Intelligent air/fuel ratio control strategy with a PI-like fuzzy knowledge–based controller for gasoline direct injection engines

Ziyang Li, Ji Li, Quan Zhou, Yunfan Zhang, Hongming Xu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

This paper proposes a new concept of PI-like fuzzy knowledge–based controller with self-tuning capability, high robustness and rapid development capability to regulate air/fuel ratio for gasoline direct injection engines. The proportional and integral terms of the PI-like fuzzy knowledge–based controller are nonlinear functions of the input signals and self-tuned in real time at operation points, which can reduce the effort spent on calibrating controller parameters. The PI-like fuzzy knowledge–based controller is implemented on a production gasoline direct injection engine and evaluated through case studies. The experimental results show that the proposed controller can regulate air/fuel ratio at stoichiometric value with less settling time and less oscillation compared with the conventional Proportional-Integral (PI) controller for transient operation.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalProceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
DOIs
Publication statusPublished - 5 Jun 2018

Keywords

  • air/fuel ratio
  • fuzzy control
  • Gasoline direct injection engine
  • nonlinear control
  • self-tuning control

ASJC Scopus subject areas

  • Aerospace Engineering
  • Mechanical Engineering

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