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A selection method of mutual inductance identification models based on sensitivity analysis for wireless electric vehicles charging

机译:基于灵敏度分析的电动汽车充电互感模型选择方法

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Wireless power transfer has been recognized as a promising technology for electric vehicles charging. However, the parking misalignments between the transmitter coil on the ground and the receiver coil inside the car may cause variations in the mutual inductance for the charging system, which will reduce its transfer power and efficiency. In order to improve the transfer efficiency and optimize the operating condition, it is essential to identify the mutual inductance. In this paper, identification models are studied with and without communication feedback from the receiver coil under two typical cases (resonant transmitter and inductive transmitter). A selection method based on sensitivity analysis is proposed to select models of high accuracy against measurement errors and sampling propagations. Simulation and experimental results verify the effectiveness and validity of the proposed method. This work is helpful for evaluating and improving the wireless charging system's tolerance against misalignments as well as optimizing its operation condition.
机译:无线电力传输已被公认为是电动汽车充电的有前途的技术。但是,地面上的发射器线圈与汽车内部的接收器线圈之间的停车不对齐可能会导致充电系统的互感发生变化,从而降低其传输功率和效率。为了提高传输效率并优化工作条件,必须确定互感。在本文中,研究了在两种典型情况下(谐振发射器和感应发射器)在有无来自接收器线圈的通信反馈的情况下的识别模型。提出了一种基于灵敏度分析的选择方法,以选择针对测量误差和采样传播的高精度模型。仿真和实验结果验证了该方法的有效性和有效性。这项工作有助于评估和提高无线充电系统对不对准的耐受性,以及优化其工作条件。

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