Hierarchical Climate Control Framework for Electric Vehicles Considering Door-Opening Event

This paper presents a control-oriented model for door-opening scenarios in commercial electric vehicles (EVs), a common real-world issue. We developed and validated a simulation model to handle door-opening interruptions in a real EV. Using the developed model, we compared four heating controllers: (i) the proposed hierarchical nonlinear model predictive controller, incorporating a unique coolant-dividing layer and a component for regulating cabin air inflow based on door-opening signals; (ii) a single model predictive controller (MPC) for coolant division combined with a rule-based cabin air controller; (iii) a rule-based coolant-dividing controller integrated with a cabin air inflow MPC; and (iv) a conventional rule-based controller. Under ambient temperatures of 0, 10, and 20${}^{\circ }$C, our hierarchical controller reduced the temperature drops by 7.2, 9.5, and 10.92${}^{\circ }$C, respectively, in the cabin section where door-opening occurred, compared with the worst-performing controller in each scenario. Furthermore, our strategy significantly reduced temperature overshooting during recovery, achieving reductions of 84–87%, 60.8–83.8%, and 57.7–66.9% at 0, 10, and 20${}^{\circ }$C, respectively, in various cabin sections. These results demonstrate the potential of our strategy to enhance passenger thermal comfort across the vehicle, providing valuable insights for future thermal management strategies in commercial EVs.