Cabin thermal management for electrical vehicles

Funding agency

The National Science Fund for Young Scholars by NSFC, 52306028, 2024-2026

Project introduction

The HVAC system in electric vehicles (EVs) constitutes a significant portion (20-60%) of their total energy consumption. Efficient management of the cabin thermal environment can greatly enhance the driving range of EVs. However, existing cabin thermal models suffer from either excessive simplification (lumped parameter model) or excessive computational demands (CFD model), making real-time optimization challenging. Moreover, the current thermal comfort evaluation metrics for EV cabins are based on a single-node steady-state heat balance model, which is inadequate for transient and non-uniform cabin environments exposed to intense solar radiation.
This proposed project aims to address these limitations. Firstly, a control-oriented EV HVAC system model and an EV cabin thermal model will be developed using a physics-informed neural network. This approach will accelerate the simulation of the thermal environment while striking a balance between model complexity and accuracy. Subsequently, thermal comfort evaluation metrics for EV cabins will be established through theoretical analysis, physiological monitoring, and subjective surveys. These metrics will quantify the relationships between the cabin thermal environment, occupant comfort, and driver fatigue. Lastly, the operation of the EV HVAC system will be optimized using model predictive control, and various types of HVAC systems will be compared.
By creating a more comfortable and energy-efficient cabin thermal environment, this project aims to extend the driving range of EVs and contribute to the promotion of low-carbon development.