Development of a surveillance system for maintenance and diagnosis of buses based on can-bus data transmitted wirelessly

Abstract

From the point of view of vehicle maintenance, one of the most important systems of urban buses is the cooling system. These vehicles run typically more than 80,000 km per year, and the radiator of the system gets fouled due to dust and dirt of the cooling air, which produces an increase in water temperature. This situation forces to stop the vehicle and perform washing of the radiator. This study is focused on the development of a model of the cooling system of urban buses based on an artificial neural network (ANN), which is used for system diagnosis and engine surveillance. Data are gathered from the CAN-bus system of every bus, which have allowed the development of a dynamic ANN that fits the cooling dynamics.