2016
DOI: 10.1016/j.energy.2016.08.061
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Improved energy supply for non-road electric vehicles by occasional charging station location modelling

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Cited by 16 publications
(12 citation statements)
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“…Investigations for charging station allocation in the BEV environment noted the most suitable application to be a maximal (gradual) covering model in order to meet the requirements of BEV recharging (Frade et al, 2011;Gimé nez-Gaydou et al, 2014), which goes in line with the approach for optimised charging station allocation for occasional recharging in industrial applications with reference to sustainability factors (Fekete et al, 2016).…”
Section: Research Environmentmentioning
confidence: 95%
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“…Investigations for charging station allocation in the BEV environment noted the most suitable application to be a maximal (gradual) covering model in order to meet the requirements of BEV recharging (Frade et al, 2011;Gimé nez-Gaydou et al, 2014), which goes in line with the approach for optimised charging station allocation for occasional recharging in industrial applications with reference to sustainability factors (Fekete et al, 2016).…”
Section: Research Environmentmentioning
confidence: 95%
“…As the shown values include energy efforts for additional charging station approaching as well as charging time reductions due to additional material handling equipment movements, it can be stated at this point that occasional charging bears the potential to increase the availability of UBE, whereas advanced charging station allocation based on indeed process knowledge can increase UBE by up to 60% (see also Fekete et al, 2016). The executed analyses showed, that an increased value of recharge energy was not necessarily synonymous to an increased downsizing potential since other factors such as process energy consumption, additional drive distance, transmission efficiency and minimal required battery capacity influence the vehicle (component) design, so that lower additional UBE in several cases showed similar results in reference to the systems overall sustainability.…”
Section: Case Studymentioning
confidence: 99%
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