Modeling and state of charge estimation of inconsistent parallel lithium-ion battery module

Parallel cell inconsistency will lead to the differences among the branch current flowing through each parallel cell, which will affect the performance characteristic of the Parallel Battery Module (PBM). Meanwhile, the current differences also lead to the State of Charge (SOC) differences among parallel cells. Therefore, it is of great significance to realize the PBM modeling and SOC estimation considering parallel cell inconsistency. Firstly, the PBM model is established to analyze the performance characteristic of PBM with heterogeneous battery capacities state. A method for determining the order of the optimal model is then proposed, which considers both voltage and branch current constraints. Results show that the first-order RC (1-RC) equivalent circuit model is the optimal model for the used battery. Furthermore, in order to ensure the safety of each battery cell, the SOC estimation method with the minimum SOC as the envelope is presented under discharge condition. Based on the optimal model, an improved Cubature Kalman Filter (CKF) algorithm with self-adjustment of the state noise matrix is proposed. Results show that the improved CKF algorithm can effectively track the minimum SOC envelope of PBM. The estimated SOC error is stable within 1.2% during the voltage plateau period and 4.3% at the end of discharge, which verifies the effectiveness of the proposed method.

Automated summary

This article proposes a method for PBM modeling and SOC estimation considering parallel cell inconsistency. Firstly, the PBM model is established and the optimal model order is determined. Then, a SOC estimation method is proposed. The results show that the proposed methods are effective in tracking the minimum SOC envelope of PBM.