Methods for forecasting the market penetration of electric drivetrains in the passenger car market. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Jochem, Patrick; Gómez Vilchez, Jonatan J.; Ensslen, Axel; Schäuble, Johannes; Fichtner, Wolf
• Is Part Of: Transport reviews. Volume 38:Issue 3(2018)
• Page Start: 322
• Page End: 348
• Publication Date: 2018-05-04
• Subjects: electric vehicles -- modeling -- methods -- diffusion -- forecasting -- alternative drivetrains; Transportation -- Periodicals; Transportation engineering -- Periodicals; 380.5
• DOI: 10.1080/01441647.2017.1326538
• Languages: English
• ISSNs: 0144-1647

Abstract

ABSTRACT: Current car technologies will not solve upcoming challenges of mitigating greenhouse gas emissions in road transport. Projections of the market penetration by alternative drive train technologies are controversial regarding both forecast market shares and applied scientific methods. Accepting this latter challenge, we provide a (so far missing) overview of methods applied in this field and give some recommendations for further work. Our focus is to classify the applied methods into a convenient pattern and to analyse models from the recent scientific literature which consider the electrification of light-duty vehicles. We differentiate the following bottom-up approaches: Econometric models with disaggregated data (such as discrete choice), and agent-based simulation models. The group of top-down models are subdivided into econometric models with aggregated data (e.g. vehicle stock data), system dynamics, as well as integrated assessment models with general equilibrium models. It becomes obvious that some methods have a stronger methodological background whereas others require comprehensive data sets or can be combined more flexibly with other methods. Even though there is no dominant method, we can identify a trend in the literature towards data-driven hybrid approaches, which considers micro and macro aspects influencing the market penetration of electric vehicles.