English

Analyzing BEV Suitability and Charging Strategies Using Italian Driving Data

Information Retrieval 2025-10-01 v1 Computational Engineering, Finance, and Science

Abstract

Battery Electric Vehicles (BEVs) are rapidly evolving from a niche alternative to an established option for private transportation, often replacing Internal Combustion Engine (ICE) vehicles. Despite growing interest, significant barriers remain, including range anxiety, the inconvenience associated with public charging stations, and higher costs. This study analyses extensive telemetry data collected from 10,441 users using ICE vehicles in an Italian province to assess the potential for switching to BEVs without changing current travel behaviour. We evaluate to what extent the BEV models can fulfil their mobility needs under different charging scenarios. To do so, we replicate trips and parking events, simulating and monitoring the battery state of charge. The analysis reveals the compromises between charging behaviours and limited BEV autonomy. Assuming access to overnight charging, at least 35% of the users could already adopt even low-capacity BEVs.

Cite

@article{arxiv.2509.26262,
  title  = {Analyzing BEV Suitability and Charging Strategies Using Italian Driving Data},
  author = {Homa Jamalof and Luca Vassio and Danilo Giordano and Marco Mellia and Claudio De Tommasi},
  journal= {arXiv preprint arXiv:2509.26262},
  year   = {2025}
}

Comments

Accepted at 2025 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC-AP 2025)

R2 v1 2026-07-01T06:07:40.519Z