Maximizing Range with Advanced Air Conditioning Optimization and Energy Management

2025-28-0364

10/30/2025

Authors Abstract
Content
Widespread adoption of electric vehicles (EVs) is hindered by "range anxiety," a major concern for consumers. A primary contributor to this issue is the significant energy consumption of the Heating, Ventilation, and Air Conditioning (HVAC) system, which can account for 15-40% of a vehicle's total energy demand, directly reducing its practical driving range.
Using the 1D simulation tool GT-SUITE, this research provides a comparative analysis of two distinct HVAC architectures: a conventional air-cooled condenser (ACC) and a proposed liquid-cooled condenser (LCC). The performance of both hardware systems was evaluated under two control strategies a Proportional-Integral (PI) controller and a basic On/Off controller—to identify the optimal configuration.
The results advocate that optimizing the system's architecture and control logic yields a substantial improvement in the Coefficient of Performance (COP) ranging from 47% to 128% compared to the baseline ACC/On-Off configuration, with a corresponding total energy consumption reduction of 10% to 39%. Critically, these significant performance gains were analyzed for both the R134a and the modern, low-GWP R1234yf refrigerants
This research confirms that a holistic optimization approach, improving both hardware and control logic, is a robust strategy for significantly reducing HVAC energy load, proven effective for both the refrigerants. By quantifying these substantial energy savings, this study provides a clear pathway for designing more sustainable EV thermal management systems that can help extend driving range and address a key barrier to EV adoption.
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DOI
https://doi.org/10.4271/2025-28-0364
Pages
8
Citation
T R, R., and Yadav, A., "Maximizing Range with Advanced Air Conditioning Optimization and Energy Management," SAE Technical Paper 2025-28-0364, 2025, https://doi.org/10.4271/2025-28-0364.
Additional Details
Publisher
Published
Oct 30
Product Code
2025-28-0364
Content Type
Technical Paper
Language
English