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Stations-E — EV Charging Optimization

Stations-E needed to identify the most strategic locations, charger types, and volumes to deploy its EV stations, balancing profitability, usage, and future mobility trends in a highly complex and capital-intensive context.

solutions

  • Stations-E partnered with Seiki to analyze real-time and predictive traffic data using Mobility Intelligence.
  • 100% of vehicle movements were mapped to identify high-potential sites with strong EV demand.
  • Charger types were matched to traffic patterns and dwell times for optimal utilization.
  • Predictive models guided expansion into areas with projected EV growth.
  • A decision-support API provided data-driven site selection to reduce investment risk.

value created

  • Strategic deployment of charging stations in high-demand areas to maximize ROI
  • Optimized charger allocation (ultra-fast vs. standard) based on real usage behavior
  • Informed, low-risk expansion decisions powered by predictive analytics and real-time mobility data via AP

summary

Optimizing EV charging station placement and volume for maximum profitability.

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