Modeling and estimation of Nickel Metal Hydride battery hysteresis for SOC estimation

Accurate estimation of battery state of charge (SOC) is essential for battery control and effective energy management of hybrid electric vehicles (HEV). Battery hysteresis poses a big challenge to the estimation of SOC. In the present battery state estimator (BSE), a rule-based hysteresis estimation method for nickel metal hydride (NiMH) batteries is used due to the lack of physical hysteresis models. The rule-based hysteresis estimation method gives only a coarse result with limited accuracy. To improve estimation accuracy and algorithm robustness, a new on-board algorithm, based on the Preisach operator, is developed to estimate battery hysteresis. The enhanced model-based algorithm is then integrated into the BSE algorithms for evaluation. Simulation and preliminary evaluation results for NiMH batteries show significant improvement in the accuracy and robustness of SOC estimation.