Abstract
Keywords - Automatic transmission, Electronic control, Diagnosis, OBD (On Board Diagnostics), Model based strategy
Powertrain diagnosis technology has been developed for On Board Diagnostics (OBD) legal requirements and for failure identification of electronic controllers. The diagnosis technology can be sophisticated as there are requirements for compliance with stringent OBD regulations for early repair work for failure recovery or for real time deterioration compensation. Deterioration of performance, such as piece-to-piece variation of products or aging must be detected and identified to satisfy requirements. One of the promising methodologies has long been to compare detected values with model behaviours.
Calculation time was a major constraint ten years ago. Model structure and sensor properties are likewise constraints even today. Model based diagnosis technology has been studied in the literature listed in references. However, conventional diagnosis methods can not be replaced such model based methods in series productions. So, we propose to apply such methodology combined with conventional methodology. The proposed system consists of two layers. Conventional physical constraint based diagnosis is placed on the base layer. Model based diagnosis and specific symptom finding diagnosis are build on the second layer. The diagnosis system was applied to a passenger car gearbox system.
Our conventional diagnosis method is based on physical constraints and common knowledge of the plant. Diagnosis rules are described in a tabular form and algorithm is described with symbolic coding tool. A dynamic gearbox plant model was introduced for the model based diagnosis method. The residual method was selected for the model based diagnosis. It is not obvious if the plant is failure when single sensor output is compared with equivalent model output. So, structural redundancy is constructed in Failure Detection and Identification (FDI) part of the diagnosis system. Observer based outputs are introduced to obtain redundancy.
Dynamic modelling of deteriorated or damaged parts such as cracks is challenging. Symptom finding in observed data may sometimes lead to better result. We applied Wavelet Transform to measured acceleration signals from a gearbox as a symptom finding.
Proposed strategy was implemented into a dynamic model for time domain simulation. Response and resolution of the FDI system were discussed and evaluated. A simulation study illustrate the proposed diagnosis process and shows effectiveness of the method.