TY - GEN
T1 - A model predictive framework for thermal management of aircraft
AU - Deppen, Timothy O.
AU - Hey, Joel E.
AU - Alleyne, Andrew G.
AU - Fisher, Timothy S.
N1 - Publisher Copyright:
Copyright © 2015 by ASME.
PY - 2015
Y1 - 2015
N2 - The challenge of managing heat dissipation and enforcing operational constraints on temperature within a highperformance 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.
AB - The challenge of managing heat dissipation and enforcing operational constraints on temperature within a highperformance 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.
UR - http://www.scopus.com/inward/record.url?scp=84973400155&partnerID=8YFLogxK
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U2 - 10.1115/DSCC2015-9771
DO - 10.1115/DSCC2015-9771
M3 - Conference contribution
AN - SCOPUS:84973400155
T3 - ASME 2015 Dynamic Systems and Control Conference, DSCC 2015
BT - 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
PB - American Society of Mechanical Engineers
T2 - ASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Y2 - 28 October 2015 through 30 October 2015
ER -