Wavelet neural network prediction of electric vehicle chaotic vibration signals#br#

NIU Zhidong 1 WU Guangqiang1, 2

Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (8) : 120-124.

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PDF(1019 KB)
Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (8) : 120-124.

Wavelet neural network prediction of electric vehicle chaotic vibration signals#br#

  •   NIU Zhidong 1   WU Guangqiang1, 2
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Abstract

A vehicle experiment was carried out to study the chaotic dynamics of electric vehicles, and chaotic time series were predicted by using wavelet neural network. First, the experiment of electric vehicle on mediumBelgian road was carried out, the vertical vibration acceleration signal of the right front wheel center and battery bottom center were obtained. Second, timefrequency analysis, threedimensional phase diagrams and the Poincaré sections of the signals were obtained. The time delay was calculated by using the mutual information method, and also minimum embedding dimension was got with the Cao method, the largest Lyapunov exponent was got with Wolf method.  The presence of chaotic motions in the vertical acceleration signal was found. Finally, chaotic time series of the right front wheel center vertical signal was predicted using wavelet neural network. It is found that the use of wavelet neural network to predict chaotic time series can achieve better results.
 

Key words

 Electric vehicle / Chaotic time series / Wavelet neural network

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NIU Zhidong 1 WU Guangqiang1, 2. Wavelet neural network prediction of electric vehicle chaotic vibration signals#br#[J]. Journal of Vibration and Shock, 2018, 37(8): 120-124

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