Pregled bibliografske jedinice broj: 1210712
Electric vehicle charging station fault detection: a machine learning approach
Electric vehicle charging station fault detection: a machine learning approach // CIRED Porto Workshop 2022
Porto, Portugal: Institution of Engineering and Technology, 2022. str. 745-749 doi:10.1049/icp.2022.0810 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1210712 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Electric vehicle charging station fault detection: a
machine learning approach
Autori
Grcić, I. ; Pandžić, H. ; Šunde, V.
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Skup
CIRED Porto Workshop 2022
Mjesto i datum
Porto, Portugal, 02.06.2022. - 03.06.2022
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
recurrent neural nets ; fault diagnosis ; battery powered vehicles ; learning (artificial intelligence)
Sažetak
The number of electric vehicles on the roads is increasing, and the number of fast DC charging stations is following this trend. However, the advantages of DC electric vehicle charging stations (ECVS) in terms of efficiency and power output compared to their AC counterparts are accompanied with protection problems. To address these problems, a recurrent neural network-based fault detection method that can detect both solid and arc faults in EVCS is presented.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
