Korrekturansätze für Fahrzeugsensordaten  zur realen Erfassung des Straßenwetters

Rietdorf, Meike; Kratzsch, Thomas; Nachtigall, Jens; Stiller, Christoph

doi:10.1007/s35148-021-0735-x

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Idw Using Local Climate Zones1

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2023

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“…The positive mean value for both methods shows a clear trend towards underestimation of the ambient temperature measured by the vehicle's sensor. A tendency of vehicle sensors to measure higher temperature values when compared to stationary measurements was also found in investigations of other authors, 15,16 a probable explanation for this is the influence of vehicle waste heat on the measurement. Since the investigated vehicle is electric driven, the influence is less strong in this case.…”

Section: Idw Using Local Climate Zonessupporting

confidence: 69%

Kriging and local climate zones – key to higher accuracy in range prediction?

Herzlieb

Sturm

2023

Composites and Advanced Materials

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Range prediction of electric vehicles requires knowledge of many parameters, including information about the vehicle environment. As an alternative to onboard measurement, external data sources (secondary data) can be used. The presented methods are suitable for estimating climatic data for vehicle application including urban areas and areas of complex topography. Compared to an inverse distance weighting approach for ambient temperature values, Kriging yields better overall accuracy especially for areas of complex topography, improving accuracy in urban regions, however, remains a challenge. An approach to improve accuracy in urban areas by considering local climate zones in the selection of secondary data sources produces mixed results.

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Section: Idw Using Local Climate Zonessupporting

confidence: 69%