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  • 标题:Individual cylinder air–fuel ratio estimation and control for a large-bore gas fuel engine
  • 本地全文:下载
  • 作者:Tianbo Wang ; Siqin Chang ; Liang Liu
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2019
  • 卷号:15
  • 期号:2
  • 页码:1
  • DOI:10.1177/1550147719833629
  • 出版社:Hindawi Publishing Corporation
  • 摘要:For internal combustion engines with multi-cylinders, the differences of fuel injection, air distribution, and even exhaust gas recirculation between cylinders may result in cylinder-to-cylinder imbalance, and then the exhaust emission and engine performance will be poor. The individual cylinder air–fuel ratio control is one of the important techniques used to improve fuel economy and reduce exhaust emission. For the large-bore gas fuel engine with gas fuel injection devices, their mass flow rates would be affected more seriously by the valve lifts than the injector of gasoline engine. In this study, we propose an individual cylinder air–fuel ratio estimation algorithm, based on Kalman filtering, for a gas fuel engine with asymmetrical exhaust runners. The coefficient matrix update step is added to the iterative process of common Kalman observer. The individual cylinder air–fuel ratios are estimated with one single universal exhaust gas oxygen sensor located on each side exhaust manifold. Furthermore, the estimation and feedback control performances with the proposed estimation algorithm are validated with a one-dimensional engine simulation tool. The results indicate that the modified Kalman observer can estimate the individual cylinder air–fuel ratio of gas fuel engine with asymmetrical exhaust runner precisely, with the maximum error smaller than 1% under steady-state conditions, and compensate the gas fuel injection devices for their mass flow rate differences.
  • 关键词:Individual air–fuel ratio estimation; gas fuel engine; gas fuel injection device; asymmetrical exhaust runner; cylinder-tocylinder imbalance
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