Databased Architecture Modeling for Battery Electric Vehicles

Lorenzo Nicoletti, Werner Schmid, Markus Lienkamp

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

5 Scopus citations

Abstract

In recent years, the number of electric vehicles on the market has continuously increased. New regulations and the progressively critical effects of global warming contribute to the acceleration of this trend. Car manufacturers are obliged to redesign their fleet, gradually substituting the internal combustion vehicles with electrified vehicles. This is a complicated task, as electric powertrains still represent a new technology and no established vehicle architectures exist. To aid engineers in identifying feasible architectures in the early development phase, package tools can be employed. As in this phase, few parameters are known, such tools have to be based on empirical models. The data upon which empirical models are based must be updated cyclically. With each update, the models have to be manually recalculated, which is a time-consuming process. Therefore, this paper will propose new modeling that will enable the empirical models to update automatically. Firstly, the authors will describe the elements that make up an electric vehicle architecture. Subsequently, a database concept that enables the required data to be stored will be presented. Finally, this paper will describe the tool implementation.

Original languageEnglish
Title of host publication2020 15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728156415
DOIs
StatePublished - 10 Sep 2020
Event15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020 - Monte-Carlo, Monaco
Duration: 10 Sep 202012 Sep 2020

Publication series

Name2020 15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020

Conference

Conference15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020
Country/TerritoryMonaco
CityMonte-Carlo
Period10/09/2012/09/20

Keywords

  • database
  • electric vehicles
  • empirical modeling
  • vehicle architecture

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