DC arc fault scenarios and detection methods in battery storage systems

Eger, Felix; Bo, Georg; Freiberger, Dennis; Lang, Nikolaus; Laukamp, H.; Rouffaud, Gilles

doi:10.1109/icdcm.2017.8001015

Cited by 6 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the proposed approach is simple and costeffective, it does present limitations in terms of the flexibility in application of faults at desired locations within the electrical system. In [69], a waveform generator is used to reproduce the recording of a real arc signal within the system under test, effectively emulating the arc behavior as can be seen from Fig. 7.…”

Section: A Arc Generating Unitsmentioning

confidence: 99%

Review of DC Series Arc Fault Testing Methods and Capability Assessment of Test Platforms for More-Electric Aircraft

Psaras¹,

Seferi

Syed

et al. 2022

IEEE Trans. Transp. Electrific.

View full text Add to dashboard Cite

In the new era of increasingly electric aircraft, the need for reliable and safe electrical systems is more important than ever. In addition, the wide scale adoption of DC distribution is considered a key enabling technology for more efficient aircraft operation. In this context, arc fault detection devices have become a topic of interest for the aviation industry with ongoing research to characterize the impact and adequately protect against severe DC series arc faults. Although DC arc faults have been widely investigated for utility applications (such as solar photo-voltaic systems), direct adoption of current practices for validating arc detection devices is not straightforward due to the distinct aircraft operating environment. This paper provides a first of its kind, landscaping exercise of published series arc fault testing based on factors associated with aircraft applications which have the potential to influence the arc characteristics. In addition, an appraisal and associated gap analysis of published arc test platforms is undertaken in order to assess their suitability to support in-depth testing of the impact and mitigation of series arcs within future aircraft DC electrical systems and identify future testing needs in particular to better facilitate a comprehensive performance validation of new arc fault detection devices.

show abstract

Section: A Arc Generating Unitsmentioning

confidence: 99%

Review of DC Series Arc Fault Testing Methods and Capability Assessment of Test Platforms for More-Electric Aircraft

Psaras¹,

Seferi

Syed

et al. 2022

IEEE Trans. Transp. Electrific.

View full text Add to dashboard Cite

show abstract

“…The whole structure is more complicated. The DC arc faults of electric vehicle (EV) battery systems have been discussed in [18][19][20][21][22]. The characteristics and detected methods of DC arc in battery are analysed.…”

Section: Introductionmentioning

confidence: 99%

Binary classification model based on machine learning algorithm for the DC serial arc detection in electric vehicle battery system

Xia

Guo

et al. 2019

IET Power Electronics

View full text Add to dashboard Cite

Direct current (DC) serial arc faults usually occur in the damaged insulation lines or line connections, which will cause serious accidents such as fires and explosions. With the rapid increase of electric vehicles, DC serial arc faults are more and more dangerous to battery system. Therefore, a binary classification model based on machine learning algorithm was proposed to detect DC serial arc faults effectively in this study. It was optimised according to the characteristic signals of the arc to be satisfied with different loads for higher detection accuracy and robustness. In the simulative experiments for the power system electric vehicle, while the loads changing to the motor, the resistor or the inverter, it will all reach a highly successful detection rate, respectively.

show abstract

Identification Method of Series Arc Fault in Electric Bicycle Battery Charging Circuit

Wang,

Feng,

et al. 2024

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

DC arc fault scenarios and detection methods in battery storage systems

Cited by 6 publications

References 4 publications

Review of DC Series Arc Fault Testing Methods and Capability Assessment of Test Platforms for More-Electric Aircraft

Review of DC Series Arc Fault Testing Methods and Capability Assessment of Test Platforms for More-Electric Aircraft

Binary classification model based on machine learning algorithm for the DC serial arc detection in electric vehicle battery system

Identification Method of Series Arc Fault in Electric Bicycle Battery Charging Circuit

Contact Info

Product

Resources

About