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  • 标题:Virtual Engine In-Cylinder Pressure Sensor for Automobiles and Agricultural Tractors
  • 本地全文:下载
  • 作者:Runzhe Han ; Christian Bohn ; Georg Bauer
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:1
  • 页码:543-548
  • DOI:10.1016/j.ifacol.2020.06.091
  • 语种:English
  • 出版社:Elsevier
  • 摘要:The cylinder pressure signal is a very useful indicator for advanced high-performance internal-combustion engines equipped in modern automobiles and agricultural tractors. In this paper, a previous framework for the cylinder pressure estimation is conducted based on a transfer path model (between the cylinder pressure signal and the vibration signal) identified in frequency domain. The main idea behind the previous framework is based on the Kalman filter (of which the input is the engine structure vibration) for the augmented model formed by augmenting the cylinder pressure signal model with delay blocks and the transfer path model identified in time domain. Two combustion metrics, pressure peak Pmax and peak location Ploc, are used for evaluating the estimation framework under the transfer path identified in frequency domain. The estimation results are compared with both experimental data collected from a four-cylinder diesel engine and previous work results, and illustrate the effectiveness of the newly identified transfer path.
  • 关键词:Kalman filters;system identification;internal combustion engines
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