A verification approach for the optimization of mild hybrid electric vehicles

Markus DIrnberger, Hans Georg Herzog

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

2 Scopus citations

Abstract

Optimization of systems is a challenging task. During this process adjustments of the model and the optimization algorithm will influence its success. Therefore, this paper introduces an analytical approach to verify the results achieved by an optimization process. This is done by pushing the observed mild hybrid electric vehicle (HEV) into the recuperation mode and the generator mode of the electrical machine. Now physical equations enable a verification approach to calculate the additional CO2 emission due to a variation of the efficiency of the electrical machine used in the power train of the HEV. The efficiency variation of the electrical machine is done on a measured efficiency map by increasing and reducing it by ±10% for the optimization process. The analytical verification approach should be easy to implement and enable to verify the results of the optimization process therefore a mid efficiency of the electrical machine is used. Compared to other approaches only changes of the CO2 emission are considered. This enables to model the internal combustion engine (ICE) in an easy way. Finally, the results of the analytical verification approach are compared to the results achieved by the optimization process.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Electric Machines and Drives Conference, IEMDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1494-1500
Number of pages7
ISBN (Electronic)9781479979417
DOIs
StatePublished - 16 Feb 2016
EventIEEE International Electric Machines and Drives Conference, IEMDC 2015 - Coeur d'Alene, United States
Duration: 11 May 201513 May 2015

Publication series

NameProceedings - 2015 IEEE International Electric Machines and Drives Conference, IEMDC 2015

Conference

ConferenceIEEE International Electric Machines and Drives Conference, IEMDC 2015
Country/TerritoryUnited States
CityCoeur d'Alene
Period11/05/1513/05/15

Keywords

  • CO2 emission
  • claw pole machine
  • drive train optimization
  • efficiency
  • hybrid electric vehicle
  • mild hybrid electric vehicle
  • optimization
  • verification

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