Thermal Management in Lithium-Ion Batteries: Latest Advances and Prospects

Dear Colleagues,

The rapidly expanding battery market presents an urgent requirement for reliable, efficient, and affordable thermal management and protection solutions. These solutions are crucial to improve the cycle life and performance, as well as to mitigate the risk of thermal runaway and catastrophic failures in battery packs. Addressing these pressing needs is of the utmost importance for the power electronics, electric vehicle, and battery industries. By enhancing the safety of battery packs, we can facilitate the widespread adoption of batteries in energy-intensive applications such as electric vehicles and grid-scale energy storage systems. In addition, a higher battery cycle life improves the long-term cost–benefit of a battery electric vehicle or energy storage system. Advanced thermal management strategies can also improve performance, such as fast charging and aggressive discharges across a large temperature band, which further supports battery technology adaptation. Therefore, there is a critical imperative to develop robust, efficient, and cost-effective thermal management strategies that ensure the performance, integrity, and stability of battery systems.

In light of the rapid growth witnessed in the electric vehicle and rechargeable battery markets, this Special Issue, entitled “Thermal Management in Lithium-Ion Batteries: Latest Advances and Prospects”, presents an opportune platform to explore diverse thermal management technologies. It specifically focuses on their application in battery and electronics systems for transportation applications, including passenger cars, trucks, buses, locomotives, boats, aircraft, and beyond, encompassing both established industry practices and emerging solutions for future advancements. By examining conventional approaches alongside cutting-edge innovations, this timely collection of articles aims to address the evolving demands of the field and foster insights into effective thermal management strategies.

We encourage contributions from diverse global stakeholders to foster a comprehensive and inclusive dialogue. Valuable insights and expertise from academic institutions, industry organizations, and national laboratories are highly valued and encouraged. Both experimental studies and numerical simulations are welcomed. Topics of interest for publication include, but are not limited to:

• Assessment of industry approaches and emerging advancements;
• Single-phase cooling (passive, direct active, indirect active, and hybrid);
• Multi-phase cooling (phase change materials, evaporative cooling, immersion/submerged cooling);
• Innovative cooling materials and structures;
• Advanced sensors, thermal control, and fault detection;
• Battery materials and designs with improved thermal properties;
• Strategies to mitigate thermal runaway and propagation;
• Cutting-edge models to gain insights into thermal-related degradation mechanisms;
• New mechanistic models to understand degradation caused by thermal issues;
• Fusion of machine learning algorithms to enhance the precision and efficiency of detection and prediction;
• Extreme conditions such as extremely fast charge and low temperatures.

Dr. Xianglin Li
Dr. Chuanbo Yang
Dr. Prahit Dubey
Guest Editors

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Title: Recent Progress of Deep Learning Methods for Health Monitoring of Lithium-ion Batteries
Authors: Seyed Saeed Madani 1; Parisa Vahdatkhah 2; S.K. Sadrnezhaad 2; Carlos Ziebert 1
Affiliation: 1. Institute of Applied Materials-Applied Materials Physics, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany; 2. Department of Materials Science and Engineering, Sharif University of Technology, Tehran 11365-9466, Iran
Abstract: In recent years, the field of transportation electrification has experienced significant advancements, predominantly driven by the adoption of lithium-ion batteries (LIBs) as the primary energy storage solution. Ensuring the safe and efficient operation of these LIBs is imperative, and Battery Management Systems (BMS) play a pivotal role in this regard. Within the spectrum of BMS functions, state and temperature monitoring stand out as critical aspects for intelligent LIB management. Accurate prediction of the state of health (SOH) of LIBs not only extends battery lifespan but also provides invaluable insights for optimizing battery usage. Furthermore, precise estimation of the Remaining Useful Life (RUL) of Li-ion batteries is essential for achieving efficient battery management and state estimation. As the demand for electric vehicles continues to rise, the necessity for advanced RUL prediction techniques becomes increasingly evident. This review underscores the significance of Machine Learning (ML) techniques in precisely predicting LIB states while simultaneously reducing computational complexity. It sheds light on the present state of research in the field and outlines promising future avenues for leveraging ML in the context of lithium-ion batteries. This comprehensive review also identifies existing challenges and proposes a structured framework to address these obstacles, focusing on the development of machine-learning applications tailored specifically for rechargeable LIBs. By harnessing the power of Artificial Intelligence (AI) technologies, researchers aspire to expedite advancements in battery performance and overcome the present limitations associated with lithium-ion batteries. The symmetrical approach of ML in this domain brings harmony to battery management and contributes to the sustainable progress of transportation electrification.

Title: Hybrid Heat Pipe-PCM-Assisted Thermal Management for Lithium-ion Batteries
Authors: Nourouddin Sharifi; Christian Millard; Hamidreza Shabgard
Affiliation: 1. Department of Engineering Technology, Tarleton State University, 1333 W. Washington Stephenville, TX 76402, USA; 2. Department of Mechanical, Environmental, and Civil Engineering, Tarleton State University, 1333 W. Washington Stephenville, TX 76402, USA; 3. School of Aerospace and Mechanical Engineering, University of Oklahoma, 865 Asp Ave., Norman, OK 73019, USA
Abstract: A hybrid cooling method for 18650 lithium-ion batteries has been studied experimentally and numerically for electric vehicle applications. The experimental setup consists of a heater section, a phase change material (PCM) reservoir, and a cooling section. The heater section mimics the heat generated by the batteries and includes two cylindrical aluminum housings with the same dimension as an 18650 battery, two cartridge heaters, and an aluminum heat sink. The PCM reservoir is made of PLA 3D-printed parts. An air flow channel is designed for the cooling section. Three copper-water heat pipes (HPs) are used to transfer the heat from the heaters to the air flow channel through the aluminum housings, the heat sink, and the PCM. Aluminum fin jackets are used on the HPs to improve the heat transfer rates. Temperatures at various locations within the setups are measured and compared across different heater powers and air velocities. It is concluded that the current experimental design is thermally efficient to bring the temperature of the batteries within an allowable operating temperature range for the conditions of the studies. Additionally, a transient three-dimensional numerical model is created in ANSYS-FLUENT, which is utilized to facilitate optimization study and offer insights into the physics of the problem. The phase change in the conjugate numerical model is accounted for by the enthalpy-porosity technique. The computational outcomes and the experimental data were reasonably in agreement.

Title: Smoke characteristics of 18650 Lithium-ion batteries during thermal abuse in non-confined environment
Authors: Pius Victor Chombo; Gerutu Bosinge Gerutu; Ramadhani Omary Kivugo; Kenedy Aliila Greyson
Affiliation: 1. Department of Electrical Engineering, Dar es Salaam Institute of Technology, Bibi Titi-Morogoro Road, Dar es Salaam 11104, Tanzania; 2. Department of Mechanical Engineering, Dar es Salaam Institute of Technology, Bibi Titi-Morogoro Road, Dar es Salaam 11104, Tanzania; 3. Department of Electronics and Telecommunication Engineering, Dar es Salaam Institute of Technology, Bibi Titi-Morogoro Road, Dar es Salaam 11104, Tanzania
Abstract: Due to the thermal sensitive and serious explosion behaviors of Lithium-ion batteries (LIBs), understanding the potential hazards during LIBs failure becomes useful to assess the safety of LIBs during storage, transport, and use. Smoke is an unavoidable effluent during LIB failure, and its constituents may pose serious hazards. Yet, there is little knowledge regarding the smoke characteristics of the failed LIB. This study broadly analyzes the smoke characteristics of 18650 LIBs with state of charge (SOC) from 25 to 100% triggered to TR by uniform heating in a non-confined environment. The smoke characteristics are analyzed in terms of filter smoke number (FSN) and soot concentration (Sconc) quantified during break out of safety vent (SV) and explosion triggered by thermal runaway (TR). Moreover, heat transfer (qrad and qconv) to the LIB is evaluated. Comparatively, qconv dominated the heat transferred, took up to 97.56% of the total heat received on the LIB under test. FSN was found to be less than one in all SOC and cathodic materials during the SV crack and reached 3.80 at 75% SOC in LCO LIB at TR stage. However, Sconc during SV and TR reached a maximum of 12.90 and 75.05 mg/kg at 100 and 50% SOC in LCO and NCA LIBs. Findings showed that the heat during onset of TR (qTR) ranged between 1.54 to 1.88; 1.86 to 1.89; and 1.51 to 2.08 for NCA, LCO and LMO, respectively. The growth rate for FSN ranged between 0.003782 and 0.016602 per unit of qTR, while growth rate for Sconc is between 0.059488 and 0.537933 per unit of qTR. In terms of energy, the normalized FSN and Sconc for NCA, LCO and LMO ranged between 0.82 ± 0.018 FSN/Wh and 22.40 ± 0.012 mg/kg.Wh; 1.17 ± 0.014 FSN/Wh and 27.49 ± 0.028 mg/kg.Wh; 0.51 ± 0.004 FSN/Wh and 10.27 ± 0.038 mg/kg.Wh, respectively. This work delivers new insights into the effects of SOC, cathode materials, and external heat energy on the FSN and Sconc, which helps to dictate the safety of both first and second responders in case of large-scale applications.