scholarly journals A Two-Level Optimization Method for Hypersonic Periodic Cruise Trajectory

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hesong Li ◽  
Yi Wang ◽  
Yunfan Zhou ◽  
Shangcheng Xu ◽  
Dan Su
Keyword(s):  
Optimal Trajectory ◽  
Optimization Method ◽  
Fuel Saving ◽  
Atmospheric Density ◽  
Acceleration Phase ◽  
Optimal Angle ◽  
Downhill Simplex ◽  
Pseudo Spectral Method ◽  
Drag Ratio ◽  
Pseudo Spectral

Periodic cruise has the potential to improve the fuel-saving efficiency of hypersonic cruise vehicle but is difficult to optimize. In this paper, a two-level optimization method for the trajectory of periodic cruise is proposed. Due to that the periodic cruise trajectory can be divided into an acceleration phase where engine works and a glide phase where engine is off, the two-level optimization method is proposed to optimize the trajectory in each phase by the corresponding level. In the first level, Downhill Simplex Method (DSM) is employed to find an optimal angle of attack in the acceleration phase. Subsequently, the optimal trajectory in glide phase is obtained by the Pseudo-Spectral Method (PSM) in the second optimization level. Numerical results demonstrate the effectiveness of the proposed method. Finally, through comparing with steady-state cruise, it is concluded that periodic cruise makes full use of the change of atmospheric density and lift-drag ratio; thus, fuel saving is achieved.

scholarly journals Optimal Fuel Saving in 4D Waypoint Networks

2020 ◽  
Author(s):  
Kawser Ahmed ◽  
Milca De Freitas Coelho ◽  
Kouamana Bousson
Keyword(s):  
Trajectory Optimization ◽  
Optimal Trajectory ◽  
Arrival Time ◽  
Optimization Method ◽  
Fuel Saving ◽  
Flight Trajectory ◽  
Shortest Path Algorithm ◽  
Cost Index ◽  
Fuel Burn ◽  
Fuel Costs

The purpose of this work is to develop a trajectory optimization method that generates a fuel optimal trajectory from a predefined 4D waypoint networks, where the arrival time is specified for each waypoint in the network. A single source shortest path algorithm is presented to generate the optimal flight trajectory that minimizes fuel burn. Generating such trajectories enables the airlines to cope with increasing fuel costs and to reduce aviation induced climate change, as emission is directly related to the amount of fuel burn. Two case studies were considered and the simulation results showed that flying a fuel optimal trajectory based on the proposed algorithm leads to a reduction of average fuel consumption on international flights by 2-4% compared with the conventional trip fuel. Keywords: Fuel saving, Cost index, 4D trajectory optimization, Waypoint network, Dijkstra’s algorithm

Joint optimization of battery mass and flight trajectory for high-altitude solar-powered aircraft

2014 ◽  
Vol 228 (13) ◽  
pp. 2439-2451 ◽  
Author(s):  
Xian-Zhong Gao ◽  
Zhong-Xi Hou ◽  
Zheng Guo ◽  
Xiao-Qing Chen ◽  
Xiao-Qian Chen
Keyword(s):  
Particle Swarm Optimization ◽  
High Altitude ◽  
Optimization Problem ◽  
Optimization Method ◽  
Joint Optimization ◽  
Flight Trajectory ◽  
Swarm Optimization ◽  
Solar Powered ◽  
Pseudo Spectral Method ◽  
Pseudo Spectral

The design parameters of high-altitude solar-powered aircraft are highly correlative with its flight trajectory. However, it is not an easy work to jointly optimize them in the concept design stage. This paper considers the joint optimization problem of battery mass and flight trajectory for high-altitude solar-powered aircraft. The system model including the aircraft dynamic model, aerodynamic parameters, and thrust model is presented. Then the problem to be optimized is formulated and a new optimization method, which uses the particle swarm optimization and Gauss pseudo-spectral method, is proposed. The Gauss pseudo-spectral method is employed to generate the minimal power consumed by following the flight trajectory in the given configuration of high-altitude solar-powered aircraft, while the particle swarm optimization is used to calculate the optimal battery mass of aircraft. The simulation result shows that the proposed joint optimization method can reduce the battery mass of high-altitude solar-powered aircraft from 16 kg to 13.6 kg, which is equivalent to enhancing its energy density by 19.7%. It can be also seen that the proposed optimization method connects each parameter in a logically clear way and hence provide a perspective for understanding the optimization problem.

Sign in / Sign up

Export Citation Format

Share Document