Pregled bibliografske jedinice broj: 1209759
Modelling decarbonisation of transport sector with method for assessing vehicle driving cycles based on real GPS data
Modelling decarbonisation of transport sector with method for assessing vehicle driving cycles based on real GPS data // Digital Proceedings of the 5th SEE Conference on Sustainable Development of Energy, Water and Environment Systems / Ban, Marko et. al. - Zagreb : SDEWES, 2022 / Ban, Marko et. al. (ur.).
Zagreb, 2022. 0031, 21 (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 1209759 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Modelling decarbonisation of transport sector with method for assessing vehicle driving cycles based on real GPS data
Autori
Herc, Luka ; Perković, Luka ; Pukšec, Tomislav
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
Digital Proceedings of the 5th SEE Conference on Sustainable Development of Energy, Water and Environment Systems / Ban, Marko et. al. - Zagreb : SDEWES, 2022
/ Ban, Marko et. al. - Zagreb, 2022
Skup
5th South East European Conference on Sustainable Development of Energy, Water and Environmental Systems (SEE SDEWES)
Mjesto i datum
Vlora, Albanija, 22.05.2022. - 26.05.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
decarbonization ; energy modelling ; statistical method
Sažetak
This research presents a novel method for the statistical evaluation of the synthetic driving cycles for small-to-medium vehicles, based on the real driving cycles recorded with GPS tracker with resolution of five seconds. The recorded data is processed so it can be used as an input for energy planning, namely the estimation of battery electric vehicles' energy demand and charging strategies in dump, smart and V2G regimes. Initial statistical analysis shows that hourly distribution among various vehicles is best represented with gamma distribution. However, due to the lower amount of data recorded from the GPS, synthetic driving cycles are matching the data measurement with correlation of 0.5 and 0.8 for work days and weekends, respectively. This drawback can be avoided with more data being recorded during the research on the topic and consequent re-tuning of the distribution parameters.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
IP-2019-04-9482 - Istraživanje puteva energetske tranzicije - međuovisnost "power-to-X" tehnologija, tehnologija odgovora potrošnje i povezivanja tržišta energijom (INTERENERGY) (Duić, Neven, HRZZ - 2019-04) ( CroRIS)