一个改进的有限集模型预测控制SRM驱动基于电压向量策略的低扭矩波动的SRM驱动的预测控制
Deepak Mohanraj1, Devakirubakaran S2, Praveen Kumar Balachandran3,4
1Department of Electrical and Electronics Engineering, KIT-Kalaignarkarunanidhi Institute of Technology, Kannampalayam post, Coimbatore, Tamil Nādu, 641402, India.
Heliyon
|November 7, 2024
概括
本研究引入了用于电动汽车的交换阻抗电机 (SRM) 的增强有限集模型预测控制 (FS-MPC). 新方法显著降低了扭矩波纹,改善了电动汽车应用的性能.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 电动汽车技术 电动汽车技术
背景情况:
- 开关抗拒电机 (SRM) 提供了坚固的结构和故障耐受性,使它们适合电动汽车 (EV).
- 现有的SRM模型预测控制 (MPC) 方法由于板块划分,电压向量 (VV) 选择和权重因素的问题而遭受高扭矩波动.
- 扭矩波动是电动汽车应用中SRM性能的一个重要限制.
研究的目的:
- 提出和验证一个改进的有限集模型预测控制 (FS-MPC) 策略,用于交换阻力电机 (SRM).
- 为了显著减少SRM驱动器中的扭矩波动,以提高电动汽车 (EV) 的性能.
- 分析非线性SRM机器分析模型的扭矩波纹性能.
主要方法:
- 为非线性SRM分析模型开发了一个新的FS-MPC策略.
- 根据旋转器位置依赖的部门分区,推导出拟议的电压向量 (VV).
- 设计了一个单一的成本函数,其中包含一个权衡因子,用于最佳的控制信号选择,以平滑扭矩.
主要成果:
- 增强的FS-MPC实现了9%的计算扭矩波动.
- 模拟研究和在四相8/6SRM驱动器上的实验验证证了拟议方法的有效性.
- 该方法在减少扭矩波纹方面表现出优异的性能,与减少流量波纹相比.
结论:
- 拟议的FS-MPC非常适合减少SRM驱动器中的扭矩波动.
- 增强的控制策略为电动汽车 (EV) 应用提供了更好的性能.
- 实验结果验证了分析结果和实时实施可行性.
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