Extremum seeking control of battery powered vapor compression systems for vehicles

Sharma, Sunny

Permalink

https://hdl.handle.net/2142/101474 Copy

Description

Title

Extremum seeking control of battery powered vapor compression systems for vehicles

Author(s)

Sharma, Sunny

Issue Date

2018-06-05

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)

• Control Systems
• Dynamics
• Optimization
• Refrigeration
• HVAC
• Extremum Seeking Control
• Vehicles

Abstract

This thesis investigates the real-time energy optimization of battery powered vapor compression systems (VCS) for vehicles. Battery powered VCS are critical for maintaining passenger comfort in engine-off situations, and are especially important to long-haul truck drivers who sleep inside their vehicle overnight. However, one drawback of battery powered vehicle VCS is their short lifespan which may not provide cooling through the whole night while the vehicle engine is turned off. One reason for short system lifespan is suboptimal input selection; the combination of inputs to the VCS often yields a power consumption higher than necessary to generate the required vehicle cooling. This thesis proposes the use of extremum seeking control (ESC), a class of real-time model-free optimization algorithms, to determine the optimal combination of system inputs that minimizes the VCS power consumption while meeting given objectives. In order to determine algorithm efficacy, we implemented three different ESC algorithms (perturbation-ESC, least squares-ESC and recursive least squares-ESC) on a simulated and physical integrated VCS (the VCS in conjunction with the battery pack and vehicle cabin). Simulation and experimental results demonstrate significant increases in energy efficiency and battery life through the use of these algorithms, with least squares-ESC and recursive least squares-ESC being the most effective of the three.

Graduation Semester

2018-08

Type of Resource

text

Permalink

http://hdl.handle.net/2142/101474

Copyright and License Information

Copyright 2018 Sunny Sharma

Owning Collections