Control of the technical condition of vehicles through analysis of information from on-board diagnostics during operation

Abstract

The increase in the average age of the rolling stock of motor transport enterprises requires clear control over its technical condition. The development of forecasting methods based on the information collected from on-board diagnostics is a promising way to solve a cluster of problems to eliminate unplanned repairs and downtime of vehicles.

The practice of updating the rolling stock by purchasing vehicles with less mileage than the vehicles available at the enterprise is widespread. The history of the vehicle and primary diagnostic files may be unavailable. In this case, complete information about the condition of the truck that is proposed to be purchased allows you to make the right management decision. On-board diagnostics of modern MAN, DAF, Volvo, Scania, Mercedes, Renault and Iveco vehicles record more than 360 parameters of the operation of various systems. Among these parameters, you can select important ones for analysis and accumulation of data in order to predict future failures. The practice of solving the problem under consideration already exists and is being developed, but is not yet possible for most of the outdated vehicles and accessible to the general public of transportation market participants.

With a detailed review of the fuel system operating parameters, it is possible to record the prerequisites for the occurrence of a failure, which affects the development of the required power by the car and maintaining a given speed. The state of boost pressure is also always of interest to diagnostic specialists. Information is collected on a number of important parameters from the turbocharger.

Temperature and gas composition indicators are recorded from the exhaust gas system. This provides important information about the condition of the engine and the processes occurring during its operation. By analyzing the pressure and temperature of technical fluids, it is possible to prevent high-cost repair work.

Key words: gradual failure, diagnostic parameters, computer diagnostics, freight transportation, auto scanner, technical condition prediction.