Evaluation of hysteresis expressions in a lumped voltage prediction model of a NiMH battery system in stationary storage applications

As a part of battery system operation, battery models are often used to determine battery characteristics such as the state of charge (SOC) and the state of health (SOH). A phenomenon that has a large impact on battery model accuracy for NiMH batteries is open circuit voltage (OCV) hysteresis, which causes the OCV to differ not only with the SOC of the battery but also with the charge-discharge history. This characteristic is especially influential when running the system in applications with dynamic current patterns. A model including a way to emulate battery hysteresis behavior would improve the battery management system function. In this study a lumped battery model for cell voltage prediction was expanded to include an OCV hysteresis model. Different expressions to describe the hysteresis behavior were explored. The different models were then evaluated using both synthetic and real-life application experimental data. In all cases the error was reduced by adding a hysteresis component to the model. Using this type of model in the battery management system of stationary energy storage systems based on NiMH batteries could help make the state prediction more accurate. This, in turn, would allow for better optimization of the system operation, something that could help increase system efficiency and lifetime.