Modeling and control of thermal management systems on electric vehicles

Russell, Kayla Michelle

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https://hdl.handle.net/2142/120205 Copy

Description

Title

Modeling and control of thermal management systems on electric vehicles

Author(s)

Russell, Kayla Michelle

Issue Date

2023-02-28

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

Alleyne, Andrew G

Department of Study

Mechanical Sci & Engineering

Discipline

Mechanical Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• dynamic modeling
• thermal management
• model predictive control
• physics-based modeling

Abstract

A growing emphasis on electrifying the transportation industry has led to an increase in the development and implementation of electric vehicles. The thermal management system on electric vehicles is one of the most critical subsystems that ensures safe and comfortable operation of these vehicles. Vapor compression systems are one of the most commonly used cooling methods in thermal management systems for electric vehicles. This thesis develops a vapor compression system model using graph-based modeling techniques. The graph-based modeling framework is extended in this work to capture coupled multi-timescale dynamics that exist in dynamic systems, such as the vapor compression system, while preserving the computational efficiency and modularity of the existing graph-modeling framework. This extended graph-based modeling framework is shown to accurately capture system dynamics within 1% of the current state of the art modeling approaches. Then the graph-based vapor compression system model is connected to a thermal cabin model to cool the interior cabin of an electric vehicle. This work also develops a model predictive control and a baseline control to manage the use of the vapor compression system to cool the cabin. The model predictive control and baseline control performed similarly in meeting the system constraints and objectives.

Graduation Semester

2023-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/120205

Copyright and License Information

Copyright 2023 Kayla Russell

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