TopN AnalyticsEV Charging Success and Failure Monitoring for Charge Point Operators
Charge Point Operators (CPO) need a monitoring system to know ongoing and historic health of their overall network, and catch high amount on charging failures quickly in order to avoid revenue losses.
Where things stood
EV Charging sessions can be interrupted by connectivity issues, hardware faults, or user behavior.
Without a monitoring & alerting mechanism, Charge Point Operators (CPO) had no clean signal for revenue assurance or for identifying reliability problems.
What we built
Charge transaction records, charge point/station/connector metadata, and user/auth data (PostgreSQL) feed a SQL business-rule classification engine.
The engine branches by how a session was originally requested — fixed amount, target battery SoC, target energy units, or fixed duration — checking whether the transaction delivered at least 90% of what was requested.
How it works
TopN Analytics designed a business-rule classification engine that determines success or failure per transaction, tailored to how the session was originally requested, computed automatically every day alongside running failure counts.
A dashboard provided hourly metrics for each date showing the overall success/failure rates with indicators to quickly identify charging stations, charge points and connectors driving high amounts of failed sessions.
What we delivered and learned
The 90%-of-requested threshold is a specific, deliberately chosen business rule reflecting genuine collaboration on defining 'success' precisely enough to automate.
Tracking running failure counts, not just a daily snapshot, surfaces underlying systemic patterns in causing failures (such as power outages)
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