Optimization design of battery thermal management system with honeycomb-shaped channels based on artificial hummingbird algorithm

One of the most significant challenges in power batteries of electric vehicles is to enhance the thermal performance and energy efficiency of cylindrical battery systems when subjected to harsh operating conditions. Therefore, a bio-inspired hybrid battery thermal management system (BH-BTMS) is presented combining honeycomb-shaped microchannels with phase-change materials. A multi-objective optimization model is developed to optimize the proposed system’s overall performance using a backpropagation neural network and artificial hummingbird algorithm. Based on the prioritization of optimization objectives, including the system’s temperature rise, temperature uniformity, and liquid pressure drop, the optimal solutions were determined according to the Pareto front. Furthermore, the system’s performance was evaluated under two standard operating conditions. The results reveal that the proposed system is markedly superior to those of conventional liquid cooling systems and the maximum temperature, temperature difference, and fluid pressure drop of the system are reduced by 3.58%, 48.66%, and 68.12%, respectively. The system temperature is maintained within a reasonable range under standard operating conditions. This design may help enhance heat dissipation capabilities and reduce power consumption for BTMS of electric vehicles.