The purpose of this study is to find ways to reduce production time spent on diagnostic operations during maintenance or repair of electronic control systems (ECS) in automotive vehicles. Existing methods of diagnosing engine control systems in vehicles are sufficiently effective, but in most cases, they require highly skilled personnel, the use of additional complex and expensive equipment, prolonged service cycles, which in turn increases the complexity of maintenance, and also does not provide for prior prediction of faults and system failures. Analysis of scientific publications has shown that to reduce the time for maintenance and repair of electronic systems, it is necessary to predict the residual life of ECS components in vehicles during maintenance, to further reduce the labor intensity of diagnostics and current repairs. In other words, diagnostics performed during maintenance or repair should include predicting the residual life of electronic system components. For the most critical ECS components in vehicles, it is proposed to apply a strategy of replacing them upon reaching a certain mileage, rather than upon failure. This organization method will reduce vehicle downtime in repair and reduce the time to troubleshoot ECS component failures. A method has been proposed for identifying design elements that limit the reliability of the ECS, taking into account the degree of influence of their failures on the engine's technical and economic characteristics and the cost of restoring its performance. The availability of such information is the basis of the ECS maintainability support system. An algorithm has been developed to search for hidden faults in the components of ECS subsystems, which includes predicting the failure of ECS components. This will help reduce the labor intensity of diagnostic operations during maintenance and repair.
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