A fuzzy coefficient deep flux weakening algorithm for IPMSM without out-of-control

IF 6.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions Pub Date : 2024-07-17 DOI:10.1016/j.isatra.2024.07.018

Chengling Lu , Junhui Cheng , Xueying Xu , Xin Wang

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引用次数: 0

Abstract

A fuzzy coefficient $q$ -axis current increment flux weakening (FCCIFW) control method is proposed in interior permanent magnet synchronous motor (IPMSM) drives. The proposed FCCIFW not only simplifies the calculation of flux weakening coefficient according to the derived formula, but also avoids the saturation of current regulator. In FCCIFW, the theoretical calculation formula of conversion coefficient is derived firstly, and then the fuzzy rule base is established according to the formula. FCCIFW not only refrains the use of complex flux weakening calculation formula or fixed control parameters, but also refrains the problem of out-of-control in the process of deep flux weakening control, so as to improve the overall performance in the process of flux weakening. The results show that the proposed method has an effective and correct calculation process and results, Compared with different control methods in the operation process, it shows that the proposed method has more stable control effect, which has great application value in engineering.

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用于无失控 IPMSM 的模糊系数深度磁通削弱算法。

在室内永磁同步电机（IPMSM）驱动器中提出了一种模糊系数 q 轴电流增量磁通削弱（FCCIFW）控制方法。所提出的 FCCIFW 不仅简化了根据推导公式计算磁通削弱系数的过程，而且避免了电流调节器的饱和。在 FCCIFW 中，首先推导出转换系数的理论计算公式，然后根据公式建立模糊规则库。FCCIFW 不仅避免了使用复杂的磁通削弱计算公式或固定的控制参数，还避免了深度磁通削弱控制过程中的失控问题，从而提高了磁通削弱过程的整体性能。结果表明，所提出的方法具有有效、正确的计算过程和结果，与运行过程中不同的控制方法相比，所提出的方法具有更稳定的控制效果，在工程中具有很大的应用价值。

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

ISA transactions 工程技术-工程：综合

CiteScore

11.70

自引率

12.30%

发文量

824

审稿时长

4.4 months

期刊介绍： ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.