基于小波变换的锂离子电池剩余寿命预测
首发时间:2020-09-24
摘要:针对锂离子电池的退化数据波动性较大导致剩余寿命预测精度不高的问题,提出了一种基于小波变换和最小二乘支持向量机的锂离子电池剩余寿命预测方法。通过小波阈值去噪方法对原始退化数据进行去噪,与原始数据相比,处理后的数据波动性较小,有利于模型的建立;在此基础上构建了基于小波变换和最小二乘支持向量机的锂离子电池剩余寿命预测方法,实现了剩余寿命预测;最后进行了实验验证并对实验结果进行了分析。与其他方法相比,实验结果表明,提出的方法的预测精度更高,鲁棒性更强
关键词: 锂离子电池 剩余寿命预测 最小二乘支持向量机 小波变换
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Remaining Useful Life Prediction of Lithium-ion Battery Based on Wavelet Transform
Abstract:Aiming at the problem of the high volatility of lithium-ion batteries\' degradation data leads to the low accuracy of remaining useful life prediction. We proposed a lithium-ion battery remaining useful life prediction method based on wavelet transform and least square support vector machine. The original data is denoised by the wavelet threshold denoising method. Compared with the original data, the processed data has less volatility, which is beneficial to establishing the model. On this basis, we built the remaining useful life prediction method of lithium-ion batteries based on wavelet transform and least squares-support vector machine and realized the remaining useful life prediction. Finally, the experiment was verified, and the experimental results were analyzed. Compared with other methods, the experimental results show that the proposed method has higher prediction accuracy and stronger robustness.
Keywords: lithium-ion battery remaining useful life prediction least squares-support vector machine wavelet transform
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