Thermal management system of electric vehicles (EVs) is critical for the
vehicle's safety and stability. While maintaining the components within their
optimal temperature ranges, it is also essential to reduce the energy
consumption of thermal management system. Firstly, a kind of architecture for
the integrated thermal management system (ITMS) is proposed, which can operate
in multiple modes to meet various demands. Two typical operating modes for
vehicle cooling in summer and heating in winter, which utilizes the residual
heat from the electric drive system, are respectively introduced. The ITMS based
on heat pump enables efficient heat transfer between different components.
Subsequently, an ITMS model is developed, including subsystems such as the
battery system, powertrain system, heat pump system and cabin system. The
description of modeling process for each subsystem is provided in detail. The
model is tested under world light vehicle test cycle (WLTC) condition of six
different temperature groups to validate its feasibility. Next, a dynamic
objective control strategy is proposed. It divides the operating condition into
multiple time steps, where at each step, non-dominated sorting genetic algorithm
II (NSGA-II) algorithm is employed to perform multi-objective optimization of
cabin temperature, battery temperature, and state of charge (SOC). Different
objectives are prioritized at different stages to achieve dynamic objective
control. A fusion control strategy is developed by combining rule-based control
with dynamic objective control. Finally, a comparative validation of the three
control strategies—rule-based control, multi-objective control, and fusion
control—is conducted under 40°C conditions. The results indicate that the
designed thermal management system is effective. The fusion control strategy not
only achieves desirable temperature control of each subsystem but also achieve
energy reduction to a certain extent, which also alleviates range anxiety.