A Novel Residual Capacity Estimation Method Based on Extension Neural Network for Lead-Add Batteries

摘要

This paper presents a state-of-charge (SOC) estimation method based on extension neural network (ENN) theory for lead-acid batteries. First, a constant electric current discharging experiment with an electronic load for lead-acid batteries is made to measure and record the internal resistance and open-circuit-voltage by utilizing internal resistance tester. Then, the experimental data are adopted to construct an estimation method based on ENN for recognizing the residual capacity of the lead-acid battery. The simulated results indicate that the proposed estimation method can determine the residual capacity of lead-acid batteries rapidly and accurately with less time and memory consumption.