Full Content is available to subscribers

Subscribe/Learn More  >

A Model Predictive Framework for Thermal Management of Aircraft

[+] Author Affiliations
Timothy O. Deppen, Andrew G. Alleyne

University of Illinois at Urbana-Champaign, Urbana, IL

Joel E. Hey, Timothy S. Fisher

Purdue University, West Lafayette, IN

Paper No. DSCC2015-9771, pp. V001T08A001; 9 pages
  • ASME 2015 Dynamic Systems and Control Conference
  • Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems
  • Columbus, Ohio, USA, October 28–30, 2015
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5724-3
  • Copyright © 2015 by ASME


The challenge of managing heat dissipation and enforcing operational constraints on temperature within a high-performance tactical aircraft is considered. For these systems, power density of the electrical equipment and the associated thermal loads are quickly outpacing the means of conventional thermal management systems (TMS) to provide on-demand cooling and in order to prevent thermal run away. The next generation of tactical aircraft is projected to include an order of magnitude greater thermal and electrical power magnitudes, and the time scale over which thermal loads will change is expected to shrink. To meet this rapidly evolving challenge, designing a TMS for the “worst case” scenario based on a steady-state thermal analysis will be infeasible. Rather, a holistic systems perspective is needed with new control methodologies that capture and even exploit the transient thermal behavior. To this end, a model predictive control strategy is presented that utilizes preview of upcoming loads and disturbances to prevent violation of temperature constraints. A simulation case study demonstrates that the predictive thermal controller can dramatically reduce constraint violations while reducing the work required by the TMS when compared to a cascaded PI feedback controller.

Copyright © 2015 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In