Analysis of Fleet Data Using Machine Learning Methods

Abstract:

To enhance the functions and improve the safety of the new generation of vehicles， this paper collected abundant history data of vehicles and then created a rule-based model by using machine learning methods， so as to detect the faulty vehicle in a fleet. Several steps were designed for detailed illustration， and the validation of the method was conducted through electrical fault of the LV （lithium-cobalt） battery. The results can be used as input for the test bench tests of the following vehicle generations.