A stochastic logical system approach to model and optimal control of cyclic variation of residual gas fraction in combustion engines. (25th January 2016)

• Record Type: Journal Article
• Authors: Wu, Yuhu; Kumar, Madan; Shen, Tielong
• Is Part Of: Applied thermal engineering. Volume 93(2016:Jan.)
• Page Start: 251
• Page End: 259
• Publication Date: 2016-01-25
• Subjects: Combustion engine -- Residual gas fraction -- Performance -- Optimal control -- Stochastic logical dynamics -- Variable valve timing; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2015.09.045
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: An in-cylinder pressure based measuring method for the RGF is derived. A stochastic logical dynamical model is proposed to represent the transient behavior of the RGF. The receding horizon controller is designed to reduce the variance of the RGF. The effectiveness of the proposed model and control approach is validated by the experimental evidence. Abstract: In four stroke internal combustion engines, residual gas from the previous cycle is an important factor influencing the combustion quality of the current cycle, and the residual gas fraction (RGF) is a popular index to monitor the influence of residual gas. This paper investigates the cycle-to-cycle transient behavior of the RGF in the view of systems theory and proposes a multi-valued logic-based control strategy for attenuation of RGF fluctuation. First, an in-cylinder pressure sensor-based method for measuring the RGF is provided by following the physics of the in-cylinder transient state of four-stroke internal combustion engines. Then, the stochastic property of the RGF is examined based on statistical data obtained by conducting experiments on a full-scale gasoline engine test bench. Based on the observation of the examination, a stochastic logical transient model is proposed to represent the cycle-to-cycle transient behavior of the RGF, and with the model an optimal feedback control law, which targets on rejection of the RGF fluctuation, is derived in the framework of stochastic logical system theory. Finally, experimental results are demonstrated to show the effectiveness of the proposed model and the control strategy.