Thermal management of parallel cells — Methodology based on non-linear dynamics

Zhang, Zeping; Li, Zhe; Yang, Xiaolong; Gong, Jinke; Zhang, Jianbo

doi:10.1016/j.etran.2022.100187

Cited by 11 publications

(8 citation statements)

References 41 publications

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“…The CHAIN framework holds profound theoretical and practical value in the management of emerging engineering systems such as the battery industry, electric vehicles, intelligent transportation system, and the energy internet. [ 210 ] CHAIN serves as a hierarchical interactive information sharing system. CHAIN offers guidance and assistance for the collaborative operation of multiscale battery material design, multifunctional BMS development, and multidimensional battery lifespan information flow management.…”

Section: Multiscale Management Pattern For Battery Life Extensionmentioning

confidence: 99%

“…In the framework of the X‐shaped flow, real production experience can offer online updates and corrections to maintain model accuracy, playing a critical role in model maintenance. [ 210 ] Information and data in the CHAIN framework link production, usage, and feedback optimization in a closed‐loop management mode. The actual performance of batteries and multiscale simulation verification results are integrated through a cloud platform, guiding updates to ML models and production processes.…”

Section: Multiscale Management Pattern For Battery Life Extensionmentioning

confidence: 99%

“…Data generated throughout the entire lifecycle's different stages will be uploaded and shared among various clients. [ 209,210 ] As shown in Figure 9, data processing methods are developed in the cloud to perform data cleaning, filtering, and feature extraction. These data, mirroring reflect real‐world physical entities, are used to establish ML models and multiscale simulation models within the cloud infrastructure.…”

Section: Multiscale Management Pattern For Battery Life Extensionmentioning

confidence: 99%

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Multiscale modeling for enhanced battery health analysis: Pathways to longevity

Yang,

Zhang,

Wang

et al. 2024

Carbon Neutralization

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The issues of health assessment and lifespan prediction have always been prominent challenges in the large‐scale application of lithium‐ion batteries (LIBs). This paper reviews the multiscale modeling techniques and their applications in battery health analysis, including atomic scale computational chemistry, particle scale reaction simulations, electrode scale structural models, macroscale electrochemical models, and data‐driven models at the system level. Multiscale modeling offers a profound insight into material behavior and the aging process of batteries, thereby providing a valuable reference for both estimation and management strategies of battery state of health. To extend the battery lifespan, the utilization of artificial intelligence for material discovery and manufacturing process optimization, the implementation of end‐cloud collaborative battery management systems, and the design of a multiscale simulation integration platform are considered. A management framework aimed at extending battery life is further proposed. This framework offers a promising roadmap for addressing health analysis challenges in LIBs, ultimately leading to more reliable, efficient, and durable solutions for next‐generation batteries.

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Section: Multiscale Management Pattern For Battery Life Extensionmentioning

confidence: 99%

Section: Multiscale Management Pattern For Battery Life Extensionmentioning

confidence: 99%

Section: Multiscale Management Pattern For Battery Life Extensionmentioning

confidence: 99%

See 1 more Smart Citation

Multiscale modeling for enhanced battery health analysis: Pathways to longevity

Yang,

Zhang,

Wang

et al. 2024

Carbon Neutralization

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“…The previous content introduces the effect of temperature on individual battery. For NEVs, the battery system is called the battery pack, which is composed of hundreds of LIBs connected in series or parallels to fulfill the requirement of voltage and power [1,8]. In fact, heat transfer between each cell is enslaved to the complicated structure of the battery pack, which will result in the pack thermal gradients.…”

Section: Battery Thermal Performancesmentioning

confidence: 99%

“…Developing an applicable energy storage device to achieve high power and high energy is essential. In order to achieve the power and energy requirements of NEVs, LIBs are connected in series/parallels to fabricate module and pack [8,9]. For these demanding applications, LIBs are deemed sensitive to pressure, vibration, and temperature.…”

Section: Introductionmentioning

confidence: 99%

A Review on Battery Thermal Management for New Energy Vehicles

Li,

Zhou,

Zhang

et al. 2023

Energies

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Lithium-ion batteries (LIBs) with relatively high energy density and power density are considered an important energy source for new energy vehicles (NEVs). However, LIBs are highly sensitive to temperature, which makes their thermal management challenging. Developing a high-performance battery thermal management system (BTMS) is crucial for the battery to retain high efficiency and security. Generally, the BTMS is divided into three categories based on the physical properties of the cooling medium, including phase change materials (PCMs), liquid, and air. This paper discusses the effect of temperature on the performance of individual batteries and battery systems, at first. Then, a systematic survey of the state-of-the-art BTMS is presented in terms of liquid-based, PCM-based, and air-based BTMS. To further utilize the heat source of the vehicle, the BTMS integrated with the vehicle thermal management system (VTMS) is discussed. Finally, the challenges and future prospects for BTMS with the ability to cut off the thermal runaway are discussed. The primary aim of this review is to offer some guidelines for the design of safe and effective BTMS for the battery pack of NEVs.

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