Robust Fault-Tolerant Estimation of Sideslip and Roll Angles for Distributed Drive Electric Buses With Stochastic Passenger Mass
Jinyong Shangguan, Ming Yue, Xu Chen, Jian Zhao
Abstract
Faults or data loss of onboard sensors are a critical concern for active safety control of distributed drive electric buses (DDEBs). In this article, a robust fault-tolerant estimation (RFTE) method is proposed to estimate sideslip and roll angles of DDEB in spite of stochastic disturbances and sensor faults. Considering the effects of sensor faults, stochastic passenger mass and modeling errors on DDEB active safety control, an augmented system consisting of DDEB states and associated sensor faults is firstly constructed, where the disturbances caused by passenger mass and modeling errors are merged as unknown input vector. Then, by decoupling partial disturbances, an unknown input observer is developed to estimate the augmented system states, while a linear matrix inequality and an estimated states correction method are introduced to further attenuate the effects of residual disturbances and thus guarantee the accuracy of the estimation. Finally, the validity of the proposed RFTE method is evaluated by a Trucksim-Simulink co-simulation platform and a hardware-in-the-loop platform. The experimental results demonstrated that the proposed RFTE method can achieve effective estimation in the presence of stochastic disturbances and sensor faults, exhibiting better robustness and reliability than existing baseline estimation method.