TU/e Microscopic Energy Consumption PRediction tOol 0.1 (TU/e MECPRO 0.1)

Dataset

Omschrijving

The files contained within this dataset describe a simulation tool that predicts the energy consumption of a battery electric vehicle. The tool is written in MATLAB-code and is connected to various API's to make use of up-to-date route information (Overpass OpenStreetMap API), height information (SRTM elevation map), and weather information (OpenWeatherMap API). The prediction method relies on a physics-based interpretation of the energy consumption of the vehicle. Both the velocity profile prediction algorithm and the subsequent energy consumption model are based on data obtained from dedicated vehicle tests. In the supplied version of this tool, the parameters represent the Voltia eVan, which is a fully electric delivery van with a swappable traction battery. The tool was developed within the Dynamics & Control research-group at Eindhoven University of Technology. This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No. 713771 (EVERLASTING).Version: 0.1.2 Date: 2021-06-23Change Log Version 0.1.2------------------------- Changed the inputs to 'readhght' to use the NASA/EarthDATA server, because the original server hosting the SRTM DEM appears to be off-line. This new server requires a NASA/EarthDATA account. If road slope is to be included, 'settings.includeSlope' (l. 76, TUe_MECPRO.m) should be set to 'true' and NASA/EarthDATA account credentials should be entered in 'NASA_Earthdata_Login.txt'.- Corrected an error in velocityProfilePredicion.m where the prescribed maximum vehicle velocity was wrongly considered to be [m/s] instead of [km/h].- Corrected an error in processOSMmap.m that resulted in the incorrect registration of the maximum legislated velocity, in case it is prescribed as 'none' (German Highways). Now, 200km/h is assumed in case the maximum legislated velocity is 'none'.
Datum van beschikbaarheid24 aug. 2021
Uitgever4TU.Centre for Research Data
Datum van data-aanmaak22 dec. 2020 -

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