Analysis reveals improved performance optimization in electric vehicles using fault-tolerant control and sliding mode methods while addressing driving system faults.
To address the degradation in power and stability performance induced by single-wheel or multi-wheel faults in the three-axle distributed drive electric vehicle, by combining K-means clustering algorithm, sliding mode method and fault-tolerant control (FTC) algorithm, an innovative adaptive FTC coordination approach is proposed. Firstly, the vehicle system model of the three-axle distributed drive vehicle is developed. Secondly, K-means clustering algorithm is used to classify different fault types based on the vehicle’s ability to maintain power and stability performance requirements. Thirdly, a hierarchical control architecture is designed for the control system: the high-level controller determines the needed longitudinal driving force and obtains the additional generalized torque through the integral sliding mode method to suppress the parameter fluctuation and improve the system robustness; the low-level controller combines the number and degree of motor faults to obtain the corresponding performance optimization objective and adjustment of constraint boundaries, and redistributes the torque by means of a quadratic programming algorithm. Finally, simulation tests of single-wheel and multi-wheel faults are conducted, and the results indicate that the proposed approach achieves the expected performance.
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Li et al. (2025) studied this question.
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