F2010C026
Analytical Life Prediction Modeling for Diesel Fuel Filters Optimization
The statistical distribution model of field reliability of systems or components is the key to synthetically optimize parts and maintenance policy. This paper is presenting the application of Weibull distribution model to develop analytical life prediction models for diesel fuel filters for modern common rail vehicles based on field filters expertise. More than 100 used diesel fuel filters have been analyze and their performances correlated to vehicles characteristics as fuel consumption, mileage, fuel quality... This first investigation has permitted to determine the real vehicle clogging evolution of our diesel fuel filters and to determine main factors impacting the clogging mechanisms. In a second step, using Weibull distribution model, a numerical model have been developed to predict filter life on vehicle. This paper is also showing that clogging mechanisms are completely different between laboratory ISO test methods and real vehicles and so proposing a new methodology to design diesel fuel filters according to vehicles characteristics and filter change interval targets. A case study on a diesel fuel filter developed for the new Renault-Nissan V6 Diesel Engine V9X is used to illustrate this methodology and to show how it permitted to decrease filter volume and weight with complete guaranty of filter change interval requirement. By the use of predictive reliability methodology apply to automotive diesel filter clogging, life prediction is now possible for the first time and specific change interval recommendations according to local fuel qualities can be done
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