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Batteries
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Thermal Management System for Lithium-Ion Batteries: 2nd Edition
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Thermal Management System for Lithium-Ion Batteries: 2nd Edition

A special issue of Batteries (ISSN 2313-0105). This special issue belongs to the section "Battery Modelling, Simulation, Management and Application".

Deadline for manuscript submissions: 20 June 2025 | Viewed by 1801

Special Issue Editors

Prof. Dr. Jinsheng Xiao

E-Mail Website
Guest Editor
Hubei Research Center for New Energy & Intelligent Connected Vehicle, School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: batteries for electric vehicles; lithium-ion batteries; thermal management; heat transfer; hydrogen production and storage; hydrogen refueling system; renewable and clean energies
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hengyun Zhang

E-Mail Website
Guest Editor
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
Interests: battery thermal management; battery test; phase change materials; electronics cooling
Special Issues, Collections and Topics in MDPI journals
Dr. Tianqi Yang

E-Mail Website
Guest Editor
Hubei Research Center for New Energy & Intelligent Connected Vehicle, School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: hydrogen energy; lithium-ion battery; heat and mass transfer; energy transition

Special Issue Information

Dear Colleagues,

Lithium-ion batteries (LIBs) have been widely used as power sources for both industry and daily life. This is mainly due to their salient features, such as high energy density, high power output, low self-discharge rate and little memory effect. Nonetheless, the performances of LIBs are highly dependent on the operating temperature. A higher temperature would cause accelerated battery degradation with shortened lifetime and even thermal runaway, and a lower temperature would cause reduced discharge capacity and rate, leading to mileage anxiety and sudden power failure. Research on the thermal and energy storage performances of LIBs is still limited in terms of thermal and safety design in demanding application scenarios.

This Special Issue, titled “Thermal Management System for Lithium-Ion Batteries: 2nd Edition”, aims to present and disseminate the most recent advances in the thermal management of LIBs under various application conditions. Topics of interest for publication include, but are not limited to, the following:

  • Liquid cooling and its hybrid forms;
  • Air cooling;
  • Phase change materials and coupled cooling;
  • Refrigeration cooling;
  • Thermal safety performance;
  • Thermal runaway;
  • Dynamic thermal performance under operating conditions;
  • Advanced modeling techniques such as machine learning;
  • Multi-scale approach (from battery cell, module, and pack to system scale).

Prof. Dr. Jinsheng Xiao
Prof. Dr. Hengyun Zhang
Dr. Tianqi Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Batteries is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • liquid cooling and its hybrid forms
  • air cooling
  • phase change materials and coupled cooling
  • refrigeration cooling
  • thermal safety performance
  • dynamic thermal performance under operating conditions
  • advanced modeling techniques

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Related Special Issue

Published Papers (2 papers)

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Research

27 pages, 15381 KiB  
Article
Design Optimization of Bionic Liquid Cooling Plate Based on PSO-BP Neural Network Surrogate Model and Multi-Objective Genetic Algorithm
by Jiaming Liu, Wenlin Yuan, Yapeng Zhou and Hengyun Zhang
Batteries 2025, 11(4), 141; https://doi.org/10.3390/batteries11040141 - 5 Apr 2025
Viewed by 283
Abstract
In this study, the particle swarm optimization (PSO) and back propagation neural network (BPNN) surrogate model in combination with a multi-objective genetic algorithm are developed for the design optimization of a bionic liquid cooling plate with a spider-web channel structure. The single-factor sensitivity [...] Read more.
In this study, the particle swarm optimization (PSO) and back propagation neural network (BPNN) surrogate model in combination with a multi-objective genetic algorithm are developed for the design optimization of a bionic liquid cooling plate with a spider-web channel structure. The single-factor sensitivity analysis is first conducted based on the numerical simulation approach, identifying three key factors as design variables for optimizing design objectives such as maximum temperature (Tmax), maximum temperature difference (ΔTmax), and pressure drop (ΔP). Subsequently, the PSO algorithm is used to optimize the parameters of the BPNN structure, thereby constructing the PSO-BPNN surrogate model. Next, the non-dominated sorting genetic algorithm II (NSGA-II) is employed to obtain the Pareto optimal set, and the TOPSIS with the entropy weight method is used to determine the optimal solution, eliminating subjective preferences in decision-making. The results show that the PSO-BPNN model outperforms the traditional BPNN in prediction accuracy for all three objectives. Compared to the initial structure, the Tmax and ΔTmax are reduced by 1.09 °C and 0.41 °C in the optimized structure, respectively, with an increase in ΔP by 21.24 Pa. Full article
(This article belongs to the Special Issue Thermal Management System for Lithium-Ion Batteries: 2nd Edition)
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18 pages, 5104 KiB  
Article
Experimental Investigation of Phase Change Material-Based Battery Pack Performance Under Elevated Ambient Temperature
by Mohammad J. Ganji, Martin Agelin-Chaab and Marc A. Rosen
Batteries 2025, 11(2), 67; https://doi.org/10.3390/batteries11020067 - 8 Feb 2025
Viewed by 1109
Abstract
This study experimentally assesses the thermal performance of a proposed phase change material (PCM)-based battery pack under elevated ambient temperatures. In addition, the novel approach of the research addresses scenarios where the ambient temperature reaches the PCM’s melting point while maintaining the initial [...] Read more.
This study experimentally assesses the thermal performance of a proposed phase change material (PCM)-based battery pack under elevated ambient temperatures. In addition, the novel approach of the research addresses scenarios where the ambient temperature reaches the PCM’s melting point while maintaining the initial temperature at the ideal operating point of 22 °C. The experiments employed nine 2500 mAh 18650 lithium-ion cells connected in series and subjected to constant-current discharges of 1C and 3C, with a conventional air-cooled system as the baseline and paraffin as the PCM. The results indicate that as the ambient temperature reached the PCM’s melting point, approximately 98% utilization of the PCM around the heating cell was achieved. Additionally, the PCM demonstrates noticeable advantages over the baseline by stabilizing the temperature profile and reducing the maximum temperature increase rate from over 18 °C in the baseline system to around 7 °C. Notably, under a high-load (3C) discharge rate, the PCM-based system successfully maintained battery temperatures below 42 °C, demonstrating its effectiveness under demanding operational scenarios. These findings establish a critical baseline for PCM-based BTMSs operating under elevated ambient temperatures and up to the melting point of the PCM, thereby informing future research and development of more efficient PCM-based thermal management solutions. Full article
(This article belongs to the Special Issue Thermal Management System for Lithium-Ion Batteries: 2nd Edition)
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