AI-Based Control of Setpoint Temperature for Electric Vehicle Cabin

This paper investigates a novel thermal comfort model for an electric vehicle (EV) cabin using a Predicted Mean Vote (PMV) -based AI model. The PMV model predicts thermal comfort based on ambient temperature, humidity, air velocity, garment thermal insulation, and metabolic rate for fixed indoor environments. The approach involves using a sensor-integrated SIMULINK model based on the CBE thermal comfort tool and information on the temperature-battery efficiency dependency to develop the model. Verified input-output data from the Simulink model. The model predicts the desired setpoint temperature based on PMV and operative temperature. The optimal thermal comfort setpoint promotes energy efficiency and reduces CO2 emissions within the electric vehicle cabin, leading to sustainable transportation. This control unit is designed for hot and humid climate conditions.