Thermal Prediction of an Electric Vehicle Lithium-Ion Battery Based on the NTGK-Derived Equivalent Internal Resistance Model

As the adoption of electric and hybrid electric vehicles becomes more widespread, it is essential to design and develop effective thermal regulation systems. Reliable and timely efficient thermal modeling is the first step in this process. To this end, this study assesses the effectiveness of the NTGK-based equivalent internal resistance model in predicting the thermal response of a ۶۵ Ah pouch-type lithium-ion battery from the Porsche Taycan during constant current (CC) charging at ۱C to ۳C rates. The model accurately captured maximum and minimum surface temperatures with minimal deviation from the full NTGK model, while reducing computational effort by approximately ۵۷%. However, it struggled to resolve the spatial temperature distribution due to its lack of consideration for detailed electrochemical processes. Overall, the NTGK-based equivalent resistance model offers a computationally efficient approach for predicting bulk thermal behavior in lithium-ion batteries, albeit with limitations in capturing localized thermal gradients.

کلیدواژه ها:

Lithium-ion battery ، Electric vehicle ، Battery thermal model ، NTGK ، Equivalent resistance