Fenexity translates route schedules, vehicle requirements, charging assets, grid limits, and market signals into decision-grade charging plans. The method is technical underneath, but the output is built for fleet operations, engineering, procurement, and IT.
Schedule-aware depot optimization
Grid, tariff, charger, and vehicle constraints in one model
Founder research in e-bus charging, market participation, and infrastructure sizing
The method starts with the operational reality of the depot rather than a generic charger count.
Blocks, departures, return windows, reserve requirements, and dispatch exceptions.
Battery capacities, consumption assumptions, charger power, connector topology, and parking constraints.
Grid connection, meters, load limits, tariff structures, PV, battery storage, and local EMS signals.
Vehicles are prioritized by next duty, required energy, operational risk, and charger availability.
Charging is shifted around price, peak, and grid limits where the operating schedule allows it.
Plans remain explainable when chargers fail, schedules shift, or local limits change.
A daily or weekly charging plan with readiness risks, exceptions, and override points.
View detailsExpected power demand, peak load, grid utilization, and sensitivity to schedule changes.
View detailsA procurement-friendly summary of inputs, limits, model scope, and result sensitivity.
View details| Evidence type | How to read it | Required support |
|---|---|---|
| Capability | Describe what Fenexity does | Product capability and feature status |
| Modelled | Show scenario ranges | Assumptions, sensitivity factors, review date |
| Measured | Use in project studies | Project data and publication permission |
Where public customer references are not available, Fenexity uses capability language and modelled scenarios. Numeric customer outcomes are shown only when validated project data can be published.
