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REVIEW 4 major objections 4 minor 47 references

A Compact Hybrid Battery Thermal Management System for Enhanced Cooling

T0 review · 4 major / 4 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read A compact hybrid cooling system lowers peak battery temperature by 3.44°C over water cooling while using only 5% more pumping power.

desk verdict Workmanlike COMSOL parametric study of a compact hybrid liquid/PCM battery cooling geometry; the headline 3.44°C gain is plausible but rests on unreported heat-source inputs and no integrated experimental validation. read the letter →

arxiv 2412.00999 v1 pith:V6SGRECB submitted 2024-12-01 eess.SY cs.SY

Zhipeng Lyu (1) , Jinrong Su (2) , Zhe Li (1) , Xiang Li (1) , Hanghang Yan (2) , Lei Chen (2) ((1) School of Mechanical Engineering , Yangtze University , Jingzhou
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China (2) Department of Mechanical Engineering University of Michigan Dearborn USA)
This is my paper · ORCID
classification eess.SYcs.SY
keywords HybridbatterythermalmanagementsystemNanofluidcoolingPhasechangematerialAluminumfoamU-shapedmicrochannelsPulsedflowPumpingpowerLi-ion
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper proposes a compact hybrid battery thermal management system that combines multi-inlet U-shaped microchannels with phase-change material embedded in aluminum foam filling the gap between channels, and cools with an alumina nanofluid whose flow is pulsed once the PCM starts melting. The authors aim to show that this 'NC+PCM+EC' scheme lowers the average maximum surface temperature of a 18650 Li-ion cell at 1C discharge and 25°C ambient to 38.87°C, which is 3.44°C below conventional water cooling, at a pumping-power penalty of only about 5%. If the simulated result holds in hardware, the thermal headroom translates into roughly 6 to 15 percent more charge cycles, which matters for EV range and safety because the fill volume of coolant and PCM is otherwise limited by pack size and weight.

What carries the argument

The argument is carried by four coupled mechanisms. First, the U-shaped multi-inlet microchannel network (channel height 7 mm, width 2 mm) lets coolant enter from the two outer sides and maximizes convection without separate cold plates. Second, the PCM/aluminum-foam composite in the inter-channel gap acts as a passive latent-heat reservoir, modeled with the enthalpy-porosity method; the aluminum foam (porosity 0.95, thermal conductivity 202.4 W/m·K) keeps the PCM's effective conductivity high. Third, the alumina nanofluid (0.2% volume fraction) raises coolant thermal conductivity over plain water. Fourth, the step-response Gaussian pulse flow function is the 'enhanced cooling' trigger: it holds a constant 0.6 g/s flow until the PCM starts liquefying at 250 s, then superimposes a 6-second-period Gaussian pulse with a peak of 0.1 g/s, and returns to steady flow once the average battery surface temperature drops to 40°C. The pulses disrupt the thermal boundary layer, improving convective heat removal during the period when PCM latent heat is most needed.

What would settle it

Build or simulate the exact proposed hybrid system (18650 cells, 7 mm U-shaped channels, RT35 in 0.95-porosity aluminum foam, alumina nanofluid at 0.6 g/s with the Gaussian pulse starting at 250 s) and measure the average maximum surface temperature at 1C discharge and 25°C ambient; if the temperature is not near 38.87°C, or the gap versus conventional water cooling is not about 3.44°C at roughly 5% higher pumping power, the central claim fails. A less expensive check is to reproduce the simulation using explicit values for internal resistance R and entropy coefficient dE/dT, which the paper does not report, and see whether 38.87°C is recovered.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is that a compact hybrid thermal management system—five-layer U-shaped composite liquid channels with the inter-channel gap packed with paraffin RT35 PCM in 0.95-porosity aluminum foam, cooled by an alumina-water nanofluid driven through a step-response Gaussian pulse flow function—achieves an average maximum Li-ion battery surface temperature of 38.87°C at 1C discharge and 25°C ambient, compared with 42.31°C for conventional water cooling. The improvement of 3.44°C comes with only a 5% increase in pumping power. The authors further convert this heat-dissipation gain into an estimated 6 to 15 percent increase in the number of battery charges, and argue this can improve EV range and driving safety.

Load-bearing premise

The predicted 38.87°C peak temperature and the 3.44°C improvement rest on simulated battery heat generation with uniform internal heating and on PCM/aluminum-foam effective properties that were validated only against battery-only experiments, not against the proposed hybrid cooling geometry itself.

Editorial extensions

If this is right

  • At 1C discharge and 25°C ambient, the NC+PCM+EC scheme keeps the average maximum battery surface temperature at 38.87°C, 3.44°C lower than the 42.31°C of conventional water cooling.
  • The cooling improvement costs only about 5% more pumping power, making it a cheap thermal gain in energy terms.
  • The paper estimates that the lower temperature translates into roughly 6 to 15 percent more battery charge cycles over the pack's life.
  • Design guidelines emerge from the parametric study: alumina nanofluid outperforms CuO, TiO2, water, glycol, and kerosene; the outer-inlet fourth cooling direction is best; channel height 7 mm is the efficiency optimum; and 0.6 g/s is the best baseline flow before pulsing.
  • The pulse trigger, starting when PCM melting begins and stopping at 40°C battery surface temperature, is a control scheme that could be implemented in a real battery thermal management controller.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the homogeneous heat-source model is close to a real 18650 cell, the same pulsed-flow control logic should generalize to fast-charging sessions, where PCM saturation arrives sooner; the paper only simulates discharge, so the charging case is an open extension.
  • The 6 to 15 percent cycle-life gain is inferred from temperature reduction, not measured in cycling tests; actual longevity gains depend on how strongly cell aging tracks maximum versus average temperature.
  • Eliminating separate cooling plates could reduce pack weight and volume, but the paper does not quantify pack-level mass or range savings, only the thermal and pumping-power numbers.
  • A direct experimental check would be to build the proposed system with RT35/aluminum-foam layers and alumina nanofluid at 1C, 25°C, and see whether the 38.87°C peak and the 3.44°C delta are reproduced.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The manuscript proposes a compact hybrid battery thermal management system (HBTMS) that combines multi-inlet U-shaped microchannels with PCM/aluminum foam, alumina nanofluid cooling (NC), and a pulsed-flow enhanced-cooling (EC) function. A COMSOL Multiphysics thermal-fluid dynamics model is developed, and the battery heat-generation portion is checked against two external datasets: a vehicle discharge test at 0.1-0.3C (maximum error 14.3%) and Qi et al. [45] at 1-3C (maximum error 4.8%). The model is then used to optimize coolant type, cooling direction, channel height, inlet flow rate, and cooling scheme. The central quantitative claim, stated in Section 3.5 and the Conclusions, is that the NC+PCM+EC scheme reduces the average maximum battery surface temperature to 38.87C at 1C discharge and 25C ambient, which is 3.44C lower than the 42.31C of conventional water cooling, with only about a 5% increase in pumping power, and that this translates to a 6-15% increase in the number of battery charges.

Significance. If the central claim holds, the proposed compact geometry and pulsed nanofluid flow offer a practically meaningful cooling improvement at small pumping-power cost. The paper has several concrete strengths: the battery heat-generation model is checked against two independent experimental datasets; a grid-independence study is reported; and the parametric comparisons across coolants, cooling directions, channel heights, flow rates, and cooling schemes are systematic and clearly presented. The paper is also explicit in its Conclusions that a complete physical experimental study of the integrated HBTMS is planned, which is an honest limitation. However, the headline 38.87C result is a prediction of the integrated simulation, and several load-bearing model inputs and submodel validations are missing, so the result is not yet reproducible or fully trustworthy as stated.

major comments (4)
  1. [Section 2.2, Eq. (2)] The heat generation rate Qgen in Eq. (2) is called the heat production per unit volume, but the equation as written, Qgen = I^2 R - I T dE/dT, has units of power if R is the internal resistance in ohms and dE/dT is in V/K; no cell volume appears. The manuscript never reports the values of R(SOC), dE/dT(SOC), the cell capacity, the 1C current, or the battery volume used in COMSOL. Without these inputs, the predicted 38.87C in Section 3.5 cannot be reproduced or audited, and a sensitivity of the headline temperature to R and dE/dT cannot be assessed. This is a load-bearing omission because Qgen is the driving source for every result in the paper.
  2. [Section 2.6 and Section 2.4] The validation in Section 2.6 is limited to the bare battery heat-generation model: the vehicle test covers 0.1-0.3C and the Qi comparison covers 1-3C, both for bare cells. The proposed HBTMS geometry, the PCM/aluminum-foam phase-change model, the nanofluid effective-property model, and the pulsed-flow submodel are never validated against experiment. The Conclusions explicitly state that a complete physical experimental study of HBTMS is planned. Therefore the abstract's phrase 'experimentally validated thermal-fluid dynamics model' overstates the evidence for the integrated system. In addition, the effective thermal conductivity k_PCM/Al used in Eq. (10) is not defined: Table 1 lists the conductivities of paraffin and aluminum foam separately, and gives a porosity of 0.95, but no mixing rule or effective-medium expression is provided, even though this parameter directly controls the PCM cooling contribution to the 38.87C result.
  3. [Section 3.5 and Section 3.2] The paper refers to the condition in Section 3.5 as a 1C discharge while using a discharge time td = 15 min. A full 1C discharge requires 60 min from 100% SOC, so 15 min corresponds to roughly 25% depth of discharge unless the cell is discharged at a higher rate or from a lower initial SOC. If the simulation ends at 15 min, then the reported maximum temperature is not the end-of-discharge maximum for a true 1C discharge, and the comparison with the conventional water-cooling case may be at different total energy throughputs. This inconsistency affects the central temperature comparison and must be clarified.
  4. [Section 3.5 and Conclusions] The secondary claim that the NC+PCM+EC scheme increases the number of battery charges by 6-15% is asserted without a quantitative basis. No equation or reference is given that converts the temperature reduction from 42.31C to 38.87C, or the different temperature histories of the cooling schemes, into cycle-life gain. The abstract and Highlights repeat this percentage as a headline result, but the manuscript provides no derivation, no SOC- or DOD-dependent aging model, and no experimental cycle data. This claim is therefore unsupported and should be either substantiated or removed.
minor comments (4)
  1. [Section 3.1, Eq. (12) and Section 2.4, Eq. (12)] The equation numbering is duplicated: Eq. (12) is used both for the pumping power P = Δp * V * t and for the PCM melt fraction xi. The figures also label P in units of J, which is energy, not pumping power; the text should distinguish power (W) from energy consumption (J).
  2. [References and Introduction] The introduction cites references starting at [11], but the reference list begins with [1]-[10], which are never cited in the text. The citation numbering should be checked and made consistent.
  3. [Section 3.1 and Table 2] The text says the comparison uses a '0.2% concentration' of nanoparticles and refers to '50% glycol,' while Table 2 lists a single glycol entry without a concentration. The definition of concentration (volume fraction or mass fraction) and the exact glycol-water composition should be stated.
  4. [Abstract and Conclusions] The paper alternately reports 'average maximum temperature' (Abstract) and 'maximum surface temperature' (Conclusions and Section 3.5). These are different quantities; the manuscript should define which is plotted in Fig. 19 and state whether 38.87C is the maximum over the battery surface or the average of the per-cell maxima.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the 3.44C cooling improvement is an unfitted COMSOL simulation output supported by external battery-only validation, not a parameter fit or a self-citation chain.

full rationale

The central prediction that NC+PCM+EC lowers the maximum battery surface temperature from 42.31C to 38.87C at 1C discharge is produced by a physics-based COMSOL model using the heat-generation relation in Eq. (2), coolant properties in Table 2, and PCM/foam parameters in Table 1. None of these inputs were calibrated to obtain 38.87C; the validation in Section 2.6 compares only the bare-cell heat-generation model against a vehicle test and Qi [45], not the integrated HBTMS geometry. The pulse-flow parameters in Eq. (9) are chosen operating conditions, not fitted targets, so the final temperature is a conditional simulation output rather than an input renamed as a prediction. No load-bearing self-citations appear in the derivation chain. The paper does contain non-circular weaknesses: the abstract's 'experimentally validated thermal-fluid dynamics model' overstates the validation scope, the 6-15% cycle-life increase is asserted without a stated conversion model, and the 15-minute '1C' discharge is inconsistent with a full 1C discharge. These are correctness and reporting concerns, not circularity, because no equation or fitted parameter makes the claimed cooling improvement equivalent to the model inputs by construction.

Assumptions & free parameters 6 free parameters · 6 assumptions · 0 invented entities

The central claim rests on a COMSOL model whose battery heat source is not fully specified, and whose validation covers only the battery cell, not the proposed hybrid cooling block. The design choices (flow rate, pulse timing, threshold, channel height, nanofluid concentration) are swept or hand-picked, and the cycle-life gain is asserted. The 1C discharge wording in the abstract conflicts with the 15-minute discharge time used in the sweeps, which is an additional input definition the reader cannot recover from the text.

free parameters (6)
  • Baseline inlet mass flow rate v_m = 0.6 g/s
    Sets coolant flow in all schemes; sweep in Section 3.4 shows the temperature and pumping power trade-off depends on it.
  • Pulse start time t_E = 250 s
    Defines when enhanced cooling begins, tied to PCM liquefaction onset; no sensitivity study is reported.
  • Return threshold T_E = 40°C
    Controls when flow returns to constant v_m; chosen by hand from simulation output.
  • Gaussian pulse parameters = 0.1 g/s peak, 6 s wavelength
    Step-pulse flow function in Eq. (9); values are selected without a reported optimization or sensitivity analysis.
  • Channel height D = 7 mm
    Optimal in Section 3.3 sweep; central to the compactness claim and PCM fill volume.
  • Nanofluid nanoparticle volume fraction = 0.2%
    Used for all nanofluid coolants in Section 3.1; taken from nanofluid practice, not optimized here.
assumptions (6)
  • domain assumption The 18650 battery is a homogeneous body with uniform volumetric heat generation Q_gen = I^2 R - I T dE/dT (Eq. 2).
    Simplifies the battery to a uniform heat source; actual current distribution and SOC-dependent parameters are not modeled or reported.
  • domain assumption Contact thermal resistance inside the HBTMS is neglected; thermophysical properties are constant; PCM volume expansion and post-melting natural convection are ignored.
    Stated in Section 2.5 assumptions (1)-(3); these simplifications tend to make simulated cooling look better than a real assembly.
  • domain assumption Natural convection in melted PCM is negligible because of the small pore size of aluminum foam (porosity 0.95).
    Section 2.4 invokes [23] for this; if convection is not negligible, the effective PCM thermal transport changes.
  • domain assumption Nanofluid density, heat capacity, and thermal conductivity are obtained from the Maxwell-type mixing rules (Eqs. 6-8).
    Effective-property correlations may not capture particle settling, viscosity increase, or clustering in long-duration pulsed flow.
  • ad hoc to paper Battery-only validation (Qi [45] for 1-3C, vehicle test for 0.1-0.3C) transfers to the proposed HBTMS geometry with PCM/foam and nanofluid.
    The central 3.44°C result assumes the heat-generation model is accurate in a different cooling configuration; no experiment on the actual HBTMS is provided.
  • domain assumption Flow is laminar (max Re < 2000) and a global convective heat transfer coefficient of 5 W/m^2K is applied at the system boundary.
    Reasonable for microchannels, but the 5 W/m^2K free-convection coefficient is an assumed value, not measured.

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Pith. "Pith review of A Compact Hybrid Battery Thermal Management System for Enhanced Cooling." pith.science (2026). https://pith.science/paper/V6SGRECB

@misc{pith2026241200999,
  author       = {Pith},
  title        = {Pith review of: A Compact Hybrid Battery Thermal Management System for Enhanced Cooling},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/V6SGRECB}},
  note         = {Machine review of arXiv:2412.00999}
}
read the original abstract

Hybrid battery thermal management systems (HBTMS) combining active liquid cooling and passive phase change materials (PCM) cooling have shown a potential for the thermal management of lithium-ion batteries. However, the fill volume of coolant and PCM in hybrid cooling systems is limited by the size and weight of the HBTMS at high charge/discharge rates. These limitations result in reduced convective heat transfer from the coolant during discharge. The liquefaction rate of PCM is accelerated and the passive cooling effect is reduced. In this paper, we propose a compact hybrid cooling system with multi-inlet U-shaped microchannels for which the gap between channels is embedded by PCM/aluminum foam for compactness. Nanofluid cooling (NC) technology with better thermal conductivity is used. A pulsed flow function is further developed for enhanced cooling (EC) with reduced power consumption. An experimentally validated thermal-fluid dynamics model is developed to optimize operating conditions including coolant type, cooling direction, channel height, inlet flow rate, and cooling scheme. The results show that the hybrid cooling solution of NC+PCM+EC adopted by HBTMS further reduces the maximum temperature of the Li-ion battery by 3.44{\deg}C under a discharge rate of 1C at room temperature of 25{\deg}C with only a 5% increase in power consumption, compared to the conventional liquid cooling method for electric vehicles (EV). The average number of battery charges has increased by about 6 to 15 percent. The results of this study can help improve the range as well as driving safety of new energy EV.

Figures

Figures reproduced from arXiv: 2412.00999 by the authors.

Figure 1
Figure 1. Integrated on-board lithium-ion HBTMS [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Front view and cross section of HBTMS 2.2 Battery heat production model The energy equation for heat transfer from a lithium-ion battery is as follows: 𝜌𝑏𝑐𝑏 𝜕𝑇 𝜕𝑡 = 𝛻(𝑘𝑏𝛻𝑇) + 𝑄𝑔𝑒𝑛 (1) where the subscript b denotes the battery.is the battery density. 𝑐𝑏 is the specific heat capacity of the battery. 𝑘𝑏 is the thermal conductivity of the battery. 𝑇 is the temperature. 𝑄𝑔𝑒𝑛 is the rate of heat generation per unit volume… view at source ↗
Figure 5
Figure 5. Grid validation of HBTMS [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗

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Works this paper leans on

47 extracted references · 47 canonical work pages

  1. [45]

    Wenjie Qi, Wenqi Huang, Juntian Niu, Feng Chen, Bin Chen, Yong Chen, Thermal management of power battery based on flexible Swiss roll type liquid cooling micro -channel, Appl. Therm. Eng. 219 (2023) 119491

    work page 2023

  2. [1]

    G. Zubi, R. Dufo-Lopez, M. Carvalho, G. Pasaoglu, The lithium-ion battery: state of the art and future perspectives, Renew. Sust. Energ. Rev. 89 (2018) 292–308

    work page 2018

  3. [2]

    Jones, R.J.R

    B. Jones, R.J.R. Elliott, V . Nguyen-Tien, The EV revolution: the road a head for critical raw materials demand, Appl. Energy. 280 (2020) 115072

    work page 2020

  4. [3]

    Lin, X.H

    J.Y . Lin, X.H. Liu, S. Li, C. Zhang, S.C. Yang, A review on recent progress, challenges and perspective of battery thermal management system, Int. J. Heat Mass Transf. 167 (2021) 120834

    work page 2021

  5. [4]

    Tete, M.M

    P.R. Tete, M.M. Gupta, S.S. Joshi, Developments in battery thermal management systems for electric vehicles: a technical review, J. Energy Storage. 35 (2021) 102255

    work page 2021

  6. [5]

    Performance of small -scale bladeless electromagnetic energy harvesters driven by water or air, Energy

    Zhao D, Ji C, Teo C, Li S. Performance of small -scale bladeless electromagnetic energy harvesters driven by water or air, Energy. 74 (2014) 99–108

    work page 2014

  7. [6]

    Multi-objective optimization of proton exchange membrane fuel cells by RSM and NSGA-II, Energy Convers Manag

    Chen Z, Zuo W, Zhou K, Li Q, Huang Y , E J. Multi-objective optimization of proton exchange membrane fuel cells by RSM and NSGA-II, Energy Convers Manag. 277(2023) 116691

    work page 2023

  8. [7]

    Numerical investigation of the effect of distributed heat sources on heat-to-sound conversion in a T -shaped thermoacoustic system , Appl

    Zhao D, Li S, Yang W, Zhang Z. Numerical investigation of the effect of distributed heat sources on heat-to-sound conversion in a T -shaped thermoacoustic system , Appl. Energy. 144 (2015) 204–13

    work page 2015

Show all 47 references
  1. [8]

    Numerical investigations on the performance of a hydrogen -fueled micro planar combustor with tube outlet for thermophotovoltaic applications, Energy

    Zuo W, Wang Z, E J, Li Q, Cheng Q, Wu Y , Zhou K. Numerical investigations on the performance of a hydrogen -fueled micro planar combustor with tube outlet for thermophotovoltaic applications, Energy. 263 (2023) 125957

    2023

  2. [9]

    Parametric study of cavity on the performance of a hydrogen-fueled micro planar combustor for thermophotovoltaic applications, Energy

    Zuo W, Li D, E J, Xia Y , Li Q, Quan Y , Zhang G. Parametric study of cavity on the performance of a hydrogen-fueled micro planar combustor for thermophotovoltaic applications, Energy. 263 (2023) 126028

    2023

  3. [10]

    Effects of structure parameters of tube outlet on the performance of a hydrogen -fueled micro planar combustor for thermophotovoltaic applications, Energy

    Zuo W, Chen Z, E J, Li Q, Zhang G, Huang Y . Effects of structure parameters of tube outlet on the performance of a hydrogen -fueled micro planar combustor for thermophotovoltaic applications, Energy. 266 (2023) 126434

    2023

  4. [11]

    Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid, Energy

    Fathy A, Ferahtia S, Rezk H, Yousri D, Abdelkareem MA, Olabi AG. Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid, Energy. 247 (2022) 123447

    2022

  5. [12]

    Battery energy storage systems and SWOT (strengths, weakness, opportunities, and threats) analysis of batteries in power transmission, Energy

    Olabi AG, Wilberforce T, Sayed ET, Abo-Khalil AG, Maghrabie HM, Elsaid K, Abdelkareem MA. Battery energy storage systems and SWOT (strengths, weakness, opportunities, and threats) analysis of batteries in power transmission, Energy. 254 (2022) 123987

    2022

  6. [13]

    Comparative analysis on parametric estimation of a PEM fuel cell using metaheuristics algorithms, Energy

    Wilberforce T, Rezk H, Olabi AG, Epelle EI, Abdelkareem MA. Comparative analysis on parametric estimation of a PEM fuel cell using metaheuristics algorithms, Energy. 262 (2023) 125530

    2023

  7. [14]

    Energy digitalization: main categories, applications, merits and barriers, Energy

    Olabi AG, Abdelkarem MA, Jouhara H. Energy digitalization: main categories, applications, merits and barriers, Energy. 270 (2023) 126899

    2023

  8. [15]

    Concept of reliability and safety assessment of lithium-ion batteries in electric vehicles: basics, progress, and challenges, Appl

    Gandoman FH, Jaguemont J, Goutam S, Gopalakrishnan R, Firouz Y , Kalogiannis T, Omar N, Van Mierlo J. Concept of reliability and safety assessment of lithium-ion batteries in electric vehicles: basics, progress, and challenges, Appl. Energy. 251 (2019) 113343

    2019

  9. [16]

    A numerical study on the performance of a thermal management system for a battery pack with cylindrical cells based on heat pipes, Appl

    Gan Y , He L, Liang J, Tan M, Xiong T, Li Y . A numerical study on the performance of a thermal management system for a battery pack with cylindrical cells based on heat pipes, Appl. Therm. Eng. 179 (2022) 115740

    2022

  10. [17]

    Investigation on the performance enhancement of baffled cold plate based battery thermal management system, J

    Wu C, Wang Z, Bao Y , Zhao J, Rao Z. Investigation on the performance enhancement of baffled cold plate based battery thermal management system, J. Energy Storage. 41 (2021) 102882

    2021

  11. [18]

    Degradation model and cycle life prediction for lithium-ion battery used in hybrid energy storage system, Energy

    Liu C, Wang Y , Chen Z. Degradation model and cycle life prediction for lithium-ion battery used in hybrid energy storage system, Energy. 166 (2019) 796–806

    2019

  12. [19]

    Mitigating thermal runaway of lithium-ion batteries, Joule

    Feng X, Ren D, He X, Ouyang M. Mitigating thermal runaway of lithium-ion batteries, Joule. 4 (2020) 743–70

    2020

  13. [20]

    Heating power effect on the thermal runaway characteristics of large -format lithium ion battery with Li(Ni1/3Co1/3Mn1/3)O2 as cathode

    Huang Z, Shen T, Jin K, Sun J, Wang Q. Heating power effect on the thermal runaway characteristics of large -format lithium ion battery with Li(Ni1/3Co1/3Mn1/3)O2 as cathode. Energy. 239 (2022) 121885

    2022

  14. [21]

    Effects of multi-factors on performance of an improved multi-channel cold plate for thermal management of a prismatic LiFePO4 battery, Energy

    Zuo W, Zhang Y , E J, Huang Y , Li Q, Zhou K, Zhang G. Effects of multi-factors on performance of an improved multi-channel cold plate for thermal management of a prismatic LiFePO4 battery, Energy. 261 (2022) 125384

    2022

  15. [22]

    Y . Chen, M. Sang, W. Jiang, Y . Wang, Y . Zou, C. Lu, Z. Ma, Fracture predictions based on a coupled chemo-mechanical model with strain gradient plasticity theory for film electrodes of Li- ion batteries, Eng. Fract. Mech. 253 (2021) 107866

    2021

  16. [23]

    263 (2023) 126026

    Yang H, Li M, Wang Z, Ma B, A compact and lightweight hybrid liquid cooling system coupling with Z-type cold plates and PCM composite for battery thermal management, Energy. 263 (2023) 126026

    2023

  17. [24]

    Cooling efficiency improvement of air -cooled battery thermal management system through designing the flow pattern , Energy

    Chen K, Wu WX, Yuan F, Chen L, Wang SF. Cooling efficiency improvement of air -cooled battery thermal management system through designing the flow pattern , Energy. 167 (2019) 781–90

    2019

  18. [25]

    Construction of effective symmetrical air- cooled system for battery thermal management, Appl

    Chen K, Chen Y , She Y , Song M, Wang S, Chen L. Construction of effective symmetrical air- cooled system for battery thermal management, Appl. Therm. Eng. 166 (2020) 114679

    2020

  19. [26]

    Self-adapting J-type air-based battery thermal management system via model predictive control, Appl

    Liu Y , Zhang J. Self-adapting J-type air-based battery thermal management system via model predictive control, Appl. Energy. 263 (2020) 114640

    2020

  20. [27]

    Thermal performance of liquid cooling based thermal management system for cylindrical lithium -ion battery module with variable contact surface , Appl

    Rao ZH, Qian Z, Kuang Y , Li YM. Thermal performance of liquid cooling based thermal management system for cylindrical lithium -ion battery module with variable contact surface , Appl. Therm. Eng. 123 (2017) 1514–22

    2017

  21. [28]

    Simulation on cooling performance characteristics of a refrigerant-cooled active thermal management system for lithium ion batteries, Int

    Park S, Jang DS, Lee D, Hong SH, Kim Y . Simulation on cooling performance characteristics of a refrigerant-cooled active thermal management system for lithium ion batteries, Int. J. Heat Mass Transfer. 135 (2019) 131–41

    2019

  22. [29]

    Boundary conditions for Onboard thermal- management system of a battery pack under ultrafast charging, Energy

    Wu X, Du J, Guo H, Qi M, Hu F, Shchurov NI. Boundary conditions for Onboard thermal- management system of a battery pack under ultrafast charging, Energy. 243 (2022) 123075

    2022

  23. [30]

    45 (2023) 102120

    Luo W, Li H, Chu T, A numerical study of battery thermal management system with square spiral ring-shaped liquid cooling plate, Thermal Science and Engineering Progress. 45 (2023) 102120

    2023

  24. [31]

    Energy Storage

    Bao Y , Shao S, Numerical study on ultrathin wide straight flow channel cold plate for Li -ion battery thermal management, J. Energy Storage. 64 (2023) 107263

    2023

  25. [32]

    20 (2023) 20100432

    Tareq S, Malek A, Abdul Ghani Olabi, Ahmed A, Mohammad A, Experimental and numerical analysis of heat transfer enhancement inside concentric counter flow tube heat exchanger using different nanofluids, International Journal of Thermofluids. 20 (2023) 20100432

    2023

  26. [33]

    Tuncer, A

    A.D. Tuncer, A. Khanlari, A. Sozen, E.Y . Gürbüz, H.I. Variyenli, Upgrading the performance of shell and helically coiled heat exchangers with new flow path by using TiO2/water and CuO– TiO2/water nanofluids, Int. J. Therm. Sci. 183 (2023) 107831

    2023

  27. [34]

    Ajeeb, R.R.S

    W. Ajeeb, R.R.S. Thieleke da Silva, S.M.S. Murshed, Experimental investigation of heat transfer performance of Al2O3 nanofluids in a compact plate heat exchanger, Appl. Therm. Eng. 218 (2023) 119321

    2023

  28. [35]

    Energy Storage

    Liu S, Liu Y , Gu H, Tian R, Huang H, Yu T, Experimental study of the cooling performance of γ-Al2O3/heat transfer fluid nanofluid for power batteries, J. Energy Storage. 72 (2023) 108476

    2023

  29. [36]

    Abed, Naef A.A

    Husam Abdulrasool Hasan, Hussein Togun, Azher M. Abed, Naef A.A. Qasem, Aissa Abderrahmane, Kamel Guedri, Sayed M. Eldin, Numerical investigation on cooling cylindrical lithium-ion-battery by using different types of nanofluids in an innovative cooling system, Case Studies in ...

    2023

  30. [37]

    Thermal performance of a cylindrical battery module impregnated with PCM composite based on thermoelectric cooling, Energy

    Jiang L, Zhang HY , Li JW, Xia P. Thermal performance of a cylindrical battery module impregnated with PCM composite based on thermoelectric cooling, Energy. 188 (2019) 116048

    2019

  31. [38]

    Investigation on battery thermal management system combining phase changed material and liquid cooling considering non -uniform heat generation of battery, J

    Ping P, Zhang Y , Kong D, Du J. Investigation on battery thermal management system combining phase changed material and liquid cooling considering non -uniform heat generation of battery, J. Energy Storage. 36 (2021) 102448

    2021

  32. [39]

    Investigation of thermal management for lithium-ion pouch battery module based on phase change slurry and mini channel cooling plate, Energy

    Bai F, Chen M, Song W, Yu Q, Li Y , Feng Z, Ding Y . Investigation of thermal management for lithium-ion pouch battery module based on phase change slurry and mini channel cooling plate, Energy. 167 (2019) 561–74

    2019

  33. [40]

    Experimental study on the thermal management performance of phase change material module for the large format prismatic lithiumion battery, Energy

    Zhou Z, Wang D, Peng Y , Li M, Wang B, Cao B, Yang LZ. Experimental study on the thermal management performance of phase change material module for the large format prismatic lithiumion battery, Energy. 238 (2022) 122081

    2022

  34. [41]

    Structure optimization of a heat pipe -cooling battery thermal management system based on fuzzy grey relational analysis, Int

    He LF, Tang XW, Luo QL, Liao YP, Luo XY , Liu JL, Ma L, Dong D, Gan YH, Li Y . Structure optimization of a heat pipe -cooling battery thermal management system based on fuzzy grey relational analysis, Int. J. Heat Mass Tran. 182 (2022) 121924

    2022

  35. [42]

    Experimental investigation on the thermal performance of heat pipe -assisted phase change material based battery thermal management system, Energy Convers Manag

    Wu W, Yang X, Zhang G, Chen K, Wang S. Experimental investigation on the thermal performance of heat pipe -assisted phase change material based battery thermal management system, Energy Convers Manag. 138 (2017) 486–92

    2017

  36. [43]

    Experimental investigation on EV battery cooling and heating by heat pipes, Appl

    Wang Q, Jiang B, Xue QF, Sun HL, Li B, Zou HM, Yan YY . Experimental investigation on EV battery cooling and heating by heat pipes, Appl. Therm. Eng. 88 (2015) 54–60

    2015

  37. [44]

    Energy Storage

    Liu Z, Xu G, Xia Y , Tian S, Numerical study of thermal management of pouch lithium -ion battery based on composite liquid-cooled phase change materials with honeycomb structure, J. Energy Storage. 70 (2023) 108001

    2023

  38. [46]

    Yonghao Wang, Tieyu Gao, Liang Zhou, Jianying Gong, Jun Li, A parametric study of a hybrid battery thermal management system that couples PCM with wavy microchannel cold plate, Appl. Therm. Eng. 219 (2023) 119625

    2023

  39. [47]

    273 (2023) 127250

    Dexin Li, Wei Zuo, Qingqing Li, Guangde Zhang, Kun Zhou, Jiaqiang E, Effects of pulsating flow on the performance of multi -channel cold plate for thermal management of lithium -ion battery pack, Energy. 273 (2023) 127250

    2023

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.