Thermal issues about Li-ion batteries and recent progress in battery thermal management systems: A review

Liu, Huaqiang; Wei, Zhongbao; He, Weidong; Zhao, Jiyun

doi:10.1016/j.enconman.2017.08.016

Cited by 949 publications

(347 citation statements)

References 188 publications

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“…

C_{p} = \frac{\sum_{i} C_{i} ρ_{i} d_{i}}{\sum_{i} ρ_{i} d_{i}},

where i represents the positive current collector of aluminum sheet, the positive electrode, separator, the negative electrode, and the negative current collector of copper sheet, respectively. It is assumed that temperature and state of charge (SOC) have little effect on the thermal properties of active materials . The above equation works well for the core region.…”

Section: Detailed Thermal Modelmentioning

confidence: 99%

“…BTMS has been commercially applied with air cooling, liquid cooling, and ohmic heating . Moreover, in recent years, some novel methods have been developed, such as phase‐change materials cooling from liquid to gas and from solid to liquid, heat pipes cooling, or a combination use of them . The appropriate BTMS should comprehensively consider battery heat generation and the operating environment .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simplification strategy research on hard‐cased Li‐ion battery for thermal modeling

Xifeng

Zeng²,

Hong-liang

et al. 2020

Int J Energy Res

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Summary Numerical simulation is widely used in research and design of the battery thermal management system (BTMS). Battery cells are commonly homogenized to a block for module or pack level modeling. However, how the homogenization method affects results is not proven. This paper works on a hard‐cased Li‐ion battery to find a proper simplification method. First, a detailed three‐dimensional thermal model (model A) is set up and validated by experimental data. Then, the other three models with different simplification strategies are proposed. They are model B (the cell is homogenized to a block), model C (the cell preserves only core region and housing case), and model D (based on model C, the thin insulation films are also considered). Take the results of model A as a reference, the calculation accuracy and efficiency are summarized. It is found that model B shows the best efficiency and is a proper choice for evaluation of temperature dynamics, while model D is more recommended when the internal temperature distribution of the battery is more concerned.

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“…

C_{p} = \frac{\sum_{i} C_{i} ρ_{i} d_{i}}{\sum_{i} ρ_{i} d_{i}},

Section: Detailed Thermal Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simplification strategy research on hard‐cased Li‐ion battery for thermal modeling

Xifeng

Zeng²,

Hong-liang

et al. 2020

Int J Energy Res

View full text Add to dashboard Cite

show abstract

“…The associated polarization resistance results in a potential difference. For the ohmic resistance, the fourth PRSM is employed, as portrayed in Equation 11. Thus, the ohmic resistance R o can be expressed as (U 1 -U 2 )/I, and the internal polarization resistance R p is (U 2 -U 3 )/I.…”

Section: Identification Of Resistance Dependency On Temperature Andmentioning

confidence: 99%

“…4 Compared with other commercial batteries, lithium-ion (Li-ion) batteries provide high energy and power densities, long lifespan, and environmental benignity, and are therefore preferred in many applications, particularly electrified vehicles. [9][10][11] Therefore, accurately monitoring and predicting temperature dynamics are critical for the design of battery management algorithms and pack structures. 8 While the capacity and power loss become severe at temperatures below 0°C, thermal runaway triggered when temperatures are over certain threshold 7 incurs significant health degradation and even sometimes catastrophic safety hazards, eg, fires and explosions.…”

Section: Introductionmentioning

confidence: 99%

A novel resistance-based thermal model for lithium-ion batteries

Xie

Yang

et al. 2018

Int J Energy Res

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Summary A thermal model considering effects of the state of charge (SOC) and temperature on heat generation is developed for lithium‐ion (Li‐ion) batteries, which models the ohmic resistance, polarization resistance, and entropy change. This model describes a coupling relationship between heat generation and temperature distribution and can be implemented in real time. Then, the thermal model is applied to predict thermal evolutions of an NCR 18650B Li‐ion battery at different ambient temperatures and discharge rates. Extensive experiments are conducted and illustrate that the proposed model can accurately capture the thermal behavior at different ambient temperatures and discharge rates, with an average error of 1.18°C. In addition, comparative studies show that this model significantly outperforms its two counterparts, namely a constant resistance‐based thermal model and a model whose heat generation depends on the temperature but not the SOC.

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“…Moreover, the complex chemical mechanism has certain adverse effects on the capacity, efficiency, and the service life of battery packs. This causes further imbalance of the energy and thermal runaway during the charging and discharging processes of the battery pack and increases the risk of catastrophic events . Therefore, equalization converters are indispensable for cell stacks to resolve the aforementioned disadvantages and prolong the overall lifetime of battery packs …”

Section: Introductionmentioning

confidence: 99%

Analysis and design of multilayer multiphase interleaved converter for battery pack equalization based on graph theory

et al. 2020

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Summary Lithium‐ion batteries play an important role in large‐scale energy storage systems. However, the power inconsistency of the battery packs restricts the developments of modern technologies in energy storage area. The motivation of the present study is to serve the growing needs of the energy balance for lithium‐ion battery packs. The present study proposes a flexible multiphase interleaved converter for the energy equalization of a lithium battery pack with series configuration. Moreover, the graph theory is applied to the analysis of equalization circuits. It is intended to establish a unified standard for the comparison. The parameter of average efficiency is considered as an important indicator to evaluate the performance of the equilibrium system. This mentioned method is verified by constructing a lithium‐ion battery pack with the equalization circuit. It is observed that the proposed multiphase interleaved converter has flexible characteristics, while it has low energy loss compared with the conventional methods. The proposed method simplifies the complex equalization circuits into graphs and facilitates the comparison of the average efficiency of the system. It is concluded that this method is a feasible and powerful for evaluating the battery equalization circuit. This approach can be applied for solving complex problems in other engineering applications.

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Thermal issues about Li-ion batteries and recent progress in battery thermal management systems: A review

Cited by 949 publications

References 188 publications

Simplification strategy research on hard‐cased Li‐ion battery for thermal modeling

Simplification strategy research on hard‐cased Li‐ion battery for thermal modeling

A novel resistance-based thermal model for lithium-ion batteries

Analysis and design of multilayer multiphase interleaved converter for battery pack equalization based on graph theory

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