| CCLPM | This project is closed |
| Customer Correlated Life Prediction Models for Improved Design Verification of Automotive Components |
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Context Predictions of the lifetime of automotive components and systems are currently made as a result of accelerated testing under extreme conditions in which it is difficult to estimate the acceleration factor. Also the predictions bear no relation to actual conditions in service. Aims To develop a generic framework for constructing the life prediction model for a variety of automotive components and systems To establish a methodology for analysis and modelling of degradation processes in correlation with the analysis of the customer usage profiles To develop life prediction models for two selected powertrain systems and to validate the models using instrumented engine dynamometer tests To validate the methodology used to develop analytical prediction models Method Condition parameters will be used to monitor the degradation process, and explanatory variable will be employed to quantify the influence of factors that have an effect on the life of the system. Degradation mechanisms will be analysed using qualitative and quantitative methods to identify the relevant condition parameters and the explanatory variable and their effects The customer usage profiles will be established from road load data. This will be analysed to obtain typical values, trends and patterns of variation for the explanatory variables which are specific to the usage profile, types of journey, loads, driving style and environmental conditions. The project will investigate analytical models suitable for modelling the degradation process and the life of the system, correlated with the patterns of variation of the usage profiles Life tests and experiments will be carried out to calibrate and validate the models and the methodology. Benefits The industrial partner will have a validated method for developing life prediction models which are correlated with the customer usage. First tier suppliers will be able to verify in-house the quality of their designs under field conditions. Longer term, the results could be used in other sectors eg medical engineering. Participants Jaguar Cars Ltd Bradford University |
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