A Microscopic Energy Consumption Prediction Tool for Fully Electric Delivery Vans

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

For cost-optimal utilization of battery electric delivery vans, energy consumption prediction is important. This paper presents a microscopic energy consumption tool, which requires the intended route as input. Both the velocity profile prediction algorithm and the subsequent energy consumption model are based on data obtained from dedicated vehicle tests. Secondly, up-to-date environmental data on the weather, the road slope profile, and local speed legislation are obtained through API’s via the internet. The results show good correspondence with the measured energy consumption. Validation with several measured trips shows that the energy consumption is predicted with an error that rarely exceeds 10 %.
Originele taal-2Engels
Titel33rd World Electric Vehicle Symposium & Exposition (EVS33) Peer Reviewed Conference Papers
UitgeverijElectric Vehicle Symposium and Exhibition
Aantal pagina's12
DOI's
StatusGepubliceerd - 11 sep. 2020
Evenement33rd International Electric Vehicle Symposium and Exposition (EVS33) - Portland, Verenigde Staten van Amerika
Duur: 14 jun. 202017 jun. 2020
Congresnummer: 33
https://evs33portland.org/

Congres

Congres33rd International Electric Vehicle Symposium and Exposition (EVS33)
Verkorte titelEVS33
Land/RegioVerenigde Staten van Amerika
StadPortland
Periode14/06/2017/06/20
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