Patent Application
20160001695
Not Applicable
The present invention relates generally to inclination measurement of a suspended portion of a vehicle with respect to a non-suspended portion and the control of an electromechanical device or system based upon such measurement.
The total inclination of a vehicle in both pitch and roll (θT, ρT) can be determined when the vehicle is at rest using a 2 or 3 axis accelerometer to determine the Gravity vector's orientation to the axes using trigonometry functions. For example θT and ρT can be calculated from acceleration data provided by a 2 axis accelerometer arranged in a plane parallel to the vehicle's longitudinal and latitudinal axes as θT=arcsine(acceleration along the x axis) and ρT as arcsine(acceleration along the y axis). For a 2 axis accelerometer arranged in a plane normal to the vehicle with the x axis aligned along the longitudinal axis of the vehicle, θT is calculated as the arctangent of the ratio of the acceleration along the x axis to the acceleration along the z axis. Adding an orthogonal third axis allows for calculation of both pitch and roll using the arctangent method. However, a vehicle, during normal operation, experiences acceleration along multiple axes of similar magnitude as the acceleration due to gravity. Low pass filtering can remove much of the interfering accelerations but cannot remove the slow changing accelerations associated with changes in the road inclination.
Measuring the inclination angle of the suspended portion of a vehicle in relation to the unsuspended portion of a vehicle (θ) while the vehicle is in motion with accelerometers or inclinometers is desirable for determining loading conditions of the vehicle. Generally vehicle loading does not change while the vehicle is in motion, therefore θv does not change. Road inclination variations and normal accelerations associated with a moving vehicle are of much greater magnitude than the acceleration changes associated with the change in posture of a vehicle on its suspension system. Road inclinations can change on the order of ±15 degrees, while the suspended portion of a vehicle in relation to the non-suspended portion of the vehicle only changes by approximately ±1.5 degrees.
It would be desirable to have a method and system that provides the ability to calculate the inclination angle θv to a high accuracy independent of the road inclination (θr) which is usable to control a vehicle headlight leveling system, or alternatively other electromechanical or electronic control systems.
In accordance with the present invention, a system and method are disclosed for obtaining a measurement of the inclination of a suspended portion of a moving vehicle in relation to the non-suspended portion independent of the road inclination. The measurement is obtained by examining the dependence of accelerations normal to the suspended portion of the vehicle (z-axis) with respect to longitudinal accelerations of the suspended portion of the vehicle (x-axis). In one embodiment, acceleration data corresponding to two or more axes are collected from an acceleration measuring device such as an accelerometer. A filtering device filters the acceleration data to provided filtered acceleration data and the filtered acceleration data is stored in a memory. A processor generates a least squares best fit regression and calculates a slope from the least squares best fit regression which corresponds to an angle of inclination of the vehicle with respect to the road. In one embodiment, the system produces an output indicative of the angle of inclination of the suspended vehicle portion with respect to the road which is used to control an electromechanical system such as a vehicle headlight leveling system.
The invention will be more fully understood by reference to the Detailed Description of the Invention in conjunction with the Drawings of which:
U.S. provisional patent application 62/020,704 and the disclosure thereof is incorporated herein by reference in its entirety.
The method and system of the present invention is described below in terms of the measurement of the inclination of a suspended portion of a vehicle with respect to the road or a non-suspended portion of the vehicle. The following description and example is intended to be illustrative of one embodiment of the invention and is not to be construed to limit the scope of the invention.
In the figures:
in
A
z
=f(Az
And more particularly:
When θv=0, the last term in the equations 1 and 2 becomes 0, and Az is independent of . When θv≠0, Az is dependent on
and will vary as
Stated another way, when θv is not equal to 0, for any given road inclination, changes in will produce a change in Az equal in magnitude to
Differentiating Az with respect to Ax using z and x instead of Az and Ax yields
The loading condition was changed (loading condition 2) such that θv was increased by 4.05 degrees for an effective θv of 2.16 degrees of inclination. Az and Ax acceleration time series data logged during the drive test is shown in
The method detailed above as applied to acceleration data collected during multiple drives has shown an accuracy of better than 0.1 degrees in determining the inclination θv of a vehicle's suspended section in relation to the non-suspended section of a vehicle independent of the road inclination.
The embodiment detailed here only used z and x acceleration data and a simple fixed window average as the filtering method to illustrate the technique and results achievable, but it should not be construed to preclude other axes of acceleration or more advanced filtering techniques, the effective sampling rate and the like.
A block diagram illustrating one embodiment of the presently disclosed system is illustrated in
Referring to
As the data is collected and processed it is stored in memory 202 for processing. The actual size of the memory array may vary and be determined for a specific vehicle type or class to optimize performance for the characteristics of the vehicle type or class.
Once the predetermined amount of data needed has been collected, a least squares linear regression is calculated 203 for the data set(s). The amount of data needed will vary depending upon vehicle type or class. One way to experimentally determine the amount of data needed to be collected for a particular vehicle type or class is described in the procedure below.
The arctangent of the slope of the calculated linear regression line is taken 204 to determine the inclination of the suspended section of the vehicle with respect the non-suspended portion of the vehicle. The partitioning of the implementation can be achieved in any manner using discrete systems for each functional block or integrating functional blocks together in part or in whole to achieve the same end result.
From a functional flow perspective, acceleration data is gathered 300 from the acceleration sensor(s) 200 at a frequency at least equal to or greater than twice the highest frequency component of interest until a predetermined number of samples are gathered as illustrated in step 302. Sampling frequency is dependent upon the sensor being used and the location of the sensor. If the sensor element has a low pass response with a −3 dB bandwidth of 20 Hz, the sampling frequency needs to at least 40 Hz to prevent aliasing. Furthermore if there is vibration energy larger in magnitude at a frequency where the attenuation of the sensor at that frequency does not reduce the magnitude to a few milli-g's, the sampling frequency must be at least 2× that frequency so the vibrational energy can be averaged out. By way of example, a sensor with a −3 dB bandwidth of 25 Hz and a roll off of 20 dB/decade is mounted in a location that has vibration acceleration of 0.1 g at 50 Hz (3000 RPM). The sensor will attenuate the 50 Hz signal by a factor of 2 (6 dB/decade). The resulting vibration acceleration will be 0.05 g. In this case sampling frequency should be increased to at least 100 Hz, so that energy from the vibration can be averaged or filtered out so as to not cause error in the calculation of θv.
The samples are then filtered using a low pass filter as depicted in step 304 with the desired effect to be attenuation of higher frequency road noise associated accelerations with minimal attenuation of lower frequency vehicle accelerations and decelerations. By way of example, a low pass filter may provide a cutoff frequency of 1 Hertz to attenuate such undesired high frequency road noise. Alternatively, a pass band filter can be used to remove very low frequency accelerations associated with slowly changing road inclination and higher frequency accelerations associated with road noise while passing accelerations associated with vehicle accelerations and decelerations. By way of example and not limitation, the band pass filter may have upper and lower cutoff frequencies of 1 Hertz and 0.1 Hertz respectively to provide desired filtering.
The filtered data points are stored in memory as illustrated in step 306 and the memory pointer is incremented as illustrated in step 308 to the next available memory location in the memory array 202. Once a predetermined number of filtered data points have been gathered to allow for accurate calculation of the slope as determined in decision step 310, for example, in the manner previously described, the data set is checked to see if there is a predetermined amount of variation in the Ax acceleration that will ensure the Az dependence on Ax can be accurately established as depicted in step 312. Once these conditions are met, the data in the memory array 202 may be additionally filtered as illustrated in step 314. By way of example, if the filter selected to filter the acceleration data were a low pass filter, and the vehicle was sitting stationary but running for a few minutes, the data array could be filled with constant acceleration values from which a dependency of Z acceleration on X accelerations cannot be determined. A simple test looking at the range of X acceleration values being greater than some reasonable limit can be used to ensure the data in the array will be able to establish a z dependence on x. Normal vehicle accelerations and decelerations are in the range of 0 to ±0.4 g (range of 0.8 g). Consequently, one could set a minimum limit for the minimum range of the x acceleration data near 0.05 g.
Other ways to qualify the data being put into the array to ensure there is an adequate X acceleration range can be realized using other optional sensors or decision techniques. Data can be qualified for storage in the array only if the vehicle is in motion. By way of example, this can be accomplished using GPS data from a GPS sensor 200d, a wheel speed sensor 200e or gyro information from one or more gyros 200f. Sequential Ax acceleration data points can be compared and Az, Ax data pairs stored only if they are different from the previous Az acceleration value.
For the processed data set, a least squares best fit linear regression line is determined as illustrated in step 316, and θv is calculated by taking the arctangent of the previously calculated linear regression line as shown in step 318. The memory pointer is checked to see if it has reached the end of the memory array as illustrated in step 320 and, if it has, it is reset to the beginning of the memory array so as to overwrite older data with newer data as shown in step 322. Processing then restarts at step 300. The least squares best fit linear regression to find the slope of the filtered acceleration Az vs. Ax data pairs may be calculated as disclosed in Bevington, Philip R., Robinson, Keith D., 2003, Data Reduction and Error Analysis for the Physical Sciences, 3rd ed., (New York, N.Y.: McGraw Hill), Chapter 6, which is incorporated by reference or via any other suitable technique known in the art.
Furthermore, once θv is successfully calculated for the first time, it can be stored in a separate memory section and new values of the θv can optionally be calculated for each new data point generated on a rolling basis.
Supplemental sensor data and GPS data can also be used to establish further confidence and credibility checking. For example, GPS position data combined with known road inclination for a given position can establish reference inclination for non-suspended portion of the vehicle θr. θv can be further calculated and checked by subtracting θr from the instantaneous total angle of inclination θT. θT can be calculated using the same processed acceleration data and simply taking the Arctangent of (Ax/Az).
Wheel speed sensors 200e and engine loading information from an engine load sensor 200f can also be used to determine θr and θv can be calculated in the same manner from θT as described above. Additionally, changes in wheel speed and engine loading can be used to qualify good data as Ax accelerations will be necessarily present and therefor make good candidates for determining Az dependence on Ax accelerations.
Pitch gyro information can be used to monitor changes in θr. When rapid changes in θr are detected, data can be flagged for additional processing or discounting partially or completely.
The above-described method is implemented using a computational device executing program steps out of a memory to provide the functional operations described herein. The data filtering described above may be achieved via analog or digital filtering techniques known in the art.
Once the inclination of the suspended portion of the vehicle with respect to the road has been determined in accordance with the presently described method, the system provides an output signal indicative of the inclination which is employed to generate at least one control signal that is provided to an electromechanical or electronic control system. In the illustrated embodiment, the at least one control signal may be employed to control a headlight leveling system, for example, such as disclosed in US published application 2012/0310486 which is incorporated herein by reference, or any other lamp assemblies providing for headlight leveling in response to a control signal as known in the art. It should be understood that the at least one output signal may alternatively be used to control a device or system for purposes of vehicle electronic stability control, vehicle oil level monitoring tilt correction, vehicle hill start assist, trailer braking, truck load monitoring for scale correction, suspension adjustment to adjust for load variation and other applications in which operation of an electrical, electronic or electromechanical device or system is based, at least in part, upon the inclination of the suspended portion of a vehicle with respect to the road.
While the disclosed system has been described in one embodiment with respect to the control of a headlight leveling substem based on a calculated angle of inclination of a suspended portion of a vehicle with respect to a non-suspended portion of a vehicle, it will be appreciated that the determined angle of inclination of one portion of an object, such as a suspended portion of a moving object, with respect to a non-suspended portion of the moving object or a reference plane, may be used to generate a control signal that is in turn employed as an input to an electromechanical or electronic control subsystem. Thus, while the disclosed technique has been described in terms of its application to a moving vehicle, it is also applicable to other moving objects.
It should be understood by those of ordinary skill in the art that the above-described method and system is illustrative of the present invention and is not to be viewed as limited except by the scope and spirit of the appended claims.
| Number | Date | Country | |
|---|---|---|---|
| 62020704 | Jul 2014 | US |
