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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Conclusion
verfasst von : Philipp Bergmeir
Erschienen in: Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data
Verlag: Springer Fachmedien Wiesbaden
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This thesis addressed the problem of analysing a huge amount of a load spectrum data, i.e., a special kind of automotive data that are recorded and computed on-board in modern vehicles such as HEVs. The aim has been manifold, where the main goal has been to determine usage and stress patterns that are related to failures of selected components of the hybrid power-train, like the hybrid car battery. The identified patterns can help the engineers to find out the reasons for component failures and, thus, to improve the dimensioning as well as the reliability of future versions of these vehicle parts.