Dynamic subsidies for synergistic development of charging infrastructure and electric vehicle adoption

44 Pages Posted: 5 Oct 2021

See all articles by Qi Luo

Qi Luo

University of Iowa - Department of Business Analytics

Yunlei Yin

Chongqing University

Pengyu Chen

Chongqing University

Zhenfei Zhan

Chongqing University

Romesh Saigal

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Date Written: October 1, 2020

Abstract

The governmental subsidy is an important instrument for catalyzing the early adoption of Electric Vehicles (EVs)}. A sustainable subsidy policy must balance between promoting EVs and expanding the charging infrastructure. This paper proposes a dynamic game approach to accelerate the adoption of EV technology. The government observes two correlated processes - the penetration of the EV market and the expansion of the charging infrastructure. It finds an optimal strategy that maximizes the cumulative social benefit in the face of uncertainty. A case study of China's EV industry finds that \blue{the established EV subsidy policies are inadequate to support EVs' growth over the next decades}. In contrast, the optimal subsidies will achieve \blue{the target EV market share and ensure the accessibility to charging infrastructure by 2030}. This non-myopic strategy can prioritize the infrastructure expansion, eliminate policy enforcement's monitoring costs, prevent compensation evasion, and help achieve long-term targets by making proactive regulatory policies.

Keywords: Electric vehicle adoption, Charging infrastructure, Technology diffusion,Policy incentive, Principal-multiagent system

Suggested Citation

Luo, Qi and Yin, Yunlei and Chen, Pengyu and Zhan, Zhenfei and Saigal, Romesh, Dynamic subsidies for synergistic development of charging infrastructure and electric vehicle adoption (October 1, 2020). Available at SSRN: https://ssrn.com/abstract=3934633 or http://dx.doi.org/10.2139/ssrn.3934633

Qi Luo (Contact Author)

University of Iowa - Department of Business Analytics ( email )

Iowa City
United States

Yunlei Yin

Chongqing University ( email )

Shazheng Str 174, Shapingba District
Shazheng street, Shapingba district
Chongqing 400044, Chongqing 400030
China

Pengyu Chen

Chongqing University ( email )

Shazheng Str 174, Shapingba District
Shazheng street, Shapingba district
Chongqing 400044, Chongqing 400030
China

Zhenfei Zhan

Chongqing University ( email )

No.174
Shazheng street, Shapingba district
Chongqing, 400044
China

Romesh Saigal

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

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