Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption

Thomas Märzinger, David Wöss, Petra Steinmetz, Werner Müller and Tobias Pröll
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Thomas Märzinger: Institute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, Austria
David Wöss: Institute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, Austria
Petra Steinmetz: VOIGT+WIPP Industrial Research GmbH, 1150 Vienna, Austria
Werner Müller: Institute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, Austria
Tobias Pröll: Institute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, Austria

Energies, 2021, vol. 14, issue 12, 1-15

Abstract: In its “Sustainable and Smart Mobility Strategy”, the European Commission assumes a 90% reduction in traffic emissions by 2050. The decarbonisation of transport logistics as a major contributor to climate change is, therefore, indicated. There are major challenges in converting logistic transport processes to electric mobility. Currently, there is little available information for the conversion of entire fleets from fossil to electric fuel. One of the biggest challenges is the additional time needed for recharging. For the scheduling of entire logistics fleets, exact knowledge of the required loading times and loading quantities is essential. In this work, a parametrized continuous function is, therefore, defined to determine the essential parameters (recharging time, retrieved power, energy amounts) in HPC (high-power charging). These findings are particularly important for the deployment of multiple e-trucks in fleets, as logistics management depends on them. A simple function was constructed that can describe all phases of the charging process in a continuous function. Only the maximum power of the charging station, the size of the battery in the truck and the start SOC (state of charge) are required as parameters while using the function. The method described in this paper can make a significant contribution to the transformation towards electro-mobile urban logistics fleets. The required charging time, for example, is crucial for the planning and scheduling of e-logistics fleets and can be determined using the function described in this paper.

Keywords: logistics; e-mobility; mathematical function; high-power charging; fleet conversion; e-truck; charging function (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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