Research and Innovation in Predictive Management for Bus Fleets: The Ravenna Case Study

The paper focuses on the methodology and the test process adopted in Ravenna and Forlì (Italy), within the
EBSF_2 research project, where a demonstrator to improve predictive management performance was tested. This
relied on a maintenance software to analyze data coming from sensors assessing the engine oil quality, therefore
detecting potential breakdowns and replacing spare parts in advance; the system also identifies which metals or
problems concurred to the oil poor quality. The test involves three urban diesel-fueled urban buses in Forlì and
three methane-fueled urban buses in the Ravenna, for a total of 27 lines and a maintenance staff of 20 units, over
an 12-month testing period. Since the initial results, the sensor-based system proved to be effective. Test results
are analyzed and operational and environmental benefits highlighted, with the research goal to advance scientific
knowledge in this field.