Intelligent heat and energy management for hydrogen electric aircraft power system based on multi-objective genetic algorithm

Although hydrogen electric aircraft have emerged as a critical technological pathway due to their zero carbon emissions, the hydrogen electric aircraft face challenges of high thermal management load and low powertrain system efficiency. A coupled heat-mass-flow-energy model integrating the electric propulsion, hydrogen/air supply, lithium battery energy storage, liquid hydrogen storage, and coolant thermal management subsystems is proposed in this work. Subsequently, an intelligent heat and energy management strategy using multi-objective genetic algorithm is built to optimize energy utilization efficiency based on the proposed model. Results demonstrate that the proposed model achieves high accuracy, with a maximum relative error of 7.44% when compared to experimental data. The total hydrogen consumption decreases from 8.13 kg to 6.40 kg, and the system level energy utilization efficiency increases from 43.25% to 50.72%. Therefore, the flight range can be extended by 21.19%. This work can provide a system level analysis tool with low computational cost and high iterative efficiency for the design of hydrogen electric aircraft energy system.