Background: The focus of the paper is on scenario studies that examine energy systems. This type of studies is usually based on formal energy models, from which energy policy recommendations are derived. In order to be valuable for strategic decision-making, the comprehensibility of these complex scenario studies is necessary. We aim at highlighting and mitigating the problematic issue of lacking transparency in such model-based scenario studies.

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This is the author's version of a work that was published in the following source: Jochem, P.; Gómez Vilchez, J. J.; Ensslen, A.; Schäuble, J.; Fichtner, W. (2018).Methods for forecasting the market penetration of electric drivetrains in the passenger car market .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.

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