Observer design for four-wheel independent control electric vehicle states based on dual strong tracking filter

Abstract

High failure rate caused by distributed driving and the model uncertainty of the four-wheel independent control electric vehicle (FWI-EV) bring motion-state-identified challenges. For solving the identified problem and achieving accurate motion states of FWI-EV, this paper designs an innovative motion state observer based on dual strong tracking filter (DSTF), which consists of vehicle and driving identification layers. The strong tracking filter (STF) with time-varying fading factor is firstly introduced in driving identification layer to rapidly and accurately identify the driving torque mutation of driving system. The driving torque mutation is considered in the vehicle identification layer by data sharing between the two identification layers. The vehicle motion states fluctuated by driving torque mutation are accurately identified by vehicle identification layer based STF. The effectiveness of the design method has been validated by simulations.