Gaussian process regression feedforward controller for diesel engine airpath

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Aran, Volkan and Ünel, Mustafa (2018) Gaussian process regression feedforward controller for diesel engine airpath. International Journal of Automotive Technology, 19 (4). pp. 635-642. ISSN 1229-9138 (Print) 1976-3832 (Online)

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Abstract

Gaussian Process Regression (GPR) provides emerging modeling opportunities for diesel engine control. Recent serial production hardwares increase online calculation capabilities of the engine control units. This paper presents a GPR modeling for feedforward part of the diesel engine airpath controller. A variable geotmetry turbine (VGT) and an exhaust gas recirculation (EGR) valve outer loop controllers are developed. The GPR feedforward models are trained with a series of mapping data with physically related inputs instead of speed and torque utilized in conventional control schemes. A physical model-free and calibratable controller structure is proposed for hardware flexibility. Furthermore, a discrete time sliding mode controller (SMC) is utilized as a feedback controller. Feedforward modeling and the subsequent airpath controller (SMC+GPR) are implemented on the physical diesel engine model and the performance of the proposed controller is compared with a conventional PID controller with table based feedforward.
Item Type: Article
Uncontrolled Keywords: Gaussian process regression; Feedforward control; Discrete time sliding mode control; Airpath control
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL1-484 Motor vehicles. Cycles
T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics
Faculty of Engineering and Natural Sciences
Depositing User: Mustafa Ünel
Date Deposited: 16 Aug 2018 16:14
Last Modified: 26 Apr 2022 09:58
URI: https://research.sabanciuniv.edu/id/eprint/35801

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