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Weather Data Mapping to Enrich Naturalistic Driving Data and Enhance Energetic Simulation
F2018/F2018-STN-053

Authors

Jens-Olav Jerratsch
Technische Universität Berlin, Chair of Naturalistic Driving Observation, Berlin, Germany

Thomas Herzlieb, Stefanie Marker

Abstract

For advanced simulation of electric vehicle total energy consumption, various parameters need consideration. For simulation of real driving patterns, secondary data mapping by time and location can help to reduce measurement efforts and enrich existing data or enable advanced prediction of energetic consumption. The methodology presented for ambient temperature mapping yields a mean difference of only 1.5°C when compared to sensor acquired onboard data. Using TUB-FVB’s total vehicle energy simulation for a small commercial electric vehicle then leads to a mean deviation in consumption of only 0.2 kWh/h or 2.5%, respectively.

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