Road load simulation algorithms evaluation using a motor-in-the-loop test bench

Qiang Song, Wenbin Liu, Wanbang Zhao, Yiting Li, Mukhtiar Ahmad, Lukai Zhao

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

3 Citations (Scopus)

Abstract

resent research evaluates three typical road load algorithms, like PI algorithm (PIA), feed forward algorithm (FFA) and inverse model algorithm (IMA), for electric powertrain testing. Models of vehicle, driver and test bench are established in MATLAB/Simulink environment, which has structural consistency with real motor-in-the-loop test bench. A novel vehicle state observation is used to reflect the effect of road loading and inertia emulation. To evaluate road load simulation, each algorithm is validated in off-line simulation and HIL testing. The results show FFA and IMA have advantageous in speed control precision, torque responds and state point tracking.

Original languageEnglish
Title of host publicationITEC Asia-Pacific 2019 - 2019 IEEE Transportation Electrification Conference and Expo, Asia-Pacific
Subtitle of host publicationNew Paradigm Shift, Sustainable E-Mobility
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728121246
DOIs
Publication statusPublished - May 2019
Event2019 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2019 - Jeju, Korea, Republic of
Duration: 8 May 201910 May 2019

Publication series

NameITEC Asia-Pacific 2019 - 2019 IEEE Transportation Electrification Conference and Expo, Asia-Pacific: New Paradigm Shift, Sustainable E-Mobility

Conference

Conference2019 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2019
Country/TerritoryKorea, Republic of
CityJeju
Period8/05/1910/05/19

Keywords

  • Electric powertrain
  • Hardware-in-the-loop
  • Road simulation algorithm
  • State observation

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