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.

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Review of Thermal Management Technology for Electric Vehicles

The control of a battery thermal management system (BTMS) is essential for the thermal safety, energy efficiency, and durability of electric vehicles (EVs) in hot weather. To address the battery cooling optimization problem, this paper utilizes dynamic programming (DP) to develop an online rule-based control strategy. Firstly, an electrical–thermal-aging model of the LiFePO4 battery pack is established. A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures. Then in the DP framework, a cost function consisting of battery aging cost and cooling-induced electricity cost is minimized to obtain the optimal compressor power. By exacting three rules ”fast cooling, slow cooling, and temperature-maintaining” from the DP result, a near-optimal rule-based cooling strategy, which uses as much regenerative energy as possible to cool the battery pack, is proposed for online execution. Simulation results show that the proposed online strategy can dramatically improve the driving economy and reduce battery degradation under diverse operation conditions, achieving less than a 2.18% difference in battery loss compared to the offline DP. Recommendations regarding battery cooling under different real-world cases are finally provided. 

Optimal battery thermal management for electric vehicles with battery degradation minimization

As electric vehicles (EVs) become more commonplace, the development and deployment of advanced battery thermal management (BTM) technologies are vital for increasing the sturdiness of EV batteries, ultimately contributing to the sustainable and massive adoption of electric mobility. This study comprehensively evaluates new advancements in BTM systems for EVs, supplemented with a comparative evaluation of various BTM technologies, including active and passive cooling strategies, structure design, and advanced control algorithms, including deep learning methods. The study also scrutinizes the software's capabilities employed for designing BTM systems. The cross-relevant papers related to BTM systems from 2019 to early 2024, which rely on Scopus and Web of Science databases, are considered. The comparative evaluation explores the strengths and obstacles of different BTM processes, shedding light on their efficacy under varying operational conditions. Additionally, this study discusses the impact of BTM on overall EV efficiency from the perspective of thermal considerations. Insights into current research trends, innovations, and emerging trends in the field are also presented. Ultimately, this state-of-the-art study aims to thoroughly understand the latest BTM for EVs. The findings offer insightful information for scientists, engineers, and professionals pursuing sustainable transportation development and the continuous enhancement of EV technology. 

Advancements in battery thermal management for electric vehicles: Types, technologies, and control strategies including deep learning methods

Collaborative thermal management is a promising approach for improving the energy efficiency of electric vehicles by optimizing both the battery and passenger cabin temperatures. This study proposes a novel collaborative thermal management system that addresses key performance aspects such as battery safety, cabin comfort, and system efficiency. The system utilizes a vehicle speed prediction-nonlinear model predictive control strategy (SP-NMPC) based on genetic algorithm. Experimental testing validates the effectiveness and accuracy of the proposed method. Temperature variations in the battery and passenger cabin are compared at ambient temperatures of 30℃ and 40℃ using the SP-NMPC and prototype original control strategy. The Mean Square Error (MSE) values are calculated and compared. Results show that the original control strategy yielded MSE values of 0.0722 and 0.3334 for the passenger cabin temperature at 30℃ and 40℃, respectively. In contrast, employing SP-NMPC under similar conditions achieved significantly lower MSE values of 0.0513 and 0.0521. This highlights the superior accuracy and resilience of SP-NMPC in maintaining passenger cabin temperature, reducing fluctuations, and enhancing passenger comfort. Moreover, the system achieves energy savings, reducing thermal management energy consumption by 5.59% and 5.20% at ambient temperatures of 30 °C and 40 °C, respectively, thereby extending the vehicle's range. 

Collaborative thermal management of power battery and passenger cabin for energy efficiency optimization

Efficient integrated thermal management scheme is crucial for improving the driving range, thermal comfort, and safety of electric vehicles. Compared with the synthetic refrigerant heat pump indirect cooling/heating on the vehicle electrical system, the natural refrigerant CO2 heat pump direct thermal controlling integrated into the thermal management system has advantages in the thermal cycle performance and environmental friendliness. The present study proposed a thermal management system based on CO2 heat hump with multiple working modes for enhancing vehicle energy utilization coefficient. The system thermal performance under the World Light Vehicle Test Cycle was investigated via energy and exergy analyses. The operational control strategies of the thermal management system were optimized for the thermal controls of the cabin, battery and motor. The results show that the minimum exergy destruction of the thermal system occurs at the optimal discharge pressure corresponding to the highest coefficient of performance. Ensuring two-phase latent heat transfer for battery cooling is the most effective measure to maintain battery temperature uniformity via dynamic collaborative regulation of expansion valves' openings and compressor speed. Compared with constant expansion valve's opening, the coefficient of performance of the system can be improved by a maximum of 10% with the saturated CO2 vapor at the outlet of battery cooling plate. Due to the low thermal capacitance and minimal thermal inertia of driving motor, its cooling performance is significantly influenced by the heat generation rate and refrigerant flow. Optimal motor cooling efficiency is achieved when controlling the refrigerant quality to 0.85 at the cooling passage outlet. Under the World Light Vehicle Test Cycle, the thermal management system effectively regulated the temperatures across different operating modes while operating at optimal discharge pressures. 

Cooling performance and optimization of a thermal management system based on CO2 heat pump for electric vehicles

A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion

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A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion