The actual contribution of plug-in hybrid and battery electric vehicles (PHEV and BEV) to greenhouse gas mitigation depends on their real-world usage. Often BEV are seen as superior as they drive only electrically and do not have any direct emissions during driving. However, empirical evidence on which vehicle electrifies more mileage with a given battery capacity is lacking. Here, we present the first systematic overview of empirical findings on actual PHEV and BEV usage for the US and Germany. Contrary to common belief, PHEV with about 60 km of real-world range currently electrify as many annual vehicles kilometres as BEV with a much smaller battery. Accordingly, PHEV recharged from renewable electricity can highly contribute to green house gas mitigation in car transport. Including the higher CO_2eq emissions during the production phase of BEV compared to PHEV, PHEV show today higher CO_2eq savings then BEVs compared to conventional vehicles. However, for significant CO_2eq improvements of PHEV and particularly of BEVs the decarbonisation of the electricity system should go on.

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.