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基于ZOH模型和双采样策略的PMSM参数监测在线多参数识别
Sidong He1, Xuewei Xiang1, Hui Li1
1State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China.
这项研究提高了永久磁铁同步电机 (PMSM) 参数识别准确度,使用零顺序保持离散和逆变器非线性补偿. 该方法提高了所有速度的精度,特别是在高速时.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
背景情况:
- 对PMSM的在线参数识别面临来自模型离散,矩阵排序缺陷和逆变器非线性等挑战.
- 现有的方法难以准确,特别是在高速操作下.
研究的目的:
- 提出一个高精度的虚拟传感器,用于PMSM的多参数识别.
- 克服当前识别技术的局限性,在各种操作条件下提高准确性.
主要方法:
- 利用零订单保持 (ZOH) 离散来准确的PMSM建模,并考虑旋转器位置变化.
- 实施了双采样策略与d轴小信号注入相结合,以解决矩阵等级缺陷.
- 使用忘记因子递归最小方程 (FFRLS) 算法进行在线多参数识别.
- 开发了一个逆变器非线性电压补偿策略,考虑了截止时间的影响,电压下降和开启延迟.
主要成果:
- 与前方欧勒相比,ZOH方法显著降低了离谱化误差,特别是在高速时.
- 结合策略有效地解决了识别矩阵中的排名缺陷问题.
- 实验验证证了整个速度范围内的增强参数识别准确性.
- 对于电阻,电感和流量连接的高速识别错误分别为5.47%,4.05%和2.46%.
结论:
- 拟议的方法为准确的在线PMSM参数识别提供了强大的解决方案.
- 集成ZOH离散和逆变器非线性补偿导致卓越的性能,特别是在苛刻的高速条件下.
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