Optimisation of battery thermal management system

Abstract

Electric driven vehicles with batteries are one way to enable lower emissions from transport sector. A key aspect to increase the battery performance, safety and lifetime is an efficient Battery Thermal Management System (BTMS). Therefore, this master thesis is performed in collaboration with the innovation center CEVT to answer the question: “How can the heat transfer in a branch standard BTMS solution be improved?". The branch standard solution, or base case, is a liquid BTMS with cooling plates and a thermal pad as thermal interface material (TIM). The research question was answered through CFD simulations in a comparative study. The study aims to reduce the total heat transfer resistance from the battery module to the coolant as well as temperature variance in the battery module. Each case consisted of pre-study, mesh study and analysis. Firstly, the base case was evaluated. From analysis together with inspiration from literature, improvements were suggested. Thereafter the improved cases were simulated and analysed through a comparative study. One identified problem was the thermal pad. So, a new TIM with higher conductivity and lower contact resistance was tested. The contact resistance was unsure, so two values were used to capture the range of improvement. This reduced the resistance with 15 - 63% and lowered the variance with 0,13 - 0,26K, compared to the base case. Another improvement was a fin in the battery module. This required additional assumptions, which made the results uncertain. But a risk of heat accumulation in the fin was recognised. A third improvement was to change the flow pattern to increase the mixture, which lowered the resistance with 5% and the variance with 0,69K. A combination case with the new TIM and flow pattern gave 20% reduced resistance and 0,98K reduced variance. Based on the results, recommendations were to replace the existing thermal pad with a more efficient TIM. If fins are of interest, they may require cooling. A new flow pattern should be investigated and optimised by comparing different patterns. Lastly, it is suggested to combine a new TIM with an optimised flow pattern for a more efficient BTMS.