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The research of traction control for the distributed driven electric vehicle

  • Gang Wang
  • , Xin Lei Liu
  • , Cheng Lin
  • , Ke Song Zhang

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

Abstract

The distributed driven electric vehicles(DDEV) employ multiple motors driven systems which effectively achieves the electronic chassis and the active safety of vehicle. In this paper, a two-stage strategies of traction control system (TCS) for the DDEV were proposed. In the first stage, a method based on the Single-layer feed-forward neural networks system (SFNN) trained by Extreme Learning Machine (ELM) is proposed for the road condition classification. In the second stage, the Active Disturbance Rejection Control (ADRC)was proposed to design the TCS. The simulation testing results show that the two-stage strategies is designed feasibly and response quickly.

Original languageEnglish
Title of host publicationIEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479942398
DOIs
Publication statusPublished - 30 Oct 2014
Event2014 IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Beijing, China
Duration: 31 Aug 20143 Sept 2014

Publication series

NameIEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014 - Conference Proceedings

Conference

Conference2014 IEEE Transportation Electrification Conference and Expo, ITEC Asia-Pacific 2014
Country/TerritoryChina
CityBeijing
Period31/08/143/09/14

Keywords

  • distributed driving
  • electric vehicle
  • road identification
  • traction control system

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