[1] Fu Zhumu, Zhao Rui,. SOC estimation of lithium-ion power battery for HEVbased on advanced wavelet neural network [J]. Journal of Southeast University (English Edition), 2012, 28 (3): 299-304. [doi:10.3969/j.issn.1003-7985.2012.03.008]

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SOC estimation of lithium-ion power battery for HEVbased on advanced wavelet neural network()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

28

Issue:

2012 3

Page:

299-304

Research Field:

Automation

Publishing date:

2012-09-30

Info

Title:

SOC estimation of lithium-ion power battery for HEVbased on advanced wavelet neural network

Author(s):

Fu Zhumu¹;  2;  Zhao Rui¹

¹Electronic Information Engineering College, Henan University of Science and Technology, Luoyang 471003, China
²School of Control Science and Engineering, Shandong University, Jinan 250061, China

Keywords:

wavelet neural network;  state of charge(SOC);  hybrid electric vehicle;  lithium-ion power battery

PACS:

TP273

DOI:

10.3969/j.issn.1003-7985.2012.03.008

Abstract:

In order to improve the estimation accuracy of the battery’s state of charge(SOC)for the hybrid electric vehicle(HEV), the SOC estimation algorithm based on advanced wavelet neural network(WNN)is presented. Based on advanced WNN, the SOC estimation model of a lithium-ion power battery for the HEV is first established. Then, the convergence of the advanced WNN algorithm is proved by mathematical deduction. Finally, using an adequate data sample of various charging and discharging of HEV batteries, the neural network is trained. The simulation results indicate that the proposed algorithm can effectively decrease the estimation errors of the lithium-ion power battery SOC from the range of ±8% to ±1.5%, compared with the traditional SOC estimation methods.

References:

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[10] Sousy F M. Robust wavelet-neural-network sliding mode control system for permanent magnet synchronous motor drive [J]. Electric Power Applications, 2011, 5(1): 113-132.
[11] Xia Z, Li X, Cui Y. Response time estimation of blinking backlight LCD based on wavelet transformation [J]. Journal of Southeast University:Natural Science Edition, 2011, 41(1): 37-40.(in Chinese)
[12] Jiwani L K, Joshi S D, Visweswaran G S. Priority wavelet packet decomposition and representation [J]. IEEE Transactions on Signal Processing, 2011, 5(6): 557-567.
[13] Zheng G, Wu W. Convergence analysis of BP neural network with momentum item algorithm [D]. Dalian: Department of Mathematics of Dalian University of Technology, 2005.

Memo

Memo:

Biography: Fu Zhumu(1974—), male, doctor, associate professor, fzm1974@163.com.
Foundation item: The National Natural Science Foundation of China(No.60904023).
Citation: Fu Zhumu, Zhao Rui.SOC estimation of lithium-ion power battery for HEV based on advanced wavelet neural network[J].Journal of Southeast University(English Edition), 2012, 28(3):299-304.[doi:10.3969/j.issn.1003-7985.2012.03.008]

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