TopN AnalyticsEV Cars Efficiency Determination
An EV fleet operator needed vehicle efficiency of their EV cars to identify and repair or replace batteries of low efficiency EVs.
Where things stood
Calculating a vehicle's efficiency (km per kWh consumed) sounds simple, but the underlying telemetry often isn't reliable enough to trust at face value.
Charging sessions can be logged through more than one protocol pathway, and these sources don't always agree on how much energy was actually delivered.
What we built
Charge transaction records and telematics odometer data plus OCPI session logs (Postgres) feed a Python reconciliation pipeline.
The pipeline matches sessions to telematics readings via time-window joins, cross-validates the energy-delivered figure.
IQR-based outlier detection flags anomalous cost-per-kilometer sessions at the per-vehicle level, before results land in a BigQuery dashboard table and Google Sheets.
How it works
TopN Analytics built a pipeline that computes vehicle efficiency (km/kwh) and cost-per-kilometer.
Efficiency (km per kWh) is calculated from odometer deltas between charging sessions, with cost-per-kilometer outliers flagged using per-vehicle IQR thresholds.
What we delivered and learned
An efficiency metric for individual vehicles of the fleet allowed the client to identify poor efficiency cars that needed repairs or battery replacement
What it's built on
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