State of Charge Estimation for Lithium Batteries in EV

Yang Yu; Wen Dong; Ze Long; Min Hong

doi:10.4028/www.scientific.net/AMR.461.155

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 461State of Charge Estimation for Lithium Batteries...

State of Charge Estimation for Lithium Batteries in EV

Abstract:

The accurate estimate to remaining power of the lithium battery has a very important significance to continued operation of the electric vehicle. Based on the electrochemical mechanism of lithium batteries during charge and discharge, by using the genetic algorithms to determine the weights of the SVM network, a combination algorithm is applied to estimate state-of-charge and the initial condition of network is optimized and has less error to the network. The simulation results show that the optimization network has higher precision for lithium battery SOC forecast method and can be used to estimate the lithium battery SOC value of the electric vehicle

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Periodical:

Advanced Materials Research (Volume 461)

Pages:

155-159

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.461.155

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Online since:

February 2012

Authors:

Yang Yu, Wen Dong, Ze Long, Min Hong

Keywords:

Genetic Algorithm (GA), Lithium Batteries, State of Charge (SOC), Support Vector Machine (SVM)

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