In-cylinder Pressure Pegging Algorithm Based on Cyclic Polytropic Coefficient Learning

• Zhang Yahui

  Sophia University

• Shen Tielong

  Sophia University

抄録

This paper presents an in-cylinder pressure pegging algorithm based on cyclic polytropic coefficient learning for combustion engines. In order to take the cycle-to-cycle variation of the polytropic coefficient into account in the incylinder measurement, an iterative learning algorithm is proposed to provide cyclic estimation of the polytropic coefficient and then with the estimation cyclic compensation method is proposed for the offset of in-cylinder pressure measurement. A comparative study of the proposed algorithm, the least-squares method (LSM) with a fixed polypropic coefficient and the nonlinear least-squares method (NLSM) with a variable polytropic coefficient is conducted using the simulated pressure data. Experimental validations are conducted on a six-cylinder gasoline engine at a motored condition and a steady fired operation condition.

収録刊行物

• International Journal of Automotive Engineering

  International Journal of Automotive Engineering 8 (2), 79-86, 2017

  公益社団法人 自動車技術会

キーワード

• electronics and control
• engine control
• measurement/diagnosis/evaluation
• pressure pegging

詳細情報

• CRID: 1390001205416763008
• NII論文ID: 130006907715
• DOI: 10.20485/jsaeijae.8.2_79
• ISSN: 21850992
• ISSN: 21850984
• Web Site: https://www.jstage.jst.go.jp/article/jsaeijae/8/2/8_20174097/_pdf
• 本文言語コード: en
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