A Microscopic Energy Consumption Prediction Tool for Fully Electric Delivery Vans

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


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 %.
Original languageEnglish
Title of host publication33rd World Electric Vehicle Symposium & Exposition (EVS33) Peer Reviewed Conference Papers
PublisherElectric Vehicle Symposium and Exhibition
Number of pages12
Publication statusPublished - 11 Sep 2020


  • BEV (battery electric vehicle)
  • energy consumption
  • medium-duty
  • van
  • efficiency

Fingerprint Dive into the research topics of 'A Microscopic Energy Consumption Prediction Tool for Fully Electric Delivery Vans'. Together they form a unique fingerprint.

Cite this