RT Journal Article
A1 Maria Vittoria Corazza
A1 Silvia Magnalardo
A1 Antonio Musso
A1 Enrico Petracci
A1 Michele Tozzi
A1 Daniela Vasari
A1 Emmanuel de Verdalle

PB iet
T1 Testing an innovative predictive management system for bus fleets: outcomes from the Ravenna case study
JN IET Intelligent Transport Systems
VO 12
IS 4
SP 286
OP 293
AB The European Bus System of the Future (EBSF_2) is a research project funded by the European Union with the aim of developing a new generation of buses across Europe. The goals are to increase the attractiveness and efficiency of buses by testing advanced operational and technological solutions. Among these are more comfortable internal layouts, the implementation of a standard IT architecture, intelligent garage procedures, energy-efficient auxiliaries and green driving assistance systems, all of which are being tested in several demonstrators. This study focuses on the innovative features of the methodology and test process adopted in Ravenna, Italy, where a demonstrator is being used to improve predictive maintenance management. The demonstrator involves maintenance software used to analyse data from CANbus and sensors to assess oil quality, detect potential breakdowns and, on this basis, replace spare parts in advance. The system also detects which substances contribute to poor oil quality. The study describes performance before and during the implementation of the demonstrator in relation to various impact areas: maintenance, operations, fuel consumption, costs, staff training and the efficiency of the intelligent transport system in processing data. The achieved results are reported with the aim of providing advanced knowledge for applications beyond EBSF_2.
K1 bus fleets
K1 European Bus System of the Future
K1 fuel consumption
K1 oil quality assessment
K1 spare parts replacement
K1 potential breakdown detection
K1 CANbus
K1 predictive management system
K1 intelligent transport system
K1 predictive maintenance management
K1 maintenance software
K1 Italy
K1 costs
K1 Ravenna
K1 sensors
K1 EBSF_2
K1 data analysis
DO https://doi.org/10.1049/iet-its.2017.0207
UL https://digital-library.theiet.org/;jsessionid=hrqr60vv48pc.x-iet-live-01content/journals/10.1049/iet-its.2017.0207
LA English
SN 1751-956X
YR 2018
OL EN