How connected vehicle data can provide insights into placements for public EV charging infrastructure.
This case study uses Compass Road Intelligence and Custom Services
A lack of charging infrastructure has been cited as a major deterrent for would-be electric vehicle (EV) owners. Increasing EV ownership has become a priority for government strategies around reducing emissions, with up to 1/3 of carbon emissions resulting from roads and vehicles. But to encourage more EV owners, more charging infrastructure is needed.
A Compass IoT client was undertaking a project to scope and plan for the installation of EV fast charging stations around major cities. This includes using data for improved charger utilisation and demand modelling. Range anxiety is a factor in EV user behaviour, especially around weekend and holiday trips, due to the increase in demand for public chargers.
Origin-destination data revealed patterns in vehicle behaviour that supported assumptions around key locations and priorities for charging infrastructure rollout.
The Compass Road Intelligence data used to unearth these insights include:
- trip times
- volume of cars
- the number of EVs as a percentage of total traffic volumes
- stopping locations and lengths
By identifying the number of EVs as a percentage of total traffic, the client was able to determine what level of demand might exist for existing infrastructure, whether new infrastructure needs to be built, and where to build it.
Overlaying vehicle makes and model information and a known origin and destination could also provide insight into the best locations for new chargers, potentially maximising the return on investment through higher utilisation rates.
Similarly, understanding popular stopping locations and average stopping times could inform what type of chargers (i.e., Ultra fast, fast, and regular chargers) should be installed based on current demand.
