DocumentCode :
2484758
Title :
Research of battery capacity fiber on-line intelligent testing technology based on SVM
Author :
Mingfu, Zhao ; Yan, Chen ; Binbin, Luo ; Lianbin, Zhong ; Ren-long, Xing
Author_Institution :
Dept. of Electron. Eng., Chongqing Inst. of Technol., Chongqing
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
3067
Lastpage :
3070
Abstract :
The support vector machine (SVM) is a learning arithmetic which based on structural risk minimization theory and has highly generalized performance. The paper aiming at the lead-acid battery capacity testing course, proposes a kind of multi-input information fusion technology based on SVM. Using the sensor to test the battery capacity under different charge and discharge states, since the input voltage information is related to the output electrolyte concentration, at the same time the concentration is related to the battery capacity very well, so adopt SVM to fit this complex non-linear course. The simulation result turned out good fitting effect and it controls the error between -0.012 to 0.015. The testing result indicated that the theory value is almost identical to the actual value; thereby show that the lead-acid battery capacity fiber on-line intelligent testing technology based on SVM is feasible.
Keywords :
battery testers; lead acid batteries; power engineering computing; sensor fusion; support vector machines; SVM; battery capacity fiber online intelligent testing technology; lead-acid battery capacity testing; learning arithmetic; multi-input information fusion technology; structural risk minimization theory; support vector machine; Arithmetic; Batteries; Intelligent sensors; Learning systems; Machine learning; Optical fiber testing; Optical fiber theory; Paper technology; Risk management; Support vector machines; battery; fiber; intelligent information fusion; residual capacity; support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593411
Filename :
4593411
Link To Document :
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