永磁游标电机虚拟矢量模型预测控制的研究

Research on Permanent Magnet Vernier Motor Model Predictive Control Based on Virtual Vector

针对永磁游标电机(PMVM)模型预测控制策略中因备选电压矢量少和单个采样周期内电压矢量大小方向受限导致存在控制精度低和输出稳定性差的问题,在研究了传统模型预测控制原理的基础上提出了一种基于虚拟矢量的双矢量模型预测控制策略,该控制策略通过构建虚拟矢量的方法扩展了电压矢量有限集个数,在此基础上设计双矢量模型预测控制器,并对代价函数进行优化,提高了控制系统的稳定性和精确性,同时也减小了逆变器的损耗。最后在仿真软件中搭建控制系统模型进行对比仿真验证。结果表明,所提出的控制策略相比与传统模型预测控制策略有更好的动态稳定性和抗干扰性以及更高的控制精度。

Aiming at the problems of low control accuracy and poor output stability in the model prediction control strategy of permanent magnet vernier motor(PMVM)due to few alternative voltage vectors and limited voltage vector size and direction in a single sampling period,a dual-vector model prediction control strategy based on virtual vector is proposed based on the principle of traditional model prediction control strategy,which constructs a virtual vector method this control strategy extends the number of finite sets of voltage vectors by constructing virtual vectors,and on this basis,a two-vector model predictive controller is designed and the cost function is optimized,which improves the stability and accuracy of the control system and reduces the losses of the inverter.Finally,the control system model is built-in the simulation software for comparative simulation verification.The results show that the proposed control strategy has better dynamic stability and interference immunity as well as higher control accuracy compared with the traditional model prediction control strategy.