Forecasting the Number of Electric Vehicles: A Case of Beijing

Electric vehicles (EVs) have enjoyed fast-growing adoption in recent years, mainly thanks to the concern of climate change, environmental pollution, advancement of battery technology and expeditiously rising prices of crude oil. Rationally forecasting the number of EVs is quite important to their orderly development. This paper forecasts the number of EVs using the Bass diffusion model. Due to lack of sufficient historical data of EVs, analogy method is used to estimate the parameters of EVs according to the history diffusion data of private cars. The fuzzy analytic hierarchy process is used to calculate the weighted average of the main factors that influence users' decisions of purchasing vehicles to estimate the parameters of Bass model.