Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption
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 pr...
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Online Access: | https://www.mdpi.com/1996-1073/14/12/3471 |
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doaj-8a99f13305c94fc89b2071255bea19112021-06-30T23:58:47ZengMDPI AGEnergies1996-10732021-06-01143471347110.3390/en14123471Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet ConsumptionThomas Märzinger0David Wöss1Petra Steinmetz2Werner Müller3Tobias Pröll4Institute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, AustriaInstitute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, AustriaVOIGT+WIPP Industrial Research GmbH, 1150 Vienna, AustriaInstitute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, AustriaInstitute of Chemical and Energy Engineering, University of Naturel Resources and Life Sciences, 1190 Vienna, AustriaIn 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.https://www.mdpi.com/1996-1073/14/12/3471logisticse-mobilitymathematical functionhigh-power chargingfleet conversione-truck |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Thomas Märzinger David Wöss Petra Steinmetz Werner Müller Tobias Pröll |
spellingShingle |
Thomas Märzinger David Wöss Petra Steinmetz Werner Müller Tobias Pröll Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption Energies logistics e-mobility mathematical function high-power charging fleet conversion e-truck |
author_facet |
Thomas Märzinger David Wöss Petra Steinmetz Werner Müller Tobias Pröll |
author_sort |
Thomas Märzinger |
title |
Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption |
title_short |
Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption |
title_full |
Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption |
title_fullStr |
Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption |
title_full_unstemmed |
Novel Modelling Approach for the Calculation of the Loading Performance of Charging Stations for E-Trucks to Represent Fleet Consumption |
title_sort |
novel modelling approach for the calculation of the loading performance of charging stations for e-trucks to represent fleet consumption |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2021-06-01 |
description |
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. |
topic |
logistics e-mobility mathematical function high-power charging fleet conversion e-truck |
url |
https://www.mdpi.com/1996-1073/14/12/3471 |
work_keys_str_mv |
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