Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking
Steer-by-Wire (SBW) systems are an integral and essential component of intelligent electrified vehicles and are critical to ensure safe vehicle operations. In this paper, a fault-tolerant control method for SBW is proposed to mitigate the adverse influence of front wheel steering angle sensor faults...
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doaj-e033c6236f1f426bbb2a82f89caad6882021-05-03T23:00:29ZengIEEEIEEE Access2169-35362021-01-019651746518610.1109/ACCESS.2021.30753259411842Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory TrackingLei Zhang0https://orcid.org/0000-0002-1763-0397Zihao Wang1https://orcid.org/0000-0002-7947-0966Xiaolin Ding2https://orcid.org/0000-0001-9051-8791Shaohua Li3https://orcid.org/0000-0002-6952-5978Zhenpo Wang4https://orcid.org/0000-0002-1396-906XBeijing Collaboration Innovation Center for Electric Vehicles, Beijing Institute of Technology, Beijing, ChinaBeijing Collaboration Innovation Center for Electric Vehicles, Beijing Institute of Technology, Beijing, ChinaBeijing Collaboration Innovation Center for Electric Vehicles, Beijing Institute of Technology, Beijing, ChinaState Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures, Shijiazhuang Tiedao University, Shijiazhuang, ChinaBeijing Collaboration Innovation Center for Electric Vehicles, Beijing Institute of Technology, Beijing, ChinaSteer-by-Wire (SBW) systems are an integral and essential component of intelligent electrified vehicles and are critical to ensure safe vehicle operations. In this paper, a fault-tolerant control method for SBW is proposed to mitigate the adverse influence of front wheel steering angle sensor faults based on the Kalman filtering technique. First, a linearized vehicle model is derived based on tire characteristics and is further combined with a steering actuator model to provide the modelling foundation for estimating the front wheel steering angle. Considering multi-source noises and their significant influence on the front wheel steering angle sensor, the Butterworth filter is employed to filter out the high-frequency noises. The front wheel steering angle estimation is realized by incorporating the measurements of the yaw rate and lateral acceleration of vehicle and the current of steering motor. In particular, a dynamic threshold mechanism is adopted to activate the fault diagnosis and fault-tolerant compensation based on the residual theory. Finally, a linear time-varying model predictive controller is presented to execute the trajectory tracking task for an intelligent electrified vehicle. The effectiveness of the proposed scheme is verified under the single lane change and double lane change maneuvers during the trajectory tracking.https://ieeexplore.ieee.org/document/9411842/Intelligent electrified vehiclessteer-by-wire systemstate estimationfault-tolerant controltrajectory tracking |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lei Zhang Zihao Wang Xiaolin Ding Shaohua Li Zhenpo Wang |
spellingShingle |
Lei Zhang Zihao Wang Xiaolin Ding Shaohua Li Zhenpo Wang Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking IEEE Access Intelligent electrified vehicles steer-by-wire system state estimation fault-tolerant control trajectory tracking |
author_facet |
Lei Zhang Zihao Wang Xiaolin Ding Shaohua Li Zhenpo Wang |
author_sort |
Lei Zhang |
title |
Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking |
title_short |
Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking |
title_full |
Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking |
title_fullStr |
Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking |
title_full_unstemmed |
Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking |
title_sort |
fault-tolerant control for intelligent electrified vehicles against front wheel steering angle sensor faults during trajectory tracking |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
Steer-by-Wire (SBW) systems are an integral and essential component of intelligent electrified vehicles and are critical to ensure safe vehicle operations. In this paper, a fault-tolerant control method for SBW is proposed to mitigate the adverse influence of front wheel steering angle sensor faults based on the Kalman filtering technique. First, a linearized vehicle model is derived based on tire characteristics and is further combined with a steering actuator model to provide the modelling foundation for estimating the front wheel steering angle. Considering multi-source noises and their significant influence on the front wheel steering angle sensor, the Butterworth filter is employed to filter out the high-frequency noises. The front wheel steering angle estimation is realized by incorporating the measurements of the yaw rate and lateral acceleration of vehicle and the current of steering motor. In particular, a dynamic threshold mechanism is adopted to activate the fault diagnosis and fault-tolerant compensation based on the residual theory. Finally, a linear time-varying model predictive controller is presented to execute the trajectory tracking task for an intelligent electrified vehicle. The effectiveness of the proposed scheme is verified under the single lane change and double lane change maneuvers during the trajectory tracking. |
topic |
Intelligent electrified vehicles steer-by-wire system state estimation fault-tolerant control trajectory tracking |
url |
https://ieeexplore.ieee.org/document/9411842/ |
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