电动汽车用永磁同步电机模型预测MRAS无速度传感器控制

针对电动汽车机械式传感器在复杂工作环境下易失效的问题,将基于模型参考自适应(MRAS)的无速度传感器技术应用于电动汽车中。针对传统MRAS无速度传感器控制存在的转子位置估计相位延迟较大、转速估计误差较大等问题,将模型预测控制算法应用到MRAS中。参考模型选用永磁同步电机(PMSM)电流磁链方程,可调模型选取电压磁链方程,代价函数是磁链的差值,待估计参数选择转子位置。与传统MRAS无速度传感器控制算法相比,转速、转子位置估计结果更加精确,估计误差较小,动态性能和稳态性能优良。通过仿真和试验验证了算法的可行性和有效性。

Sensorless Control of Permanent Magnet Synchronous Motor for Electric Vehicle Based on Model Predictive MRAS

Aiming at the problem that mechanical sensors of electric vehicle were easy to fail in complex working environment, the speed sensorless technology based on model reference adaptive system (MRAS) was applied to electric vehicle. In order to solve the problem of large phase delay of rotor position estimation and large speed estimation error in traditional MRAS speed sensorless control, the model predictive control algorithm was applied to MRAS. Permanent magnet synchronous motor (PMSM) current flux linkage equation was selected as the reference model, and voltage flux linkage equation was selected as the adjustable model. The cost function was the difference of flux linkage, and the rotor position was selected as the estimated parameters. Compared with the traditional MRAS speed sensorless control algorithm, the proposed algorithm had more accurate speed and rotor position estimation, less estimation error, and excellent dynamic and steady state performance. The feasibility and effectiveness of the algorithm were verified by simulation and experiment.