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A novel online PMSM parameter identification method for electric and hybrid electric vehicles based on cluster technique

机译:基于聚类技术的电动混合动力在线PMSM参数辨识新方法

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In order to save costs and volume, the torque is calculated based on a machine model instead of measuring it with a torque sensor. Thus, an accurate knowledge of the machine's electrical parameters is required for a high performance field-oriented control and torque accuracy. In this work, an innovative method is presented and developed for the online identification and correction of the electrical parameters of electrical machines based on cluster technique. This technique allows for the estimation of all electrical parameters with low computational cost. It uses the information of stator currents, stator voltages, and rotor angular speed. The algorithmic performance has been tested using simulation data of a 75-kW permanent magnet synchronous motor for electric vehicles. The results confirm the high accuracy of the identification method. This approach is applicable to electric and hybrid electric vehicles.
机译:为了节省成本和体积,扭矩是根据机器模型计算的,而不是使用扭矩传感器进行测量。因此,对于高性能的磁场定向控制和转矩精度,需要对电机的电气参数有准确的了解。在这项工作中,提出并开发了一种基于聚类技术的在线识别和校正电机电气参数的创新方法。该技术允许以较低的计算成本来估计所有电参数。它使用定子电流,定子电压和转子角速度的信息。使用75 kW电动汽车永磁同步电动机的仿真数据对算法性能进行了测试。结果证实了该识别方法的高精度。这种方法适用于电动和混合动力电动汽车。

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