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The prediction of the battery temperature and terminal voltage under dynamic load condition is crucial for a satellite battery management system. Restricted by parameter measurability and computing resources, equivalent circuit model has been commonly used in battery management system. But this model cannot satisfy the necessary performance under dynamic load for usual work of satellites. On account of this problem, a combined temperature single particle model is developed for 18650 cells in this paper. The proposed model consists of two sub-models, an electrochemical model and a thermal model, which are coupled together in an iterative manner through physicochemical temperature dependent parameters. The electrochemical sub-model mainly simplifies the calculation of lithium-ion concentration in electrode, while an expression for battery temperature distribution is employed in the thermal sub-model. In addition, genetic algorithm is adopted to estimate model parameters by exciting the battery under different operation conditions. This proposed model can provide accurate predictions of terminal voltage and surface temperature at various operating conditions and the proper simplification of mathematical structure making it ideal for real-time battery management system application. Finally, the model is validated against both constant and dynamic load conditions.

A Simplified Extension of Physics-Based Single Particle Model for Dynamic Discharge Current