Title: Experimental-based dynamic calibration of the diesel air-path

Authors: Kamil Ostrowski; A. Thomas Shenton; Ben Neaves

Addresses: Powertrain Control Group, Centre for Engineering Dynamics and Control, University of Liverpool, Liverpool L69 3GH, UK ' Powertrain Control Group, Centre for Engineering Dynamics and Control, University of Liverpool, Liverpool L69 3GH, UK ' Powertrain Controls Research, Jaguar Land Rover, Whitley, Coventry CV3 4LF, UK

Abstract: An experimental study is presented of a novel dynamic calibration methodology applied to the air-path of a Jaguar Land Rover turbocharged diesel engine. The calibration is obtained in a one-shot process solely from data obtained from dynamic dynamometer testing, without any in-vehicle tuning. Although limited here to control of only boost pressure and exhaust gas recirculation rate with constraints on NOx and particle emissions, the methodology has the potential for a complete engine calibration including emission constrained optimisation of fuel consumption. The approach combines state space neural network (SSNN) modelling and optimisation to determine a feedforward Hammerstein-Wiener control map from the synthesised optimal control behaviour. The controller performance was verified by vehicle testing at the Jaguar Land Rover Test Track, Gaydon, UK. The outcome demonstrates a method for systematically obtaining dynamic control calibrations for good driveability and reduced emissions from limited dynamometer testing time without the need for manual tuning.

Keywords: air-path; calibration; control; diesel; dynamics; neural-network; state-space; system-identification.

DOI: 10.1504/IJPT.2017.085682

International Journal of Powertrains, 2017 Vol.6 No.2, pp.169 - 183

Received: 31 Oct 2014
Accepted: 30 Sep 2015
Published online: 07 Aug 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article