Research on Trajectory Optimization of Continuous Descent Operations for Green Aviation

Continuous descent operation is an important means to reduce fuel consumption, lower emissions, and promote the development of green aviation. The airborne flight management system is the main task-executing equipment on the airborne side for continuous descent operations, and constructing an optimal continuous descent path is the core function of flight management in supporting the implementation of continuous descent in high-density terminal areas. In response to the requirement that the initial descent state must be determined first for optimizing the continuous descent trajectory, a genetic algorithm-based method for optimizing the position of the top of descent and a method for predicting the aircraft state at the top of descent are designed. Based on the cost index concept commonly used in the civil aviation industry, a cost-objective function and other constraint models are constructed, and the Gauss pseudospectral method is used to convert the optimal control problem into a nonlinear programming problem for efficient solution. A simulation model driven by A320 aircraft performance data is utilized to carry out trajectory optimizations for the minimum total cost and the fastest descent time of continuous descent operation. The results show that continuous descent operation has obvious advantages in indicators such as minimum total cost and fastest descent time. The proposed method provides a reference for airborne flight management system to expand the continuous descent trajectory optimization function.