A Method for Estimating the State of Health of Lithium-Ion Batteries Based on the Capacity Increment (IC) Curve

Battery management systems are core technologies ensuring the performance and safety of lithium-ion battery packs in new energy vehicles and energy storage systems, where State of Health (SOH) estimation plays a critical role. To address the current challenges in accurately and efficiently estimating the SOH of lithium-ion batteries, this paper proposes a SOH estimation method using the IC curve. By extracting multi-dimensional feature parameters from the IC curve, analyzing the correlation strength between each parameter and the remaining battery capacity using Pearson's correlation coefficient, and selecting core feature parameters, a SOH estimation model is constructed using a Backpropagation (BP) neural network. Validation experiments on the lithium-ion battery aging dataset from the Battery Intelligence Laboratory at the University of Oxford show that the proposed method achieves high estimation accuracy, with a maximum error of less than 2.5%, verifying its effectiveness and practical value.