Multi-Objective Optimization of an Aeroengine Accessory Gearbox Transmission Based on a Heuristic Algorithm
Mingzhu Hu, Jiazan Zhu, Liangliang Gong, Zehua Lu, Huaiju Liu
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.