and vibrations. Alternate designs based on SAW technology lend themselves more readily to wireless and powerless operation as discussed below. The Honeywell sensors can be networked wirelessly but still require power.
Since this system is independent of the dedicated sensor monitoring system and instead is observing more than one sensor, inconsistencies in sensor output can be detected and reported indicating the possible erratic or inaccurate operation of a sensor even if this is intermittent (such as may be caused by a lose wire) thus essentially eliminating many of the problems reported in the above-referenced article “What's Bugging the High-Tech Car”. Furthermore, the software can be independent of the vehicle specific software for a particular sensor and system and can further be based on pattern recognition, to be discussed next, rendering it even less likely to provide the wrong diagnostic. Since the output from the diagnostic and prognostic system herein described can be sent via telematics to the dealer and vehicle manufacturer, the occurrence of a sensor or system failure can be immediately logged to form a frequency of failure log for a particular new vehicle model allowing the manufacturer to more quickly schedule a recall if a previously unknown problem surfaces in the field.
In accordance with at least one invention, each of the signals emitted by the sensors can be converted into electrical signals and then digitized (i.e., the analog signal is converted into a digital signal) to create numerical time series data which is entered into a processor. Pattern recognition algorithms can be applied by the processor to attempt to identify and classify patterns in this time series data. For a particular component, such as a tire for example, the algorithm attempts to determine from the relevant digital data whether the tire is functioning properly or whether it requires balancing, additional air, or perhaps replacement.
Frequently, the data entered into the pattern recognition algorithm needs to be preprocessed before being analyzed. The data from a wheel speed sensor, for example, might be used “as is” for determining whether a particular tire is operating abnormally in the event it is unbalanced, whereas the integral of the wheel speed data over a long time period (a preprocessing step), when compared to such sensors on different wheels, might be more useful in determining whether a particular tire is going flat and therefore needs air. This is the basis of some tire monitors now on the market. Such indirect systems are not permitted as a means for satisfying federal safety requirements. These systems generally depend on the comparison of the integral of the wheel speed to determine the distance traveled by the wheel surface and that system is then compared with other wheels on the vehicle to determine that one tire has relatively less air than another. Of course this system fails if all of the tires have low pressure. One solution is to compare the distance traveled by a wheel with the distance that it should have traveled. If the angular motion (displacement and/or velocity) of the wheel axle is known, than this comparison can be made directly. Alternately, if the position of the vehicle is accurately monitored so that the actual travel along its path can be determined through a combination of GPS and an IMU, for example, then again the pressure within a vehicle tire can be determined.
In some cases, the frequencies present in a set of data are a better predictor of component failures than the data itself. For example, when a motor begins to fail due to worn bearings, certain characteristic frequencies began to appear. In most cases, the vibrations arising from rotating components, such as the engine, will be normalized based on the rotational frequency. Moreover, the identification of which component is causing vibrations present in the vehicle structure can frequently be accomplished through a frequency analysis of the data. For these cases, a Fourier transformation of the data can be made prior to entry of the data into a pattern recognition algorithm. Wavelet transforms and other mathematical transformations are also made for particular pattern recognition purposes in practicing the teachings of this invention. Some of these include shifting and combining data to determine phase changes for example, differentiating the data, filtering the data and sampling the data. Also, there exist certain more sophisticated mathematical operations that attempt to extract or highlight specific features of the data. The inventions herein contemplate the use of a variety of these preprocessing techniques and the choice of which one or ones to use is left to the skill of the practitioner designing a particular diagnostic and prognostic module. Note, whenever diagnostics is used below it will be assumed to also include prognostics.
As shown in
Important to some embodiments of the inventions herein is the manner in which the diagnostic module 51 determines a normal pattern from an abnormal pattern and the manner in which it decides what data to use from the vast amount of data available. This can be accomplished using pattern recognition technologies such as artificial neural networks and training and in particular, combination neural networks as described in U.S. patent application Ser. No. 10/413,426 (Publication 20030209893). The neural network pattern recognition technology is one of the most developed of pattern recognition technologies. The invention described herein frequently uses combinations of neural networks to improve the pattern recognition process, as discussed in detail in U.S. patent application Ser. No. 10/413,426.
The neural network pattern recognition technology is one of the most developed of pattern recognition technologies. The neural network will be used here to illustrate one example of a pattern recognition technology but it is emphasized that this invention is not limited to neural networks. Rather, the invention may apply any known pattern recognition technology including various segmentation techniques, sensor fusion and various correlation technologies. In some cases, the pattern recognition algorithm is generated by an algorithm-generating program and in other cases, it is created by, e.g., an engineer, scientist or programmer. A brief description of a particular simple example of a neural network pattern recognition technology is set forth below.
Neural networks are constructed of processing elements known as neurons that are interconnected using information channels called interconnects and are arranged in a plurality of layers. Each neuron can have multiple inputs but generally only one output. Each output however is usually connected to many, frequently all, other neurons in the next layer. The neurons in the first layer operate collectively on the input data as described in more detail below. Neural networks learn by extracting relational information from the data and the desired output. Neural networks have been applied to a wide variety of pattern recognition problems including automobile occupant sensing, speech recognition, optical character recognition and handwriting analysis.
To train a neural network, data is provided in the form of one or more time series that represents the condition to be diagnosed, which can be induced to artificially create an abnormally operating component, as well as normal operation. In the training stage of the neural network or other type of pattern recognition algorithm, the time series data for both normal and abnormal component operation is entered into a processor which applies a neural network-generating program to output a neural network capable of determining abnormal operation of a component.
As an example, the simple case of an out-of-balance tire will be used. Various sensors on the vehicle can be used to extract information from signals emitted by the tire such as an accelerometer, a torque sensor on the steering wheel, the pressure output of the power steering system, a tire pressure monitor or tire temperature monitor. Other sensors that might not have an obvious relationship to tire unbalance (or imbalance) are also included such as, for example, the vehicle speed or wheel speed that can be determined from the anti-lock brake (ABS) system. Data is taken from a variety of vehicles where the tires were accurately balanced under a variety of operating conditions also for cases where varying amounts of tire unbalance was intentionally introduced. Once the data had been collected, some degree of pre-processing (e.g., time or frequency modification) and/or feature extraction is usually performed to reduce the total amount of data fed to the neural network-generating program. In the case of the unbalanced tire, the time period between data points might be selected such that there are at least ten data points per revolution of the wheel. For some other application, the time period might be one minute or one millisecond.
Once the data has been collected, it is processed by the neural network-generating program, for example, if a neural network pattern recognition system is to be used. Such programs are available commercially, e.g., from NeuralWare of Pittsburgh, Pa. or from International Scientific Research, Inc., of Panama for modular neural networks. The program proceeds in a trial and error manner until it successfully associates the various patterns representative of abnormal behavior, an unbalanced tire in this case, with that condition. The resulting neural network can be tested to determine if some of the input data from some of the sensors, for example, can be eliminated. In this manner, the engineer can determine what sensor data is relevant to a particular diagnostic problem. The program then generates an algorithm that is programmed onto a microprocessor, microcontroller, neural processor, FPGA, or DSP (herein collectively referred to as a microprocessor or processor). Such a microprocessor appears inside the diagnostic module 51 in
Once trained, the neural network, as represented by the algorithm, is installed in a processor unit of a motor vehicle and will now recognize an unbalanced tire on the vehicle when this event occurs. At that time, when the tire is unbalanced, the diagnostic module 51 will receive output from the sensors, determine whether the output is indicative of abnormal operation of the tire, e.g., lack of tire balance, and instruct or direct another vehicular system to respond to the unbalanced tire situation. Such an instruction may be a message to the driver indicating that the tire should now be balanced, as described in more detail below. The message to the driver is provided by an output device coupled to or incorporated within the module 51, e.g., an icon or text display, and may be a light on the dashboard, a vocal tone or any other recognizable indication apparatus. A similar message may also be sent to the dealer, vehicle manufacturer or other repair facility or remote facility via a communications channel between the vehicle and the dealer or repair facility which is established by a suitable transmission device.
A diagram of one example of a neural network used for diagnosing an unbalanced tire, for example, based on the teachings of this invention is shown in
Each of the input nodes is usually connected to each of the second layer nodes, h-1, h-2, . . . , h-n, called the hidden layer, either electrically as in the case of a neural computer, or through mathematical functions containing multiplying coefficients called weights, in the manner described in more detail in the above references. At each hidden layer node, a summation occurs of the values from each of the input layer nodes, which have been operated on by functions containing the weights, to create a node value. Similarly, the hidden layer nodes are, in a like manner, connected to the output layer node(s), which in this example is only a single node 0 representing the decision to notify the driver, and/or a remote facility, of the unbalanced tire. During the training phase, an output node value of 1, for example, is assigned to indicate that the driver should be notified and a value of 0 is assigned to not notifying the driver. Once again, the details of this process are described in above-referenced texts and will not be presented in detail here.
In the example above, twenty input nodes were used, five hidden layer nodes and one output layer node. In this example, only one sensor was considered and accelerations from only one direction were used. If other data from other sensors such as accelerations from the vertical or lateral directions were also used, then the number of input layer nodes would increase. Again, the theory for determining the complexity of a neural network for a particular application has been the subject of many technical papers and will not be presented in detail here. Determining the requisite complexity for the example presented here can be accomplished by those skilled in the art of neural network design. Also one particular preferred type of neural network has been discussed. Many other types exist as discussed in the above references and the inventions herein is not limited to the particular type discussed here.
The particular neural network described and illustrated above contains a single series of hidden layer nodes. In some network designs, more than one hidden layer is used, although only rarely will more than two such layers appear. There are of course many other variations of the neural network architecture illustrated above which appear in the referenced literature. For the purposes herein, therefore, “neural network” can be defined as a system wherein the data to be processed is separated into discrete values which are then operated on and combined in at least a two stage process and where the operation performed on the data at each stage is in general different for each discrete value and where the operation performed is at least determined through a training process. A different operation here is meant any difference in the way that the output of a neuron is treated before it is inputted into another neuron such as multiplying it by a different weight or constant.
The implementation of neural networks can take on at least two forms, an algorithm programmed on a digital microprocessor, FPGA, DSP or in a neural computer (including a cellular neural network or support vector machine). In this regard, it is noted that neural computer chips are now becoming available.
During the training process, the pattern recognition program sorts out from the available vehicle data on the data bus or from other sources, those patterns that predict failure of a particular component. If more than one sensor is used to sense the output from a component, such as two spaced-apart microphones or acceleration sensors, then the location of the component can sometimes be determined by triangulation based on the phase difference, time of arrival and/or angle of arrival of the signals to the different sensors. In this manner, a particular vibrating tire can be identified, for example. Since each tire on a vehicle does not always make the same number of revolutions in a given time period, a tire can be identified by comparing the wheel sensor output with the vibration or other signal from the tire to identify the failing tire. The phase of the failing tire will change relative to the other tires, for example. This technique can also be used to associate a tire pressure monitor RF signal with a particular tire. An alternate method for tire identification makes use of an RFID tag or an RFID switch as discussed below.
In
Note, where applicable in one or more of the inventions disclosed herein, any form of wireless communication is contemplated for intra vehicle communications between various sensors and components including amplitude modulation, frequency modulation, TDMA, CDMA, spread spectrum, ultra wideband and all variations. Similarly, all such methods are also contemplated for vehicle-to-vehicle or vehicle-to-infrastructure communication.
Sensor 1 is a crash sensor having an accelerometer (alternately one or more dedicated accelerometers or IMUs 31 can be used), sensor 2 is represents one or more microphones, sensor 3 is a coolant thermometer, sensor 4 is an oil pressure sensor, sensor 5 is an oil level sensor, sensor 6 is an air flow meter, sensor 7 is a voltmeter, sensor 8 is an ammeter, sensor 9 is a humidity sensor, sensor 10 is an engine knock sensor, sensor 11 is an oil turbidity sensor, sensor 12 is a throttle position sensor, sensor 13 is a steering torque sensor, sensor 14 is a wheel speed sensor, sensor 15 is a tachometer, sensor 16 is a speedometer, sensor 17 is an oxygen sensor, sensor 18 is a pitch/roll sensor, sensor 19 is a clock, sensor 20 is an odometer, sensor 21 is a power steering pressure sensor, sensor 22 is a pollution sensor, sensor 23 is a fuel gauge, sensor 24 is a cabin thermometer, sensor 25 is a transmission fluid level sensor, sensor 26 is a yaw sensor, sensor 27 is a coolant level sensor, sensor 28 is a transmission fluid turbidity sensor, sensor 29 is brake pressure sensor and sensor 30 is a coolant pressure sensor. Other possible sensors include a temperature transducer, a pressure transducer, a liquid level sensor, a flow meter, a position sensor, a velocity sensor, a RPM sensor, a chemical sensor and an angle sensor, angular rate sensor or gyroscope.
Many sensors are now in vehicles and many more will be installed in vehicles. The following disclosure is primarily concerned with wireless sensors which can be based on MEMS, SAW and/or RFID technologies. Vehicle sensors include tire pressure, temperature and acceleration monitoring sensors; weight or load measuring sensors; switches; vehicle temperature, acceleration, angular position, angular rate, angular acceleration sensors; proximity; rollover; occupant presence; humidity; presence of fluids or gases; strain; road condition and friction, chemical sensors and other similar sensors providing information to a vehicle system, vehicle operator or external site. The sensors can provide information about the vehicle and/or its interior or exterior environment, about individual components, systems, vehicle occupants, subsystems, and/or about the roadway, ambient atmosphere, travel conditions and external objects.
For wireless sensors, one or more interrogators can be used each having one or more antennas that transmit energy at radio frequency, or other electromagnetic frequencies, to the sensors and receive modulated frequency signals from the sensors containing sensor and/or identification information. One interrogator can be used for sensing multiple switches or other devices. For example, an interrogator may transmit a chirp form of energy at 905 MHz to 925 MHz to a variety of sensors located within and/or in the vicinity of the vehicle. These sensors may be of the RFID electronic type and/or of the surface acoustic wave (SAW) type or a combination thereof. In the electronic type, information can be returned immediately to the interrogator in the form of a modulated backscatter RF signal. In the case of SAW devices, the information can be returned after a delay. RFID tags may also exhibit a delay due to the charging of the energy storage device. Naturally, one sensor can respond in both the electronic (either RFID or backscatter) and SAW delayed modes.
When multiple sensors are interrogated using the same technology, the returned signals from the various sensors can be time, code, space or frequency multiplexed. For example, for the case of the SAW technology, each sensor can be provided with a different delay or a different code. Alternately, each sensor can be designed to respond only to a single frequency or several frequencies. The radio frequency can be amplitude, code or frequency modulated. Space multiplexing can be achieved through the use of two or more antennas and correlating the received signals to isolate signals based on direction.
In many cases, the sensors will respond with an identification signal followed by or preceded by information relating to the sensed value, state and/or property. In the case of a SAW-based or RFID-based switch, for example, the returned signal may indicate that the switch is either on or off or, in some cases, an intermediate state can be provided signifying that a light should be dimmed, rather than or on or off, for example. Alternately or additionally, an RFID based switch can be associated with a sensor and turned on or off based on an identification code or a frequency sent from the interrogator permitting a particular sensor or class of sensors to be selected.
SAW devices have been used for sensing many parameters including devices for chemical and biological sensing and materials characterization in both the gas and liquid phase. They also are used for measuring pressure, strain, temperature, acceleration, angular rate and other physical states of the environment.
Economies are achieved by using a single interrogator or even a small number of interrogators to interrogate many types of devices. For example, a single interrogator may monitor tire pressure and temperature, the weight of an occupying item of the seat, the position of the seat and seatback, as well as a variety of switches controlling windows, door locks, seat position, etc. in a vehicle. Such an interrogator may use one or multiple antennas and when multiple antennas are used, may switch between the antennas depending on what is being monitored.
Similarly, the same or a different interrogator can be used to monitor various components of the vehicle's safety system including occupant position sensors, vehicle acceleration sensors, vehicle angular position, velocity and acceleration sensors, related to both frontal, side or rear impacts as well as rollover conditions. The interrogator could also be used in conjunction with other detection devices such as weight sensors, temperature sensors, accelerometers which are associated with various systems in the vehicle to enable such systems to be controlled or affected based on the measured state.
Some specific examples of the use of interrogators and responsive devices will now be described.
The antennas used for interrogating the vehicle tire pressure transducers can be located outside of the vehicle passenger compartment. For many other transducers to be sensed the antennas can be located at various positions within passenger compartment. At least one invention herein contemplates, therefore, a series of different antenna systems, which can be electronically switched by the interrogator circuitry. Alternately, in some cases, all of the antennas can be left connected and total transmitted power increased.
For strain gage weight sensing, the frequency of interrogation can be considerably higher than that of the tire monitor, for example. However, if the seat is unoccupied, then the frequency of interrogation can be substantially reduced. For an occupied seat, information as to the identity and/or category and position of an occupying item of the seat can be obtained through the multiple weight sensors described. For this reason, and due to the fact that during the pre-crash event, the position of an occupying item of the seat may be changing rapidly, interrogations as frequently as once every 10 milliseconds or faster can be desirable. This would also enable a distribution of the weight being applied to the seat to be obtained which provides an estimation of the center of pressure and thus the position of the object occupying the seat. Using pattern recognition technology, e.g., a trained neural network, sensor fusion, fuzzy logic, etc., an identification of the object can be ascertained based on the determined weight and/or determined weight distribution.
Generally there is an RFID implementation that corresponds to each SAW implementation. Therefore, where SAW is used herein the equivalent RFID design will also be meant where appropriate.
Although a preferred method for using the invention is to interrogate each of the SAW devices using wireless mechanisms, in some cases, it may be desirable to supply power to and/or obtain information from one or more of the SAW devices using wires. As such, the wires would be an optional feature.
Temperature measurement is another field in which SAW technology can be applied and the invention encompasses several embodiments of SAW temperature sensors.
U.S. Pat. No. 4,249,418 is one of many examples of prior art SAW temperature sensors. Temperature sensors are commonly used within vehicles and many more applications might exist if a low cost wireless temperature sensor is available such as disclosed herein. The SAW technology can be used for such temperature sensing tasks. These tasks include measuring the vehicle coolant temperature, air temperature within passenger compartment at multiple locations, seat temperature for use in conjunction with seat warming and cooling systems, outside temperatures and perhaps tire surface temperatures to provide early warning to operators of road freezing conditions. One example, is to provide air temperature sensors in the passenger compartment in the vicinity of ultrasonic transducers used in occupant sensing systems as described in the current assignee's U.S. Pat. No. 5,943,295 (Varga et al.), since the speed of sound in the air varies by approximately 20% from −40° C. to 85° C. Current ultrasonic occupant sensor systems do not measure or compensate for this change in the speed of sound with the effect of reducing the accuracy of the systems at the temperature extremes. Through the judicious placement of SAW temperature sensors in the vehicle, the passenger compartment air temperature can be accurately estimated and the information provided wirelessly to the ultrasonic occupant sensor system thereby permitting corrections to be made for the change in the speed of sound.
Since the road can be either a source or a sink of thermal energy, strategically placed sensors that measure the surface temperature of a tire can also be used to provide an estimate of road temperature.
Although they will not be discussed in detail, SAW sensors operating in the wireless mode can also be used to sense for ice on the windshield or other exterior surfaces of the vehicle, condensation on the inside of the windshield or other interior surfaces, rain sensing, heat-load sensing and many other automotive sensing functions. They can also be used to sense outside environmental properties and states including temperature, humidity, etc.
SAW sensors can be economically used to measure the temperature and humidity at numerous places both inside and outside of a vehicle. When used to measure humidity inside the vehicle, a source of water vapor can be activated to increase the humidity when desirable and the air conditioning system can be activated to reduce the humidity when necessary or desirable. Temperature and humidity measurements outside of the vehicle can be an indication of potential road icing problems. Such information can be used to provide early warning to a driver of potentially dangerous conditions. Although the invention described herein is related to land vehicles, many of these advances are equally applicable to other vehicles such as airplanes and even, in some cases, homes and buildings. The invention disclosed herein, therefore, is not limited to automobiles or other land vehicles.
Road condition sensing is another field in which SAW technology can be applied and the invention encompasses several embodiments of SAW road condition sensors.
The temperature and moisture content of the surface of a roadway are critical parameters in determining the icing state of the roadway. Attempts have been made to measure the coefficient of friction between a tire and the roadway by placing strain gages in the tire tread. Naturally, such strain gages are ideal for the application of SAW technology especially since they can be interrogated wirelessly from a distance and they require no power for operation. As discussed herein, SAW accelerometers can also perform this function. The measurement of the friction coefficient, however, is not predictive and the vehicle operator is only able to ascertain the condition after the fact. Boosted SAW or RFID based transducers have the capability of being interrogated as much as 100 feet from the interrogator. Therefore, the judicious placement of low-cost powerless SAW or RFID temperature and humidity sensors in and/or on the roadway at critical positions can provide an advance warning to vehicle operators that the road ahead is slippery. Such devices are very inexpensive and therefore could be placed at frequent intervals along a highway.
An infrared sensor that looks down the highway in front of the vehicle can actually measure the road temperature prior to the vehicle traveling on that part of the roadway. This system also would not give sufficient warning if the operator waited for the occurrence of a frozen roadway. The probability of the roadway becoming frozen, on the other hand, can be predicted long before it occurs, in most cases, by watching the trend in the temperature. Once vehicle-to-vehicle communications are common, roadway icing conditions can be communicated between vehicles.
Some lateral control of the vehicle can also be obtained from SAW transducers or electronic RFID tags placed down the center of the lane, either above the vehicles and/or in the roadway, for example. A vehicle having two receiving antennas, for example, approaching such devices, through triangulation or direct proportion, is able to determine the lateral location of the vehicle relative to these SAW devices. If the vehicle also has an accurate map of the roadway, the identification number associated with each such device can be used to obtain highly accurate longitudinal position determinations. Ultimately, the SAW devices can be placed on structures beside the road and perhaps on every mile or tenth of a mile marker. If three antennas are used, as discussed herein, the distances from the vehicle to the SAW device can be determined. These SAW devices can be powered in order to stay below current FCC power transmission limits. Such power can be supplied by a photocell, energy harvesting where applicable, by a battery or power connection.
Electronic RFID tags are also suitable for lateral and longitudinal positioning purposes, however, the range available for current electronic RFID systems can be less than that of SAW-based systems unless either are powered. On the other hand, as disclosed in U.S. Pat. No. 6,748,797, the time-of-flight of the RFID system can be used to determine the distance from the vehicle to the RFID tag. Because of the inherent delay in the SAW devices and its variation with temperature, accurate distance measurement is probably not practical based on time-of-flight but somewhat less accurate distance measurements based on relative time-of-arrival can be made. Even if the exact delay imposed by the SAW device was accurately known at one temperature, such devices are usually reasonably sensitive to changes in temperature, hence they make good temperature sensors, and thus the accuracy of the delay in the SAW device is more difficult to maintain. An interesting variation of an electronic RFID that is particularly applicable to this and other applications of this invention is described in A. Pohl, L. Reindl, “New passive sensors”, Proc. 16th IEEE Instrumentation and Measurement Technology Conf., IMTC/99, 1999, pp. 1251-1255.
Many SAW devices are based on lithium niobate or similar strong piezoelectric materials. Such materials have high thermal expansion coefficients. An alternate material is quartz that has a very low thermal expansion coefficient. However, its piezoelectric properties are inferior to lithium niobate. One solution to this problem is to use lithium niobate as the coupling system between the antenna and the material or substrate upon which the surface acoustic wave travels. In this manner, the advantages of a low thermal expansion coefficient material can be obtained while using the lithium niobate for its strong piezoelectric properties. Other useful materials such as Langasite™ have properties that are intermediate between lithium niobate and quartz.
The use of SAW tags as an accurate precise positioning system as described above would be applicable for accurate vehicle location, as discussed in U.S. Pat. No. 6,370,475, for lanes in tunnels, for example, or other cases where loss of satellite lock, and thus the primary vehicle location system, is common.
The various technologies discussed above can be used in combination. The electronic RFID tag can be incorporated into a SAW tag providing a single device that provides both a quick reflection of the radio frequency waves as well as a re-transmission at a later time. This marriage of the two technologies permits the strengths of each technology to be exploited in the same device. For most of the applications described herein, the cost of mounting such a tag in a vehicle or on the roadway far exceeds the cost of the tag itself. Therefore, combining the two technologies does not significantly affect the cost of implementing tags onto vehicles or roadways or side highway structures.
Based on the frequency and power available, and on FCC limitations, SAW or RFID or similar devices can be designed to permit transmission distances of many feet especially if minimal power is available. Since SAW and RFID devices can measure both temperature and humidity, they are also capable of monitoring road conditions in front of and around a vehicle. Thus, a properly equipped vehicle can determine the road conditions prior to entering a particular road section if such SAW devices are embedded in the road surface or on mounting structures close to the road surface as shown at 60 in
Furthermore, the determination of freezing conditions of the roadway could be transmitted to a remote location where such information is collected and processed. All information about roadways in a selected area could be collected by the roadway maintenance department and used to dispatch snow removal vehicles, salting/sanding equipment and the like. To this end, the interrogator would be coupled to a communications device arranged on the vehicle and capable of transmitting information via a satellite, ground station, over the Internet and via other communications means. A communications channel could also be established to enable bi-directional communications between the remote location and the vehicle.
The information about the roadway obtained from the sensors by the vehicle could be transmitted to the remote location along with data on the location of the vehicle, obtained through a location-determining system possibly using GPS technology. Additional information, such as the status of the sensors, the conditions of the environment obtained from vehicle-mounted or roadway-infrastructure-mounted sensors, the conditions of the vehicle obtained from vehicle-mounted sensors, the occupants obtained from vehicle-mounted sensors, etc., could also be transmitted by the vehicle's transmission device or communications device to receivers at one or more remote locations. Such receivers could be mounted to roadway infrastructure or on another vehicle. In this manner, a complete data package of information obtained by a single vehicle could be disseminated to other vehicles, traffic management locations, road condition management facilities and the like. So long as a single vehicle equipped with such a system is within range of each sensor mounted in the roadway or along the roadway, information about the entire roadway can be obtained and the entire roadway monitored.
If a SAW device 63 is placed in a roadway, as illustrated in
The SAW device 63 does not have to be in the center of the road. Alternate locations for positioning of the SAW device 63 are on overpasses above the road and on poles such as 64 and 65 on the roadside. For such cases, a source of power may be required. Such a system has an advantage over a competing system using radar and reflectors in that it is easier to measure the relative time between the two received pulses than it is to measure time-of-flight of a radar signal to a reflector and back. Such a system operates in all weather conditions and is known as a precise location system. Eventually, such a SAW device 63 can be placed every tenth of a mile along the roadway or at some other appropriate spacing. For the radar or laser radar reflection system, the reflectors can be active devices that provide environmental information in addition to location information to the interrogating vehicle.
If a vehicle is being guided by a DGPS and an accurate map system such as disclosed in U.S. Pat. No. 6,405,132 is used, a problem arises when the GPS receiver system looses satellite lock as would happen when the vehicle enters a tunnel, for example. If a precise location system as described above is placed at the exit of the tunnel, then the vehicle will know exactly where it is and can re-establish satellite lock in as little as one second rather than typically 15 seconds as might otherwise be required. Other methods making use of the cell phone system can be used to establish an approximate location of the vehicle suitable for rapid acquisition of satellite lock as described in G. M. Djuknic, R. E. Richton “Geolocation and Assisted GPS”, Computer Magazine, February 2001, IEEE Computer Society, which is incorporated by reference herein in its entirety. An alternate location system is described in U.S. Pat. No. 6,480,788.
More particularly, geolocation technologies that rely exclusively on wireless networks such as time of arrival, time difference of arrival, angle of arrival, timing advance, and multipath fingerprinting, as is known to those skilled in the art, offer a shorter time-to-first-fix (TTFF) than GPS. They also offer quick deployment and continuous tracking capability for navigation applications, without the added complexity and cost of upgrading or replacing any existing GPS receiver in vehicles. Compared to either mobile-station-based, stand-alone GPS or network-based geolocation, assisted-GPS (AGPS) technology offers superior accuracy, availability and coverage at a reasonable cost. AGPS for use with vehicles can comprise a communications unit with a minimal capability GPS receiver arranged in the vehicle, an AGPS server with a reference GPS receiver that can simultaneously “see” the same satellites as the communications unit and a wireless network infrastructure consisting at least of base stations and a mobile switching center. The network can accurately predict the GPS signal the communication unit will receive and convey that information to the mobile unit such as a vehicle, greatly reducing search space size and shortening the TTFF from minutes to a second or less. In addition, an AGPS receiver in the communication unit can detect and demodulate weaker signals than those that conventional GPS receivers require. Because the network performs the location calculations, the communication unit only needs to contain a scaled-down GPS receiver. It is accurate within about 15 meters when they are outdoors, an order of magnitude more sensitive than conventional GPS. Of course with the additional of differential corrections and carrier phase corrections, the location accuracy can be improved to centimeters.
Since an AGPS server can obtain the vehicle's position from the mobile switching center, at least to the level of cell and sector, and at the same time monitor signals from GPS satellites seen by mobile stations, it can predict the signals received by the vehicle for any given time. Specifically, the server can predict the Doppler shift due to satellite motion of GPS signals received by the vehicle, as well as other signal parameters that are a function of the vehicle's location. In a typical sector, uncertainty in a satellite signal's predicted time of arrival at the vehicle is about ±5 μs, which corresponds to ±5 chips of the GPS coarse acquisition (C/A) code. Therefore, an AGPS server can predict the phase of the pseudorandom noise (PRN) sequence that the receiver should use to despread the C/A signal from a particular satellite (each GPS satellite transmits a unique PRN sequence used for range measurements) and communicate that prediction to the vehicle. The search space for the actual Doppler shift and PRN phase is thus greatly reduced, and the AGPS receiver can accomplish the task in a fraction of the time required by conventional GPS receivers. Further, the AGPS server maintains a connection with the vehicle receiver over the wireless link, so the requirement of asking the communication unit to make specific measurements, collect the results and communicate them back is easily met. After despreading and some additional signal processing, an AGPS receiver returns back “pseudoranges” (that is, ranges measured without taking into account the discrepancy between satellite and receiver clocks) to the AGPS server, which then calculates the vehicle's location. The vehicle can even complete the location fix itself without returning any data to the server.
Sensitivity assistance, also known as modulation wipe-off, provides another enhancement to detection of GPS signals in the vehicle's receiver. The sensitivity-assistance message contains predicted data bits of the GPS navigation message, which are expected to modulate the GPS signal of specific satellites at specified times. The mobile station receiver can therefore remove bit modulation in the received GPS signal prior to coherent integration. By extending coherent integration beyond the 20-ms GPS data-bit period (to a second or more when the receiver is stationary and to 400 ms when it is fast-moving) this approach improves receiver sensitivity. Sensitivity assistance provides an additional 3-to-4-dB improvement in receiver sensitivity. Because some of the gain provided by the basic assistance (code phases and Doppler shift values) is lost when integrating the GPS receiver chain into a mobile system, this can prove crucial to making a practical receiver.
Achieving optimal performance of sensitivity assistance in TIA/EIA-95 CDMA systems is relatively straightforward because base stations and mobiles synchronize with GPS time. Given that global system for mobile communication (GSM), time division multiple access (TDMA), or advanced mobile phone service (AMPS) systems do not maintain such stringent synchronization, implementation of sensitivity assistance and AGPS technology in general will require novel approaches to satisfy the timing requirement. The standardized solution for GSM and TDMA adds time calibration receivers in the field (location measurement units) that can monitor both the wireless-system timing and GPS signals used as a timing reference.
Many factors affect the accuracy of geolocation technologies, especially terrain variations such as hilly versus flat and environmental differences such as urban versus suburban versus rural. Other factors, like cell size and interference, have smaller but noticeable effects. Hybrid approaches that use multiple geolocation technologies appear to be the most robust solution to problems of accuracy and coverage.
AGPS provides a natural fit for hybrid solutions since it uses the wireless network to supply assistance data to GPS receivers in vehicles. This feature makes it easy to augment the assistance-data message with low-accuracy distances from receiver to base stations measured by the network equipment. Such hybrid solutions benefit from the high density of base stations in dense urban environments, which are hostile to GPS signals. Conversely, rural environments, where base stations are too scarce for network-based solutions to achieve high accuracy, provide ideal operating conditions for AGPS because GPS works well there.
From the above discussion, AGPS can be a significant part of the location determining system on a vehicle and can be used to augment other more accurate systems such as DGPS and a precise positioning system based on road markers or signature matching as discussed above and in patents assigned to Intelligent Technologies International.
SAW transponders can also be placed in the license plates 67 (
A general SAW temperature and pressure gage which can be wireless and powerless is shown generally at 70 located in the sidewall 73 of a fluid container 74 in
A SAW load sensor can also be used to measure load in the vehicle suspension system powerless and wirelessly as shown in
Since a portion of the dynamic load is also carried by the shock absorber, the SAW strain gages 77 and 78 will only measure the steady or average load on the vehicle. However, additional SAW strain gages 79 can be placed on a piston rod 81 of the shock absorber to obtain the dynamic load. These load measurements can then be used for active or passive vehicle damping or other stability control purposes. Knowing the dynamic load on the vehicle coupled with measuring the response of the vehicle or of the load of an occupant on a seat also permits a determination of the vehicle's inertial properties and, in the case of the seat weight sensor, of the mass of an occupant and the state of the seat belt (is it buckled and what load is it adding to the seat load sensors).
In one implementation, SAW temperature and other sensors can be made from PVDF film and incorporated within the ultrasonic transducer assembly. For the 40 kHz ultrasonic transducer case, for example, the SAW temperature sensor would return the several pulses sent to drive the ultrasonic transducer to the control circuitry using the same wires used to transmit the pulses to the transducer after a delay that is proportional to the temperature within the transducer housing. Thus, a very economical device can add this temperature sensing function using much of the same hardware that is already present for the occupant sensing system. Since the frequency is low, PVDF could be fabricated into a very low cost temperature sensor for this purpose. Other piezoelectric materials can of course also be used.
Note, the use of PVDF as a piezoelectric material for wired and wireless SAW transducers or sensors is an important disclosure of at least one of the inventions disclosed herein. Such PVDF SAW devices can be used as chemical, biological, temperature, pressure and other SAW sensors as well as for switches. Such devices are very inexpensive to manufacture and are suitable for many vehicle-mounted devices as well as for other non-vehicle-mounted sensors. Disadvantages of PVDF stem from the lower piezoelectric constant (compared with lithium niobate) and the low acoustic wave velocity thus limiting the operating frequency. The key advantage is very low cost. When coupled with plastic electronics (plastic chips), it now becomes very economical to place sensors throughout the vehicle for monitoring a wide range of parameters such as temperature, pressure, chemical concentration etc. In particular implementations, an electronic nose based on SAW or RFID technology and neural networks can be implemented in either a wired or wireless manner for the monitoring of cargo containers or other vehicle interiors (or building interiors) for anti-terrorist or security purposes. See, for example, Reznik, A. M. “Associative Memories for Chemical Sensing”, IEEE 2002 ICONIP, p. 2630-2634, vol. 5. In this manner, other sensors can be combined with the temperature sensors 85, or used separately, to measure carbon dioxide, carbon monoxide, alcohol, biological agents, radiation, humidity or other desired chemicals or agents as discussed above. Note, although the examples generally used herein are from the automotive industry, many of the devices disclosed herein can be advantageously used with other vehicles including trucks, boats, airplanes and shipping containers.
The SAW temperature sensors 85 provide the temperature at their mounting location to a processor unit 83 via an interrogator with the processor unit 83 including appropriate control algorithms for controlling the heating and air conditioning system based on the detected temperatures. The processor unit 83 can control, e.g., which vents in the vehicle are open and closed, the flow rate through vents and the temperature of air passing through the vents. In general, the processor unit 83 can control whatever adjustable components are present or form part of the heating and air conditioning system.
In
There are many applications for which knowledge of the pitch and/or roll orientation of a vehicle or other object is desired. An accurate tilt sensor can be constructed using SAW devices. Such a sensor is illustrated in
In particular, an alternate preferred configuration is illustrated in
Either of the SAW accelerometers described above can be utilized for crash sensors as shown in
The SAW accelerometer for this particular crash sensor design is housed in a container 96 which is assembled into a housing 97 and covered with a cover 98. This particular implementation shows a connector 99 indicating that this sensor would require power and the response would be provided through wires. Alternately, as discussed for other devices above, the connector 99 can be eliminated and the information and power to operate the device transmitted wirelessly. Also, power can be supplied thorough a connector and stored in a capacitor while the information is transmitted wirelessly thus protecting the system from a wire failure during a crash when the sensor is mounted in the crush zone. Such sensors can be used as frontal, side or rear impact sensors. They can be used in the crush zone, in the passenger compartment or any other appropriate vehicle location. If two such sensors are separated and have appropriate sensitive axes, then the angular acceleration of the vehicle can also be determined. Thus, for example, forward-facing accelerometers mounted in the vehicle side doors can be used to measure the yaw acceleration of the vehicle. Alternately, two vertical sensitive axis accelerometers in the side doors can be used to measure the roll acceleration of vehicle, which would be useful for rollover sensing.
U.S. Pat. No. 6,615,656, assigned to the current assignee of this invention, and the description below, provides multiple apparatus for determining the amount of liquid in a tank. Using the SAW pressure devices of this invention, multiple pressure sensors can be placed at appropriate locations within a fuel tank to measure the fluid pressure and thereby determine the quantity of fuel remaining in the tank. This can be done both statically and dynamically. This is illustrated in
SAW sensors also have applicability to various other sectors of the vehicle, including the powertrain, chassis, and occupant comfort and convenience. For example, SAW and RFID sensors have applicability to sensors for the powertrain area including oxygen sensors, gear-tooth Hall effect sensors, variable reluctance sensors, digital speed and position sensors, oil condition sensors, rotary position sensors, low pressure sensors, manifold absolute pressure/manifold air temperature (MAP/MAT) sensors, medium pressure sensors, turbo pressure sensors, knock sensors, coolant/fluid temperature sensors, and transmission temperature sensors.
SAW sensors for the occupant comfort and convenience field include low tire pressure sensors, HVAC temperature and humidity sensors, air temperature sensors, and oil condition sensors.
SAW sensors also have applicability such areas as controlling evaporative emissions, transmission shifting, mass air flow meters, oxygen, NOx and hydrocarbon sensors. SAW based sensors are particularly useful in high temperature environments where many other technologies fail.
SAW sensors can facilitate compliance with U.S. regulations concerning evaporative system monitoring in vehicles, through a SAW fuel vapor pressure and temperature sensors that measure fuel vapor pressure within the fuel tank as well as temperature. If vapors leak into the atmosphere, the pressure within the tank drops. The sensor notifies the system of a fuel vapor leak, resulting in a warning signal to the driver and/or notification to a repair facility, vehicle manufacturer and/or compliance monitoring facility. This application is particularly important since the condition within the fuel tank can be ascertained wirelessly reducing the chance of a fuel fire in an accident. The same interrogator that monitors the tire pressure SAW sensors can also monitor the fuel vapor pressure and temperature sensors resulting in significant economies.
A SAW humidity sensor can be used for measuring the relative humidity and the resulting information can be input to the engine management system or the heating, ventilation and air conditioning (HVAC) system for more efficient operation. The relative humidity of the air entering an automotive engine impacts the engine's combustion efficiency; i.e., the ability of the spark plugs to ignite the fuel/air mixture in the combustion chamber at the proper time. A SAW humidity sensor in this case can measure the humidity level of the incoming engine air, helping to calculate a more precise fuel/air ratio for improved fuel economy and reduced emissions.
Dew point conditions are reached when the air is fully saturated with water. When the cabin dew point temperature matches the windshield glass temperature, water from the air condenses quickly, creating frost or fog. A SAW humidity sensor with a temperature-sensing element and a window glass-temperature-sensing element can prevent the formation of visible fog formation by automatically controlling the HVAC system.
In general, sensors 105-111 provide a measurement of the state of the vehicle, such as its velocity, acceleration, angular orientation or temperature, or a state of the location at which the sensor is mounted. Thus, measurements related to the state of the sensor would include measurements of the acceleration of the sensor, measurements of the temperature of the mounting location as well as changes in the state of the sensor and rates of changes of the state of the sensor. As such, any described use or function of the sensors 105-111 above is merely exemplary and is not intended to limit the form of the sensor or its function. Thus, these sensors may or may not be SAW or RFID sensors and may be powered or unpowered and may transmit their information through a wire harness, a safety or other bus or wirelessly.
Each of the sensors 105-111 may be single axis, double axis or triaxial accelerometers and/or gyroscopes typically of the MEMS type. One or more can be IMUs. These sensors 105-111 can either be wired to the central control module or processor directly wherein they would receive power and transmit information, or they could be connected onto the vehicle bus or, in some cases, using RFID, SAW or similar technology, the sensors can be wireless and would receive their power through RF from one or more interrogators located in the vehicle. In this case, the interrogators can be connected either to the vehicle bus or directly to control module. Alternately, an inductive or capacitive power and/or information transfer system can be used.
One particular implementation will now be described. In this case, each of the sensors 105-111 is a single or dual axis accelerometer. They are made using silicon micromachined technology such as described in U.S. Pat. No. 5,121,180 and U.S. Pat. No. 5,894,090. These are only representative patents of these devices and there exist more than 100 other relevant U.S. patents describing this technology. Commercially available MEMS gyroscopes such as from Systron Doner have accuracies of approximately one degree per second. In contrast, optical gyroscopes typically have accuracies of approximately one degree per hour. Unfortunately, the optical gyroscopes are believed to be expensive for automotive applications. However new developments by the current assignee are reducing this cost and such gyroscopes are likely to become cost effective in a few years. On the other hand, typical MEMS gyroscopes are not sufficiently accurate for many control applications unless corrected using location technology such as precise positioning or GPS-based systems as described elsewhere herein.
The angular rate function can be obtained by placing accelerometers at two separated, non-co-located points in a vehicle and using the differential acceleration to obtain an indication of angular motion and angular acceleration. From the variety of accelerometers shown in
Instead of using two accelerometers at separate locations on the vehicle, a single conformal MEMS-IDT gyroscope may be used. Such a conformal MEMS-IDT gyroscope is described in a paper by V. K. Varadan, “Conformal MEMS-IDT Gyroscopes and Their Comparison With Fiber Optic Gyro”, Proceedings of SPIE Vol. 3990 (2000). The MEMS-IDT gyroscope is based on the principle of surface acoustic wave (SAW) standing waves on a piezoelectric substrate. A surface acoustic wave resonator is used to create standing waves inside a cavity and the particles at the anti-nodes of the standing waves experience large amplitude of vibrations, which serves as the reference vibrating motion for the gyroscope. Arrays of metallic dots are positioned at the anti-node locations so that the effect of Coriolis force due to rotation will acoustically amplify the magnitude of the waves. Unlike other MEMS gyroscopes, the MEMS-IDT gyroscope has a planar configuration with no suspended resonating mechanical structures. Other SAW-based gyroscopes are also now under development.
The system of
As mentioned above, the combination of the outputs from these accelerometer sensors and the output of strain gage weight sensors in a vehicle seat, or in or on a support structure of the seat, can be used to make an accurate assessment of the occupancy of the seat and differentiate between animate and inanimate occupants as well as determining where in the seat the occupants are sitting. This can be done by observing the acceleration signals from the sensors of
For this embodiment, a sensor, not shown, that can be one or more strain gage weight sensors, is mounted on the seat or in connection with the seat or its support structure. Suitable mounting locations and forms of weight sensors are discussed in the current assignee's U.S. Pat. No. 6,242,701 and contemplated for use in the inventions disclosed herein as well. The mass or weight of the occupying item of the seat can thus be measured based on the dynamic measurement of the strain gages with optional consideration of the measurements of accelerometers on the vehicle, which are represented by any of sensors 105-111.
A SAW Pressure Sensor can also be used with bladder weight sensors permitting that device to be interrogated wirelessly and without the need to supply power. Similarly, a SAW device can be used as a general switch in a vehicle and in particular as a seatbelt buckle switch indicative of seatbelt use. SAW devices can also be used to measure seatbelt tension or the acceleration of the seatbelt adjacent to the chest or other part of the occupant and used to control the occupant's acceleration during a crash. Such systems can be boosted as disclosed herein or not as required by the application. These inventions are disclosed in patents and patent applications of the current assignee.
The operating frequency of SAW devices has hereto for been limited to less that about 500 MHz due to problems in lithography resolution, which of course is constantly improving and currently SAW devices based on lithium niobate are available that operate at 2.4 GHz. This lithography problem is related to the speed of sound in the SAW material. Diamond has the highest speed of sound and thus would be an ideal SAW material. However, diamond is not piezoelectric. This problem can be solved partially by using a combination or laminate of diamond and a piezoelectric material. Recent advances in the manufacture of diamond films that can be combined with a piezoelectric material such as lithium niobate promise to permit higher frequencies to be used since the spacing between the inter-digital transducer (IDT) fingers can be increased for a given frequency. A particularly attractive frequency is 2.4 GHz or Wi-Fi as the potential exists for the use of more sophisticated antennas such as the Yagi antenna or the Motia smart antenna that have more gain and directionality. In a different development, SAW devices have been demonstrated that operate in the tens of GHz range using a novel stacking method to achieve the close spacing of the IDTs.
In a related invention, the driver can be provided with a keyless entry device, other RFID tag, smart card or cell phone with an RF transponder that can be powerless in the form of an RFID or similar device, which can also be boosted as described herein. The interrogator determines the proximity of the driver to the vehicle door or other similar object such as a building or house door or vehicle trunk. As shown in
As shown in
A SAW device can also be used as a wireless switch as shown in
An alternate approach is to place a switch across the IDT 127 as shown in
Most SAW-based accelerometers work on the principle of straining the SAW surface and thereby changing either the time delay or natural frequency of the system. It is important to note that all of these devices have a high dynamic range compared with most competitive technologies. In some cases, this dynamic range can exceed 100,000 and up to 1,000,000 has been reported. This is the direct result of the ease with which frequency and phase can be accurately measured.
As discussed, theoretically a SAW can be used for any sensing function provided the surface across which the acoustic wave travels can be modified in terms of its length, mass, elastic properties or any property that affects the travel distance, speed, amplitude or damping of the surface wave. Thus, gases and vapors can be sensed through the placement of a layer on the SAW that absorbs the gas or vapor, for example (a chemical sensor or electronic nose). Similarly, a radiation sensor can result through the placement of a radiation sensitive coating on the surface of the SAW.
Normally, a SAW device is interrogated with a constant amplitude and frequency RF pulse. This need not be the case and a modulated pulse can also be used. If for example a pseudorandom or code modulation is used, then a SAW interrogator can distinguish its communication from that of another vehicle that may be in the vicinity. This doesn't totally solve the problem of interrogating a tire that is on an adjacent vehicle but it does solve the problem of the interrogator being confused by the transmission from another interrogator. This confusion can also be partially solved if the interrogator only listens for a return signal based on when it expects that signal to be present based on when it sent the signal. That expectation can be based on the physical location of the tire relative to the interrogator which is unlikely to come from a tire on an adjacent vehicle which only momentarily could be at an appropriate distance from the interrogator. The interrogator would of course need to have correlation software in order to be able to differentiate the relevant signals. The correlation technique also permits the interrogator to separate the desired signals from noise thereby improving the sensitivity of the correlator. An alternate approach as discussed elsewhere herein is to combine a SAW sensor with an RFID switch where the switch is programmed to open or close based on the receipt of the proper identification code.
U.S. Pat. No. 6,622,567 describes a peak strain RFID technology based device with the novelty being the use of a mechanical device that records the peak strain experienced by the device. Like the system of the invention herein, the system does not require a battery and receives its power from the RFID circuit. The invention described herein includes the use of RFID based sensors either in the peak strain mode or in the preferred continuous strain mode. This invention is not limited to measuring strain as SAW and RFID based sensors can be used for measuring many other parameters including chemical vapor concentration, temperature, acceleration, angular velocity etc.
A key aspect of at least one of the inventions disclosed herein is the use of an interrogator to wirelessly interrogate multiple sensing devices thereby reducing the cost of the system since such sensors are in general inexpensive compared to the interrogator. The sensing devices are preferably based of SAW and/or RFID technologies although other technologies are applicable.
1.3.1 Antenna Considerations
Antennas are a very important aspect to SAW and RFID wireless devices such as can be used in tire monitors, seat monitors, weight sensors, child seat monitors, fluid level sensors and similar devices or sensors which monitor, detect, measure, determine or derive physical properties or characteristics of a component in or on the vehicle or of an area near the vehicle, as disclosed in the current assignee's patents and pending patent applications. In many cases, the location of a SAW or RFID device needs to be determined such as when a device is used to locate the position of a movable item in or on a vehicle such as a seat. In other cases, the particular device from a plurality of similar devices, such as a tire pressure and/or temperature monitor that is reporting, needs to be identified. Thus, a combination of antennas can be used and the time or arrival, angle of arrival, multipath signature or similar method used to identify the reporting device. One preferred method is derived from the theory of smart antennas whereby the signals from multiple antennas are combined to improve the signal-to-noise ratio of the incoming or outgoing signal in the presence of multipath effects, for example.
Additionally, since the signal level from a SAW or RFID device is frequently low, various techniques can be used to improve the signal-to-noise ratio as described below. Finally, at the frequencies frequently used such as 433 MHz, the antennas can become large and methods are needed to reduce their size. These and other antenna considerations that can be used to improve the operation of SAW, RFID and similar wireless devices are described below.
1.3.1.1 Tire Information Determination
One method of maintaining a single central antenna assembly while interrogating all four tires on a conventional automobile, is illustrated in
A vehicle body is illustrated as 620 having four tires 621 and a centrally mounted four element, switchable directional antenna array 622. The four beams are shown schematically as 623 with an inactivated beam as 624 and the activated beam as 625. The road surface 626 supports the vehicle. An electronic control circuit, not shown, which may reside inside the antenna array housing 622 or elsewhere, alternately switches each of the four antennas of the array 622 which then sequentially, or in some other pattern, send RF signals to each of the four tires 621 and wait for the response from the RFID, SAW or similar tire pressure, temperature, ID, acceleration and/or other property monitor arranged in connection with or associated with the tire 621. This represents a time domain multiple access system.
The interrogator makes sequential interrogation of wheels as follows:
In another application, the antennas of the array 622 transmit the RF signals simultaneously and space the returns through the use of a delay line in the circuitry from each antenna so that each return is spaced in time in a known manner without requiring that the antennas be switched. Another method is to offset the antenna array, as illustrated in
In another application, not shown, two wide angle antennas can be used such that each receives any four signals but each antenna receives each signal at a slightly different time and different amplitude permitting each signal to be separated by looking at the return from both antennas since, each signal will be received differently based on its angle of arrival.
Additionally, each SAW or RFID device can be designed to operate on a slightly different frequency and the antennas of the array 622 can be designed to send a chirp signal and the returned signals will then be separated in frequency, permitting the four signals to be separated. Alternately, the four antennas of the array 622 can each transmit an identification signal to permit separation. This identification can be a numerical number or the length of the SAW substrate, for example, can be random so that each property monitor has a slightly different delay built in which permits signal separation. The identification number can be easily achieved in RFID systems and, with some difficulty and added expense, in SAW systems. Other methods of separating the signals from each of the tires 621 will now be apparent to those skilled in the art. One preferred method in particular will be discussed below and makes use of an RFID switch.
Although the discussion herein concerns the determination of tire information, the same system can be used to determine the location of seats, the location of child seats when equipped with sensors, information about the presence of object or chemicals in vehicular compartments and the like.
1.3.1.2 Summary
A general system for obtaining information about a vehicle or a component thereof or therein is illustrated in
A control system 628 is coupled to the antenna array 622 and controls the antennas in the array 622 to be operative as necessary to enable reception of return signals from the sensors 627. There are several ways for the control system 628 to control the array 622, including to cause the antennas to be alternately switched on in order to sequentially transmit the RF signals therefrom and receive the return signals from the sensors 627 and to cause the antennas to transmit the RF signals simultaneously and space the return signals from the sensors 627 via a delay line in circuitry from each antennas such that each return signal is spaced in time in a known manner without requiring switching of the antennas. The control system can also be used to control a smart antenna array.
The control system 628 also processes the return signals to provide information about the vehicle or the component. The processing of the return signals can be any known processing including the use of pattern recognition techniques, neural networks, fuzzy systems and the like.
The antenna array 622 and control system 628 can be housed in a common antenna array housing 630.
Once the information about the vehicle or the component is known, it is directed to a display/telematics/adjustment unit 629 where the information can be displayed on a display 629 to the driver, sent to a remote location for analysis via a telematics unit 629 and/or used to control or adjust a component on, in or near the vehicle. Although several of the figures illustrate applications of these technologies to tire monitoring, it is intended that the principles and devices disclosed can be applied to the monitoring of a wide variety of components on and off a vehicle.
2. Summary
The inventions described above are, of course, susceptible to many variations, combinations of disclosed components, modifications and changes, all of which are within the skill of the art. It should be understood that all such variations, modifications and changes are within the spirit and scope of the inventions and of the appended claims. Similarly, it will be understood that applicant intends to cover and claim all changes, modifications and variations of the examples of preferred embodiments of the invention herein disclosed for the purpose of illustration which do not constitute departures from the spirit and scope of the present invention as claimed.
Although several preferred embodiments are illustrated and described above, there are possible combinations using other geometries, sensors, materials and different dimensions for the components that perform the same functions. This invention is not limited to the above embodiments and should be determined by the following claims.
This application is a continuation-in-part (CIP) of U.S. patent application Ser. No. 12/020,684 filed Jan. 28, 2008, which is: 1. a CIP of U.S. patent application Ser. No. 11/082,739 filed Mar. 17, 2005, now U.S. Pat. No. 7,421,321, which is a CIP of U.S. patent application Ser. No. 10/701,361, filed Nov. 4, 2003 now U.S. Pat. No. 6,988,026, which is a CIP of U.S. patent application Ser. No. 10/079,065 filed Feb. 19, 2002, now U.S. Pat. No. 6,662,642, which claims priority under 35 U.S.C. §119(e) of U.S. provisional patent application Ser. No. 60/269,415 filed Feb. 16, 2001, U.S. provisional patent application Ser. No. 60/291,511 filed May 16, 2001, and U.S. provisional patent application Ser. No. 60/304,013 filed Jul. 9, 2001; and 2. a CIP of U.S. patent application Ser. No. 10/940,881 filed Sep. 13, 2004, now U.S. Pat. No. 7,663,502, which is a A. a CIP of U.S. patent application Ser. No. 10/613,453 filed Jul. 3, 2003, now U.S. Pat. No. 6,850,824, which is a continuation of U.S. patent application Ser. No. 10/188,673 filed Jul. 3, 2002, now U.S. Pat. No. 6,738,697, which is a CIP of U.S. patent application Ser. No. 10/079,065 filed Feb. 19, 2002, now U.S. Pat. No. 6,662,642, which claims priority under 35 U.S.C. §119(e) of U.S. provisional patent application Ser. No. 60/269,415 filed Feb. 16, 2001, U.S. provisional patent application Ser. No. 60/291,511 filed May 16, 2001, and U.S. provisional patent application Ser. No. 60/304,013 filed Jul. 9, 2001; and this application is also a CIP of U.S. patent application Ser. No. 11/968,844 filed Jan. 3, 2008, which is: 1. a CIP of U.S. patent application Ser. No. 10/940,881 filed Sep. 3, 2004, now U.S. Pat. No. 7,663,502, which is: A. a CIP of U.S. patent application Ser. No. 10/457,238 filed Jun. 9, 2003, now U.S. Pat. No. 6,919,803, which claims priority under 35 U.S.C. §119(e) of U.S. provisional patent application Ser. No. 60/387,792 filed Jun. 11, 2002;B. a CIP of U.S. patent application Ser. No. 10/931,288 filed Aug. 31, 2004, now U.S. Pat. No. 7,164,117; 2. a CIP of U.S. patent application Ser. No. 11/278,979 filed Apr. 7, 2006, now U.S. Pat. No. 7,386,372, which is a CIP of U.S. patent application Ser. No. 10/931,288 filed Aug. 31, 2004, now U.S. Pat. No. 7,164,117; 3. a CIP of U.S. patent application Ser. No. 11/380,574 filed Apr. 27, 2006, now U.S. Pat. No. 8,159,338, which is a CIP of U.S. patent application Ser. No. 10/931,288 filed Aug. 31, 2004, now U.S. Pat. No. 7,164,117; 4. a CIP of U.S. patent application Ser. No. 11/619,863 filed Jan. 4, 2007 which is a CIP of U.S. patent application Ser. No. 10/931,288 filed Aug. 31, 2004, now U.S. Pat. No. 7,164,117; 5. a CIP of U.S. patent application Ser. No. 11/755,199 filed May 30, 2007, now U.S. Pat. No. 7,911,324; 6. a CIP of U.S. patent application Ser. No. 11/843,932 filed Aug. 23, 2007, now U.S. Pat. No. 8,310,363; and 7. a CIP of U.S. patent application Ser. No. 11/865,363 filed Oct. 1, 2007, now U.S. Pat. No. 7,819,003; and this application is also a CIP of U.S. patent application Ser. No. 11/619,863 filed Jan. 4, 2007, which is: 1. a CIP of U.S. patent application Ser. No. 10/940,881 filed Sep. 3, 2004, now U.S. Pat. No. 7,663,502, which is a CIP of U.S. patent application Ser. No. 10/457,238 filed Jun. 9, 2003, now U.S. Pat. No. 6,919,803, which claims priority under 35 U.S.C. §119(e) of U.S. provisional patent application Ser. No. 60/387,792 filed Jun. 11, 2002; and 2. a CIP of U.S. patent application Ser. No. 10/931,288 filed Aug. 31, 2004, now U.S. Pat. No. 7,164,117, which is a CIP of U.S. patent application Ser. No. 10/457,238 filed Jun. 9, 2003, now U.S. Pat. No. 6,919,803, which claims priority under 35 U.S.C. §119(e) of U.S. provisional patent application Ser. No. 60/387,792 filed Jun. 11, 2002.
Number | Name | Date | Kind |
---|---|---|---|
4709265 | Silverman et al. | Nov 1987 | A |
5025150 | Oldham et al. | Jun 1991 | A |
5311197 | Sorden et al. | May 1994 | A |
5324948 | Dudar et al. | Jun 1994 | A |
5334974 | Simms et al. | Aug 1994 | A |
5416476 | Rendon | May 1995 | A |
5491337 | Jenkins et al. | Feb 1996 | A |
5532679 | Baxter, Jr. | Jul 1996 | A |
5592372 | Artail et al. | Jan 1997 | A |
5673305 | Ross | Sep 1997 | A |
5774070 | Rendon | Jun 1998 | A |
5850619 | Rasmussen | Dec 1998 | A |
5867801 | Denny | Feb 1999 | A |
5908981 | Atalar et al. | Jun 1999 | A |
5917433 | Keillor et al. | Jun 1999 | A |
5936523 | West | Aug 1999 | A |
5959529 | Kail, IV | Sep 1999 | A |
6023223 | Baxter, Jr. | Feb 2000 | A |
6100806 | Gaukel | Aug 2000 | A |
6147598 | Murphy et al. | Nov 2000 | A |
6155160 | Hochbrueckner | Dec 2000 | A |
6166627 | Reeley | Dec 2000 | A |
6255942 | Knudsen | Jul 2001 | B1 |
6293861 | Berry | Sep 2001 | B1 |
6360031 | Harrah | Mar 2002 | B1 |
6395558 | Duveneck et al. | May 2002 | B1 |
6400265 | Saylor et al. | Jun 2002 | B1 |
6429773 | Schuyler | Aug 2002 | B1 |
6453687 | Sharood et al. | Sep 2002 | B2 |
6490530 | Wyatt | Dec 2002 | B1 |
6670887 | Dungan | Dec 2003 | B2 |
6720866 | Sorrlls et al. | Apr 2004 | B1 |
6728552 | Chatain | Apr 2004 | B2 |
6794991 | Dungan | Sep 2004 | B2 |
6816072 | Zoratti | Nov 2004 | B2 |
6816088 | Knoska et al. | Nov 2004 | B1 |
6826514 | Antico et al. | Nov 2004 | B1 |
6858182 | Ito et al. | Feb 2005 | B1 |
6866819 | Chandra et al. | Mar 2005 | B1 |
7002481 | Crane et al. | Feb 2006 | B1 |
7056474 | Dumas et al. | Jun 2006 | B2 |
RE40073 | Breed | Feb 2008 | E |
7479877 | Mortenson et al. | Jan 2009 | B2 |
7563416 | Fleischer | Jul 2009 | B2 |
7768380 | Breed et al. | Aug 2010 | B2 |
7809377 | Lau et al. | Oct 2010 | B1 |
7846742 | Sapir et al. | Dec 2010 | B2 |
7961094 | Breed | Jun 2011 | B2 |
8086266 | Kotidis | Dec 2011 | B2 |
8115620 | Breed | Feb 2012 | B2 |
20020038353 | Yamamoto | Mar 2002 | A1 |
20020070869 | Dungan | Jun 2002 | A1 |
20020143469 | Alexander et al. | Oct 2002 | A1 |
20030093484 | Petite | May 2003 | A1 |
20030201900 | Bachinski et al. | Oct 2003 | A1 |
20040015336 | Kulesz et al. | Jan 2004 | A1 |
20040017300 | Kotzin et al. | Jan 2004 | A1 |
20040080256 | Hampden-Smith et al. | Apr 2004 | A1 |
20040094416 | Chen et al. | May 2004 | A1 |
20040119591 | Peeters | Jun 2004 | A1 |
20040220753 | Tabe | Nov 2004 | A1 |
20050021233 | Christensen | Jan 2005 | A1 |
20070000305 | Ma et al. | Jan 2007 | A1 |
20080061959 | Breed | Mar 2008 | A1 |
20080146890 | LeBoeuf et al. | Jun 2008 | A1 |
20080282817 | Breed | Nov 2008 | A1 |
20080287144 | Sabata et al. | Nov 2008 | A1 |
20090015400 | Breed | Jan 2009 | A1 |
20100283626 | Breed | Nov 2010 | A1 |
20140080129 | Klunder et al. | Mar 2014 | A1 |
Entry |
---|
Cell-All: Super Smartphones Sniff Out Suspicious Substances, Department of Homeland Security, http://www.dhs.gov/cell-all-super-smartphones-sniff-out-suspicious-substances, undated, printed Jun. 20, 2014. |
NASA Ames Scientist Develops Cell Phone Chemical Sensor, http://www.nasa.gov/centers/ames/news/features/2009/cell—phone—sensors.html, Oct. 30, 2009, printed Jun. 20, 2014. |
Sensors to “Crowdsource” Detection of Deadly Chemicals, Bruce V. Bigelow, http://www.xconomy.com/san-diego/2009/11/02/homeland-security-backs-cell-phone-sensors-to-%E2%80%9Ccrowdsource%E2%80%9D-detection-of-deadly-chemicals/, Nov. 2, 2009, printed Jun. 20, 2014. |
.Chemical and Biological Sensors using Nanotechnology, Compiled by Earl Boysen of Hawk's Perch Technical Writing, LLC and UnderstandingNano.com, http://www.understandingnano.com/sensor.html, undated, printed Jun. 26, 2014. |
Vantage Health to Commercialize Award Winning NASA Chemical Sensor Technology, http://www.parabolicarc.com/2014/01/07/vantage-health/, Posted by Doug Messier on Jan. 7, 2014, printed Jun. 20, 2014. |
DHS Wants to Turn Cell Phones Into Chemical Sensors, by Matthew Harwood, http://www.securitymanagement.com/news/dhs-wants-turn-cell-phones-chemical-sensors-007003, Apr. 12, 2010, printed Jun. 20, 2014. |
NASA Scientist Converts iPhone into Chemical Sniffer: A new plug-in iPhone device can detect airborne ammonia, chlorine gas and methane, http://www.popsci.com/technology/article/2009-11/nasa-scientist-converts-iphone-chemical-sniffer, by Jeremy Hsu Posted Nov. 11, 2009, printed Jun. 20, 2014. |
Smartphone sensor could detect toxic chemicals, by Ben Coxworth, Apr. 10, 2010. |
Number | Date | Country | |
---|---|---|---|
20150142209 A1 | May 2015 | US |
Number | Date | Country | |
---|---|---|---|
60269415 | Feb 2001 | US | |
60291511 | May 2001 | US | |
60304013 | Jul 2001 | US | |
60231378 | Sep 2000 | US | |
60387792 | Jun 2002 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 10188673 | Jul 2002 | US |
Child | 10613453 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 12020684 | Jan 2008 | US |
Child | 14611554 | US | |
Parent | 11082739 | Mar 2005 | US |
Child | 12020684 | US | |
Parent | 10701361 | Nov 2003 | US |
Child | 11082739 | US | |
Parent | 10079065 | Feb 2002 | US |
Child | 10701361 | US | |
Parent | 09765558 | Jan 2001 | US |
Child | 10079065 | US | |
Parent | 10940881 | Sep 2004 | US |
Child | 12020684 | US | |
Parent | 10613453 | Jul 2003 | US |
Child | 10940881 | US | |
Parent | 09765558 | Jan 2001 | US |
Child | 10188673 | US | |
Parent | 14611554 | US | |
Child | 10188673 | US | |
Parent | 11968844 | Jan 2008 | US |
Child | 14611554 | US | |
Parent | 10457238 | Jun 2003 | US |
Child | 11968844 | US | |
Parent | 10931288 | Aug 2004 | US |
Child | 10940881 | US | |
Parent | 11278979 | Apr 2006 | US |
Child | 11968844 | US | |
Parent | 11380574 | Apr 2006 | US |
Child | 11968844 | US | |
Parent | 11619863 | Jan 2007 | US |
Child | 11968844 | US | |
Parent | 11755199 | May 2007 | US |
Child | 11968844 | US | |
Parent | 11843932 | Aug 2007 | US |
Child | 11755199 | US | |
Parent | 11865363 | Oct 2007 | US |
Child | 11843932 | US |