Sustainable and resilient Cloud-Edge-IoT (CEI) ecosystem, fostering a smoother transition towards a cleaner energy future.

AI-V2GO Project

AI Innovation for Vehicle to Grid Energy Exchange Orchestration

O-CEI Pilot 2: Software Defined Vehicle for VaS in Urban Areas 

Domain: Mobility

Location: Timisoara, Romania

Transforming vehicles into active infrastructure elements through Cloud-Edge-IoT

Pilot 2 demonstrates how Software Defined Vehicles (SDVs) can evolve into Vehicle-as-a-Service (VaS) environments, acting as hubs for computation, data exchange, and context-aware connectivity leveraging energy footprint drivers: onboard AI/edge compute, connectivity (5G/V2X), and data processing workloads. By integrating such technologies with O-CEI utilities, Pilot 2 orbits around smart grid optimization, safety and sustainability in large-scale urban mobility.

TARGETS:

  • Create new opportunities for OEMs to monetise digital services.
  • Enable SDVs with IoT capacities (Lidar, radar, ADAS, cabin sensing, cameras, telematics).
  • Optimize energy use and grid interaction via V2G and dynamic scheduling.
  • Demonstrate urban-scale Vehicle-as-a-Service models that support sustainability and realtime optimisation.

AI-V2GO addressing the O-CEI Pilot 2 Challenge 4 

Vehicle as Software (VaS) for Grid Optimization 

AI-V2GO addresses the Pilot 2 Challenge P2C4 by introducing a Dynamic V2G Orchestration solution for Grid Optimization (VaS-GO). 

Our core innovation is a Cloud-Edge AI framework that leverages Time Series Forecasting (TSF) to predict grid under/over-utilization periods. By integrating this real-time grid forecast with contextual vehicle data (EV location, State of Charge – SoC, and proximity to V2G charging stations), the system dynamically schedules Vehicle-to-Grid (V2G) discharge events during peak grid stress and Grid-to-Vehicle (G2V) charging during off-peak times. 

This highly localized and predictive control mechanism transforms the connected EV fleet into a reliable, distributed, mobile energy storage unit, significantly enhancing grid stability and energy efficiency in Timisoara.

Project Website: https://local-ai.gr/project/ai-v2go/ 

GitHub Repo: https://github.com/local-ai-gr/ai-v2go