Total cost of ownership of electric vehicles compared to conventional vehicles: A probabilistic analysis and projection across market segments

• Published in: Energy policy Vol. 80; pp. 196 - 214
• Main Authors: Wu, Geng, Inderbitzin, Alessandro, Bening, Catharina
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.05.2015; Elsevier Science Ltd
• Subjects: Alternative fuel vehicles; batteries; Battery; Capital; Capital costs; Consumers; Cost; Cost analysis; Cost comparison; cost effectiveness; Costs; Decision making; Electric vehicles; Energy market; Energy policy; Infrastructure; issues and policy; Market segments; Marketing; Markets; Operating costs; Ownership; probability analysis; Sensitivity analysis; Simulation; simulation models; Studies; Technology; Technology transfer; Total cost of ownership; Transport sector; Vehicles; vehicles (equipment); Electric vehicles; Total cost of ownership; Transport sector; Technology transfer; Cost comparison
• ISSN: 0301-4215; 1873-6777
• DOI: 10.1016/j.enpol.2015.02.004

While electric vehicles (EV) can perform better than conventional vehicles from an environmental standpoint, consumers perceive them to be more expensive due to their higher capital cost. Recent studies calculated the total cost of ownership (TCO) to evaluate the complete cost for the consumer, focusing on individual vehicle classes, powertrain technologies, or use cases. To provide a comprehensive overview, we built a probabilistic simulation model broad enough to capture most of a national market. Our findings indicate that the comparative cost efficiency of EV increases with the consumer's driving distance and is higher for small than for large vehicles. However, our sensitivity analysis shows that the exact TCO is subject to the development of vehicle and operating costs and thus uncertain. Although the TCO of electric vehicles may become close to or even lower than that of conventional vehicles by 2025, our findings add evidence to past studies showing that the TCO does not reflect how consumers make their purchase decision today. Based on these findings, we discuss policy measures that educate consumers about the TCO of different vehicle types based on their individual preferences. In addition, measures improving the charging infrastructure and further decreasing battery cost are discussed. •Calculates the total cost of ownership across competing vehicle technologies.•Uses Monte Carlo simulation to analyse distributions and probabilities of outcomes.•Contains a comprehensive assessment across the main vehicle classes and use cases.•Indicates that cost efficiency of technology depends on vehicle class and use case.•Derives specific policy measures to facilitate electric vehicle diffusion.