Fuzzy Sliding Mode Control of Intelligent Electric Vehicles Based on Phase Plane Stability Domain Boundaries

In order to effectively improve the chassis handling stability and driving safety of intelligent electric vehicles (IEVs), especially in combing nonlinear observer and chassis control for improving road handling. Simultaneously, uncertainty with system input, are always existing, e.g., variable control boundary, varying road input or control parameters. Due to the higher fatality rate caused by variable factors, how to precisely chose and enforce the reasonable chassis prescribed performance control strategy of IEVs become a hot topic in both academia and industry. To issue the above mentioned, a fuzzy sliding mode control method based on phase plane stability domain is proposed to enhance the vehicle’s chassis performance during complex driving scenarios. Firstly, a two-degree-of-freedom vehicle dynamics model, accounting for tire non-linearity, was established. Secondly, combing with phase plane theory, the stability domain boundary of vehicle yaw rate and side-slip phase plane based on vehicle dynamic model was drew in real time. The boundary was validated with a high-fidelity CarSim® software and a test rig platform. Thirdly, a fuzzy sliding mode controller based on dynamically identified phase boundary was designed. The stability of the algorithm was validated using Lyapunov theory. Finally, using a cooperative platform of CarSim and Matlab/Simulink, results confirm that the proposed fuzzy sliding mode control method based on phase plane stability domain significantly improves the vehicle’s chassis handling stability and driving safety under various conditions. The research achievements develop a reasonable algorithm to apply to the improving road handling and ride comfort performance for a IEVs.