Modelling market diffusion of electric vehicles with real world driving data – German market and policy options

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Martin Wietschel Modelling Market Diffusion of Electric Vehicles with Real World Driving Data German Market and Policy OptionsAbstract Electric vehicles (EVs) have the potential to reduce green house gas emissions from the transport sector. However, the limited electric range of EVs could impede their market introduction. Still some potential users are willing to pay more for EVs. The combined effect of these and other influencing factors as well as the resulting future market evolution are unclear. Here, we study the market evolution of EVs in Germany until 2020. Our results reveal a great deal of uncertainty in the market evolution of EVs due to external conditions and the users' willingness to pay. We find the future share of EVs in German passenger car stock to range from 0.4% to almost 3% by 2020. Energy prices have a large impact on EV market evolution as a 25% increase in fuel prices would double the number of EVs in stock by 2020 compared to a reference scenario. The high uncertainty of the market evolution implies that policies to foster market diffusion of EVs should be dynamically adaptable to react to changing framework conditions. We find a special depreciation allowance for commercial vehicles and a subsidy of 1,000 Euro as the most effective and efficient monetary policy options.

Methods to Identify User Needs and Decision Mechanisms for the Adoption of Electric Vehicles

“…in a survey with French-German EV users they stated several advantages (such as advantageous driving characteristics, their characteristic to reduce CO 2 emissions, particularly on the local level [10] and enhanced prestige perceived [8]) but also two main barriers: the limited range and high purchase prices [9]. These findings were supported by many other surveys [4,15,35]. The two major barriers might shrink for the new generation of EV, which are going to have higher ranges and lower costs due to declining battery prices [33].…”

A discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services

“…For example, Plötz et al (2014), estimated an agent-based simulation model of the diffusion process of electric vehicles using real-world driving data that captured heterogeneity among decisionmakers, psychological factors and attributes of the new technology. Another study, please refer to Gnann et al (2015), used an Alternative Automobiles Diffusion and Infrastructure (ALADIN) diffusion model to forecast market penetration of plug-in electric vehicles through simulation techniques. Their proposed methodology incorporated an agent-based simulation model that catered for different types of users in addition to their respective decision making processes to make it behaviorally richer.…”

What works? An ANFIS-based policy evaluation framework for electric vehicle technology development

“…Moreover, the tendency to treat incumbents as a monolithic block may act to obscure divergent capacities and strategies with regard to future change, both within the regime as a whole and even within individual companies (or other regime participants) or between different spatial jurisdictions and time periods (Geels and Penna, 2015). In other words, there are certainly times when regime participants do act as a group, most obviously through consumer, trade or industry associations, but equally there may be various schisms within such a collective or individual members may take divergent stances (Sarasini, 2014;Gnann et al, 2015;Weiller et al, 2015).…”