吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (3): 726-734.doi: 10.13229/j.cnki.jdxbgxb201403024

• Orignal Article • Previous Articles     Next Articles

Joint non-linear model predict control for air-fuel ratio of SI engine

SHI Yi-ran1,TIAN Yan-tao1,ZHANG Li2,SHAN Ze-biao1,WU Hao1   

  1. 1.College of Communication Engineering, Jilin University, Changchun 130012,China;
    2.Zhuhai College of Jilin University, Zhuhai 519041,China
  • Received:2013-12-23 Online:2014-03-01 Published:2014-03-01

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Abstract: A variable sampling period Modified Volterra model is proposed for the Air-Fuel Ratio (AFR) control system in Spark Ignition (SI) engine. On this basis, a joint Nonlinear Model Predictive Control (NMPC) method is developed based on the Radial Basis Function Neural Network (RBFNN) model combining with the modified Volterra model. The advantages of this method are small amount of calculation and high prediction accuracy; also the optimal control sequence can be directly calculated. Thus it significantly improves the AFR control performance of SI engine, and greatly reduces the computing time compared with the conventional iterative optimization algorithm. Real-time simulations based on the mean value engine model are conducted on the dSPASCE simulation platform. Results show that the control performance of the proposed method is significantly better than the RBFNN model or the Modified Volterra model based NMPC method.

Key words: automatic control technology, Volterra model, air-fuel ratio(AFR), RBFNN model

CLC Number: 

  • TP273
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