Electric vehicle stock forecasting and planning in the USA

ABSTRACT

Projecting annual electric vehicle (EV) stock serves as the first step in the processes to estimate future demand for electricity, charging stations, batteries, and integrated circuits. Accurate projections pay dividends by allowing policymakers optimize incentives and support for the EV industry, transportation sections and customers. Despite early starter in EV technologies, the US lags behind the major EV markets in terms of EV production and sales. While studying the development of the US EV industry, the current study aims to forecast the EV stock in the US till 2030. The study argues that the optimized discrete grey forecasting model DGM (1,1,α) is an effective data-driven technique to forecast stock of two types of electric vehicles – Battery Electric Vehicles (BEV) and Plug-in Hybrid Electric Vehicles (PHEV). The comparative analysis with the classical discrete grey model DGM (1,1), even grey model EGM (1,1) and Grey Verhulst model reveals that the model DGM (1,1,α) is most suitable for forecasting the US EV stock. It is estimated that the US EV stock would be around 30 million by 2030, to support which 0.7 million EV charging stations would be required. The findings are potentially useful for fuel demand management by utility companies, evaluation and incentive policies by public agencies, and marketing and sales strategies by automakers involved with zero-emission vehicles.

Keywords: Forecasting; Battery electric vehicle; Plug-in electric vehicles; New energy vehicles; The United States of America; Grey Model; Grey System; Grey Forecast

Read the full paper at Grey Forecasting and Planning of Electric vehicle stock in the United States

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