A dynamic electro‐thermal coupled model for temperature prediction of a prismatic battery considering multiple variables. (21st October 2020) - Li, Wei; Xie, Yi; Zhang, Yangjun; Lee, Kuining; Liu, Jiangyan; Mou, Lisa; Chen, Bin; Li, Yunlong
Summary: A dynamic coupled electro‐thermal model including the impact of the state of charge (SOC), inner temperature and current flux on resistance and heat generation rate is proposed for prismatic batteries, including the ohmic and polarization resistances and entropy coefficient. This model reflects the interaction between generation rate of heat and temperature distribution and is appropriate to be employed. Subsequently, the dynamic model is implemented to reveal the temperature increase of a Li‐ion prismatic battery with the capacity of 50‐Ah under the conditions of static and dynamic currents. Experiments are performed to demonstrate the model which is given in this article can precisely describe the thermal behavior under the conditions of static and dynamic currents and different ambient temperatures, with an average relative error of 5.87% for the static condition and of 11.81% for the dynamic condition. In addition, comparative studies are utilized to decide the application range of the dynamic model. It shows according to the results that it should be used for the temperature prediction under the condition of dynamic current. As for the static current condition, the static model ignoring the effect of current can replace the dynamic model, although the temperature prediction precision of the dynamic model is slightly higher than that of the static model. Finally, the proposed dynamic model is compared with a resistance‐based thermal model where the heat generation depends only on SOC and is demonstrated to be superior to its counterpart. Abstract : The dynamic thermal model in this paper is helpful for the precise prediction of temperature increase, especially under the dynamic condition. Moreover, the electro‐thermal coupled model accounting for influences of SOC, temperature and current on the heat generation can implement real‐time coupling relationships between the heat generation and temperature distribution. Finally, it is necessary to use the dynamic electro‐thermal coupled model or R(SOC, T, I) model to predict the temperature under the condition of the dynamic current.