Electric vehicles, or EVs, are significantly transforming the automotive industry as a cleaner and more environmentally friendly which finds an alternative solution for the vehicles propelled using internal combustion engines. As EV utilize the energy directly from the battery which causes customer or a user to be in panic state as charging infra is not developed well in most of the countries, thus improving vehicle efficiency and driving range requires optimizing energy consumption from battery of EVs. Apart from traction motor load for driving, major supplemental loads in electric car are climate control system, sometimes referred to as HVAC (Heating, Ventilation, and Air Conditioning). HVAC systems can consume a lot of battery power, especially during severe temperatures, which can drastically reduce the vehicle's range.
Range anxiety continues to be an important barrier to the general adoption of EVs, the intelligent climate management systems which helps to reduce HVAC power usage without impacting passenger comfort will solve the problem for both automotive manufacturers and consumers. Predictive thermal management, cabin pre-conditioning, zonal control of temperatures, and integration with renewable energy sources are a few strategies of the systems. As EVs can deliver increased environmental advantages, increased user pleasure, and improved range performance by making development system in such way that the energy been harnessed fully in an effective way.
Intelligent features like Auto mode, which dynamically modifies fan speed, airflow direction, and temperature settings based on current cabin and ambient conditions which plays a crucial role in modern EV climate control systems. Auto mode optimizes the total HVAC energy used for the thermal components in the vehicle using sensor data and adaptive control algorithms. This auto levels were essential in lowering HVAC-related consumption of electricity and to enhance overall range and system economy without trade-off for passenger comfort.
This study introduces three distinct calibration profiles for auto mode in climate control of the vehicle, each calibration profiles were engineered to achieve the same cabin temperature under different dynamic conditions which can contribute significant changes in total overall energy consumption. These calibration profiles allows user to choose between faster thermal response or reduced power usage, effectively enabling a trade-off between immediate comfort and extended driving range. This leads the way towards AI based thermal control system where the calibration model is automatically identified to achieve customer comfort automatically by sensing customer conditions of fatigue, body temperature.