基于遗传算法和转矩分配函数的开关磁阻电机转矩脉动抑制

开关磁阻电机(SRM)特殊的双凸极结构导致其运行时会产生很强的转矩脉动。传统的转矩分配函数(TSF)控制方法虽然可以在一定程度上起到抑制转矩脉动的作用,但是受到开关频率、功率电源电压值等物理条件的限制,仍会存在较大的转矩脉动。为此,提出了一种基于遗传算法的SRM TSF控制方案。利用遗传算法良好的寻优能力,在指数型TSF控制的基础上,将转矩脉动作为优化目标来寻取最优的开关角。将1台四相8/6极的SRM作为研究对象,搭建了以TMS320F28335为控制核心的试验平台。试验结果验证了基于遗传算法的TSF控制方法可以有效减小SRM的转矩脉动。

Torque Ripple Suppression of Switched Reluctance Motor Based on Genetic Algorithm and Torque Sharing Function

Torque ripple of switched reluctance motor (SRM) was inevitable due to its special doubly salient motor structure. Although the conventional torque sharing function (TSF) control method of SRM could largely suppress the torque ripple, the torque ripple suppression was still limited by the physical conditions such as the switching frequency and the power supply voltage. A TSF control method was proposed based on genetic algorithm. The torque ripple was used as the optimization target to find the optimal switching angle using the optimization ability of the genetic algorithm. The experimental system based on genetic algorithm using TMS320F28335 was established. The experimental results on designed controller for a 8/6 prototype SRM validated the effectiveness of torque ripple minimization.