Cabin Temperature and Humidity Comfort Control for Electric Vehicles in High Temperature and Humidity Environment

With the gradual increase of the market share of electric vehicles, their endurance mileage in extreme temperature environment has become the most concerned indicator for consumers and the comfort control of the cabin is directly related to the battery range. In order to further improve the energy efficiency level of the whole vehicle, this paper introduces a hybrid hierarchical and centralized Model Predictive Control(MPC) that balances energy consumption with temperature and humidity control, enabling precise regulation of the temperature and humidity within the vehicle cabin. Firstly, dynamic equations for the cabin temperature and humidity are established based on the automotive air-conditioning simulation model CoolSim, and the model parameters are obtained through linear regression fitting. Secondly, a sensitivity relationship between the air-conditioning system and vehicle speed is established through statistical analysis, so that an expression for the energy consumption of the air-conditioning system as a function of vehicle speed is derived. Finally, the hybird control algorithm is employed to achieve coordinated control of temperature, humidity, and energy consumption within the air-conditioning system. The simulation results show that the hybrid control algorithm is effective and can reduce the energy consumption of the air conditioning system on the premise of ensuring the comfort of cabin temperature and humidity.