무인자율주행 차량의 고장 진단 알고리즘 검증

Actuators and sensors fault diagnosis is very important in autonomous vehicle system. In this research, fault diagnosis algorithm for yaw-rate sensor, lateral acceleration sensor, steering wheel angle sensor, steer-by-wire, throttle-by-wire, and brake-by-wire of an autonomous driving vehicle is designed. Vehicle sensors and steer system fault diagnosis algorithm consists of yaw-rate residuals which are differences between yaw-rate sensor signal and estimations. Thresholds of residuals are based on the actual vehicle actuator dynamics. Throttle system fault diagnosis algorithm and brake system fault diagnosis algorithm consist of longitudinal acceleration residual which is difference between longitudinal acceleration sensor and desired acceleration. Vehicle acceleration sensor and yaw-rate sensor signals are estimated by Kalman filter. Acceleration estimation of both throttle system fault diagnosis algorithm and brake system fault diagnosis algorithm consider the angle of inclination which can be estimated by difference between longitudinal acceleration and wheel acceleration. In order to verify this algorithm, Hardware-in-the-loop simulation is executed.