Gaussian process regression-based modelling of lithium-ion battery temperature-dependent open-circuit-voltage

Open-circuit-voltage (OCV) plays a significant role in state-of-charge (SOC) estimation for lithium-ion batteries. The slight difference in OCV at various temperatures can result in a large deviation of SOC estimation. In this Letter, a novel model based on Gaussian process regression is proposed to describe the sophisticated relationship among the OCV, SOC, and temperature. To validate the effectiveness of the proposed model, a comprehensive comparison with widely considered benchmarking OCV models is conducted. Experiment results demonstrate the proposed model can provide the most accurate prediction of OCV compared with benchmarking models.