engleski

Modelling decarbonisation of transport sector with method for assessing vehicle driving cycles based on real GPS data

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.

decarbonization ; energy modelling ; statistical method

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