A novel method for accurate modeling of a switched reluctance motor with low measurement effort

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2025-05-22 DOI:10.1016/j.measurement.2025.117792

Linhao Sheng , Guofeng Wang , Yunsheng Fan , Jian Liu , Di Liu

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引用次数: 0

Abstract

This paper suggests a novel method for accurately determining the flux-linkage characteristics of a switched reluctance motor (SRM) with low measurement effort. The method integrates both static and dynamic measurements without rotor clamping devices and position sensors. The static flux-linkage characteristics at four torque-balanced positions are measured first, and an error compensation scheme is introduced. Through this compensation, the influence of magnetic coupling between phases is minimized. Then, a rotational measurement method is developed that greatly increases the flux-linkage data between balanced positions with low measurement effort. Finally, based on the obtained sample data, the complete flux-linkage characteristics are constructed by integrating the transfer learning method into a back-propagation (BP) neural network. The accuracy of the constructed model is verified by comparison with the measurement results of the rotor clamping method. Additionally, the advantages and feasibility of the proposed method are further verified through dynamic performance comparisons and experimental tests.

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一种低测量量、精确建模开关磁阻电机的新方法

本文提出了一种新的方法，能以较低的测量量精确测定开关磁阻电机的磁链特性。该方法集成了静态和动态测量，不需要转子夹紧装置和位置传感器。首先测量了四个力矩平衡位置的静磁链特性，并提出了误差补偿方案。通过这种补偿，使相间磁耦合的影响降到最低。然后，开发了一种旋转测量方法，以较低的测量工作量大大增加了平衡位置之间的磁链数据。最后，基于获得的样本数据，将迁移学习方法集成到BP神经网络中，构建完整的通量-链接特征。通过与转子夹紧法测量结果的对比，验证了所建模型的准确性。通过动态性能对比和实验测试，进一步验证了所提方法的优越性和可行性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.