感应电动机降低开关频率的多步模型预测控制

Qingxuan Wang, Yunpeng Zhang, Haidong Cao, Qing Bi
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引用次数: 0

摘要

针对小功率异步电机能效低的问题,提出了一种降低逆变器开关频率的多步模型预测电流控制策略。该策略基于电机驱动系统的离散数学模型,采用二次插值迭代预测方法扩展各允许开关序列对应的电流轨迹,并以预测范围内的平均开关频率作为代价函数。为了实时获取理想的切换向量,代价函数进行在线滚动优化。与模型预测直流控制相比,该方法可以降低两电平逆变器的平均开关频率,同时提高电流谐波性能。仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multistep Model Predictive Control of Induction Motors for Reducing Switching Frequency
A multistep model predictive current control strategy for reducing the switching frequency of inverters is proposed to address the challenges of low energy efficiency of small power induction motors. Based on the discrete mathematical model of the motor drive system, the strategy extends the current trajectory corresponding to each allowable switching sequence employing iterative prediction with quadratic interpolation, and uses average switching frequency within the predicted range as a cost function. In order to acquire the ideal switching vector in real-time, the cost function conducts online rolling optimization. Compared to model predictive direct current control, this method can reduce the average switching frequency of the two-level inverter while enhancing current harmonic performance. The simulation results verify the efficiency of the proposed method.
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