基于转矩分配函数的开关磁阻电机的效率优化方法

An Efficiency Optimization Method of Switched Reluctance Motor Based on Torque Sharing Function

开关磁阻电机使用传统的转矩分配函数(TSF)控制时虽然可以起到一定的抑制转矩脉动的作用,但却由于换相阶段电流峰值过高,电流可控性下降等问题使得其在换相阶段出现较为明显的转矩脉动,以及较高的铜耗。针对这一问题,提出了一种基于TSF的开关磁阻电机的效率优化方法。将电机特性作为约束条件,以铜耗为优化目标建立最优化模型,利用多重嵌套的遗传算法将该最优化模型应用于Simulink仿真中,得到不同参数下最优的电流参考曲线。再根据不同转速下对电机性能的需求,进一步筛选权重参数,从而得到最优的电流参考曲线。仿真和实验结果表明,该方法能够有效地降低换相阶段的电流峰值、降低电流控制难度,进而在较低转速下抑制转矩脉动、在较高转速下提高效率。

The switched reluctance motor uses the traditional torque sharing function(TSF) control, it can play a certain role in suppressing the torque ripple.However, due to the high current peak during the commutation phase and the decrease of current controllability, obvious torque pulsation and higher copper loss appear in the commutation phase.In order to solve this problem, an efficiency optimization method for switched reluctance motors based on the torque distribution function is proposed.Taking the motor characteristics as constraints, and the copper consumption as the optimization goal, the optimization model is established.The optimization model is applied to Simulink simulation by using multiple nested genetic algorithms to obtain the optimal current reference curve under different parameters.Then according to the demand for motor performance at different speeds, the weight parameters are further screened to obtain the optimal current reference curve.Simulation and experimental results show that this method can effectively reduce the current peak value in the commutation phase, reduce the difficulty of current control, and then suppress the torque ripple at lower speeds and improve the efficiency at higher speeds.