Methods for forecasting the market penetration of electric drivetrains in the passenger car market

TLDR

Current car technologies cannot address the imminent greenhouse gas mitigation challenges in road transport, and projections of alternative drivetrain market penetration are contentious in both forecast shares and scientific methods. The study aims to provide an overview and recommendations of forecasting methods for electric drivetrain penetration, classifying them and analyzing recent literature on light‑duty vehicle electrification. The authors classify forecasting approaches into bottom‑up econometric and agent‑based models, and top‑down econometric, system dynamics, and integrated assessment models with general equilibrium frameworks. No single method dominates; however, the literature shows a shift toward data‑driven hybrid approaches that integrate micro and macro factors to forecast electric vehicle market penetration.

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.