Optimisation investigation on hybrid battery thermal management system for electric aircraft based on genetic algorithm - Yuzhuo Wang; Qing Guo; Zhijie Zhou; Haodi Li; Dexiao Ma (Engineering Applications of Computational Fluid Mechanics)
Lithium batteries are increasingly being used in electric aircraft, where the discharge conditions and working environment are more severe compared to those of electric vehicles. Under a typical working condition of an aircraft, the battery temperature is above 40°C nearly 90% of the full running time if a single air cooling system is used. This paper proposes a hybrid thermal management system that combines phase change materials (PCMs) with air cooling. Numerical simulations of four common PCMs are carried out in this paper, and the results show that the battery temperature with Paraffin Wax is reduced to 38.12°C and the average liquid fraction is 65.64%, which is a better overall performance. The study examines how battery arrangement, PCM thickness, inlet wind speed, and battery spacing affect thermal performance. Results show that maximum battery temperatures vary by no more than 1°C, clustering around 36.5°C. Traditional optimisation methods struggle to find the best combination of these factors. Therefore, this paper uses genetic algorithm to identify the optimal parameters for the battery thermal management system (BTMS). The model accurately predicts thermal performance with only a 0.5037% error between predicted and simulated values. This paper offers an efficient method for selecting and designing battery thermal management systems.