Energy & Resilience
AI-Powered BMS for EV Fleet Operator
Key outcome
+10% range, same cells
The Challenge
An EV fleet operator was seeing premature battery degradation, inconsistent range estimates, and early cell failures — all pointing to a one-size-fits-all BMS strategy that ignored per-vehicle cell aging behaviour and real-world usage patterns.
What We Built
We deployed an AI-powered Battery Management System that continuously learns individual cell aging curves for each vehicle in the fleet. Charging profiles and discharge strategies are adapted per cell history, not generic lookup tables. The system runs on existing BMS hardware via OTA.
The Result
+10% effective range on the same cells within 6 months. Cell replacement rate dropped 28%. Fleet operators gained accurate per-vehicle state-of-health dashboards, enabling data-driven procurement decisions.