The present invention generally relates to the field of electric motors and, more specifically, to methods and systems for performing fault diagnostics for rotors of electric motors.
Electric motors (or electric machines) are finding an increasing number of applications in various fields, including the automotive industry, for example due to the electrification of the automotive drive system. Electric and/or hybrid vehicles utilize electric motors as either primary or supplemental torque sources in the automotive drive system. These electric motors are expected to function over extreme operating conditions for an extended period of time with high reliability. However, over time, the operating stresses applied to the electric motor may degrade the condition of one or more rotors of the electric motor.
Accordingly, it is desirable to provide an improved method for performing fault diagnosis for rotors of electric motors, such as in the automotive industry, for example that may provide improved results, that may require fewer sensors and/or other apparatus, and/or that may be easier and/or more cost effective to implement. It is also desirable to provide an improved system for performing fault diagnosis for rotors of electric motors, such as in the automotive industry, for example that may provide improved results, that may require fewer sensors and/or other apparatus, and/or that may be easier and/or more cost effective to implement. Furthermore, other desirable features and characteristics of the present invention will be apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background.
In accordance with an exemplary embodiment of the present invention, a method for fault diagnosis for a rotor of an electric motor, the electric motor also having a stator, is provided. The method comprises the steps of generating, via a processor, a measured motor current for the stator, determining, via the processor, a resolver angle of the rotor, determining, via the processor, a flux angle of the rotor, calculating, via the processor, a transformation angle using the resolver angle and the flux angle, conducting, via the processor, a transformation of the motor current using the transformation angle, and identifying, via the processor, a fault condition based on the transformation.
In accordance with another exemplary embodiment of the present invention, a method for fault diagnosis for a rotor of an electric motor, the electric motor also having a stator, is provided. The method comprises the steps of generating, via a processor, a measured motor current for the stator, determining, via the processor, a resolver angle of the rotor, determining, via the processor, a flux angle of the rotor, calculating, via the processor, a first transformation angle using the resolver angle, the flux angle, or both, subtracting, via the processor, the resolver angle from the flux angle, to thereby generate a slip angle, calculating, via the processor, a second transformation angle using the slip angle and the flux angle, conducting, via the processor, a first transformation of the motor current using the first transformation angle, to thereby generate a first fault component, conducting, via the processor, a second transformation of the motor current using the second transformation angle, to thereby generate a second fault component, calculating, via the processor, a fault index using the first fault component and the second fault component, and identifying, via the processor, a fault condition using the fault index.
In accordance with a further exemplary embodiment of the present invention, an electrical system for use in a vehicle is provided. The electrical system comprises an electric motor, an energy source, an inverter module, a current sensor, and a control module. The electric motor has a rotor and a stator. The inverter module is coupled between the energy source and the stator, and is configured to provide a commanded voltage from the energy source to a stator of the electric motor. The current sensor is coupled between the inverter module and the stator, and is configured to measure current through the stator, resulting in measured current. The control module is coupled to the inverter module and the plurality of current sensors, and is configured to generate a measured current for the stator, determine a resolver angle of the rotor, determine a flux angle of the rotor, calculate a first transformation angle using the resolver angle, the flux angle, or both, subtract the resolver angle from the flux angle, to thereby generate a slip angle, calculate a second transformation angle using the slip angle and the flux angle, conduct a first transformation of the motor current using the first transformation angle, to thereby generate a first fault component, conduct a second transformation of the motor current using the second transformation angle, to thereby generate a second fault component, calculate a fault index using the first fault component and the second fault component, and identify a fault condition using the fault index.
The present invention will hereinafter be described in conjunction with the following drawing figures, wherein like numerals denote like elements, and wherein:
The following detailed description is merely exemplary in nature and is not intended to limit the invention or the application and uses of the invention. Furthermore, there is no intention to be bound by any theory presented in the preceding background or the following detailed description.
In an exemplary embodiment, the inverter module 104 is coupled between the energy source 102 and the electric motor 106. In an exemplary embodiment, the current sensors 112 are coupled between the inverter module 104 and the electric motor 106 and configured to measure the currents flowing from the inverter module 104 through the stator of the electric motor 106, as described in greater detail below. The control module 110 is coupled to the current sensors 112 and obtains the measured currents through the stator of the electric motor 106 from the current sensors 112. The resolver system 108 is coupled between the electric motor 106 and the control module 110, and the resolver system 108 is suitably configured to measure, sense, or otherwise obtain the position of the rotor of the electric motor 106. As described in greater detail below, in an exemplary embodiment, the control module 110 is configured to regulate current through the stator to a commanded value by controlling the voltage provided from the energy source 102 to the electric motor 106. In an exemplary embodiment, the control module 110 is configured to identify a fault condition in the rotor of the electric motor 106 based on the rotor fault diagnostic method as described in greater detail below.
In one exemplary embodiment the vehicle is realized as an automobile. In alternative embodiments, the vehicle may be any one of a number of different types of automobiles, such as, for example, a sedan, a wagon, a truck, or a sport utility vehicle (SUV), and may be two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive (4WD), or all-wheel drive (AWD). The vehicle may also incorporate any one of, or combination of, a number of different types of engines, such as, for example, a gasoline or diesel fueled combustion engine, a “flex fuel vehicle” (FFV) engine (i.e., using a mixture of gasoline and alcohol), a gaseous compound (e.g., hydrogen and natural gas) fueled engine, a combustion/electric motor hybrid engine, and an electric motor. In alternative embodiments, the vehicle may be a plug-in hybrid vehicle, a fully electric vehicle, a fuel cell vehicle (FCV), or another suitable alternative fuel vehicle.
In an exemplary embodiment, the energy source 102 (or power source) is capable of providing a direct current (DC) voltage to the inverter module 104 for operating the electric motor 106. Depending on the embodiment, the energy source 102 may be realized as a battery, a fuel cell, a rechargeable high-voltage battery pack, an ultracapacitor, or another suitable energy source known in the art.
In one exemplary embodiment, the electric motor 106 is an induction motor. However, in various embodiments, the electric motor 106 may be one of a number of different types of motors. The subject matter described herein should not be construed as being limited to use with any particular type of electric motor. For example, in certain other embodiments, the electric motor 106 may be realized as an internal permanent magnet (IPM) motor, a synchronous reluctance motor, or another suitable motor known in the art. In this regard, the electric motor 106 may be realized as a non-salient machine (e.g., an induction motor, permanent surface mount machine) having a spatial impedance that is independent of the rotor position or a salient machine (e.g., a synchronous reluctance motor, interior permanent magnet motor) having a spatial impedance that depends on the rotor position with respect to the stator, as will be appreciated in the art, among other possible different types of motors.
In an exemplary embodiment, the electric motor 106 is a three-phase alternating current (AC) electric machine having a rotor and stator windings (or coils). In an exemplary embodiment, for a three-phase motor, the stator is arranged in three sets of windings, wherein each set of windings corresponds to a phase of the electric motor 106. In this regard, each current sensor 112 is associated with a particular phase of the electric motor 106 and obtains the current for the respective phase of the electric motor 106 in a conventional manner. It should be understood that although the subject matter may be described herein in the context of a three-phase electric motor, the subject matter is not limited to three-phase machines and may be adapted for an electric motor having any number of phases or an electrical system having any number of current sensors.
In a preferred embodiment, only one such current sensor 112 is necessary. This provides a significant advantage over other designs in the industry that typically rely on three current sensors for measurement. Accordingly, in a preferred embodiment, failure in any of the current sensors would result in malfunction of such prior designs in the industry but not the embodiment disclosed herein, because the disclosed embodiment utilizes the current from the other healthy sensor.
In an exemplary embodiment, the inverter module 104 includes a power inverter configured to convert the DC power from the energy source 102 into AC power for driving the electric motor 106 in a conventional manner, as will be appreciated in the art. In this regard, the inverter module 104 includes one or more phase legs corresponding to the one or more phases of the electric motor 106, wherein switches of the phase leg are modulated (opened or closed) at a particular switching frequency to produce an AC voltage across the stator of the electric motor 106, which in turn creates torque-producing current in the stator and operates the electric motor 106, as will be appreciated in the art.
In an exemplary embodiment, the resolver system 108 comprises a resolver coupled to the electric motor 106, and the output of the resolver is coupled to a resolver-to-digital converter. The resolver (or similar sensing device) senses the position of the rotor (θr) of the electric motor 106. The resolver-to-digital converter converts the signals from the resolver to digital signals (e.g., a digital rotor position signal) which are provided to the control module 110.
The control module 110 generally represents the hardware suitably configured to implement field-oriented control or current-regulated control of the electric motor 106 by controlling and/or operating the inverter module 104 to provide a commanded voltage from the energy source 102 to the electric motor 106. In this regard, the commanded voltage is a current-regulated voltage, that is, a voltage configured to regulate current in the stator of the electric motor 106 to a particular value, as described in greater detail below. Depending on the embodiment, the control module 110 may be implemented or realized with a general purpose processor, a content addressable memory, a digital signal processor, an application specific integrated circuit, a field programmable gate array, any suitable programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, designed to perform the functions described herein. In this regard, the control module 110 may be realized as a microprocessor, a controller, a microcontroller, a state machine, or the like. The control module 110 may also be implemented as a combination of computing devices, e.g., a combination of a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other such configuration. In practice, the control module 110 includes processing logic that may be configured to carry out the functions, techniques, and processing tasks associated with the operation of the electrical system 100, as described in greater detail below. Furthermore, the steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in firmware, in a software module executed by the control module 110, or in any practical combination thereof.
In an exemplary embodiment, the control module 110 is implemented in the d-q synchronous reference frame, that is, the d-q axes of the reference frame rotate in lockstep with a reference characteristic of the rotor (e.g., the rotor position, the rotor flux angle) of the electric motor 106 such that rotation (or angular displacement) of the rotor characteristic produces a corresponding rotation (or angular displacement) of the d-q axes. In an exemplary embodiment, the control module 110 is implemented in the counterclockwise synchronous reference frame such that rotation of the rotor characteristic produces a corresponding counterclockwise rotation of the d-q axes. As shown in the illustrated embodiment of
In an exemplary embodiment, the control module 110 includes a speed regulator 114, a flux regulator 116, a current regulator 118, a first transformation block 120, a second transformation block 122, a speed calculator 124, a flux estimator 126, and a rotor diagnostic block 128. The elements of the control module 110 are suitably configured to create a current-regulating control loop (or alternatively, field-oriented control loop or current-controlled feedback loop), as described in greater detail below. In an exemplary embodiment, the rotor diagnostic block 128 is configured to identify or detect the existence of a fault condition in the rotor of the electric motor 106 (such as broken rotor faults or rotor eccentricity faults), as described in greater detail below. In a preferred embodiment, the rotor diagnostic block 128 comprises a control module 129 having a processor 130 that performs the calculations, determinations, and other functions, steps, and processes of the rotor diagnostic block 128.
In the illustrated embodiment, the output of a first summing junction 113 is coupled to the input of the speed regulator 114, and the output of the speed regulator is coupled to a second summing junction 115. The output of a third summing junction 117 is coupled to the input of the flux regulator 116, and the output of the flux regulator 116 is coupled to a fourth summing junction 119. The output of the second summing junction 115 and the output of the fourth summing junction 119 are each coupled to the input of the current regulator 118. The outputs of the current regulator 118 are coupled to the first transformation block 120, and the outputs of the first transformation block 120 is coupled to the inverter module 104. The second transformation block 122 is coupled to the current sensors 112, and the individual outputs of the second transformation block 122 are coupled to the second summing junction 115 and the fourth summing junction 119, as described in greater detail below. In an exemplary embodiment, the inputs of the flux estimator 126 are coupled to the output of the second transformation block 122 and the output of the current regulator 118, as described in greater detail below. A first output of the flux estimator 126 is coupled to the third summing junction 117 and the second output of the flux estimator 126 is coupled to the transformation blocks 120, 122 and the rotor diagnostic block 128.
In an exemplary embodiment, the first summing junction 113 is configured to receive a speed command (ωr*) that represents a desired speed (or commanded speed) for the rotor of the electric motor 106. The speed command may be provided by another module in the vehicle, such as, for example, an electronic control unit (ECU). The speed calculator 124 calculates or otherwise determines the observed (or measured) rotor speed (ωr) based on the change in rotor position (θr) versus time, as will be appreciated in the art. The first summing junction 113 is configured to determine the difference between the speed command (ωr*) and the observed rotor speed (ωr) and provide the difference to the speed regulator 114. Based on the difference between the speed command (ωr*) and the rotor speed (ωr), the speed regulator 114 determines and/or generates a q-axis synchronous frame current command (iqe*) (e.g., the torque-producing q-axis current command). The speed regulator 114 may be realized as a proportional-integral (PI) controller or another suitable element known in the art.
In an exemplary embodiment, the third summing junction 117 is configured to receive a flux command (λe*) that represents a desired rotor flux for the electric motor 106. The flux command may be provided by another module in the vehicle, such as, for example, an electronic control unit (ECU). The flux estimator 126 calculates or otherwise estimates the rotor flux (λe) based on the relationship between the synchronous motor currents (ide, iqe) and the synchronous motor voltages (vde, vqe), as will be appreciated in the art and described in greater detail below. The third summing junction 117 is configured to determine the difference between the flux command (λe*) and the estimated rotor flux (λe) and provide the difference to the flux regulator 116. Based on the difference between the flux command and the estimated flux, the flux regulator 116 determines and/or generates a d-axis synchronous frame current command (ide*) (e.g., the flux-producing d-axis current command). The flux regulator 116 may be realized as a proportional-integral (PI) controller or another suitable element known in the art.
In an exemplary embodiment, the flux estimator 126 also calculates or otherwise estimates rotor flux angle (θe) for the rotor of the electric motor 106 based on the relationship between the synchronous motor current (ide, iqe) and the synchronous motor voltage (vde, vqe). In the illustrated embodiment of
The current regulator 118 regulates the currents through the stator by generating and/or providing a voltage command for the inverter module 104 corresponding to a commanded voltage for the stator of the electric motor 106 such that the measured currents through the stator are regulated to or otherwise track the commanded motor current (or current command). In an exemplary embodiment, the current regulator 118 is realized as a synchronous frame current regulator configured to generate the voltage command in the synchronous reference frame (vde*, vqe*) (alternatively referred to herein as the synchronous frame voltage commands) based on the difference between the commanded current (ide*, iqe*) (alternatively referred to herein as the synchronous frame current commands) and the measured motor current (ide, iqe)(alternatively referred to herein as the synchronous frame motor currents). In this regard, in accordance with one or more embodiments, the second summing junction 115 determines a q-axis current error command (iq
As set forth above, the first transformation block 120 transforms the synchronous frame voltage commands (vde*, vqe*) from the output of the current regulator 118 to the stationary reference frame, resulting in three-phase stationary voltage commands (vas*, vbs*, vcs*) corresponding to commanded voltages for the respective phases of the stator of the electric motor 106. In an exemplary embodiment, the inverter module 104 is configured to process the stationary voltage commands and generate PWM command signals for operating the phase legs of the power inverter to provide the commanded voltages to the respective phases of the stator in a conventional manner, as will be appreciated in the art. In this manner, changes in the synchronous frame voltage commands (vde*, vqe*) produce corresponding changes in stationary voltage commands, and thus, the duty cycles of the PWM commands used to modulate the switches of the inverter phase legs. In this regard, the synchronous frame voltage commands (vde*, vqe*) may be used to estimate the rotor flux (λe) and transformation angle (θe) (e.g., vde*≈vde, vqe*≈vqe), based on the assumption that the inverter module 104 is accurately reproducing the commanded voltages (vas*, vbs*, vcs*) in the stator and in lieu of using voltage sensors to sense the voltage across the stator or performing other computationally intensive tasks to obtain the motor voltage.
Referring now to
Referring again to
As depicted in
In addition, a resolver angle (θr) is obtained (step 204). The resolver angle (θr) represents an angle of the rotor. In a preferred embodiment, the resolver angle (θr) is obtained by the rotor diagnostic block 128 of
A flux angle (θe) is also obtained (step 206). The flux angle (θe) represents an angle of the flux of the rotor. In a preferred embodiment, the flux angle (θe) is obtained by the rotor diagnostic block 128 of
A first transformation angle is then calculated (step 208). In a preferred embodiment, the first transformation angle is calculated using the resolver angle (θr), the flux angle (θe), or both. In a preferred embodiment, the first transformation angle is calculated by the rotor diagnostic block 128 of
In a preferred embodiment, a second transformation angle is also calculated (step 210). In a preferred embodiment, the second transformation angle is calculated using the resolver angle (θr) (after conversion into the appropriate respective units for the embodiments of
As described above, in the embodiment of
Transformations are then conducted for the motor current of step 202 using the first and second transformation angles (step 212). In a preferred embodiment, transformations are conducted for the measured current of only one phase from the current sensors 112 of
Multiple fault components are calculated using the different transformations (step 214). In a preferred embodiment, the fault components are calculated by the rotor diagnostic block 128 of
The fault components are then utilized to calculate a fault index for the rotor (step 216). The fault index comprises a value that can then be used in comparison with a know table or other set of values in identifying whether there are any faults in the rotor, and that can also be used in identifying the specific nature and severity of any such faults. In a preferred embodiment, the fault index is calculated by the rotor diagnostic block 128 of
Specifically, in a preferred embodiment, first a determination is made as to whether there is a fault present rotor (step 217). In a preferred embodiment, this determination is made by the rotor diagnostic block 128 of
In an exemplary embodiment, if the rotor diagnostic process 200 determines in step 217 that a fault condition does not exist, then the process returns to step 202, and steps 202-217 repeat until there is a determination in an iteration of step 217 that a fault is present in the rotor of the engine. If a determination is made in any iteration of step 217 that a fault is present in the rotor, then the specific nature and severity of the fault are determined in step 218 using the fault index calculated in step 216 and comparing the fault index value with a know table or other set of values corresponding to possible faults in the rotor and severities thereof, for example based on prior knowledge, publications, and/or experimental data. In a preferred embodiment, these determinations are made by the rotor diagnostic block 128 of
Also in a preferred embodiment, one or more remedial actions are implemented to help remedy such a fault of the rotor (step 220). In a preferred embodiment, the remedial action is tailored to the specific fault and severity thereof as determined in step 218 above. Also in a preferred embodiment, the remedial action is initiated by the rotor diagnostic block 128 of
As referenced above,
In the first variation algorithm 300 embodiment of
In addition, the second transformation angle (referenced in step 210 of
Second Transformation Angle=(θe)−2(θslip)
In a preferred embodiment, these calculations are made by the rotor diagnostic block 128 of
The transformations (referenced in step 212) of the measured motor current of one phase from the current sensor 112 obtained in the above-described step 202 used during the transformation process are then performed in accordance with steps 302 and 312 of
fbroken bar=(1±2ks)f1,
in which broken bar is the estimated number of broken bars, f1 is the fundamental frequency, s is the slip angle, and k is a predetermined constant. In addition, also in a preferred embodiment, the first and second transformations of steps 302 and 312, respectively, are conducted by the rotor diagnostic block 128 of
The fault component calculations (referenced in step 214) are then performed in accordance with steps 304, 306, 314, and 316 of
The different fault components are then combined together in step 318 in order to generate a fault index of step 320. In the depicted embodiment, the fault components of steps 306 and 316 are combined in step 318 in accordance with the following equation:
(ILSB/IP)×NB,
in which ILSB represents the lower side-band current value (i.e., the second fault component of step 316), IP represents the positive-sequence current value (i.e., the first fault component of step 306), and NB represents the number of bars on the rotor. This equation can be utilized in calculated an expected number of broken bars for the rotor (preferably rounded off to the nearest integer value) as represented in the numerical fault index value of step 320 (also corresponding to step 216 of
The estimated number of broken bars of the rotor also serves as a measure of the type and severity of the fault in step 322 (also corresponding to step 218 of
In the second variation algorithm 400 embodiment of
First Transformation Angle(combined angle)=(θe)+(θr)
In a preferred embodiment, this calculation is made by the rotor diagnostic block 128 of
In addition, the second transformation angle (referenced in step 210 of
Second Transformation Angle(difference angle)=(θe)−(θr)
In a preferred embodiment, this calculation is also made by the rotor diagnostic block 128 of
The transformations (referenced in step 212) of the motor current are then performed in accordance with steps 404 and 412 of
In addition, also in a preferred embodiment, the first and second transformations of steps 404 and 412, respectively, are conducted by the rotor diagnostic block 128 of
The fault component calculations (referenced in step 214) are then performed in accordance with steps 406, 408, 414, and 416 of
The different fault components are then combined together in step 417 and normalized in step 418 to generate a fault index of step 420. In the depicted embodiment, the fault components of steps 408 and 416 are added together in step 417 in accordance with the following equation:
IUSB+ILSB=Combined Value,
in which IUSB represents the upper side-band current value (i.e., the first fault component of step 408) and ILSB represents the lower side-band current value (i.e., the second fault component of step 416). The resulting combined value is then preferably normalized with respect to a no-load current in step 418. In a preferred embodiment, the calculations and normalization of steps 417 and 418 are conducted by the rotor diagnostic block 128 of
The normalized value is then used for the fault index of step 420 (also corresponding to step 216 of
Due to the transformation angles and techniques utilized in the above-described systems and processes, improve diagnostics can be performed for rotors of electrical systems, for example in vehicle motors. For example, the disclosed systems and processes offer a method of online diagnostic and condition monitoring of rotor faults in induction machines using only one current sensor measurement. The disclosed systems and processes utilize a Reference Frame Theory approach, and are designed to function under field-oriented control (FOC) operation. For example, because the side-band frequency components, due to rotor fault, appear in all phases of the stator currents, only the current measurement of one phase is required.
This represents a significant improvement over prior techniques. For example, in some prior techniques that use a Reference Frame Theory approach for fault detection, all three current measurement are used for the transformation process, as opposed to using one current measurement in the disclosed embodiment. Using one current sensor measurement can be particularly beneficial in systems which have remedial control in the event of a current sensor failure. In such a case, the present method can still be employed, even though prior techniques which utilized all three current measurements would not be able to perform. Also, in some prior techniques, these fault components can also be obtained using a Fast Fourier Transform. However, such prior techniques are not applicable for online diagnostic. In the disclosed embodiment, Reference Frame Theory approach is adopted for online fault detection, with improved results.
For example, in the case of broken rotor bar fault (corresponding to the first variation algorithm 300 of
fbroken bar=(1±2ks)f1
Specifically, by leveraging the available information signals (such as the motor speed from a resolver or rotor position sensor) present in the FOC system, the measured current can be transformed to a reference frame rotating at (1−2s)f1. In this reference frame, the respective side-band component at (1−2s)f1 will appear as a dc component, whereas the rest of the harmonic terms present in the motor current signal will appear as ac harmonic components. Using a low-pass filter, the amplitude of this side-band component can be extracted for fault severity assessment. In the above-described example, the side-band component at (1−2s)f1, (referenced above as the LSB or lower side-band) was selected as the fault indicator, due for example to the fact that the LSB component is primarily related to rotor broken bar fault, whereas the side-band component at (1+2s)f1, (referenced above as the USB or upper side-band) may be associated with speed ripple effect as a result of rotor fault, and this USB component is inertia dependent. In addition, having the knowledge of the amplitude of LSB component can be important in estimating the severity of the fault, for example, the number of broken bars in the rotor in the above-described exemplary embodiment of
By way of further example, in the case of rotor fault eccentricity faults (corresponding to the second variation algorithm 400 of
By monitoring and comparing the amplitudes of the side-band components at the respective frequencies as given in this above equation with the baseline healthy data, one can identify whether there is an eccentricity fault based on the rate of change of the side-band amplitudes, and may also obtain information as to the severity of such an eccentricity fault of the rotor, if one exists.
Accordingly, the disclosed methods and systems provide improved techniques for performing fault diagnosis for rotors of electric motors, such as in the automotive industry. For example, the disclosed methods and systems may provide improved results, may require fewer sensors and/or other apparatus, and/or may be easier and/or more cost effective to implement as compared with prior techniques.
It will be appreciated that the disclosed method and systems may vary from those depicted in the Figures and described herein. For example, as mentioned above, certain elements of the electrical system 100 of
While at least one exemplary embodiment has been presented in the foregoing detailed description, it should be appreciated that a vast number of variations exist. It should also be appreciated that the exemplary embodiment or embodiments described herein are not intended to limit the scope, applicability, or configuration of the claimed subject matter in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing the described embodiment or embodiments. It should be understood that various changes can be made in the function and arrangement of elements without departing from the scope defined by the claims, which includes known equivalents and foreseeable equivalents at the time of filing this patent application.
Number | Name | Date | Kind |
---|---|---|---|
6069467 | Jansen | May 2000 | A |
6236947 | Dowling et al. | May 2001 | B1 |
6308140 | Dowling et al. | Oct 2001 | B1 |
6462491 | Iijima et al. | Oct 2002 | B1 |
6566830 | Walters | May 2003 | B2 |
6636823 | Unsworth et al. | Oct 2003 | B1 |
6741060 | Krefta et al. | May 2004 | B2 |
6828752 | Nakatsugawa et al. | Dec 2004 | B2 |
6838844 | Shimizu et al. | Jan 2005 | B2 |
6838848 | Shindo | Jan 2005 | B2 |
7075260 | Maeda | Jul 2006 | B2 |
7116068 | Boesch et al. | Oct 2006 | B2 |
7116077 | Raftari et al. | Oct 2006 | B2 |
7151354 | Yoshinaga et al. | Dec 2006 | B2 |
7176652 | Wakabayashi et al. | Feb 2007 | B2 |
7243006 | Richards | Jul 2007 | B2 |
7286906 | Richards | Oct 2007 | B2 |
7474067 | Ueda et al. | Jan 2009 | B2 |
7577545 | Hu | Aug 2009 | B2 |
7671552 | Tonamai et al. | Mar 2010 | B2 |
7768220 | Schulz et al. | Aug 2010 | B2 |
8044678 | Kao et al. | Oct 2011 | B2 |
20020145837 | Krefta et al. | Oct 2002 | A1 |
20020172509 | Kameya et al. | Nov 2002 | A1 |
20030034751 | Walters | Feb 2003 | A1 |
20030062868 | Mir et al. | Apr 2003 | A1 |
20030086222 | Stoupis et al. | May 2003 | A1 |
20030107339 | Shimizu et al. | Jun 2003 | A1 |
20030193310 | Raftari et al. | Oct 2003 | A1 |
20030227271 | Shindo | Dec 2003 | A1 |
20040103719 | Raftari et al. | Jun 2004 | A1 |
20040109267 | Habetler | Jun 2004 | A1 |
20040134267 | Boesch et al. | Jul 2004 | A1 |
20040169482 | Maeda | Sep 2004 | A1 |
20050029972 | Imai et al. | Feb 2005 | A1 |
20050073280 | Yoshinaga et al. | Apr 2005 | A1 |
20060138992 | Yamamoto | Jun 2006 | A1 |
20060192512 | Maeda | Aug 2006 | A1 |
20060192513 | Maeda | Aug 2006 | A1 |
20060192516 | Maeda | Aug 2006 | A1 |
20070052381 | Ueda et al. | Mar 2007 | A1 |
20070069682 | Ide et al. | Mar 2007 | A1 |
20080300820 | Hu | Dec 2008 | A1 |
20090021194 | Tonamai et al. | Jan 2009 | A1 |
20090189561 | Patel et al. | Jul 2009 | A1 |
20090261770 | Fujishiro et al. | Oct 2009 | A1 |
20090261774 | Yuuki et al. | Oct 2009 | A1 |
20090267555 | Schulz et al. | Oct 2009 | A1 |
20100169030 | Parlos | Jul 2010 | A1 |
20100295491 | Schulz et al. | Nov 2010 | A1 |
Number | Date | Country | |
---|---|---|---|
20110089882 A1 | Apr 2011 | US |