Multi-scale path planning for reduced environmental impact of aviation

Campbell, Scot E.

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https://hdl.handle.net/2142/16034 Copy

Description

Title

Multi-scale path planning for reduced environmental impact of aviation

Author(s)

Campbell, Scot E.

Issue Date

2010-05-19T18:32:53Z

Director of Research (if dissertation) or Advisor (if thesis)

Bragg, Michael B.

Doctoral Committee Chair(s)

Bragg, Michael B.

Committee Member(s)

• Neogi, Natasha A.
• Wuebbles, Donald J.
• Coverstone, Victoria L.
• Langbort, Cedric

Department of Study

Aerospace Engineering

Discipline

Aerospace Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Date of Ingest

2010-05-19T18:32:53Z

Keyword(s)

• contrail
• aviation
• environment
• path planning
• Mixed-integer linear programming (MILP)
• optimization
• trajectory
• air traffic management

Abstract

A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year.

Graduation Semester

2010-5

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http://hdl.handle.net/2142/16034

Copyright and License Information

Copyright 2010 Scot Edward Campbell

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