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In this paper, for the first time, an equivalent circuit electrical model is integrated with a two-state thermal model to form an electro-thermal model for cylindrical lithium ion batteries. The parameterization of such model for an A123 26650 LiFePO 4 cylindrical battery is presented. The resistances and capacitances of the equivalent circuit model are identified at different temperatures and states of charge (SOC), for charging and discharging. Functions are chosen to characterize the fitted parameters. A two-state thermal model is used to approximate the core and surface temperatures of the battery. The electrical model is coupled with the thermal model through heat generation and the thermal states are in turn feeding a radially averaged cell temperature affecting the parameters of the electrical model. Parameters of the thermal model are identified using a least squares algorithm. The electro-thermal model is then validated against voltage and surface temperature measurements from a realistic drive cycle experiment.

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Lithium ion batteries should always be prevented from overheating and, hence, thermal monitoring is indispensable. Since only the surface temperature of the battery can be measured, a thermal model is needed to estimate the core temperature of the battery, which can be higher and more critical. In this paper, an online parameter identification scheme is designed for a cylindrical lithium ion battery. An adaptive observer of the core temperature is then designed based on the online parameterization methodology and the surface temperature measurement. A battery thermal model with constant internal resistance is explored first. The identification algorithm and the adaptive observer is validated with experiments on a 2.3 Ah 26650 lithium iron phosphate/graphite battery. The methodology is later extended to address temperature-dependent internal resistance with nonuniform forgetting factors. The ability of the methodology to track the long-term variation of the internal resistance is beneficial for battery health monitoring.Index Terms-Adaptive estimation, core temperature, lithium ion battery, state of health.

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