Estimation of Lead-Acid Battery SOC Based on Kalman Filtering Algorithm

Abstract:

The key technology of electric vehicle battery management lies in the battery state of charge (SOC) estimation, accurate and efficient estimation of SOC can provide the reference data for the control system of the electric vehicle in time. On the basis of the Ah measurement method, Calman filtering method, open circuit voltage method to estimate method, the estimation procedure to estimate the charged battery optimized Calman filtering method, effectively shorten the calculation process, improve the estimation accuracy, in the normal operation of electric vehicles under the influence of comprehensive consideration about the discharge voltage, battery temperature to estimate the state of charge, the Calman filter optimization algorithm, and its application in the electric vehicle battery management system. The experimental results show that, the algorithm can calculate the real-time high charge state of surplus value, provides a set of effective estimation scheme of calculating the battery charge state.

• Periodical: Applied Mechanics and Materials (Volumes 651-653)
• Pages: 1064-1067
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.651-653.1064
• Online since: September 2014
• Authors: Dong Zhao Chen, Li Jun Jia
• Keywords: Battery Management, Calman Optimization Algorithm, Estimation

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