Electric Vehicles (EVs) are rapidly transforming the automotive landscape, offering a cleaner and more sustainable alternative to internal combustion engine vehicles. As EV adoption grows, optimizing energy consumption becomes critical to enhancing vehicle efficiency and extending driving range. One of the most significant auxiliary loads in EVs is the climate control system, commonly referred to as HVAC (Heating, Ventilation, and Air Conditioning). HVAC systems can consume a substantial portion of the battery's energy—especially under extreme weather conditions—leading to a noticeable reduction in vehicle range.
This energy demand poses a challenge for EV manufacturers and users alike, as range anxiety remains a key barrier to widespread EV acceptance. Consequently, developing intelligent climate control strategies is essential to minimize HVAC power consumption without compromising passenger comfort. These strategies may include predictive thermal management, cabin pre-conditioning, zonal climate control, and integration with renewable energy sources. By implementing such energy-efficient solutions, EVs can achieve better range performance, improved user satisfaction, and greater environmental benefits.
Modern EV climate control systems increasingly rely on intelligent features such as Auto mode, which dynamically adjusts fan speed, airflow direction, and temperature settings based on real-time cabin and ambient conditions. By leveraging sensor data and adaptive control algorithms, Auto mode optimizes thermal comfort while minimizing unnecessary energy expenditure. This automated regulation plays a crucial role in reducing HVAC-related power consumption, thereby contributing to overall range improvement and enhancing system efficiency without compromising passenger comfort.
This study focuses on the development of three distinct Auto mode calibration levels for each set condition, designed to achieve the same cabin temperature with varying dynamic responses and energy consumption profiles. In Auto mode, the cabin temperature is regulated through intelligent control of compressor speed, blower speed, and evaporator temperature. While all Auto levels can maintain the desired setpoint, the time required to reach this temperature and the system’s responsiveness to sudden thermal loads can vary significantly. This study introduces three distinct calibration profiles, each engineered to achieve the same cabin temperature under different dynamic conditions and energy consumption levels. These profiles allow users to choose between faster thermal response or reduced power usage, effectively enabling a trade-off between immediate comfort and extended driving range