Retrieved from Vol. 28, No. 2, 2025
Pages 21 -40
Received 12.08.2025
Revised 01.12.2025
Accepted 29.12.2025
Retrieved from Vol. 28, No. 2, 2025
Pages 21 -40
Abstract
The article presents a comprehensive reliability analysis of the power equipment of urban electric transport, including traction electric motors, inverters, cable–terminal connections, and cooling systems. Based on a literature review, the strengths (development of non-invasive diagnostic methods, application of machine learning algorithms, and formation of combined maintenance strategies) and weaknesses (limited statistical data for urban fleets, sensitivity of algorithms to noise, insufficient integrationwith risk management) of current research were identified. A conceptual model of integrated reliability management is proposed, combining multi-source data collection, FMEA-lite methodology, Pareto analysis, and the development of an Action Plan. The analysis results revealed that the highest RPN values are associated with external factors (moisture, overloads) and critical components such as bearings, windings, and cable connections. A Matlab/Simulink model was developed to simulate vibration diagnostics of traction motor bearings, confirming the effectiveness of envelope analysis for early defect detection. The Action Plan implementation reduced average RPN values by 25–40%, proving the practical value of the methodology for transport depots. The obtained results provide a foundation for the transition to predictive maintenance and the enhancement of operational reliability in urban electric transport
Keywords:
urban electric transport; power equipment; reliability; diagnostics; FMEA-lite; Pareto analysis; vibration monitoring; Matlab/Simulink; Action Plan; Predictive Maintenance