Date of Award

1-31-2023

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

Keywords

Aerodynamic drag, Air conditioning, Model predictive control, Modeling, Active grille shutters

Supervisor

J.Defoe

Supervisor

A.Rahimi

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This thesis expands upon the state-of-the-art in nonlinear modeling of automotive air conditioning (A/C) systems. It presents a model predictive control (MPC) approach to reduce the A/C system energy consumption considering the control of the compressor clutch, condenser fan, and active grille shutters (AGS). There are two new aspects included in the modeling here. First, we create a mathematical model for front-end underhood airflow, considering vehicle speed, condenser fan rotational speed, and AGS position. In addition, we present a new model for the power consumption of the vehicle associated with aerodynamic drag caused by underhood flow, as well as a fan power model which accounts not only for changes in rotational speed but also changes in flow rate. The models developed are coded in MATLAB/Simulink. By including the AGS as a controllable actuator and the impact of underhood flow on vehicle drag and fan power consumption, control schemes can be developed to holistically target reduced energy consumption for the air conditioning system and thus improve the overall vehicle energy efficiency. In the second part of this thesis, we explore a new avenue for A/C system control by considering the power consumption due to vehicle drag (regulated by the condenser fan and AGS) to reduce the energy consumption of the A/C system and improve the overall vehicle fuel economy. The controller is designed in Simulink, where the compressor clutch signal, condenser fan speed, and AGS open fraction are inputs. The controller is connected to a high-fidelity vehicle model in GT-Suite (which is treated as the plant) to form a software-in-the-loop simulation environment, where the controller sends actuator inputs to GT-Suite, and the vehicle response is sent back to the controller in Simulink. Quadratic programming is used to solve the optimization problem outlined in this work and determine the optimal input trajectory at each time step. The results of this work found that using MPC to control the compressor clutch, condenser fan, and AGS can provide a 37.6% reduction in the overall energy consumption and a 32.7% reduction in the error for the air temperature reference tracking compared to the conventional baseline control present in the GT-Suite model.

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