The research of traction control for the distributed driven electric vehicle

The distributed driven electric vehicles(DDEV) employ multiple motors driven systems which effectively achieves the electronic chassis and the active safety of vehicle. In this paper, a two-stage strategies of traction control system (TCS) for the DDEV were proposed. In the first stage, a method based on the Single-layer feed-forward neural networks system (SFNN) trained by Extreme Learning Machine (ELM) is proposed for the road condition classification. In the second stage, the Active Disturbance Rejection Control (ADRC)was proposed to design the TCS. The simulation testing results show that the two-stage strategies is designed feasibly and response quickly.