Model predictive combustion control implementation using parallel computation on an FPGA

Fussey, Peter and Limebeer, David (2016) Model predictive combustion control implementation using parallel computation on an FPGA. SAE International Journal of Engines, 9 (2). pp. 1163-1169. ISSN 19463936

Full text not available from this repository.

Abstract

The introduction of transient test cycles and the focus on real world driving emissions has increased the importance of ensuring the NOₓ and soot emissions are controlled during transient manoeuvres. At the same time, there is a drive to reduce the number of calibration variables used by engine control strategies to reduce development effort and costs. In this paper, a control orientated combustion model, [1], and model predictive control strategy, [2], that were developed in simulation and reported in earlier papers, are applied to a Diesel engine and demonstrated in a test vehicle. The paper describes how the control approach developed in simulation was implemented in embedded hardware, using an FPGA to accelerate the emissions calculations. The development of the predictive controller includes the application of a simplified optimisation algorithm to enable a real-time calculation in the test vehicle. The test vehicle was calibrated over a constant speed step manoeuvre and then demonstrated over the standard US06 drive cycle, where it was found to reduce NOₓ and CO₂ emissions. The paper concludes with a discussion on the merits of an emissions based engine control strategy, where the controller seeks to control emissions directly rather than an indirect quantity such as boost pressure.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ0212 Control engineering systems. Automatic machinery (General)
T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL0001 Motor vehicles.Cycles
Related URLs:
Depositing User: Peter Fussey
Date Deposited: 14 May 2018 09:41
Last Modified: 14 May 2018 09:41
URI: http://sro.sussex.ac.uk/id/eprint/75688
📧 Request an update