Rail transportation interior permanent magnet synchronous motor traction control system (IPMSM TCS) requires high torque output capability. Traditional algorithms used to find the maximum torque per ampere (MTPA) operating point in TCS have strong dependence on motor parameters. Because the algorithm is less robust to motor parameters, there will be deviation between the MTPA operating point and the actual value when the parameters change, so that it is difficult to guarantee the torque output capability of the traction system under different working conditions. This paper introduces a current angle signal injection control method (CASIM) to solve this problem. The proposed method tracks the MTPA operating point and generates d-axis current command according injecting an angle signal to current and making the partial derivative of torque to current angle equal to zero. At the same time, less motor parameters are needed to calculate the torque in this method. Consequently, in the process of looking for MTPA operating point, the accuracy is less affected by the variation of motor parameters. And also it does not inject any real signal to IPMSM, so that it does not increase copper and iron losses. Moreover, it is robust to speed mutation and torque disturbances. The effectiveness of CASIM proposed in this paper is proved by simulation and experiment results on an IPMSM TCS platform.

中文翻译：

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基于电流角信号注入法的IPMSM牵引系统最大安培转矩控制

轨道交通内部永磁同步电机牵引控制系统（IPMSM TCS）需要高扭矩输出能力。用于在 TCS 中找到最大每安培扭矩 (MTPA) 工作点的传统算法对电机参数有很强的依赖性。由于算法对电机参数的鲁棒性较差，当参数变化时，MTPA工作点与实际值之间会出现偏差，从而难以保证牵引系统在不同工况下的扭矩输出能力。本文介绍了一种电流角信号注入控制方法（CASIM）来解决这个问题。所提出的方法跟踪MTPA工作点并根据向电流注入角度信号并使转矩对电流角度的偏导数为零来生成d轴电流命令。同时，该方法计算转矩所需的电机参数较少。因此，在寻找MTPA工作点的过程中，精度受电机参数变化的影响较小。而且它不会向 IPMSM 注入任何实际信号，因此不会增加铜损和铁损。此外，它对速度突变和扭矩干扰具有鲁棒性。在 IPMSM TCS 平台上的仿真和实验结果证明了本文提出的 CASIM 的有效性。在寻找MTPA工作点的过程中，精度受电机参数变化的影响较小。而且它不会向 IPMSM 注入任何实际信号，因此不会增加铜损和铁损。此外，它对速度突变和扭矩干扰具有鲁棒性。在 IPMSM TCS 平台上的仿真和实验结果证明了本文提出的 CASIM 的有效性。在寻找MTPA工作点的过程中，精度受电机参数变化的影响较小。而且它不会向 IPMSM 注入任何实际信号，因此不会增加铜损和铁损。此外，它对速度突变和扭矩干扰具有鲁棒性。在 IPMSM TCS 平台上的仿真和实验结果证明了本文提出的 CASIM 的有效性。