Date of Award

10-11-2024

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

Keywords

1-Dimensional;Defogging;Dehumidifying;Heating;Optimization;Recirculation

Supervisor

Ofelia Jianu

Creative Commons License

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

Abstract

Minimizing the power consumption of an automotive HVAC system is one of the main focuses of the automotive industry in the current day, as a reduction HVAC in power consumption can improve vehicle efficiency and provide customers with a higher quality product. During defogging operations in cold weather, the HVAC is programmed to maintain a condensation-free windshield but the question of “is the defogging operation as efficient as possible?” remains. This research develops a 1-dimensional mathematical methodology to predict the thermodynamics and psychometrics of steady-state heat exchange through the front windshield. This methodology is implemented in Siemens AmeSim software and applied for multiple possible environmental scenarios to develop a predictive simulation tool that can be used by Stellantis engineers for the purpose of improving energy efficiency of the HVAC system during vehicle development and improve the defogging strategy. Experiments conducted in a thermal wind tunnel show a strong behavioural trend between the simulation and experimental results but there is not enough data to perform an accurate correlation. Further simulations and experiments are required to fully validate the model, though the simulation could reasonably predict defogging and minimize power consumption with further development. This simulation can be expanded in the future to cover more scenarios, all window glass of the cabin, and be compatible with other HVAC control strategies to potentially accurately predict defogging controls during the development phase, or even be implemented on-board for continuous proactive steady-state defogging.

Available for download on Thursday, October 09, 2025

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