Acceptance of electric mobility is hampered by an insufficient charging infrastructure as investors refrain from investing into additional charging stations while potential buyers of electric vehicles wait for a more advanced charging infrastructure to be established. The optimal siting and sizing of charging infrastructure is a major issue of electric mobility. In this context, the analysis of charging transaction data is a promising means to identify regions with lacking charging infrastructure as well as to learn about utilization and patterns in the charging behavior. Additionally, charging transaction data yields potential to learn about battery degradation when combined with state-of-health readings. To exploit the full potential of analytical assessment of charging transaction data, the enrichment of the data to integrate background as well as environmental information from various sources, e.g., weather and location data, is discussed. Different perspectives for analytics of charging transactions are motivated and preliminary findings are presented that motivate further research in this area.


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    Title :

    Enrichment and context-based analytics of Electric Vehicle charging transaction data


    Contributors:


    Publication date :

    2016-11-01


    Size :

    384103 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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