Premium
Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation
Author(s) -
LiaoMcPherson Dominic,
Huang Mike,
Kim Shinhoon,
Shimada Masanori,
Butts Ken,
Kolmanovsky Ilya
Publication year - 2020
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5188
Subject(s) - exhaust gas recirculation , model predictive control , control theory (sociology) , diesel engine , controller (irrigation) , engineering , robustness (evolution) , throttle , automotive engineering , feed forward , dynamometer , internal combustion engine , computer science , control engineering , control (management) , agronomy , biochemistry , chemistry , artificial intelligence , gene , biology
Summary This article presents the development and experimental validation of an emissions oriented model predictive controller for a diesel engine. The control objective is to minimize cumulative NOx and hydrocarbon emissions while limiting visible smoke production and without compromising fuel economy or torque response. This is accomplished by using a supervisory model predictive controller (SMPC) and nonlinear model predictive controller (NMPC) in tandem. The SMPC controller coordinates the exhaust gas recirculation (EGR) rate target and fuel supplied to the engine in real time to satisfy combustion quality constraints, while the NMPC controller tracks the EGR rate target by manipulating the EGR throttle, EGR valve, and variable geometry turbine. The NMPC controller uses MPC for feedforward and feedback in a novel configuration to simultaneously achieve fast tracking performance, disturbance rejection, and robustness. We demonstrate that the proposed diesel engine MPC controller is able to reduce cumulative emissions by 10% to 15% relative to a state of the art benchmark strategy when placed in closed loop with an engine on a transient dynamometer.