基于状态转移约束的永磁同步电机模型预测控制策略

针对车用永磁同步电机传统模型预测控制方法存在转矩波动和转速波动较大,从而影响汽车乘坐舒适性的问题,提出 了一种新型的考虑永磁同步电机开关切换状态转移概率的改进型模型预测控制方法。 通过永磁同步电机工作中开关切换状态 的历史数据计算状态转移概率矩阵。 在获得转移概率的基础上,根据当前的开关状态和状态转移矩阵得到状态转移约束误差。 接着在模型预测控制算法中制定包含状态转移约束误差项的代价函数,通过代价函数对下一时刻的开关状态进行在线寻优以 获得最优的控制变量。 并基于 MATLAB 平台对该改进型模型预测控制策略进行仿真分析,仿真结果表明,改进型模型预测控 制策略具有更好的转矩和转速响应特性,从而表明基于状态转移的模型预测控制方法能够用于车用永磁同步电机的控制中,并 且对于改善汽车的乘坐舒适性具有重要意义。

Model predictive control method of permanent magnet synchronous motor based on state transition constraint

Conventional model predictive control method of permanent magnet synchronous motor (PMSM) suffers from high torque ripple and speed fluctuation, which affects the ride comfort of vehicle. A model predictive control method based on state transition constraint of a PMSM is proposed. First, the state transition probability matrix is calculated based on the historical data of the switching state of the PMSM. Secondly, the constraint error is obtained according to the current switch state and state transition probability matrix. This constraint error can limit the switching state of the switch at the next moment. Then, the cost function including the state transition constraint error is formulated in the model predictive control algorithm. The optimal switching state at the next moment is searched according to the cost function. The results of simulation study and experiment show that the improved model predictive control strategy proposed in this paper has better torque and speed response characteristics in terms of speed ripple and torque fluctuation. The results show that the proposed model predictive control method based on state transition can be used in the control of vehicle PMSM. It is essential to improve the ride comfort of the vehicle.