With the development of More/All-Electric Aircraft, especially the progress of hybrid electrical propulsion or electrical propulsion aircraft, the problem of optimizing the energy system design and operation of the aircraft must be solved regarding the increasing electrical power demand-limited thermal sink capability. The paper overviews the state of the art in architecture optimization and an energy management system for the aircraft power system. The basic design method for power system architecture optimization in aircraft is reviewed from the multi-energy form in this paper. Renewable energy, such as the photo-voltaic battery and the fuel cell, is integrated into the electrical power system onboard which can also make the problem of optimal energy distribution in the aircraft complex because of the uncertainty and power response speed. The basic idea and research progress for the optimization, evaluation technology, and dynamic management control methods of the aircraft power system are analyzed and presented in this paper. The trend in optimization methods of engineering design for the energy system architecture in aircraft was summarized and derived from the multiple objective optimizations within the constraint conditions, such as weight, reliability, safety, efficiency, and characteristics of renewable energy. The cost function, based on the energy efficiency and power quality, was commented on and discussed according to different power flow relationships in the aircraft. The dynamic control strategies of different microgrid architectures in aircraft are compared with other methods in the review paper. Some integrated energy management optimization strategies or methods for electrical propulsion aircraft and more electric aircraft were reviewed. The mathematical consideration and expression of the energy optimization technologies of aircraft were analyzed and compared with some features and solution methods. The thermal and electric energy coupling relationship research field is discussed with the power quality and stability of the aircraft power system with some reference papers. Finally, the future energy interaction optimization problem between the airport microgrid and electric propulsion aircraft power system was also discussed and predicted in this review paper. Based on the state of the art technology development for EMS and architecture optimization, this paper intends to present the industry’s common sense and future trends on aircraft power system electrification and proposes an EMS+TMS+PHM to follow in the electrified aircraft propulsion system architecture selection

This paper proposes a nested optimization framework to design an optimal fuel cell (FC)–battery hybrid powertrain for unmanned aerial vehicles (UAVs). The framework integrates a genetic algorithm (GA) to explore the powertrain design space and the dynamic programming-based energy management strategies (EMSs) to evaluate each candidate configuration's feasibility and cost under a typical mission profile. The physics-based UAV dynamics model is embedded in the optimization loop to capture the feedback among powertrain sizing, UAV weight, and propulsion power demand. As powertrain components vary in size across design options, the corresponding changes in UAV weight directly alter the required thrust and energy consumption, which are iteratively updated throughout the optimization process. Two distinct EMS objectives, minimizing hydrogen consumption (MHC) and minimizing total cost (MTC), are systematically compared across two powertrain topologies (Full-active and FC semi-active). Optimization results reveal that, the MTC strategy consistently yields lighter and more cost-effective designs than MHC. In the full-active topology, MTC reduces UAV weight by 12.50% and total cost by 19.15%. In the FC semi-active topology, UAV weight and total cost are reduced by 7.66% and 12.08%, respectively. The FC semi-active topology combined with the MTC strategy achieves the best overall performance, delivering the lowest UAV weight and total cost, relative to the full-active topology under MHC, UAV weight decreases by 14.92% and total cost by 23.95%. These findings highlight the strong coupling between powertrain sizing, aerodynamics, and EMSs, emphasizing the importance of integrated optimization approaches in hybrid electric UAV design.

The design of the fuel cell/battery hybrid electric powertrain for unmanned aerial vehicles (UAVs) involves three interdependent factors: topology, size, and energy management strategy (EMS). This paper proposes a multi-objective optimization framework that decomposes the design problem into a topology evaluation subproblem and two concurrent optimization subproblems—size optimization and EMS optimization. The proposed framework jointly optimizes powertrain size and EMS parameters, while the comparison subproblem is solved by evaluating potential topologies based on the optimal solutions. Two different EMSs, dynamic programming-based strategy and filter-based strategy are incorporated into the optimization process for comparative analysis. Within this framework, the initial data include mission requirements, constraints, fuel cell and battery cell datasheets. The genetic algorithm is employed to explore the size and EMS parameters in the outer optimization loop, while the inner loop utilizes the updated parameters to simulate the complete UAV flight process, implements energy management, and provides feedback to the outer loop. Based on the optimal solutions derived, a comparative analysis of different powertrain topologies is performed. Furthermore, hardware-in-the-loop experiments are conducted to validate the effectiveness of the optimized EMS and powertrain sizing results.