Temperature prediction and thermal management are critical to maintain batteries in safe and efficient operations. In this work we present a finite volume modelling framework based upon the solution of the solid energy balance able to rapidly compute the temperature distribution inside Sodium Metal Chloride batteries. The proposed simulation tool is validated against relevant experimental results describing any operative condition possible for a 10 × 10 cells battery and its performances are evaluated in terms of accuracy and computational time required to run simulations. The developed model enables accurate estimation of the battery temperature distribution, generally yielding deviations from experimental measurements below 4 °C, with a maximum error of approximately 8 °C observed at the end of a low-current discharge phase. Reliable results are obtained under any load conditions within a few seconds of computation time, making the model a fast and effective alternative to experimental testing for battery characterization during the design and validation phases. Compared with a commercial software, the proposed computational framework is significantly more efficient and flexible, achieving a 850× speed-up while providing fully comparable accuracy.
Piaz et al. (Mon,) studied this question.