Many equalization circuits have been proposed to improve pack performance and reduce imbalance. Although bidirectional equalization topologies are promising in these methods, pre-equalization global equalization strategy is lacking. This study proposes a novel state-of-charge (SoC) equalization algorithm for bidirectional equalizer based on particle swarm optimization (PSO), which is employed to find optimal equalization time and steps. The working principle of bidirectional equalization topologies is analyzed, and the reason behind the application of SoC as a balancing criterion is explained. To verify the performance of the proposed algorithm, a pack with 12 LiFePO4 batteries is applied in the experiment. Results show that the maximum SoC gap is within 2% after equalization, and the available pack capacity is enhanced by 13.2%. Furthermore, a comparison between previously used methods and the proposed PSO equalization algorithm is presented. Experimental tests are performed, and results show that the proposed PSO equalization algorithm requires fewer steps and is superior to traditional methods in terms of equalization time, energy loss, and balancing performance.

Abstract

Accurate estimation of battery State of Charge (SOC) is essential for battery control and effective energy management of Hybrid Electric Vehicles (HEV). Taking the dynamic hysteresis characteristic of battery into account, an equivalent circuit model is built. Based on the Hybrid Pulse Power Characterization (HPPC) test data, the parameters was adopt by means of on-line least-square regression. The accuracy of SOC estimation algorithm was verified by the energy balance test, the energy consumption test, New Europe Driving Cycle (NEDC) test and real vehicle driving cycle test, respectively. The experimental results show that this method is with high accuracy and reliability.