Questionnaire-Based Prospect Analysis of Energy Vehicle-to-Vehicle Connected Technology
Electric vehicles (EVs) have become a foremost policy option to reduce carbon emissions and mitigate climate change; however, the consumer recharging anxiety is increasingly apparent due to the lack of charging facilities and uneven distribution of charging station. The EVs’ energy-connected system leverages the distributed energy storage benefits of EVs and automatic driving technology, which can effectively combine intelligent connected vehicle system and energy system. Shenzhen, one of the largest cities in the world in terms of EV application market, the demand for charging piles for EVs as well as the pressure on the power grid is becoming increasingly evident. The vehicle-to-vehicle (V2V) energy sharing system is proposed in this paper to reduce the EV consumer’s charging anxiety and lower the carbon emissions, which can combine EV information, transport communication system, and energy system together. As an emerging energy supply model, it needs to be researched from the perspectives of the market, consumers’ mindset, and sustainable development. Therefore, 500 questionnaires were produced to investigate the V2V technology acceptance and its impact on the EV market and environment. Through the data from the questionnaires, we analyze the V2V’s benefits to the EV sales market, energy trading, and carbon emissions, as well as the adoption intentions and indicators of V2V technology. V2V energy transfer has proved to be of significant potential in both economic and environmental impacts and effectively activates the energy interconnections among EVs.
Authors
- Heyan Li (ORCID: https://orcid.org/0009-0002-6558-4724)
- Xiaobao Yang (ORCID: https://orcid.org/0000-0002-5545-4128)
- Xiaolin Mou (ORCID: https://orcid.org/0000-0002-1940-8394)
- Gang Xu (ORCID: https://orcid.org/0000-0003-2329-9458)
- Liqun Chen (ORCID: https://orcid.org/0000-0003-2484-9722)
- D. J. Li (ORCID: https://orcid.org/0000-0003-0660-5724)
Institutions
- Beijing Institute of Technology (CN)
Publication Details
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1061/9780784485484.034
- Primary Topic
- Electric Vehicles and Infrastructure
- Type
- article
- Field-Weighted Citation Impact
- 0.00