在SRM驱动器中对增强的有限集模型预测控制和直接扭矩控制进行实验分析,以减少扭矩波动
Deepak M1, Devakirubakaran Samithas2, Praveen Kumar Balachandran3,4
1Department of Electrical and Electronics Engineering, KIT-Kalaignarkarunanidhi Institute of Technology, Kannampalayam Post, Coimbatore, Tamil Nadu, 641402, India.
Scientific reports
|July 22, 2024
概括
本研究引入了一种新的有限集模型预测控制 (FS-MPC) 用于切换阻抗电机 (SRM) 来减少扭矩和流量波动. 拟议的方法有效地减少了电动汽车引力驱动器中的这些波纹.
科学领域:
- 电气工程 电气工程
- 汽车工程 汽车工程
- 控制系统 控制系统
背景情况:
- 交换式阻力电机 (SRM) 提供了成本效益高的电动汽车 (EV) 引驱动解决方案,因为它们的设计没有磁铁.
- 然而,SRM遭受了显著的扭矩和流量波动,特别是在低速时,阻碍了性能.
- 现有的控制策略,如直接扭矩控制 (DTC) 和模型预测控制 (MPC),难以有效地减轻这些波纹.
研究的目的:
- 开发SRM驱动器的先进控制策略,以最大限度地减少扭矩和流量波动.
- 通过解决SRM的局限性来提高电动汽车引系统的性能和效率.
- 提出一种新的有限集模型预测控制 (FS-MPC) 方法来减少波纹.
主要方法:
- 开发了一种有限集模型预测控制 (FS-MPC) 策略,使用单个成本函数目标而没有加权因子.
- 预测的扭矩被用来评估电压向量 (VVs) 以进行最佳选择,最大限度地减少波纹.
- 拟议的FS-MPC在MATLAB/Simulink中进行模拟,并通过SRM驱动器上的实验结果进行验证.
主要成果:
- 与传统的DTC相比,拟议的FS-MPC显著减少了SRM驱动器中的扭矩和流量波动.
- 在稳定状态和动态操作条件下都证明了有效的波纹最小化.
- 模拟和实验结果证实了拟议的控制方法的优越性能.
结论:
- 开发的FS-MPC是一种高效的方法,可以最大限度地减少SRM驱动器中的扭矩和流量波动.
- 这种方法为提高电动汽车引系统的性能和驾驶能力提供了一个有希望的解决方案.
- 拟议的控制策略为无磁引擎提供了更精细,更高效的操作.
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