A coordinated torque control strategy for PHEV based on Cloud Computing

Likang Fan, Youtong Zhang*

*Corresponding author for this work

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

Abstract

The performance of plug-in hybrid electric vehicles (PHEV) depends on the energy management strategy (EMS). An optimal EMS guarantees the maximum use of the energy through the electric power grid, coordinates the power output of the main power sources, and exploits the comprehensive advantages of both engine and motor. However, the current EMS can not guarantee the real-time processing of the optimal allocation problem. With the rapid development of communication network technology and Internet of vehicles technology, it provides a new idea to solve the above problems, namely cloud computing. EMS based on cloud computing is divided into online cloud and offline cloud. The off-line cloud uses dynamic programming to pre distribute torque according to the expected driving conditions, while the online cloud modifies the vehicle torque based on real-time vehicle speed and road information. The simulation is carried out under the Beijing speed condition. The simulation results show that this method can make most of the working points of the engine and motor run in the high efficiency range, which verifies the effectiveness of this method.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages363-366
Number of pages4
ISBN (Electronic)9781728191461
DOIs
Publication statusPublished - Oct 2020
Event2020 International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2020 - Beijing, China
Duration: 23 Oct 202025 Oct 2020

Publication series

NameProceedings - 2020 International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2020

Conference

Conference2020 International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2020
Country/TerritoryChina
CityBeijing
Period23/10/2025/10/20

Keywords

  • PHEV
  • cloud computing
  • dynamic programming
  • torque distribution

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