Multi-Objective Optimization of an Aeroengine Accessory Gearbox Transmission Based on a Heuristic Algorithm

Abstract

The accessory gearbox transmission is an essential component of an aeroengine, and it affects an aircraft’s safe operation. The high-reliability, lightweight design of accessory gearbox transmissions remains challenging owing to the complicated structure and loading conditions. In this study, a multi-objective optimization method based on the heuristic search nondominated sorting genetic algorithm II (HS-NSGA II) is proposed to obtain gratifying structural parameters. The proposed method optimized 30 structural parameters of the gearbox under 21 constraint conditions within 12 min. Compared with the initial design scheme, the optimized result reduced gearbox weight by 10.2% while improving its safety by 2.98%. Due to the introduction of the HS algorithm, the proposed method outperforms classic optimization methods in design results and calculation efficiencies, such as the multi-objective particle swarm optimization (MOPSO), ant colony optimization (ACO), and nondominated sorting genetic algorithm II (NSGA II). The proposed method has strong versatility and potentially can be extended to other gear transmission designs. The application of the heuristic search nondominated sorting genetic algorithm II to optimize accessory gearbox transmissions offers substantial advantages in aeroengine design and enhances aeroengine safety within the aviation sector. This method efficiently explores the design space by optimizing structural parameters, leading to notable reductions in weight and enhancements in safety. Moreover, this approach has the potential for software development, offering effective tools for accessory gearbox transmissions and various other transmission systems across aerospace applications. The applicability of HS-NSGA II extends beyond the aerospace sector to encompass diverse aerospace transmission systems, including rotorcraft gearboxes, satellite deployment mechanisms, and propulsion systems for space exploration vehicles. Additionally, the versatility of this method allows for its adaptation to transmission systems in other domains such as wind turbines, electric vehicles, and industrial machinery. The multifaceted nature of HS-NSGA II underscores its capacity to drive innovation and progress across disparate domains, ultimately culminating in the realization of more efficient and reliable systems.