Preventive maintenance of charge points should include both regular inspections and in-depth EV charger monitoring.
Inspections are critical because they allow inspectors or electricians to identify visual signs of wear, corrosion, loose connections, and thermal issues. For example, we’ve encountered cases where electrical wires were loose, or specific components showed early signs of corrosion. During inspections, staff can either replace the faulty units immediately or schedule a replacement within the coming weeks.
These inspections also provide an opportunity to clean the charging equipment, both inside and out. Dirt and dust can block airflow and cause overheating, so cleaning or replacing air filters during inspections can significantly extend the equipment's lifespan.
In addition to inspections and cleaning, operations staff should review error reports for each charger daily or at least weekly. These reports are often combined with call center logs to identify chargers with recurring issues. Technicians can then run remote diagnostics on the EV charger and, if necessary, schedule an on-site inspection.
EV charging stations generate vast amounts of data logs, error messages, and general metering data. Software companies use this data to create visual graphs and provide insights to the charging point operator.
With the advent of more powerful AI models, such as ChatGPT, there are new opportunities for advanced functionalities. AI models can scan logs and messages, comparing them to previous patterns to identify potential issues more quickly. This automated analysis helps charge companies detect problems faster without manually sifting through logs and comparing them with past error reports. AI also enables the processing of more data than a human could feasibly handle.
While AI models for EV charger maintenance are improving and offering more capabilities, it's important to note that many instances of downtime still stem from basic issues: lack of proper monitoring, missing 24/7 support teams, or simple mistakes. Therefore, AI should be seen as a supplemental tool rather than a solution to these fundamental challenges.
One of the most significant obstacles to effective monitoring and repairs is the lack of proper technical documentation for EV chargers, including a list of error codes and contacts for OEM support. This information is vital for maintenance and monitoring, and without it, maintaining a fleet of EV chargers can become nearly impossible. Key information includes:
Charger Documentation: Detailed technical information about charger components, maintenance instructions, interfaces, and other relevant details.
Charger Error Codes: A comprehensive list of codes that refer to specific errors. These codes are transmitted from the charger to the monitoring software for the remote monitoring team. Some manufacturers have over 500 error codes.
Maintenance Logs: Detailed records of all maintenance activities, inspections, repairs, and replacements. These logs help track component performance and identify trends that might indicate underlying problems.
Service History: A complete service history for each major component, including power inverters, transformers, and switchgear. This documentation is essential for planning replacements and upgrades.
Proper documentation and a well-maintained service history not only streamline maintenance but also support predictive analysis for future repairs and upgrades.
Charger inspection
AI tools
Predictive monitoring