A Fault Diagnosis of Engine Starting System Via Starter Motors Using Fuzzy Logic Algorithm
Uncertainties in the system models, the presence of noise and the stochastic behavior of several variables reduce the reliability and robustness of the fault diagnosis methods. For overcoming these kinds of problems, this study proposes the fault diagnosis of starter motors based on fuzzy logic methodology. A starter motor is a serial wound dc motor which is used for running the Internal Combustion Engine (ICE). If a fault occurs with the starter motor, the ICE cannot be run. Especially in emergency vehicles (such as ambulance, fire engine, etc), starter motor faults causes any other faults. In this study, a fuzzy logic based fault detection system has been developed for implementation on emergency vehicles. Information of the current and the voltage of a starter motor is acquired and then practiced on a fuzzy logic fault diagnosis system (FLFDS). For this purpose, a graphical user interface (GUI) software is developed by using Visual Basic 6.0 programming language. FLFDS is effective in detection of six types of starter motor faults. The proposed system can be used in a Quality Control unit of manufacturers and maintenance-repairing units.
Key words: Engine starting system; Starter motor faults; Fault diagnosis, Fuzzy logic.