Abstract
Thermal management of Li-ion batteries is important because of the high energy content and the risk of rapid temperature development in the high current range. Reliable and safe operation of these batteries is seriously endangered by high temperatures. It is important to have a simple but accurate model to evaluate the thermal behavior of batteries under a variety of operating conditions and be able to predict the internal temperature as well. To achieve this goal, a radial-axial model is developed to investigate the evolution of the temperature distribution in cylindrical Li-ion cells. Experimental data on LiFePO4 cylindrical Li-ion batteries are used to determine the overpotentials and to estimate the State-of-Charge-dependent entropies from the previously developed adaptive thermal model [1]. The heat evolution is assumed to be uniform inside the battery. Heat exchange from the battery surfaces with the ambient is non-uniform, i.e. depends on the temperature of a particular point at the surface of the cell. Furthermore, the model was adapted for implementation in battery management systems. It is shown that the model can accurately predict the temperature distribution inside the cell in a wide range of operating conditions. Good agreement with the measured temperature development has been achieved. Decreasing the heat conductivity coefficient during cell manufacturing and increasing the heat transfer coefficient during battery operation suppresses the temperature evolution. This modified model can be used for the scale-up of large size batteries and battery packs.
Highlights
A successful design of battery packs starts with the correct accommodation of the thermal battery properties
In a battery management system (BMS), it is desirable to accurately predict the internal temperature evolution of the battery according to the state-of-charge (SOC), cell potential, current and surface temperature
The battery measurements and simulation have been performed at 0 ̊C and 40 ̊C to determine equilibrium potentials and derive entropy change values to further validation of the model
Summary
A successful design of battery packs starts with the correct accommodation of the thermal battery properties. In a battery management system (BMS), it is desirable to accurately predict the internal temperature evolution of the battery according to the state-of-charge (SOC), cell potential, current and surface temperature Such a system requires an efficient thermal model with a limited number of measured parameters at each state. Theoretical models, which are usually based on a combination of electrochemistry and physics, can give accurate predictions for various operating conditions [310] These are complicated and need sophisticated measurements and estimation of transport properties, electrochemical reaction constants, etc. Experimental-based models employ battery measurements on the cell level to determine equilibrium potentials and, overpotentials and in some studies, entropy contributions in heat generation, but do not go into detail of the electrochemical processes occurring inside the cells [1,11,12,13,14,15,16,17,18,22]. COMSOL multiphysics is used for finite element modeling, and the model is exported to MATLAB for estimation of the various parameters
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