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Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data: Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart

Autor Philipp Bergmeir
en Limba Engleză Paperback – 8 dec 2017
Philipp Bergmeir works on the development and enhancement of data mining and machine learning methods with the aim of analysing automatically huge amounts of load spectrum data that are recorded for large hybrid electric vehicle fleets. In particular, he presents new approaches for uncovering and describing stress and usage patterns that are related to failures of selected components of the hybrid power-train.
 
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Specificații

ISBN-13: 9783658203665
ISBN-10: 3658203668
Pagini: 166
Ilustrații: XXXII, 166 p. 34 illus., 11 illus. in color.
Dimensiuni: 148 x 210 mm
Greutate: 0.25 kg
Ediția:1st ed. 2018
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Vieweg
Seria Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart

Locul publicării:Wiesbaden, Germany

Cuprins

Classifying Component Failures of a Vehicle Fleet.- Visualising Different Kinds of Vehicle Stress and Usage.- Identifying Usage and Stress Patterns in a Vehicle Fleet.

Notă biografică

Philipp Bergmeir did a PhD in the doctoral program “Promotionskolleg HYBRID” at the Institute for Internal Combustion Engines and Automotive Engineering, University of Stuttgart, in cooperation with the Esslingen University of Applied Sciences and a well-known vehicle manufacturer. Currently, he is working as a data scientist in the automotive industry.

Textul de pe ultima copertă

Philipp Bergmeir works on the development and enhancement of data mining and machine learning methods with the aim of analysing automatically huge amounts of load spectrum data that are recorded for large hybrid electric vehicle fleets. In particular, he presents new approaches for uncovering and describing stress and usage patterns that are related to failures of selected components of the hybrid power-train.

Contents
  • Classifying Component Failures of a Vehicle Fleet
  • Visualising Different Kinds of Vehicle Stress and Usage
  • Identifying Usage and Stress Patterns in a Vehicle Fleet
Target Groups 
  • Students and scientists in the field of automotive engineering and data science
  • Engineers in the automotive industry
About the Author
Philipp Bergmeir did a PhD in the doctoral program “Promotionskolleg HYBRID” at the Institute for Internal Combustion Engines and Automotive Engineering, University of Stuttgart, in cooperation with the Esslingen University of Applied Sciences and a well-known vehicle manufacturer. Currently, he is working as a data scientist in the automotive industry.


Caracteristici

New Approaches for Identifying Harmful Vehicle Usage Patterns Includes supplementary material: sn.pub/extras