Charger certainty

Project Info

Zirkarta thumbnail

Team Name


Team Members

Sonja , Dylan

Project Description


   "A lot of us now seem to be turning up at the same charger at the same time"
   Dave, Canberra EV Driver

With a petrol or diesel car, if you arrive at a service station and all the bowsers are full, you know you will only have to wait a few minutes until a bowser is free.

With an Electric Vehicle (EV), you may have to wait anywhere from a few minutes to hours.

While there are existing web-based systems that provide information about if EV chargers are being used, they do not provide information on how long chargers that are currently being used will remain unavailable and how long chargers that are not being used will remain available. This introduces uncertainty to any EV trip that involves charging.

   "We need automated trip planning that selects the optimum charging location(s) along your route
   and automatically reserves a charging session time based on your arrival time."
   Purrpullberra, EV driver 2016

Overseas, where the uptake of electric vehicles is more advanced, this lack of visibility and certainty is leading to “charge rage” (see

Concerns about this issue from non-EV users is one of the barriers to them adopting EVs - a barrier that needs addressing for the Government to meet its 2045 Net Zero Emissions target.

Charger providers are already operating on very thin margins and installing further chargers to increase the number of chargers per EV without government incentives is not commercially viable for them.

Increased numbers of chargers increases the difficulty of managing the electricity grid because this increases uncertainty for electricity suppliers who currently can only react to demand.


How can certainty about the availability of EV chargers be increased without increasing the number of chargers per EV?

#electric vehicles #trip optimisation #artificial intelligence #geospatial #travel time #wait time #data fusion

Data Story

How data is used

The solution fuses data from
• on-road EVs including location, route and remaining charge,
• charger data such as location and availability, and
• road data such as traffic.

Optimising AI uses this fused data to identify the charging location that will minimise travel time, including charger waiting time, for every vehicle.

Chargers can be booked, guaranteeing availability. If it is not booked, it can still be used for unscheduled charging.

The solution also increases certainty for charger providers enabling them to make data driven decisions which will result in increased margins and the confidence to install more chargers.

Electricity suppliers will have increased ability to predict future demand.

Find out more

Evidence of Work


Project Image

Team DataSets

ACT Road Centrelines

Description of Use This roads data is used (1) for drivers to identify their destination, (2) to calculate the optimised route, and (3) to calculate the distance and answer the question is the destination or charger within range?

Data Set

Challenge Entries

The Electric Vehicle Future

How do we help people go green?

Go to Challenge | 3 teams have entered this challenge.