International Journal of Computer Theory and Engineering

Editor-In-Chief: Prof. Mehmet Sahinoglu
Frequency: Quarterly
ISSN: 1793-8201 (Print), 2972-4511 (Online)
Publisher:IACSIT Press

OPEN ACCESS
4.0
CiteScore

IJIET 2017 Vol.9(6): 473-478
doi: 10.7763/IJCTE.2017.V9.1189

An Energy Measurement Method of Electric Vehicle Based on FFT and Wavelet Transform

Zhengqi Tian1 , Jian Liu1 , Qing Xu1 , Shunran Qi2 , Guangwei Chen3

  • 1Jiangsu Electric Power Company Research Institute, China.
  • 2School of Instrument Science and Engineering, Southeast University, China.
  • 3Purdue University, China.

Abstract

Electric vehicle charging process of nonlinear load caused by harmonic components affects the accuracy of energy metering. The energy metering algorithm of electric vehicle is constructed by combining Fast Fourier Transformation algorithm (FFT) with the wavelet time scale transform method, then FFT can analyze steady-state harmonic and wavelet algorithm can deal with the singular signals effectively. According to the approximation parameters and local characteristic parameters of wavelet analysis, a high resolution harmonic analysis model is established. Then, the wavelet decomposition number of the signal and reconstruction are determined by fundamental signal frequency and sampling frequency, steady-state and non-steady-state harmonics are identified and separated, and the harmonic energy metering is achieved. Simulation demonstrates that FFT and wavelet transform of the electric vehicle energy measurement method can effectively extract the order of the harmonic signal, track and observe the band within the harmonic changes, and improve the measurement accuracy of the electric vehicle charging electric power.

Keywords

  • Electric vehicles charger
  • Harmonic wave
  • Electric power energy measurement
  • Fourier transform algorithm
  • Wavelet transform
1189-G1667

How to Cite

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Zhengqi Tian, Jian Liu, Qing Xu, Shunran Qi, and Guangwei Chen, "An Energy Measurement Method of Electric Vehicle Based on FFT and Wavelet Transform," International Journal of Computer Theory and Engineering, vol. 9, no. 6, pp. 473-478, 2017. https://doi.org/10.7763/IJCTE.2017.V9.1189

Copyright & License

Copyright © 2017 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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