Ten years of electrochemical research, 100+ white papers, and 1,200+ provisional patent opportunities — built into a three-layer AI platform that gives transit agencies the battery intelligence their fleets demand.
The Science Behind EVCare™
EVCare™ is built on a foundational body of electrochemical research developed over ten years — 100+ white papers covering every major battery health mechanism, failure mode, and management strategy relevant to large-format lithium-ion packs in commercial electric vehicles.
The platform doesn’t apply generic machine learning to telemetry data. It applies physics-based electrochemical models, validated against real fleet data, to give you a battery health picture that reflects what’s actually happening at the cell level.
Three-Layer Intelligence Architecture
EVCare™’s intelligence architecture processes raw battery data through three distinct layers — each building on the last — to produce a single, actionable fleet fitness picture.
CareStar™ is the sensing foundation. It continuously monitors every electrochemical signal available from the battery system — 47 distinct parameters per vehicle, monitored continuously. The goal is to see what is actually happening at the cell level, not just what the BMS surface reports.
BattHealthScore™ takes the 47 CareStar™ data streams and synthesises them into a single composite health index per vehicle. Physics-based electrochemical models translate raw signals into a meaningful health score that reflects actual battery condition, not just fault codes.
FitStar™ translates individual vehicle health scores into fleet-wide operational intelligence, scoring across five weighted domains and producing actionable outputs for dispatch, maintenance scheduling, and capital planning.
FitStar™ Scoring Domains
FitStar™ v5.0 evaluates battery health across five weighted domains, ensuring that no single factor dominates the health assessment while giving operators a clear, single-number readout for every vehicle.
Core cell condition — capacity, power capability, and degradation state.
How effectively the pack manages heat across cells and cooling systems.
The real-world demand each vehicle's duty cycle places on its battery.
How charging practices influence long-term battery health.
External conditions that shape degradation over time.
See the Technology in Action
The EVCare™ SiL Simulator runs a full 72-hour BEB fleet simulation — showing every layer in action, from CareStar™ thermal detection through to AMS™ maintenance prescriptions.