Overview
Uses AI to optimise EV charging and energy return via Vehicle-to-Grid (V2G) capabilities, with edge and cloud software supporting fleet-wide data analysis and operations.
Expected Outcomes
- To demonstrate that Software-Defined Vehicle (VaS) capabilities can reduce electric energy consumption per vehicle kilometre by up to 15% for selected EVs.
- KPI: 15% reduction of energy consumption of VaS vehicles.
This use case is now available in the hourglass canvas, mapping the relevant stakeholders against the capabilities required for delivery and uptake. Explore it to identify who needs to be engaged, what is already in place, and where capability gaps remain
View this use case on the hourglass model
Explore the community around this use case
Energy and infrastructure resilience
The Energy and Infrastructure Sphere focuses on energy systems and critical infrastructure, with an emphasis on resilience, efficiency, and secure operati..
Discover more about sphere (opens in a new window)
Mobility logistics and software defined vehicles
The Mobility, Logistics and the Software-Defined Vehicle Sphere covers transport, logistics, and connected mobility ecosystems, including software-defined vehicles.
Discover more about sphere (opens in a new window)