Energy and computational efficient estimation of battery intrinsic parameters

This paper presents an efficient battery parameter extraction technique with energy recycling feature. Based on transferring the testing energy to and from a supercapacitor (storage device) through a bidirectional DC-DC converter, the charging and discharging current profile of a battery can be obtained for analyzing the battery characteristics and parameters extraction. With the testing energy stored in a supercapacitor, the concern of thermal management is eliminated. By applying a newly modified efficient particle swarm optimization algorithm, the voltage and current data are used to estimate the intrinsic parameters of a high-order electrical battery model. A prototype has been implemented for extracting the intrinsic parameters of four different types of 12V lead-acid battery, and with evaluation current evaluated up to 150A. The estimated parameters have been verified against the theoretical predictions as well as the test results obtained from the NHR battery testing system.