Suchergebnisse

Facing climate change, The European Union has set ambitious greenhouse gas (GHG) reduction targets. Within Europe, heavy-duty vehicles (HDV) account for a quarter of greenhouse gas emissions in the transport sector and therefore plays a central role in achieving the climate targets. A potential solution to reduce GHG emissions is the use of battery electric vehicles (BEV). However, the limited range of BEV requires a European public fast-charging network to ensure widespread deployment of BEV. Here, European road freight transport flows are modelled based on the publicly available European Transport policy Information System (ETISplus) dataset. The resulting truck flows serve as input for a charging infrastructure network model. Potential charging stations are located using a coverage-oriented approach and sized according to a queuing model such that an average waiting time of five minutes is guaranteed at each location. Our results show that for a share of 15% BEV in HDV stock and a dense network with charging locations every 50 km, a total of 4,067 charging points at 1,640 locations are required by 2030. In contrast, with a share of 5% BEV and charging locations every 100 km, 1,715 charging points are needed at 812 locations. Our findings provide insights for the design of a public fastcharging network in Europe and thus supports the planning of future infrastructure projects.

Facing climate change, The European Union has set ambitious greenhouse gas (GHG) reduction targets. Within Europe, heavy-duty vehicles (HDV) account for a quarter of greenhouse gas emissions in the transport sector and therefore plays a central role in achieving the climate targets. A potential solution to reduce GHG emissions is the use of battery electric vehicles (BEV). However, the limited range of BEV requires a European public fast-charging network to ensure widespread deployment of BEV. Here, European road freight transport flows are modelled based on the publicly available European Transport policy Information System (ETISplus) dataset. The resulting truck flows serve as input for a charging infrastructure network model. Potential charging stations are located using a coverage-oriented approach and sized according to a queuing model such that an average waiting time of five minutes is guaranteed at each location. Our results show that for a share of 15% BEV in HDV stock and a dense network with charging locations every 50 km, a total of 4,067 charging points at 1,640 locations are required by 2030. In contrast, with a share of 5% BEV and charging locations every 100 km, 1,715 charging points are needed at 812 locations. Our findings provide insights for the design of a public fast-charging network in Europe and thus supports the planning of future infrastructure projects.

Die Verbreitung von Elektrofahrzeugen spielt eine wichtige Rolle zur Erreichung der Klimaziele im Verkehrssektor und kann auch zu einer größeren Unabhängigkeit der Energieversorgung beitragen. Die Erforschung ihrer Verbreitung ist daher weiterhin von großer Relevanz. Im Rahmen einer Studie für die Nationale Plattform Elektromobilität (NPE) wurden im Jahr 2013 Markthochlaufszenarien für Elektrofahrzeuge bis zum Jahr 2020. Fast zehn Jahre später wird ihm Rahmen dieses Working Papers die damalige Methodik und die Ergebnisse mit realen Entwicklungen abgeglichen. Zudem werden methodische Neuerungen erläutert und ein Ausblick auf Modellergebnisse für das Jahr 2030 gewagt, um die neue politisch gesetzte Zielerreichung von 15 Millionen reinen Elektrofahrzeugen und die Treibhausgas(THG)-Minderungsziele unter die Lupe zu nehmen. Es zeigt sich, dass viele Entwicklungen gut eingeschätzt wurden und man aufgrund der niedrigen Kraftstoffpreise lange keine nennenswerte Marktdurchdringung von Elektrofahrzeugen sehen konnte. Mit zahlreichen politischen Fördermaßnahmen und der EU-Regulierung über die Flottengrenzwerte lag Deutschland Ende 2020 jedoch im mittleren Bereich des 2013 aufgespannten Ergebnisraums. Auch für 2030 ist die Zielerreichung maßgeblich abhängig vom Niveau der Flottengrenzwerte und ambitionierten Zwischenschritten bei der THG-Emissionsminderung. Nur dann können 15 Millionen reine Elektrofahrzeuge 2030 erreicht werden.

Electric vehicles (EVs) can help to reduce greenhouse gas emissions of the transportation sector. Therefore, the German government has defined various measures and targets to promote the diffusion of EVs. However, factors influencing the market diffusion of EVs as well as interdependencies between policy measures and vehicle diffusion are often unclear and hence, diffusion simulations are probably inaccurate. At the same time, a precise simulation of EV diffusion is a relevant parameter in travel demand models building the base for transportation planning. This paper addresses the gaps in current market diffusion models for EVs with a particular focus on environmental effects as additional influencing factors of the market diffusion. Results will be drawn for the German car market with a market diffusion simulation until 2050. The market diffusion model ALADIN is applied and energy prices are extended by a CO2 price to improve the consideration of environmental factors in the market diffusion modelling. The effectiveness of environmental policy measures is assessed in scenarios with three different CO2 prices and their impact on the diffusion of EVs. The results show that the market diffusion is highly dependent on the evolution of external factors. A CO2 price of at least 150 €/t of CO2 by 2030 can have a significant impact on the market diffusion of EVs and may as well lead to changes in the drive mix for both, electric and conventional drives within the German passenger car fleet. The German government's target of seven to ten million EVs registered by 2030 seems in general achievable, if currently adopted purchase bonuses and expected cost degression for EVs also take effect. Until 2050, we find large effects with CO2 prices up to 500 €/t, yet limited growth in market share above that threshold.

Electric vehicles (EVs) can help to reduce greenhouse gas emissions of the transportation sector. Therefore, the German government has defined various measures and targets to promote the diffusion of EVs. However, factors influencing the market diffusion of EVs as well as interdependencies between policy measures and vehicle diffusion are often unclear and hence, diffusion simulations are probably inaccurate. At the same time, a precise simulation of EV diffusion is a relevant parameter in travel demand models building the base for transportation planning. This paper addresses the gaps in current market diffusion models for EVs with a particular focus on environmental effects as additional influencing factors of the market diffusion. Results will be drawn for the German car market with a market diffusion simulation until 2050. The market diffusion model ALADIN is applied and energy prices are extended by a CO2 price to improve the consideration of environmental factors in the market diffusion modelling. The effectiveness of environmental policy measures is assessed in scenarios with three different CO2 prices and their impact on the diffusion of EVs. The results show that the market diffusion is highly dependent on the evolution of external factors. A CO2 price of at least 150 €/t of CO2 by 2030 can have a significant impact on the market diffusion of EVs and may as well lead to changes in the drive mix for both, electric and conventional drives within the German passenger car fleet. The German government's target of seven to ten million EVs registered by 2030 seems in general achievable, if currently adopted purchase bonuses and expected cost degression for EVs also take effect. Until 2050, we find large effects with CO2 prices up to 500 €/t, yet limited growth in market share above that threshold.