scholarly journals A Modified Dynamic Programming Approach for 4D Minimum Fuel and Emissions Trajectory Optimization

Aerospace ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 135
Author(s):  
Kawser Ahmed ◽  
Kouamana Bousson ◽  
Milca de Freitas Coelho
Keyword(s):  
Dynamic Programming ◽  
Fuel Consumption ◽  
Trajectory Optimization ◽  
Optimization Problems ◽  
Computational Effort ◽  
Programming Approach ◽  
Optimal Trajectories ◽  
Flight Trajectory ◽  
Aircraft Fuel ◽  
Fuel Consumption And Emissions

4D flight trajectory optimization is an essential component to improve flight efficiency and to enhance air traffic capacity. this technique not only helps to reduce the operational costs, but also helps to reduce the environmental impact caused by the airliners. This study considers Dynamic Programming (DP), a well-established numerical method ideally suited to solve 4D flight Trajectory Optimization Problems (TOPs). However, it bears some shortcomings that prevent the use of DP in many practical real-time implementations. This paper proposes a Modified Dynamic Programming (MDP) approach that reduces the computational effort and overcomes the drawbacks of the traditional DP. In this paper, two numerical examples with fixed arrival times are presented, where the proposed MDP approach is successfully implemented to generate optimal trajectories that minimize aircraft fuel consumption and emissions. Then the obtained optimal trajectories are compared with the corresponding reference commercial flight trajectory for the same route in order to quantify the potential benefit of reduction of aircraft fuel consumption and emissions.

scholarly journals The impact of single engine taxiing on aircraft fuel consumption and pollutant emissions

2018 ◽  
Vol 122 (1258) ◽  
pp. 1967-1984 ◽  
Author(s):  
M. E. J. Stettler ◽  
G. S. Koudis ◽  
S. J. Hu ◽  
A. Majumdar ◽  
W. Y. Ochieng
Keyword(s):  
Fuel Consumption ◽  
Pollutant Emissions ◽  
Future Research ◽  
Reduce Fuel Consumption ◽  
Flight Data ◽  
Set Operations ◽  
Aircraft Fuel ◽  
Fuel Consumption And Emissions ◽  
The Impact

ABSTRACTOptimisation of aircraft ground operations to reduce airport emissions can reduce resultant local air quality impacts. Single engine taxiing (SET), where only half of the installed number of engines are used for the majority of the taxi duration, offers the opportunity to reduce fuel consumption, and emissions of NOX, CO and HC. Using 3510 flight data records, this paper develops a model for SET operations and presents a case study of London Heathrow, where we show that SET is regularly implemented during taxi-in. The model predicts fuel consumption and pollutant emissions with greater accuracy than previous studies that used simplistic assumptions. Without SET during taxi-in, fuel consumption and pollutant emissions would increase by up to 50%. Reducing the time before SET is initiated to the 25th percentile of recorded values would reduce fuel consumption and pollutant emissions by 7–14%, respectively, relative to current operations. Future research should investigate the practicalities of reducing the time before SET initialisation so that additional benefits of reduced fuel loadings, which would decrease fuel consumption across the whole flight, can be achieved.

A Fuzzy Dynamic Programming Approach for Mixed-Discrete Multistage Decision Processes

2004 ◽  
Author(s):  
Ying Xiong ◽  
Singiresu S. Rao
Keyword(s):  
Decision Making ◽  
Dynamic Programming ◽  
Design Space ◽  
Optimization Problems ◽  
Real Life ◽  
Optimal Solution ◽  
Dynamic Programming Method ◽  
Programming Approach ◽  
Fuzzy Goal ◽  
Fuzzy State

Many engineering optimization problems can be considered as multistage decision-making problems. If the system involves uncertainty in the form of linguistic parameters and vague data, a fuzzy approach is to be used for its description. The solution of such problems can be accomplished through fuzzy dynamic programming. However, most of the existing fuzzy dynamic programming algorithms can not deal with mixed-discrete design variables in the optimization of mechanical systems containing fuzzy information. They often assumed that a fuzzy goal is imposed only on the final state for simplicity, the values of fuzzy goal and other parameters need to be predefined, and an optimal solution is obtained in the continuous design space only. To better reflect the nature of uncertainties present in real-life optimization problems, a mixed-discrete fuzzy dynamic programming (MDFDP) approach is proposed in this work for solving multistage decision-making problems in mixed-discrete design space with a fuzzy goal and a fuzzy state imposed on each stage. The feasibility and versatility of the proposed method are illustrated by considering the design of a four-bar truss. To the authors’ knowledge, this work represents the first fuzzy dynamic programming method reported in the literature for dealing with mixed-discrete optimization problems.

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