Volume 9 Number 3 (Mar. 2014)
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JCP 2014 Vol.9(3): 766-773 ISSN: 1796-203X
doi: 10.4304/jcp.9.3.766-773

The Nonlinear Variable Selection and Its Realtime Detection of Lead-acid Battery Capacity

Yingying Su1, 2, Xinghua Liu2, Shan Liang1, Jingzhe Lee2, Lizhong Yao2, and Kesheng Yan3
1College of Automation, Chongqing University, Chongqing, 400044
2School of Electric and Information Engineering, Chongqing University of Science and Technology, Chongqing, 401331
3School of Mathematics and Statistics, Chongqing University of Technology, Chongqing, 400054


Abstract—Real-time detection of lead-acid battery capacity is hard for not having the suitable instrument. The soft sensing method is considered. It is studied on the basis of variable selection, the confirming of structure and parameters for the predicted model. The importance of each related nonlinear secondary variable is computed and sorted with RReliefF method. After that, the secondary variable sets are selected in turn. Soft sensing model with neural network is finally confirmed by cross-validation method. Simulation results show that the established model is effective with mean square error is 0.0011 for the testing data. It provides one way of simplifying the real-time detection of battery capacity.

Index Terms—variable selection, real-time, detection, leadacid battery, capacity

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Cite: Yingying Su, Xinghua Liu, Shan Liang, Jingzhe Lee, Lizhong Yao, and Kesheng Yan, "The Nonlinear Variable Selection and Its Realtime Detection of Lead-acid Battery Capacity," Journal of Computers vol. 9, no. 3, pp. 766-773, 2014.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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