电动汽车用永磁同步电机遗传优化鲁棒控制研究

Robust Control of Genetic Algorithm for Permanent Magnet Synchronous Motor Used in Electric Vehicles

针对四轮毂式电动汽车车用永磁同步电机的车速跟踪问题和由复杂路况引起的负载扰动问题,建立了永磁电机的状态空间模型。利用鲁棒H∞混合灵敏度方法设计了交轴电流环控制器,并采用遗传算法选取最优的鲁棒加权函数。仿真结果表明,即使在系统外界干扰存在的情况下仍能保证整个系统稳定。该方法可以提高汽车在行驶过程中的抗干扰性能和车速跟踪性能。

Aiming at the speed tracking problem and load disturbance problem resulting from the complicated road conditions of the permanent magnet synchronous motor used in four-wheel hub electric vehicle, the state-space model of permanent magnet synchronous motor was established. The quadrature-axis current loop controller was designed by using of robust H-infinity mixed sensitivity method. The optimal robust weighting function was selected through using genetic algorithms. Simulation results show that the closed-loop system is stable regardless of load disturbance. This method can enhance anti-jamming performance and speed tracking performance of the system.