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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.

Frontmatter --Inhalt --Einleitung --I. Kooperative Technikgestaltung mit Bürgerinnen und Nutzerinnen --Zur Wissenspolitik von Smart-Grid-Experimenten --Algorithmen erklärt Euch! --Digitalisierung und Verkehrswende --Es ist Zeit für bessere Ideen --II. Soziotechnische Imaginationen und Kräfteverhältnisse --Schöne neue Bauwelt? --»Die Benutzer sind das Problem, nicht das System« --Digitale Energiezukünfte und ihre Wirkungsmacht --Human-Machine Learning und Digital Commons --III. Soziodigitale Neukonfiguration von Politik und Öffentlichkeit --Codes, Strategien, Verhalten --Öffentliche Kommunikation in der digitalisierten Gesellschaft --Reallabore --Bericht aus der Praxis --Verzeichnis der Autorinnen und Autoren