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Development of an Algorithm Capable of Classifying the Starting, Gear Change and Engine Brake Variables of a Vehicle by Analyzing OBD II Signals

Abstract:

The present project shows an algorithm capable of visualizing the behavior of the PID signals of a vehicle by identifying common driving maneuvers such as: starting, changing gear and engine braking during a road test. The data of this study were acquired through the OBD-II connector of a vehicle, by means of a data logger device capable of collecting the information and writing it to a data file. Later the data is post processed in MATLAB® using the unsupervised learning method k-means. Finally, the results obtained by the algorithm are able to discriminate the erroneous values of the signals by means of a multivariate statistical analysis that classifies the study variables: start, gear change and engine brake.