Core Temperature Estimation for a Lithium ion 18650 Cell

This paper deals with the estimation of core temperature (T-c) of a Lithium (Li) ion battery using measured ambient and surface temperatures. The temperatures were measured using thermocouples placed at appropriate locations. A second order thermal model was considered for the core temperature (T-c) estimation. A set of coupled linear ordinary differential equations (ODEs) were obtained by applying Kirchhoff's current and voltage laws to the thermal model. The coupled ODEs were redefined in the discrete state space representation. The thermal model did not account for small changes in surface temperature (T-s). MATLAB/Simulink were used for modelling a Kalman filter with appropriate process and measurement noise levels. It was found that the temperatures closely followed the current patterns. For high currents, T-c dominated the surface temperature by about 3 K. T-c estimation plays a very important role in designing an effective thermal management and maintaining the state of health (SOH) during fast discharges under limits. Most of the battery management system (BMS) applications required T-s as the input to the controller. Hence, an inverse calculation for estimating T-s from known T-c was carried out and found to be reasonably accurate. It was found that the thermal parameter C-s played a major role in the accuracy of T-s prediction and must have low values to minimize errors.

Automated summary

This paper discusses the estimation of core temperature of a Lithium ion battery using measured ambient and surface temperatures, and highlights the importance of accurate temperature estimation for effective thermal management and maintaining battery health. By studying coupled linear ordinary differential equations and discrete state space representation, it was found that core temperature estimation plays a crucial role in battery design and health maintenance, and inverse calculation can be used to accurately estimate surface temperature.