Title: Stochastic model-based regulation problem of residual gas mass in gasoline engines

Authors: Jun Yang; Xiaohong Jiao; Jian Wang; Fengyan Yi

Addresses: Department of Automotive Engineering, Shandong Jiaotong University, Jinan, Shandong, China ' Department of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei, China ' Department of Automotive Engineering, Shandong Jiaotong University, Jinan, Shandong, China ' Department of Automotive Engineering, Shandong Jiaotong University, Jinan, Shandong, China

Abstract: The regulation problem of the residual gas mass (RGM) is investigated in this paper based on the stochastic control theory. By the physics, the dynamic model of the RGM is developed in which the residual gas fraction (RGF) as a crucial system parameter is modelled as a stochastic process with Markov property. The regulator is given by utilising control design technology for the discrete-time jump system. The performance of the closed-loop system with the proposed controller, which is presented by the numerical simulation, shows that the RGM can be regulated to different levels according to the requirement of the internal exhaust gas recirculated (EGR) and has narrower dispersion under the same level compared with the open-loop controller. Compared with the PI controller, the proposed feedback controller has faster response in the transient working conditions.

Keywords: residual gas mass; RGM; stochastic regulation; residual gas fraction; RGF.

DOI: 10.1504/IJMIC.2017.085298

International Journal of Modelling, Identification and Control, 2017 Vol.28 No.1, pp.70 - 77

Available online: 03 Jul 2017 *

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