State-of-health monitoring and fault diagnosis with adaptive thresholds for integrated vehicle stability system

• US 20070067078A1
• Filed: 09/16/2005
• Published: 03/22/2007
• Est. Priority Date: 09/16/2005
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (Motors Liquidation Co. GUC Trust)
• Inventors: Salman, Mutasim, Howell, Mark
• Granted Patent: US 7,376,499 B2
• Time in Patent Office: Days
• US Class Current: 701/34
• CPC Class Codes: G01R 31/007 using microprocessors or computers
• CPC Class Codes: G01R 31/2829 Testing of circuits in sensor or actuator systems testing of apparatus for measuring electric or magnetic variables G01R35/00; testing of indicating or recording apparatus G01D; in airbag systems B60R21/0173; checking gas analysers G01N33/007; monitoring or fail-safe circuits for electromagnets H01F7/1844
• CPC Class Codes: G01R 31/2846 using hard- or software simulation or using knowledge-based systems, e.g. expert systems, artificial intelligence or interactive algorithms

Abstract

A system and related method for monitoring the state of health of sensors in an integrated vehicle stability control system. In one embodiment, the system determines whether a yaw rate sensor, a lateral acceleration sensor or a hand-wheel angle sensor has failed. The system uses a plurality of models to generate estimates of the outputs of the sensors based on the actual sensor measurements. Residuals are generated as the difference between the measured value and each of the estimates for the particular sensor. The residuals are compared to a threshold to determine whether a fault flag will be set for each residual. The threshold for the hand-wheel angle sensor is an adaptive threshold because it does not have physical redundancy. If the fault flags for the residuals for each sensor have a particular pattern, then a fault is output for that sensor.

Claims

1. A method for determining whether a sensor in a vehicle has failed, said method comprising:

generating a plurality of estimates of an output of the sensor based on a plurality of models;

comparing the estimates to a measured output signal from the sensor to generate a plurality of residuals;

comparing the plurality of residuals to a threshold;

providing a first value if the residual exceeds the threshold and a second value if the residual does not exceed the threshold; and

determining that the sensor has failed if the pattern of the values is a predetermined pattern.

2. The method according to claim 1 wherein the sensor is selected from the group consisting of a hand-wheel angle sensor, a lateral acceleration sensor and a yaw rate sensor.

3. The method according to claim 1 wherein the threshold is an adaptive threshold that varies depending on measured values from certain vehicle sensors.

4. The method according to claim 3 wherein the certain vehicle sensors include a lateral acceleration sensor and a yaw rate sensor.

5. The method according to claim 3 wherein the sensor is a hand-wheel angle sensor.

6. The method according to claim 1 wherein generating a plurality of estimates of an output of the sensor based on a plurality of models includes generating a plurality of estimates of an output of the sensor based on a plurality of models, where the models use measurements from a plurality of sensors.

7. The method according to claim 1 wherein generating a plurality of estimates of an output of the sensor based on a plurality of models includes using three different models.

8. The method according to claim 1 wherein the sensor is part of an integrated vehicle stability system.

9. The method according to claim 8 wherein the integrated vehicle stability system includes an active braking control sub-system, an active front-wheel steering assist sub-system and a semi-active suspension sub-system.

10. A method for determining whether one or more of a plurality of sensors in a vehicle have failed, said method comprising:

providing a hand-wheel angle sensor for providing a road wheel angle signal;

providing a lateral acceleration sensor for providing a lateral acceleration signal;

providing a yaw rate sensor for providing a yaw rate signal;

providing a vehicle speed sensor for providing a vehicle speed signal;

generating a plurality of road wheel angle estimates of an output of the hand-wheel angle sensor based on a plurality of road wheel angle models, said road wheel angle models using the lateral acceleration signal, the yaw rate signal and the vehicle speed signal;

generating a plurality of lateral acceleration estimates of an output of the lateral acceleration sensor based on a plurality of lateral acceleration models, said lateral acceleration models using the road wheel angle signal, the yaw rate signal and the vehicle speed signal;

generating a plurality of yaw rate estimates of an output of the yaw rate sensor based on a plurality of yaw rate models, said yaw rate models using the lateral acceleration signal, the road wheel angle signal and the vehicle speed signal;

comparing the road wheel angle estimates to the road wheel angle signal to generate a plurality of road wheel angle residuals;

comparing the lateral acceleration estimates to the lateral acceleration signal to generate a plurality of lateral acceleration residuals;

comparing the yaw rate estimates to the yaw rate signal to generate a plurality of yaw rate residuals;

comparing the plurality of road wheel angle residuals to an adaptive threshold that changes for different vehicle operating conditions, said adaptive threshold being based on the lateral acceleration signal and a derivative of the yaw rate signal;

comparing the plurality of lateral acceleration residuals to a lateral acceleration threshold;

comparing the plurality of yaw rate residuals to a yaw rate threshold;

providing a first value if the particular residual exceeds the particular threshold and a second value if the particular residual does not exceed the particular threshold;

determining that the hand-wheel angle sensor has failed if the pattern of the first and second road values is a predetermined pattern;

determining that the lateral acceleration sensor has failed if the pattern of the first and second values is a predetermined pattern; and

determining that the yaw rate sensor has failed if the pattern of the first and second values is a predetermined pattern.

11. The method according to claim 10 wherein generating a plurality of estimates of an output of the hand-wheel angle sensor, the lateral acceleration sensor and the yaw rate sensor includes using three separate road wheel angle models, three separate lateral acceleration models and three separate yaw rate models.

12. The method according to claim 10 wherein the sensors are part of an integrated vehicle stability system.

13. The method according to claim 12 wherein the integrated vehicle stability system includes an active braking control sub-system, an active front-wheel steering assist sub-system and a semi-active suspension sub-system.

14. A system for monitoring a particular sensor in a vehicle, said system comprising:

a plurality of vehicle sensors providing measured output signals of vehicle parameters;

a model processor for generating a plurality of estimate signals of the output of the particular sensor based on a plurality of models, wherein the models use the measured output signals of vehicle parameters;

a first comparator responsive to a measured signal from the particular sensor and the estimate signals, said first comparator generating a plurality of residuals based on the difference between the measured signal and the estimate signals;

a threshold processor generating a threshold signal;

a second comparator responsive to the plurality of residuals and the threshold signal, said second comparator outputting a first value if the residual is greater than the threshold signal and a second value if the residual is less than the threshold signal; and

a decision logic processor responsive to the plurality of first and second values, said decision logic processor determining that the particular sensor has failed if the pattern of values is a predetermined pattern.

15. The system according to claim 16 wherein the plurality of sensors are selected from the group consisting of a hand-wheel angle sensor, a lateral acceleration sensor, a vehicle speed sensor and a yaw rate sensor.

16. The system according to claim 14 wherein the threshold processor is an adaptive threshold processor that provides an adaptive threshold that changes in response to the measured signals from at least two of the plurality of sensors.

17. The system according to claim 16 wherein the at least two sensors are a yaw rate sensor and a lateral acceleration sensor.

18. The system according to claim 16 wherein the particular sensor is a hand-wheel angle sensor.

19. The system according to claim 14 wherein the model generator uses three separate models.

20. The system according to claim 14 wherein the system is part of an integrated vehicle stability system.

21. The system according to claim 20 wherein the integrated vehicle stability system includes an active braking control sub-system, an active front-wheel steering assist sub-system and a semi-active suspension sub-system.