Effect of Cell-to-Cell Thermal Imbalance and Cooling Strategy on Electric Vehicle Battery Performance and Longevity

This work develops a reduced-order numerical model of a custom-built commuter electric vehicle (EV) to study the lifetime performance of EV battery packs and battery thermal management systems (BTMS). The model uses experimental battery and BTMS data collected from a commuter EV and applies drive cycles corresponding to typical highway and city driving conditions. The main advantage of this numerical modeling approach is its ability to simulate large timescales, spanning years of vehicle operation. Cell level degradation is captured, allowing for the study of battery pack longevity under a variety of temperature profiles generated by various BTMS strategies with series and parallel indirect liquid cooling configurations. Monte Carlo simulations are also used to estimate the variation in BTMS performance caused by beginning-of-life (BOL) variations and cell-to-cell thermal imbalance/spreading in the battery cells. The proposed modeling approach was demonstrated to be an effective tool in studying long timescale BTMS performance, and tradeoffs between BTMS energy consumption and pack energy retention for the case-study commuter vehicle. A 7% reduction in the mean maximum pack temperature and a 10% reduction in the mean lifetime BTMS energy consumption were achieved by tuning BTMS control parameter thresholds. However, the variability in pack energy retention greatly increased, highlighting the need to consider BOL variations and cell spreading in BTMS modeling and design.