External short circuit performance of Graphite-LiNi1/3Co1/3Mn1/3O2 and Graphite-LiNi0.8Co0.15Al0.05O2 cells at different external resistances

Kriston, Ákos; Pfrang, Andreas; Döring, Harry; Fritsch, Benjamin; Ruíz, Vanesa; Adanouj, Ibtissam; Kosmidou, Theodora; Ungeheuer, J.; Boon-Brett, L.

doi:10.1016/j.jpowsour.2017.06.056

Cited by 81 publications

(60 citation statements)

References 20 publications

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“…An external short circuit generally occurs when the tabs are connected by a low resistance path [11]. Another cause is electrolyte leakage from cell swelling due to gas generation from side reactions during overcharge [22]. It can also occur due to water immersion and collision deformation.…”

Section: External Short Circuitmentioning

confidence: 99%

“…An external short circuit specifically transpires when an external heat-conducting element makes contact with the positive and negative terminals simultaneously, causing an electrical connection between the electrodes to occur [23]. A study [22] concluded that due to external short circuit, the Li-ion diffusion in the negative electrode leads to limited current, and the heat generated by the electrolyte decomposition in the positive electrode is responsible for thermal runaway occurrence. An external short circuit also leads to excessive discharge of the energy that is being stored in a cell [11].…”

Section: External Short Circuitmentioning

confidence: 99%

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A Review of Lithium-Ion Battery Fault Diagnostic Algorithms: Current Progress and Future Challenges

Fowler

2020

Algorithms

184

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The usage of Lithium-ion (Li-ion) batteries has increased significantly in recent years due to their long lifespan, high energy density, high power density, and environmental benefits. However, various internal and external faults can occur during the battery operation, leading to performance issues and potentially serious consequences, such as thermal runaway, fires, or explosion. Fault diagnosis, hence, is an important function in the battery management system (BMS) and is responsible for detecting faults early and providing control actions to minimize fault effects, to ensure the safe and reliable operation of the battery system. This paper provides a comprehensive review of various fault diagnostic algorithms, including model-based and non-model-based methods. The advantages and disadvantages of the reviewed algorithms, as well as some future challenges for Li-ion battery fault diagnosis, are also discussed in this paper.Algorithms 2020, 13, 62 2 of 18 combustion and explosion [7]. The consequences of Li-ion battery faults can be minimized or eliminated by the BMS, as it prevents the battery from functioning outside its safe operational range, and also detects faults using various fault diagnostic methods [8]. It is an indispensable component in the Li-ion battery system since it can handle failures safely by going into failure mode, providing a safer environment for the users of Li-ion battery applications.Since fault diagnosis is a crucial part of Li-ion battery advancements, various methods for fault diagnosis have been studied and developed. Many fault diagnostic algorithms have been proposed, which can be categorized into model-based and non-model-based methods. Model-based methods include parameter estimation, state estimation, parity space, and structural analysis. Non-model-based methods include signal processing and knowledge-based methods [1,9]. Fault diagnosis research in other fields has shown that the most effective approach is often a combination of more than one method [9].Lu et al.[8] briefly presented fault diagnosis as one of the key issues for Li-ion battery management in electric vehicles. In [10], a review of sensor fault diagnosis for Li-ion battery systems was provided, but other types of faults were not discussed. Wu et al.[1] conducted a review on fault mechanism and diagnosis for Li-ion battery, but there have been many new developments in the field since then. Researchers have made significant progress in understanding the mechanism and operation of Li-ion batteries, and with that, many innovations in battery fault diagnosis have emerged. Therefore, there is a need to identify the current progress and future direction of Li-ion battery fault diagnosis research. The contribution of this paper is the comprehensive review of recent developments in Li-ion battery fault diagnosis, as well as the discussion of some future challenges that need to be addressed.The rest of this paper is organized as follows. Section 2 introduces different types of faults in Li-ion battery, and their causes, ...

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Section: External Short Circuitmentioning

confidence: 99%

Section: External Short Circuitmentioning

confidence: 99%

A Review of Lithium-Ion Battery Fault Diagnostic Algorithms: Current Progress and Future Challenges

Fowler

2020

Algorithms

184

View full text Add to dashboard Cite

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“…investigated the complex short circuit behavior and divided the performance into 3 segments (Figure d) . Therein, the source of the generated current is the double layer capacity, governed by the diffusion and double layer discharge of the cell (Figure d) . Mass transport resistances become the current limiting factor in the second segment .…”

Section: Resultsmentioning

confidence: 99%

“…Therein, the source of the generated current is the double layer capacity, governed by the diffusion and double layer discharge of the cell (Figure d) . Mass transport resistances become the current limiting factor in the second segment . Since the mass transport resistance is temperature dependent and the temperature is constantly rising, the current increases again until the Li + ion concentration in the negative electrode is depleted .…”

Section: Resultsmentioning

confidence: 99%

Safety Performance of 5 Ah Lithium Ion Battery Cells Containing the Flame Retardant Electrolyte Additive (Phenoxy) Pentafluorocyclotriphosphazene

et al. 2018

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Investigations on the effect of flame retardant additives (FRs) on the abuse tolerance of large scale lithium ion battery (LIB) cells (5 Ah) are of high relevance in battery science and industry but rarely performed as they are cost and time consuming. In addition, even though FRs are frequently investigated, their positive effect on the safety properties of larger full LIB cells under abusive condition has not been proven yet. The promising FR (phenoxy) pentafluorocyclotriphosphazene (FPPN) is known to exhibit excellent flame retardant-and electrochemical properties at the same time.Therefore, FPPN is investigated towards abuse tolerance in 5 Ah LIB cells in this study. Calorimetric investigations show that a mass percentage of 5 wt % FPPN mixed to a standard electrolyte, significantly reduces the self-heating rate of 5 Ah cells in the temperature range from 80°C to 110°C. While nail penetration and external short circuit experiments provide no significant difference between standard and FPPN-containing cells, an increased overcharge tolerance and a favorable thermal stability at � 120°C in overcharge and oven experiments could be shown. [a] T. . Nail penetration experiment of 5 Ah cells containing electrolyte with (blue) and without (black) 5 wt % FPPN. a) scheme showing the position of the thermocouples. b) Voltage over time of two cells per additive mixture. Temperature over time of two cells per electrolyte mixture are presented in c) for thermocouple position 1 and in d) for thermocouple position 2. . Overcharge experiment of 5 Ah cells containing electrolyte with (blue) and without (black) 5 wt % FPPN. a) Voltage and b) temperature (position 1) vs. time diagrams of two cells per additive mixture are presented.

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“…The ISCr can be caused by manufacturing defects [13,14] and various types of abuse such as overcharge [15,16] and overdischarge [17]. Furthermore, when a magnitude of ISCr resistance (R ISCr ) is lower than a particular value [18], a temperature of the battery exceeds a certain point due to the ISCr [19][20][21]. Then, the battery may experience thermal runaway with a fire and can even explode [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Detection Method for Soft Internal Short Circuit in Lithium-Ion Battery Pack by Extracting Open Circuit Voltage of Faulted Cell

et al. 2018

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Early detection of internal short circuit which is main cause of thermal runaway in a lithium-ion battery is necessary to ensure battery safety for users. As a promising fault index, internal short circuit resistance can directly represent degree of the fault because it describes self-discharge phenomenon caused by the internal short circuit clearly. However, when voltages of individual cells in a lithium-ion battery pack are not provided, the effect of internal short circuit in the battery pack is not readily observed in whole terminal voltage of the pack, leading to difficulty in estimating accurate internal short circuit resistance. In this paper, estimating the resistance with the whole terminal voltages and the load currents of the pack, a detection method for the soft internal short circuit in the pack is proposed. Open circuit voltage of a faulted cell in the pack is extracted to reflect the self-discharge phenomenon obviously; this process yields accurate estimates of the resistance. The proposed method is verified with various soft short conditions in both simulations and experiments. The error of estimated resistance does not exceed 31.2% in the experiment, thereby enabling the battery management system to detect the internal short circuit early.

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External short circuit performance of Graphite-LiNi1/3Co1/3Mn1/3O2 and Graphite-LiNi0.8Co0.15Al0.05O2 cells at different external resistances

Cited by 81 publications

References 20 publications

A Review of Lithium-Ion Battery Fault Diagnostic Algorithms: Current Progress and Future Challenges

A Review of Lithium-Ion Battery Fault Diagnostic Algorithms: Current Progress and Future Challenges

Safety Performance of 5 Ah Lithium Ion Battery Cells Containing the Flame Retardant Electrolyte Additive (Phenoxy) Pentafluorocyclotriphosphazene

Detection Method for Soft Internal Short Circuit in Lithium-Ion Battery Pack by Extracting Open Circuit Voltage of Faulted Cell

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