Research on life cycle SOC estimation method of lithium-ion battery oriented to decoupling temperature

Abstract

The efficiency, safety, and durability of lithium-ion batteries serve as the focus of energy storage systems. Among them, the accurate estimation of State of Charge (SOC) in the whole life cycle and wide temperature range is currently a capacity bottleneck that must be surpassed. In light of this issue, a joint estimation method of SOC and State of Health (SOH) based on Interacting Multiple Model (IMM) was proposed in this paper. Through the parallel filtering process of IMM, several battery models with different temperatures and aging degrees were established. The likelihood function was then used to calculate the model probability of a single model, and the state estimates of multiple single models were fused and outputted. Then, the accurate estimation of the SOC of the whole life cycle of the lithium-ion battery oriented to the decoupling temperature was realized. Finally, the proposed method was experimentally verified on two sets of battery data with different aging degrees and temperatures. The results show that the maximum errors of SOC estimation and capacity estimation are less than 2.27% and 3.43% respectively, which meets the needs of the industry. It is proved that the proposed method can achieve accurate tracking of battery SOC and real-time estimation of battery capacity.