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Prediction Method of High Frequency Electromagnetic Noise of Micro Electric Vehicle based on Wavelet Time-Frequency Analysis

机译:基于小波时频分析的微电动车高频电磁噪声预测方法

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摘要

In order to reduce the high-frequency electromagnetic noise of micro-electric vehicles, a method for predicting high-frequency electromagnetic noise of micro-electric vehicles based on wavelet time-frequency analysis is proposed. Through the electromagnetic structure design and excitation source, the motor vibration and noise are analyzed to obtain the high-frequency electromagnetic noise harmonics of electric vehicles. The time-step finite element method is used to calculate the electromagnetic force wave of the induction motor used for driving the electric vehicle, and the electromagnetic noise information is collected. Randomly sort the collected power supply margins of electric vehicles connected to charging, correct the corresponding data feature values, establish accurate motor CAD models and FEA models, and complete the prediction of high-frequency electromagnetic noise of micro-electric vehicles. By optimizing the shape of the permanent magnet and the stator potting and sealing, the improved motor was tested and verified, the noise results before and after optimization were compared, and the effectiveness of the motor noise reduction design was proved.
机译:为了降低微电动车的高频电磁噪声,提出了一种预测基于小波时频分析的微电器高频电磁噪声的方法。通过电磁结构设计和激励源,分析电机振动和噪声以获得电动车辆的高频电磁噪声谐波。时间阶跃有限元方法用于计算用于驱动电动车辆的感应电动机的电磁力波,并且收集电磁噪声信息。随机排序电动车辆连接到充电的电动车辆,校正相应的数据特征值,建立精确的电机CAD型号和FEA型号,并完成微电动车的高频电磁噪声的预测。通过优化永磁体和定子灌装和密封的形状,测试并验证了改进的电动机,比较了优化前后的噪声结果,并证明了电机降噪设计的有效性。

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