A full-scale electrical-thermal-fluidic coupling model for li-ion battery energy storage systems

Cao, Wenbin; Qiu, Yishu; Peng, Peng; Jiang, Fangming

doi:10.1016/j.applthermaleng.2020.116360

Cited by 22 publications

(4 citation statements)

References 52 publications

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“…Conventional temperature detection and voltage detection methods have been quite mature, but these methods do not fully confirm the health state of the battery. The pseudo‐two‐dimensions model and further neural networks algorithms can quickly and efficiently calculate thermal runaway processes in systems consisting of many batteries 162,168 . With the booming development of big data, the optimization algorithms and the accumulation of databases can provide more accurate predictions of SSLMBs at operating conditions.…”

Section: Strategies For Safer Sslmbsmentioning

confidence: 99%

“…The pseudo-two-dimensions model and further neural networks algorithms can quickly and efficiently calculate thermal runaway processes in systems consisting of many batteries. 162,168 With the booming development of big data, the optimization algorithms and the accumulation of databases can provide more accurate predictions of SSLMBs at operating conditions. Some advanced detection methods in LIBs can also be applied directly to SSLMBs.…”

Section: Safety Detection and Warningmentioning

confidence: 99%

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Safer solid‐state lithium metal batteries: Mechanisms and strategies

Yang,

Hu,

Jiang

et al. 2023

InfoMat

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Solid‐state batteries that employ solid‐state electrolytes (SSEs) to replace routine liquid electrolytes are considered to be one of the most promising solutions for achieving high‐safety lithium metal batteries. SSEs with high mechanical modulus, thermal stability, and non‐flammability can not only inhibit the growth of lithium dendrites but also enhance the safety of lithium metal batteries. However, several internal materials/electrodes‐related thermal hazards demonstrated by recent works show that solid‐state lithium metal batteries (SSLMBs) are not impenetrable. Therefore, understanding the potential thermal hazards of SSLMBs is critical for their more secure and widespread applications. In this contribution, we provide a comprehensive overview of the thermal failure mechanism of SSLMBs from materials to devices. Also, strategies to improve the thermal safety performance of SSLMBs are included from the view of material enhancement, battery design, and external management. Consequently, the future directions are further provided. We hope that this work can shed bright insights into the path of constructing energy storage devices with high energy density and safety.image

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Section: Strategies For Safer Sslmbsmentioning

confidence: 99%

Section: Safety Detection and Warningmentioning

confidence: 99%

Safer solid‐state lithium metal batteries: Mechanisms and strategies

Yang,

Hu,

Jiang

et al. 2023

InfoMat

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“…This strategic approach not only streamlined equalization but also improved its speed. Our previous works [148,149] developed the active equalization battery management system, optimized the adaptive current equalization strategy, reduced the impact of inconsistency on system performance, and improved the available capacity of the system.…”

Section: Battery Equalization Technologymentioning

confidence: 99%

Revolutionizing the Afterlife of EV Batteries: A Comprehensive Guide to Echelon Utilization Technologies

Wang,

Hu,

Wang

et al. 2023

ChemElectroChem

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In the burgeoning new energy automobile industry, repurposing retired power batteries stands out as a sustainable solution to environmental and energy challenges. This paper comprehensively examines crucial technologies involved in optimizing the reuse of batteries, spanning from disassembly techniques to safety management systems. The review assesses the viability of retired batteries, comparing their performance with that of new units, and evaluates scenarios for echelon utilization. Early safety warning systems based on temperature, voltage, and gas emissions are analyzed to enhance the understanding of safety management. In addition, the current state and enhancement opportunities for the second life of electric vehicle batteries are presented. The research highlights the integral role of retired power batteries in applications such as energy storage, communication bases, and streetlights. It is indicated that ensuring safety through robust early warning systems is of paramount importance. Ultimately, this paper envisions a sustainable future, driven by innovative strategies that facilitate the effective utilization of retired batteries in the new energy automobile industry.

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“…The lithium-ion battery (LIB) has become one of the most important energy storage technology routes [6,7], mainly due to its significant advantages with respect to other battery types [8][9][10], such as a longer lifecycle, a faster response speed, a lower self-discharge rate, and higher energy conversion efficiency. In China, a batch of one hundred megawattscale demonstration energy storage systems (ESSs) were combined successively to the grid in 2021, and the important application scenarios of the stable peak adjustment and fast frequency adjustment of the large-scale LIB-ESS were verified successfully.…”

Section: Introductionmentioning

confidence: 99%

Potential Failure Prediction of Lithium-ion Battery Energy Storage System by Isolation Density Method

et al. 2022

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Lithium-ion battery energy storage systems have achieved rapid development and are a key part of the achievement of renewable energy transition and the 2030 “Carbon Peak” strategy of China. However, due to the complexity of this electrochemical equipment, the large-scale use of lithium-ion batteries brings severe challenges to the safety of the energy storage system. In this paper, a new method, based simultaneously on the concepts of statistics and density, is proposed for the potential failure prediction of lithium-ion batteries. As there are no strong assumptions about feature independence and sample distribution, and the estimation of the anomaly scores is conducted by integrating several trees on the isolation path, the algorithm has strong adaptability and robustness, simultaneously. For validation, the proposed method was first applied to two artificial datasets, and the results showed that the method was effective in dealing with different types of anomalies. Then, a comprehensive evaluation was carried out on six public datasets, and the proposed method showed a better performance with different criteria when compared to the conventional algorithms. Finally, the potential failure prediction of lithium-ion batteries of a real energy storage system was conducted in this paper. In order to make full use of the time series characteristics, voltage variation during a whole discharge cycle was taken as the representation of the operation condition of the lithium-ion batteries, and three different types of voltage deviation anomalies were successfully detected. The proposed method can be effectively used for the predictive maintenance of energy storage systems.

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A full-scale electrical-thermal-fluidic coupling model for li-ion battery energy storage systems

Cited by 22 publications

References 52 publications

Safer solid‐state lithium metal batteries: Mechanisms and strategies

Safer solid‐state lithium metal batteries: Mechanisms and strategies

Revolutionizing the Afterlife of EV Batteries: A Comprehensive Guide to Echelon Utilization Technologies

Potential Failure Prediction of Lithium-ion Battery Energy Storage System by Isolation Density Method

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