General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Cecilia Xie
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • APC: 800 USD
    • E-mail: editor@ijcte.org
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IJCTE 2017 Vol.9(6): 473-478 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2017.V9.1189

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

Zhengqi Tian, Jian Liu, Qing Xu, Shunran Qi, and Guangwei Chen

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.

Index Terms—Electric vehicles charger, Harmonic wave, Electric power energy measurement, Fourier transform algorithm, Wavelet transform.

Zhengqi Tian, Jian Liu, and Qing Xu are with Jiangsu Electric Power Company Research Institute, China (e-mail: wlhseu@163.com).
Shunran Qi is with School of Instrument Science and Engineering, Southeast University, China.
Guangwei Chen is with Purdue University, China.

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Cite: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.


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