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Research Papers

Experimental Validation of Graph-Based Hierarchical Control for Thermal Management

[+] Author and Article Information
Herschel C. Pangborn

Mechanical Science and Engineering
Department,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801
e-mail: pangbor2@illinois.edu

Justin P. Koeln

Department of Mechanical Engineering,
University of Texas at Dallas,
Richardson, TX 75080
e-mail: justin.koeln@utdallas.edu

Matthew A. Williams

Northrop Grumman Corporation,
Falls Church, VA 22042
e-mail: matt.a.williams@ngc.com

Andrew G. Alleyne

Mechanical Science and Engineering
Department,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801
e-mail: alleyne@illinois.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received September 11, 2017; final manuscript received May 1, 2018; published online June 4, 2018. Assoc. Editor: Mahdi Shahbakhti.

J. Dyn. Sys., Meas., Control 140(10), 101016 (Jun 04, 2018) (17 pages) Paper No: DS-17-1458; doi: 10.1115/1.4040211 History: Received September 11, 2017; Revised May 01, 2018

This paper proposes and experimentally validates a hierarchical control framework for fluid flow systems performing thermal management in mobile energy platforms. A graph-based modeling approach derived from the conservation of mass and energy inherently captures coupling within and between physical domains. Hydrodynamic and thermodynamic graph-based models are experimentally validated on a thermal-fluid testbed. A scalable hierarchical control framework using the graph-based models with model predictive control (MPC) is proposed to manage the multidomain and multi-timescale dynamics of thermal management systems. The proposed hierarchical control framework is compared to decentralized and centralized benchmark controllers and found to maintain temperature bounds better while using less electrical energy for actuation.

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Figures

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Fig. 1

Notional graph example to demonstrate key features of the modeling framework

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Fig. 3

Interconnection between a hydraulic graph (middle) and a thermal graph (top), with pump dynamics (bottom) affecting the hydraulic graph and hydrodynamics affecting the thermal graph

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Fig. 2

Hydraulic and thermal graphs for individual fluid-thermal component models

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Fig. 4

Example thermal-fluid testbed configuration for experimental validation

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Fig. 5

Schematic of example testbed configuration

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Fig. 6

Hydraulic graph for example testbed configuration

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Fig. 7

Thermal graph for example testbed configuration

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Fig. 8

Inputs and disturbances used for model validation

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Fig. 9

Selected signals for validation of experimental data with nonlinear and linear graph-based models: (a) hydraulic signals and (b) thermal signals

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Fig. 10

Closer view of several signals from Fig. 9. All experimental traces show the envelope between the maximum and minimum values measured at each time among five experimental trials.

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Fig. 11

Four layer hierarchical control framework for the testbed configuration

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Fig. 13

Centralized benchmark controller framework

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Fig. 12

Decentralized benchmark controller framework

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Fig. 14

Heat load disturbance profile for closed-loop experiments

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Fig. 19

Comparison of total pump energy consumption for hierarchical and baseline controllers

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Fig. 17

Hierarchical MPC controller in experiment: (a) pump commands and (b) cold plate temperatures

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Fig. 18

Comparison of constraint violations for hierarchical and baseline controllers: (a) total temperature violations and (b) peak cold plate wall temperature violations

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Fig. 16

Centralized MPC controller in experiment: (a) pump commands and (b) cold plate temperatures

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Fig. 15

Decentralized PI controller in experiment: (a) pump commands and (b) cold plate temperatures

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Fig. 21

Infrared image of CP 1 and reservoir 1 from example testbed configuration in Fig. 4

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Fig. 20

Individual components as labeled in Table 4 with a 6″ ruler for scale. A fluid temperature sensor is pictured in (g).

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Fig. 22

Hydraulic coupling in pumps 3 and 4: (a) envelope of mass flow rates above 0.03 kg/s and (b) pump commands generating mass flow rates in Fig. 22(a)

Tables

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