An up-to-date review on the design improvement and optimization of the liquid-cooling battery thermal management system for electric vehicles

Zhao, Gang; Wang, Xiaolin; Negnevitsky, M; Li, Chengjiang

doi:10.1016/j.applthermaleng.2022.119626

Cited by 161 publications

(33 citation statements)

References 194 publications

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Section: Mathematical Modelingmentioning

confidence: 99%

“…According to the law of the conservation of energy, the amount of energy added to the battery pack is equal to the energy generated within it plus the energy transferred to it by the coolant. The change in battery pack temperature is caused by its increased heat, as shown in eqn (7): 30,31 where T b is the temperature of the battery pack, C b is the specific heat capacity of the battery pack, m b,p is the collective mass of the battery pack, Q g,p is the heat generated inside the battery pack, Q h,p is the heat absorbed by the battery pack from the coolant, and Q a is the heat diffused from the battery pack to the external low temperature environment.…”

Section: Experimental Platform and Mathematical Modelingmentioning

confidence: 99%

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Reinforcement learning-based control for the thermal management of the battery and occupant compartments of electric vehicles

Zhang,

Huang,

et al. 2024

Sustainable Energy Fuels

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Section: Mathematical Modelingmentioning

confidence: 99%

Section: Experimental Platform and Mathematical Modelingmentioning

confidence: 99%

Reinforcement learning-based control for the thermal management of the battery and occupant compartments of electric vehicles

Zhang,

Huang,

et al. 2024

Sustainable Energy Fuels

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“…Presently, the principal cooling modes of BTMS encompass liquid cooling, [6,7] air cooling, [5,8,9] phase change material cooling, [3,10] and combinations for these modes. [11][12][13] Among these, air cooling is widely used in automotive applications owing to its low cyclical cost and straightforward structure.…”

Section: Introductionmentioning

confidence: 99%

Cooling Performance Optimization of Air‐Cooled Battery Thermal Management System with L‐Type Flow

2023

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The development of electric vehicles has driven the refinement of thermal management technology for batteries. Due to the limitations of device locations during operation, battery thermal management systems (BTMS) with diverse geometric configurations should be considered. Herein, optimization of the L‐type air‐cooled structures (L(A) and L(B)) is performed with the objective of minimizing the maximum temperature difference while avoiding increasing system power consumption. The simulation indicates that optimization of the plenum angle is more effective than the widths of the divergence and convergence plenums for the BTMS L(A). Multivariate optimization of angle and widths decreases maximum temperature (Tmax) by 1.79 K and maximum temperature difference (ΔTmax) by 2.45 K compared to the original BTMS. The adjustment of BTMS L(B) takes place in three aspects: plenum widths, inlet position, and baffle setting. Among these, optimizing the plenum widths proves to be the most efficient method. The Tmax and ΔTmax decrease by 1.41 and 2.13 K, respectively, and the power consumption decreases by 11.30% compared to the original BTMS. The optimal systems display improved cooling performance under varying battery heat generation rates and air flow rates, demonstrating the effectiveness of the optimization methods in enhancing cooling efficiency.

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“…Lithium-ion batteries are the primary power source of electric vehicles and energy storage power stations [3][4] .…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Effect of State of Charge on Failure Propagation Characteristics within Battery Modules

Rui

et al. 2023

Chin. J. Electr. Eng.

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To investigate the effect of different states of charge(SOC) on the thermal runaway(TR) propagation behaviors within lithium-ion-batteries based energy storage modules, an experimental setup was developed to conduct failure propagation tests on battery modules at an SOC of 97%, 85%, and 50%. The result indicates that an increase in the SOC of batteries can decrease the TR trigger temperature, making batteries trigger TR earlier and reducing the average failure propagation time between two adjacent cells.In addition, the failure propagation tests reveal that at higher SOCs, the TR reaction becomes more violent, the maximal reaction temperature is also much higher, and the damage to the battery module is severe. Compared to the battery module with 97% SOC, the TR trigger time of the battery module with 50% SOC was postponed by approximately 57.8%. Meanwhile, the average failure propagation time got prolonged by approximately 36.0%. Thus, this study can provide references for the thermal safety design of energy-storage battery modules.

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An up-to-date review on the design improvement and optimization of the liquid-cooling battery thermal management system for electric vehicles

Cited by 161 publications

References 194 publications

Reinforcement learning-based control for the thermal management of the battery and occupant compartments of electric vehicles

Reinforcement learning-based control for the thermal management of the battery and occupant compartments of electric vehicles

Cooling Performance Optimization of Air‐Cooled Battery Thermal Management System with L‐Type Flow

Experimental Study on the Effect of State of Charge on Failure Propagation Characteristics within Battery Modules

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