The burgeoning electric vehicle industry has become a crucial player in tackling environmental pollution and addressing oil scarcity. As these vehicles continue to advance, effective thermal management systems are essential to ensure battery safety, optimize energy utilization, and prolong vehicle lifespan. This paper presents an exhaustive review of diverse thermal management approaches at both the component and system levels, focusing on electric vehicle air conditioning systems, battery thermal management systems, and motor thermal management systems. In each subsystem, an advanced heat transfer process with phase change is recommended to dissipate the heat or directly cool the target. Moreover, the review suggested that a comprehensive integration of AC systems, battery thermal management systems, and motor thermal management systems is inevitable and is expected to maximize energy utilization efficiency. The challenges and limitations of existing thermal management systems, including system integration, control algorithms, performance balance, and cost estimation, are discussed, along with potential avenues for future research. This paper is expected to serve as a valuable reference for forthcoming research.

Electric vehicles are seen as the prevailing choice for eco-friendly transportation. In electric vehicles, the thermal management system of battery cells is of great significance, especially under high operating temperatures and continuous discharge conditions. To address this issue, a pack-level battery thermal management system with phase change materials and liquid cooling was discussed in this paper. A dynamic electro-thermal coupled model for cells, the enthalpy–porosity model for phase change materials, and the k-ε model for the coolant flow were used. Various parameters, such as ambient temperatures, discharge rates, components of phase change materials, inlet mass flow rates, and temperatures of the coolant were considered. The results indicated that a battery thermal management system with both phase change materials and liquid cooling is more effective than the one with only liquid cooling. The phase change material with a mass fraction of 10% expanded graphite in paraffin wax had a favorable performance for the battery thermal management system. Additionally, increasing the mass flow rate or decreasing the flow temperature of the coolant can reduce the maximum temperature of the battery pack. However, the former can limit the maximum temperature difference, while the latter will deteriorate the temperature uniformity. The present work may shed light on the design of battery thermal management systems in the electric vehicle industry.

Thermal management technology based on loop heat pipes (LHPs) has broad application prospects in heat transfer control for aerospace and new energy vehicles. LHPs offer excellent heat transfer performance, reliability, and flexibility, making them suitable for high-heat flux density, high-power heat dissipation, and complex thermal management scenarios. However, due to limitations in heat source temperature and heat transfer power range, LHP-based thermal management systems still face challenges, especially in thermohydraulic modeling, component design, and optimization. Steady-state models improve computational efficiency and accuracy, while transient models capture dynamic behavior under various conditions, aiding performance evaluation during start-up and non-steady-state scenarios. Designs for single/multi-evaporators, compensation chambers, and wick materials are also reviewed. Single-evaporator designs offer compact and efficient start-up, while multi-evaporator designs handle complex thermal environments with multiple heat sources. Innovations in wick materials, such as porous metals, composites, and 3D printing, enhance capillary driving force and heat transfer performance. A comprehensive summary of working fluid selection criteria is conducted, and the effects of selecting organic, inorganic, and nanofluid working fluids on the performance of LHPs are evaluated. The selection process should consider thermodynamic properties, safety, and environmental friendliness to ensure optimal performance. Additionally, the mechanism and optimization methods of the start-up behavior, temperature oscillation, and non-condensable gas on the operating characteristics of LHPs were summarized. Optimizing vapor/liquid distribution, heat load, and sink temperature enhances start-up efficiency and minimizes temperature overshoot. Improved capillary structures and working fluids reduce temperature oscillations. Addressing non-condensable gases with materials like titanium and thermoelectric coolers ensures long-term stability and reliability. This review comprehensively discusses the development trends and prospects of LHP technology, aiming to guide the design and optimization of LHP.

Predicting the core temperature of a Li-ion battery is crucial for precise state estimation, but it is difficult to directly measure. Existing quick temperature-predicting approaches can hardly consider the thermal mass of complex structure that may cause time delays, particularly under high C-rate dynamic conditions. In this paper, we developed a quick temperature prediction algorithm based on a thermal convolution method (TCM) to calculate the core temperature of a flat heat pipe-based battery thermal management system (FHP-BTMS) under dynamic conditions. The model could predict the core temperature rapidly through convolution of the thermal response map which contains full physical information. Firstly, in order to obtain a high fidelity spatio-temporal temperature distribution, the thermal capacitance-resistance network (TCRN) of the FHP-BTMS is established and validated by constant and dynamic discharging experiments. Then, the response map of the core temperature motivated by various impulse heat sources and heat sinks is obtained. Specifically, the dynamic thermal characteristics of an FHP are discussed to correct the boundary conditions of the TCM. Afterwards, the temperature prediction performances of the TCM and a lumped model under different step operating conditions are compared. The TCM results show a 70–80% accuracy improvement and better dynamic adaptivity than the lumped model. Lastly, a vertical take-off and landing (VTOL) profile is employed. The temperature prediction accuracy results show that the TCM can maintain a relative error below 5% throughout the entire prediction period.