Modelling market diffusion of electric vehicles with real world driving data. Pt.I: Model structure and validation

Abstract

The future market diffusion of electric vehicles (EVs) is of great importance for transport related green house gas emissions and energy demand. But most studies on the market diffusion of EVs focus on average driving patters and neglect the great variations in daily driving of individuals present in real-world driving data. Yet these variations are important for EVs since range limitations and the electric driving share of plug-in hybrids strongly impact the economic evaluation and consumer acceptance. Additionally, studies often focus on private cars only and neglect that commercial buyers account for relevant market shares in vehicle sales. Here, we propose a reliable, user specific model for the market diffusion of EVs and evaluation of EV market diffusion policies based on real world driving data. The data and model proposed include both private and commercial users in Germany and allow the calculation of realistic electric driving shares for all usage patterns. The proposed model explicitly includes user heterogeneity in driving behaviour, different user groups, psychological aspects and the effect of charge-at-home options. Our results show that the proposed model reproduces group specific market shares, gives confidence bands of market shares and reliably simulates individual electric driving shares.