Analyzing charging technologies for autonomous electric vehicles : A use case of public transport operations in Tampere Region, Finland

Abstract

Transport is the backbone of today’s economy and societal development. However, it also has some negative external impacts including carbon emissions, accidents, traffic congestion, and poor air quality. While electrification and automation can help to tackle these challenges. However, both target different challenges. Electrification can help to reduce carbon emissions and improve air quality whereas, automation can help to improve safety and reduce congestion. Synergies of both automation and electrification can reduce the external impact of transport. The current charging of autonomous electric vehicles involves human intervention which contradicts the idea of fully autonomous vehicles. To achieve full autonomy, the charging process should also be automated and without human intervention. This research identifies the factors that can affect the charging strategy for autonomous electric vehicles, analyzes available automated charging technologies based on their techno-economic factors, and assesses their impact on public transport operations through a use case in the Tampere region, Finland.

In the study, a combination of different research methods is used. The research methods in clude a comprehensive literature review, and a techno-economic framework derived from existing literature for comparing automated charging technologies to compare technical and economic factors such as charging efficiency, infrastructural requirements, power levels, and costs. Moreover, use-case scenario analysis is considered which involves two scenarios for different operational characteristics of a public transport route, comparing various automated charging technologies and their impact on total charging time, service downtime, charging cost, and total cycle time.

The findings indicate that weather conditions, operational characteristics, charging price, and charging methods can significantly influence the charging strategy. Moreover, five automated charging technologies were identified: robotic arm, pantograph, inductive charging, under-body coupler, and battery swapping station. Among these, pantograph, inductive charger, and robotic arm are optimal for public transport operation based on cost, efficiency, and technological readiness level. Moreover, it was identified that in terms of safety, charging infrastructure can face the following challenges: physical threats, cyber-attacks, and fire hazards. Mitigation strategies were proposed. Furthermore, use case scenarios analysis reveals that, increasing the operating hours and the frequency will lead to service breaks when charging is done only at the terminus stop. Also, the charging cost is higher when only opportunity charging is considered. Moreover, the fleet size requirement is higher for depot charging compared to on-route charging. This research can help transit agencies or public transport operators to decide on automated charging technology for autonomous electric vehicles based on their needs.