Capacity detection of internal short circuit

Reichl, Tomáš; Hrzina, Pavel

doi:10.1016/j.est.2017.12.006

Cited by 20 publications

(3 citation statements)

References 3 publications

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“…In [18,19], physics-based model ESC detection scheme is proposed using different models for faulty and healthy conditions, which are obtained from experiments. In [20], according to time dependence of the capacity evaluation, ISC detection is evaluated while the cell is being charged. Furthermore, soft SC quantitative analysis is developed with cell difference model and state estimation algorithm in [21].…”

Section: Introductionmentioning

confidence: 99%

Incipient short-circuit fault diagnosis of lithium-ion batteries

Meng

Boukhnifer

Delpha

et al. 2020

Journal of Energy Storage

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Section: Introductionmentioning

confidence: 99%

Incipient short-circuit fault diagnosis of lithium-ion batteries

Meng

Boukhnifer

Delpha

et al. 2020

Journal of Energy Storage

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“…Various faults may occur at each cell or the associated accessories in battery pack due to the natural aging and various (including mechanical, electrical, and thermal) abuse manoeuvres in actual usage of EVs [5][6][7]. Unchecked faults would have great impacts on battery, or even lead to battery thermal runaway under extreme conditions [8].…”

Section: Introductionmentioning

confidence: 99%

Battery voltage fault diagnosis for electric vehicles considering driving condition variation

Zhang

Chen

et al. 2022

IET Intelligent Trans Sys

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To ensure the real‐time operation safety of electric vehicles (EVs), it is essential to diagnose the fault in a battery pack timely and accurately. In this paper, with considering driving condition, a battery voltage fault diagnosis method is proposed based on the real‐world operation data of EVs with a high sampling frequency. Firstly, based on driving behaviour, the driving condition of EVs is classified into four categories, and accordingly, the operation process is divided into four segments. The influencing mechanism of driving condition on battery voltage is revealed by detailed analysis on extracted operation segments. Secondly, four BP neural network (BPNN)‐based voltage prediction models are developed, respectively, for the four kinds of driving conditions. Based on the statistical analysis of prediction error and the comparison with other voltage prediction models, the superiority and stability of the four well‐trained BPNN models are verified. Thirdly, the voltage abnormity levels and thresholds for fault diagnosis are set considering driving condition differences. The effectiveness of the proposed method is verified using the actual operational data. The verification results show that the proposed method can achieve good voltage prediction and fault diagnosis for EVs under various driving conditions during the entire operation process.

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“…(d) Inconsistency detection. Here, an ISC is characterized by a difference in state‐of‐charge (SOC), 12 capacity, 24 internal resistance 25 or open‐circuit‐voltage (OCV) 26 among cells. (e) Remaining charging capacity (RCC) 27 .…”

Section: Introductionmentioning

confidence: 99%

Online internal short circuit detection method considering equalization electric quantity for lithium‐ion battery pack in electric vehicles

Lai

Wei

Hai-li³

et al. 2020

Int J Energy Res

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The timely and accurate detection of an internal short circuit (ISC) is critical for improving electric vehicle (EV) safety. Typical ISC detection approaches are based on consistency differences between each cell in a module. However, the indispensable equalizer in a battery management system reduces inconsistency, affecting the accuracy and timeliness of ISC detection. Hence, an online ISC detection method considering equalization electric quantity (EEQ) is proposed. First, the remaining charge capacity and state-of-charge difference approaches are investigated. Next, the negative impact of EEQ on ISC detection is analyzed; thereafter, improved approaches based on EEQ compensation are proposed. Moreover, an ISC routing inspection approach for dormant EVs is proposed. Lastly, the proposed approaches are verified. The main results are as follow: (a) The ISC detection method without EEQ compensation has issues, such as significant errors, undetected ISC, and longer detection periods; our approaches help effectively overcome these issues, while the detection error is maintained below 5%; (b) Supplementing the above approaches, the proposed ISC routing inspection approach can help detect a moderate ISC even for a dormant EV, while further improving timeliness in ISC detection.

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Capacity detection of internal short circuit

Cited by 20 publications

References 3 publications

Incipient short-circuit fault diagnosis of lithium-ion batteries

Incipient short-circuit fault diagnosis of lithium-ion batteries

Battery voltage fault diagnosis for electric vehicles considering driving condition variation

Online internal short circuit detection method considering equalization electric quantity for lithium‐ion battery pack in electric vehicles

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