轮毂电机独立驱动电动汽车线性时变模型预测主动安全控制

To address the active safety and parameter estimation of the in-wheel motor driven electric vehicles(IMDEV), an adaptive sideslip angle observer and a line-time-varying(LTV) model predictive controller(MPC) for the yaw stability are proposed. Firstly, an exponential slide mode observer is established and the closed-loop lateral force integration algorithm is utilized to eliminate the static error. Then, a quasi linear tire model is adopted to design the model predictive yaw stability controller. In addition, Laguerre networks are utilized to approximate the full-horizon control sequence. The external yaw moment is obtained by solving the quadratic programming function with inequality constraints, and thereby it is allocated into four in-wheel motors. Results of the numerical simulation and experimental test manifest that the proposed adaptive slide observer can accurately estimate the sideslip angle with high robustness, the proposed yaw stability controller can address the nonlinear tire saturation and enhance the active safety of IMDEV.