Review of Thermal Management Technology for Electric Vehicles

Dan, Dan; Zhao, Yihang; Wei, Mingshan; Wang, Xuehui

doi:10.3390/en16124693

Cited by 28 publications

(9 citation statements)

References 192 publications

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“…One primary issue is thermal management, predominantly the dissipation of waste heat, i.e., cooling [8,9]. In fuel combustion cars, heat production predominantly correlates with the duration of use and the velocity attained, and hence heat dissipation is mostly achieved by harvesting the air motion resulting from self-motion.…”

Section: Introduction 1cooling In Electric Mobilitymentioning

confidence: 99%

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Reducing Automotive Cooling System Complexity through an Adaptive Biomimetic Air Control Valve

Thuilot,

Wullweber,

Fischer

et al. 2024

Biomimetics

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Future automotive mobility is predominantly electric. Compared to existing systems, the requirements of subsystems change. Air flow for cooling components is needed predominantly when the car is in rest (i.e., charging) or at slow speeds. So far, actively driven fans consuming power and generating noise are used in this case. Here we propose a passive adaptive system allowing for convection-driven cooling. The developed system is a highly adaptive flat valve derived from the bordered pit. It was developed through an iterative design process including simulations, both structural and thermodynamic. In hardwoods and conifers, bordered pits enable the challenging transport of vertical fluids by locally limiting damage. Depending on the structure, these can close at sudden pressure changes and take the function of valves. The result of the biomimetic abstraction process is a system-integrative, low-profile valve that is cheap to produce, long-lasting, lightweight, maintenance-free, and noise-free. It allows for the passive switching of air flow generation at the heat exchanger of the cooling between natural convection or an active airstream without the need for complex sensing and control systems. The geometric and material design factors allow for the simple tuning of the valve to the desired switching conditions during the design process.

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Section: Introduction 1cooling In Electric Mobilitymentioning

confidence: 99%

“…On the other hand, battery-electric vehicles generate the most heat both during charging and at low speeds when generating high torque (e.g., uphill driving) [8,9]. In both cases, "free" wind cannot be harnessed, and additional generated ventilation becomes a recurring, noisy, and power-consuming nuisance.…”

Section: Introduction 1cooling In Electric Mobilitymentioning

confidence: 99%

Reducing Automotive Cooling System Complexity through an Adaptive Biomimetic Air Control Valve

Thuilot,

Wullweber,

Fischer

et al. 2024

Biomimetics

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“…Therefore, the current transportation sector is undergoing a drastic change of replacing internal combustion engine vehicles with electric vehicles to achieve a carbon-free and energy-sustainable future [5,6]. Electric vehicles offer several benefits, such as a safe and clean environment and improved safety and human health [7,8]. In addition, the ecological benefits of electric vehicles could be extended by charging their batteries from renewable energy sources [9].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Modeling to Predict Thermal and Electrical Performances of Batteries with Direct Oil Cooling

Garud,

Han,

Hwang

et al. 2023

Batteries

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The limitations of existing commercial indirect liquid cooling have drawn attention to direct liquid cooling for battery thermal management in next-generation electric vehicles. To commercialize direct liquid cooling for battery thermal management, an extensive database reflecting performance and operating parameters needs to be established. The development of prediction models could generate this reference database to design an effective cooling system with the least experimental effort. In the present work, artificial neural network (ANN) modeling is demonstrated to predict the thermal and electrical performances of batteries with direct oil cooling based on various operating conditions. The experiments are conducted on an 18650 battery module with direct oil cooling to generate the learning data for the development of neural network models. The neural network models are developed considering oil temperature, oil flow rate, and discharge rate as the input operating conditions and maximum temperature, temperature difference, heat transfer coefficient, and voltage as the output thermal and electrical performances. The proposed neural network models comprise two algorithms, the Levenberg–Marquardt (LM) training variant with the Tangential-Sigmoidal (Tan-Sig) transfer function and that with the Logarithmic-Sigmoidal (Log-Sig) transfer function. The ANN_LM-Tan algorithm with a structure of 3-10-10-4 shows accurate prediction of thermal and electrical performances under all operating conditions compared to the ANN_LM-Log algorithm with the same structure. The maximum prediction errors for the ANN_LM-Tan and ANN_LM-Log algorithms are restricted within ±0.97% and ±4.81%, respectively, considering all input and output parameters. The ANN_LM-Tan algorithm is suggested to accurately predict the thermal and electrical performances of batteries with direct oil cooling based on a maximum determination coefficient (R2) and variance coefficient (COV) of 0.99 and 1.65, respectively.

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“…With the continuous advancement of electric vehicle (EV) technology, thermal management systems have been a crucial part of electric vehicles and are evolving toward high integration [1,2]. The performance of an integrated thermal management system (ITMS), which consists of an air conditioning (AC) system, battery thermal management system (BTMS), and drive motor thermal management system [3][4][5], significantly impacts the mileage, performance, and lifespan of EVs [6,7].…”

Section: Introductionmentioning

confidence: 99%

Flow Loss Analysis and Structural Optimization of Multiway Valves for Integrated Thermal Management Systems in Electric Vehicles

Zheng

Wei

2023

Energies

Self Cite

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The multiway valve is the core component of the integrated thermal management system in an electric vehicle, and its heat transfer loss and pressure loss significantly impact the performance of the whole thermal management system. In this paper, heat transfer loss and pressure loss in multiway valves are investigated using three-dimensional unsteady numerical simulations. Heat transfer loss and pressure loss under different operating modes are revealed, and relationships between pressure loss and mass flow rate, inlet temperature, and valve materials are studied. The results show that the significant temperature gradient around the control shaft results in heat transfer loss and pressure loss mainly occurs around the junction of the control shaft and the shell, where the flow direction changes sharply. The pressure loss is nonlinearly and positively correlated with the mass flow rate. Furthermore, the main geometric parameters of the pipeline and the control shaft are optimized. The pressure loss firstly increases and then decreases, with the increasing curvature of the inner walls of the pipe corners in four flow channels. Compared with the structural optimization at the pipe corners, increasing the curvature of the inner wall of the control shaft and the shell corners reduces pressure loss continuously. Moreover, this study obtains an optimal structure with minimum pressure loss using coupled structure optimization at the control shaft and shell corners.

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Review of Thermal Management Technology for Electric Vehicles

Cited by 28 publications

References 192 publications

Reducing Automotive Cooling System Complexity through an Adaptive Biomimetic Air Control Valve

Reducing Automotive Cooling System Complexity through an Adaptive Biomimetic Air Control Valve

Artificial Neural Network Modeling to Predict Thermal and Electrical Performances of Batteries with Direct Oil Cooling

Flow Loss Analysis and Structural Optimization of Multiway Valves for Integrated Thermal Management Systems in Electric Vehicles

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