DocumentCode :
2904546
Title :
Model Predictive Controller design for throttle and wastegate control of a turbocharged engine
Author :
Santillo, Mario ; Karnik, Aditya
Author_Institution :
Ford Res. & Adv. Eng., Dearborn, MI, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
2183
Lastpage :
2188
Abstract :
In this paper, we consider the problem of turbocharged gasoline engine air-path control. Specifically, we apply linear Model Predictive Control (MPC) to coordinate throttle and turbocharger wastegate actuation for engine airflow and boost pressure control. Simplification of the prediction model used for the MPC reduces the memory requirement for implementation. We neglect the effects of variable cam timing in the prediction model, and instead, these effects are considered through a robustness analysis of the MPC to system variability. We compare two methods to achieve offset-free reference tracking, namely, the use of an integrator with actuator-saturation-based anti-windup logic, and the use of a Kalman filter to estimate plant-model mismatches. Evaluation of these methods for a vehicle acceleration scenario demonstrates advantages with using the Kalman-filter-based approach in the presence of system variability.
Keywords :
Kalman filters; automotive components; control system synthesis; fuel systems; internal combustion engines; predictive control; pressure control; stability; Kalman filter; MPC robustness analysis; actuator-saturation-based anti-windup logic; automotive companies; boost pressure control; engine airflow; integrator; linear model predictive control; model predictive controller design; offset-free reference tracking; plant-model mismatch estimation; system variability; throttle actuation; throttle control; turbocharged gasoline engine air-path control; turbocharger wastegate actuation; vehicle acceleration scenario; wastegate control; Actuators; Atmospheric modeling; Engines; Mathematical model; Predictive models; Turbines; Valves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580159
Filename :
6580159
Link To Document :
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