Diagnostics of Automobile Mechatron Systems by Integrated Environmental Indicators

Author Name(s): F. Suleimanov, D. A. Kharlyamov*, G. V. Mavrin, A. A. Goncharov, P. A. Goncharov, A. N. Melnikov
Author Email: kharlyamov@gmail.ru

Abstract

The current level of motorization makes high demands on the reliability of vehicles, to the provision of technical and economic properties and to reduce the technogenic impact, primarily – the emissions of harmful substances into the environment. The world automobile industry is currently developing in the direction of electronic engine management system use to improve the quality of vehicle operation, fuel efficiency and environmental safety.

The analysis of automotive internal combustion engine performance equipped with electronic control systems showed that at the first stages the design improvement led to functional and parametric failure increase, as well as to their qualitative change. In this regard, the need appeared to develop new methods and tools for diagnosis. Thus, the problem of new methods creation and the development of existing methods to diagnose electronic engine control systems is topical.

The research was carried out using the elements of system analysis and decision theory, mathematical modeling, probability theory and mathematical statistics, the theory of expert evaluations, image recognition and experimental research.

The paper demonstrated the results of the mathematical model development for the interrelation of the technical state of element parameters concerning automotive mechatronic systems with the output parameters of automobile engines, diagnostic algorithms, and the experimentally obtained parameters of diagnostic areas.

The obtained results are diagnostic algorithms, diagnostic parameter values and their interpretation which allow to reduce the time spent on the troubleshooting of automotive mechatronic systems during car maintenance and repair.

The developed theoretical positions, the results of experimental research and practical recommendations are intended for the use in motor transport and service enterprises during the servicing and the repair of mechatronic automotive systems.

Introduction

The purpose of the performed study is to increase the efficiency of vehicle mechatronic system operation on the basis of diagnostic methodology improvement according to a comprehensive environmental indicator, which consists in the obtaining of diagnostic information in real time using telematics.

It is known that telematics tools are widely used to monitor the rolling stock on a route and to ensure its transport security [1-6]. At the same time, there is a wide range of practical tasks to be solved using the same tools related to the rapid assessment of the technical condition of vehicles and the transfer of this information to the responsible technical services.

During the research, the technique for the diagnosing automobile engine mechatronic systems was developed, characterized by the use of normalized environmental indicator remote monitoring interconnected with the parameters of an electronic engine management system technical state.

They studied the relationship between the concentration of exhaust gas components (CO and O2) in front of the catalytic converter of exhaust gases with the faults of electronic system elements for an engine control. At the theoretical stage of the study the mathematical model was developed that includes the expressions describing the relationship between environmental diagnostic parameters and the technical condition parameters of mechatronic system elements, as well as the system of limitations for characteristic diagnostic areas based on the provisions of an image recognition theory.

The result of the studies is the establishment of model parameters and the characteristics of diagnostic areas using the example of electronic control systems for LADA vehicles, they determined the possibilities of telematics complex use installed on new vehicles for operational monitoring of mechatronic system state and environmental indicators.

Conclusions

The use of the developed technique for mechatronic system diagnosing using telematic means allows to identify an operatively faulty subsystem and to establish a specific malfunction according to the developed algorithm based on standard diagnostic procedures.

The developed mathematical model establishes the relationship between the concentration of CO and O2 in the exhaust gases of automobile engines with the parameters of mechatronic system element technical state, characterized by the change of excess air coefficient, which makes it possible to assess their technical condition objectively and reasonably.

The developed diagnostic technique allows to evaluate the mechatronic system element technical state based on the assignment of diagnostic parameters (combination of CO, O2 and qst) to the reference diagnostic areas corresponding to specific faults of mechatronic system elements.

Summary

As a result of the pilot study, the analytical relationship was established between the concentration of CO and O2 in the exhaust gases with an excess air factor, on the basis of which the parameters of the reference diagnostic areas were established. The correct state corresponds to the region with the center qst = 1.6 ± 0.1, mg/ms, CO = 0.7 ± 0.2%; the faults in the fuel system are represented by the values ​​qst = 1.45 ± 0.05 mg/ms, CO = 2 ± 1%; the faults of the ignition system correspond to the values ​​qst = 1.4 ± 0.05 mg/ms, CO = 4 ± 1%; the deviations in the work of the mass air flow sensor are represented by the values ​​of qst = 1.8 ± 0.1 mg/ms, CO = 1.5 ± 0.5%; the malfunctions of the mass air flow sensor are represented by the values ​​of qst = 1.95 ± 0.06 mg/ms, CO = 3 ± 1%.

The diagnostic technique developed as the result of the theoretical and experimental studies made it possible to build a general technology to diagnose engines, which reduces labor intensity by 10% and improves the accuracy and the reliability of the diagnosis.

Acknowledgements

The work is performed according to the Russian Government Program of Competitive Growth of Kazan Federal University.

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