Explainable AI-Based Predictive Maintenance for Public EV Charging Infrastructure Using Real OCPP Data with SHAP Analysis
Ladataan...
Kokoteksti luettavissa vain Tritonian asiakaskoneilla.
Pysyvä osoite
Kuvaus
Opinnäytetyö kokotekstinä PDF-muodossa.
Crucially impacting user satisfaction and the downtime of electric vehicle (EV) charging
stations, the reliability of EV infrastructure inevitably drives the transition toward car-
bon-free emission vehicles.
Proposing an explainable artificial intelligence (AI)-based predictive maintenance frame-
work for public EV charging infrastructure using real-world Open Charge Point Protocol
(OCPP) data with SHAP analysis, this thesis combines large-scale feature engineering,
multiple machine learning models, SHAP-based feature selection, and decision-thresh-
old optimization to predict station-level failures in advance and identify the key factors
driving these failures; it is evaluated using real data from ENGIE Vianeo, considering both
an initial dataset of 104 charging stations and an extended dataset of 291 stations under
different observation periods. Experimental results demonstrate that tree-based ensem-
ble methods outperform linear and distance-based models, with Random Forest achiev-
ing the best performance (0.800 F1-score and 0.828 recall). The integration of SHAP-
based feature selection and threshold optimization consistently improves model perfor-
mance, particularly on the larger dataset.
From an operational perspective, the results highlight the potential economic impact of
predictive maintenance. Based on observed downtime of approximately 32,000 days per
year and an estimated annual cost of €243,000, the proposed framework could enable
the early detection of up to 82.8% of faults. Assuming that 30% to 50% of predicted
failures can be prevented, this corresponds to potential annual savings between €60,000
and €100,000. Overall, the proposed framework demonstrates that explainable machine
learning techniques can effectively support predictive maintenance in EV charging infra-
structure, offering both improved reliability and significant operational benefits.
Keywords: Predictive Maintenance, Electric Vehicle (EV) Charging Infrastructure, Ex-
plainable Artificial Intelligence (XAI), SHAP Analysis.
Islam Elmorshidy
02/06/2026