Data-driven monitoring and validation of experiments on automotive engine test beds |
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| Affiliation: | 1. Institute of Automation, University of Rostock, Richard-Wagner-Str. 31, 18119 Rostock, Germany;2. Institute of Automatic Control and Complex Systems, University of Duisburg Essen, Duisburg, Germany;3. IAV Automotive Engineering, Gifhorn, Germany;1. Institute of Sound and Vibration Research, University of Southampton, Southampton SO17 1BJ, UK;2. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK;1. University of Bayreuth, Mathematical Institute, Germany;2. Ruhr-University Bochum, Institute of Automation and Computer Control, Germany;1. Federal Technological University of Paraná, Av. Alberto Carazai, 86300-000 Cornélio Procópio, PR, Brazil;2. Department of Automation and Systems - Federal University of Santa Catarina, 88040-900 Florianópolis, SC, Brazil;1. Universidade Federal de Santa Catarina, Departamento de Automação e Sistemas, 88040-900 Florianópolis, SC, Brazil;2. Dpto. de Informática, Universidad de Almería - CIESOL, Campus de Excelencia Internacional Agroalimentario, ceiA3. Crta. Sacramento s/n, 04120 La Cañada, Spain;1. University “Politehnica” of Bucharest, Faculty of Aerospace Engineering, Str. Polizu, No. 1, 011063, Bucharest, Romania;2. Control Department, IMI Advanced Systems Div., P.O.B. 1044/77, Ramat Hasharon, 47100, Israel |
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| Abstract: | Engine test beds are widely used to estimate automotive engine parameters and design controllers in the preliminary development phase. The controller parameters are optimized to fulfill emission, fuel consumption and driving comfort requirements and they will be further validated on chassis dynamometer and road driving experiments. It is common that the results of two experiments deviate, due to some external disturbances or faults. The main purpose of this paper is to demonstrate the application of data-driven fault diagnosis techniques to detect the deviations in the experiments and analyze their root-causes to reduce the costs and time of the engine design and its control concept. To this end, two different methods are introduced for detection of the problems in the experiment. Based on the results of the detection step, a fault isolation technique has been proposed to support test engineers in finding the cause of the deviations. The results have been demonstrated on an industrial engine test bed and the effectiveness of the methods is discussed. |
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| Keywords: | Data-driven Fault detection Fault isolation Engine test bed Multimode systems |
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