QUALITY ASSESSMENT OF MULTI-PARAMETER CONTROL OF VEHICLE COMPLEX SYSTEMS EFFICIENCY

The aim of the study is to quantify and predict the risks of diagnosing multi-parameter systems of vehicle The object of research is the process of technical maintenance of multi-agent systems. The subject of the research is the process of quantitative evaluation and prediction of the risks of working capacity in the process of diagnosing vehicle multi-parameter systems. To achieve goal the following aim is fulfilled in the article: sources of errors on the trajectory of the formation of the total measurement uncertainty were identified on the example of monitoring phase parameters of diesel engine fuel supply. A vehicle is considered as a complex multi-parameter multi-agent system with feedback to restore system performance. The control process is accompanied by errors in the form of a false and undetected defect. Probable errors determine risks of two types: risk of vehicle health checker and risk of a customer. For a quantitative assessment of these risks random and simulation models have been developed. Models allow to investigate the influence of statistical characteristics of modeling agents on control risks. For the integral assessment of the quality of maintenance, a "fuzzy" model and algorithm were developed by the example of the "personnel quality" criterion. Reliability and effectiveness of modeling is tested by a computer experiment based on a simulation approach. The developed mathematical model and simulation algorithm are universal and can be used in various scientific and technical practical applications. The authors proposed a new multi-approach method for quantitative assessment of decision-making risks in a multi-parameter control and management system using differentiated and integral functional indicators of the object under study.