OCV-SOC-Temperature Relationship Construction and State of Charge Estimation for a Series– Parallel Lithium-Ion Battery Pack

Accurate state of charge (SOC) estimation of a battery pack is more meaningful than that of a cell in practical applications. The existing methods are difficult to provide an accurate SOC of a battery pack under a wide range of temperature due to cell inconsistency. In this paper, a SOC estimation method for a series-parallel lithium-ion battery pack based on the newly constructed OCV-SOC-temperature relationship was proposed. In the proposed method, firstly the cosine similarity is used to quantify cell inconsistency and the representative cells in the battery pack are determined by the largest cosine similarity value. Secondly, the OCV-SOC curves of the representative cells at different temperatures are used to construct the OCV-SOC-temperature relationship of the battery pack. Finally, a multi-branch fusion method is developed to estimate the SOC of the battery pack through the SOC of each branch by means of a Bayesian probability formula. The effectiveness of the newly constructed OCV-SOC-temperature relationship and the proposed SOC estimation method of the battery pack is verified under various dynamic conditions. The estimated SOC error of the series–parallel battery pack is less than 1.5%, which is approximately 60% lower than the traditional methods.