Statistically Refined Hysteresis Modeling in High-Nickel-Ternary-Cathode Cells

A battery management system (BMS) relies on accurate battery models to perform predictions, where, equivalent circuit models (ECMs) are most practical. However, batteries possessing significant hysteresis cannot be effectively modeled with conventional ECMs, limiting BMS accuracy. Therefore, this study improves ECM accuracy by addressing hysteresis, a key lithium-ion (Li-ion) cell characteristic. In this context, a second-order Thevenin ECM, incorporating dynamic and instantaneous hysteresis was developed and tested on high-nickel-ternary-cathode (HNTC) Li-ion cells. When working with hysteresis models, the hysteresis tuning rate, 7, is an estimated parameter often defined as a constant and is overlooked in adjusting the rate of hysteresis decay. In the ECMs of this work, a variable gamma was identified and examined for different state of charge (SOC) intervals and temperatures. An n-way analysis of covariance (ANCOVAN) was applied to the variable response of gamma and indicated a significant gamma-hysteresis voltage relationship for specific SOC windows. Comparatively through validation of dynamic and total hysteresis modeling, results also indicate that incorporating instantaneous hysteresis does not necessarily improve overall model performance.