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Torque Performance Improvement of Permanent Magnet Arc Motor Based on Two-Step Strategy

机译：基于两步策略的永磁电弧电动机扭矩性能改进

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摘要

In this article, we present a two-step strategy for the torque performance improvement of a dual-stator permanent magnet arc motor (DS-PMAM), which is used in some industrial applications, such as robot joint. The proposed strategy can achieve high average torque, low torque ripple, and, eventually, improve the quality of manufactured products. In the first step, the no-load torque model caused by the end effect is analytically established. In order to suppress the inductance unbalance and the torque ripple, two DS-PMAM models with different winding connection methods are investigated and compared in terms of inductances, backelectromotive force, and torque characteristics. In the second step, a new sensitivity analysis method based on the shapley additive explanations value is first proposed to evaluate the sensitivity of each structural parameter to different optimization objectives. Then, an efficient optimization design method is proposed by combining the machine learning algorithm named eXtreme gradient boosting (XGBoost) and the intelligent optimization algorithm called nondominated sorting genetic algorithm-II (NSGA-II). The XGBoost is innovatively introduced to efficiently approximate the function relationship between the optimization objectives and the structural parameters. The NSGA-II is adopted to determine the optimal combination of the structural parameters and motor performances. Finally, based on the optimal results obtained by the two-step strategy, a prototype of DS-PMAM is manufactured and tested to validate the proposed strategy.
机译：在本文中，我们为双定子永磁电弧电机（DS-PMAM）的扭矩性能改善提供了两步策略，该扭矩性能改善在一些工业应用中，例如机器人关节。所提出的策略可以实现高平均扭矩，低扭矩波动，并最终提高制造产品的质量。在第一步中，通过对最终效果引起的空载扭矩模型进行了分析建立。为了抑制电感不平衡和扭矩脉动，在电感，硬电器电力和扭矩特性方面，研究了两个具有不同绕组连接方法的DS-PMAM模型。在第二步中，首先提出基于福利添加剂解释值的新灵敏度分析方法来评估每个结构参数对不同优化目标的灵敏度。然后，通过组合名为极梯度升压（XGBoost）的机器学习算法和称为NondoMinated分类遗传算法-II（NSGA-II）的智能优化算法来提出有效优化设计方法。 XGBoost创新地介绍，以有效地近似于优化目标与结构参数之间的功能关系。采用NSGA-II确定结构参数和电动机性能的最佳组合。最后，基于通过两步策略获得的最佳结果，制造和测试DS-PMAM的原型以验证所提出的策略。

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