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Title:Analytical sensitivity analysis methodology for the co-design of thermal management systems
Author(s):Wagenmaker, Minda Joy
Advisor(s):Alleyne, Andrew G
Department / Program:Mechanical Sci & Engineering
Discipline:Mechanical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Sensitivity Analysis
Graph-Based Modeling
Abstract:This thesis presents an analytical sensitivity analysis methodology to be used in a co-design approach to simultaneously optimize plant parameter variables and controller gains. Sensitivity analysis methods are commonly used in system design. The sensitivity of the system output to design variables can be calculated either analytically or numerically. These sensitivities inform the engineer which variables should be the focus of the majority of time and effort to yield the optimal result or, conversely, which variables are inconsequential and can be removed from the optimization design space. Sensitivity analysis methods are also used in control system design. The controller design is influenced by the analysis of how system parameters affect the controlled states. This thesis presents a plant and controller co-design approach where the system parameters which affect the plant output and the ones which affect the controlled states the most are identified. These parameters are optimized using a brute-force numerical method at the same time as the controller gains. This improved plant and controller pair is designed to lower the control input without sacrificing performance. By designing both the plant and the controller simultaneously, better results can be achieved than by only optimizing either the plant or controller. The methodology explored in this thesis is widely applicable to many other systems. However, it has been specifically designed to work with a graph-based modelling framework. This project was carried out with the intention of improving thermal management systems for electrified vehicles. A fluid loop with additional heat loads was used as the example framework to showcase the sensitivity analysis methods. This thesis demonstrates how optimizing the most influential parameters along with the controller gains, lowers the necessary control input, or pump energy, while improving tracking of a reference signal.
Issue Date:2021-07-22
Type:Thesis
URI:http://hdl.handle.net/2142/113089
Rights Information:Copyright 2021 Minda Wagenmaker
Date Available in IDEALS:2022-01-12
Date Deposited:2021-08


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