posted on 2019-03-26, 15:55authored byWen Gu, Dezong Zhao, Byron Mason
With the increasing complexity of engines and number of control parameters, optimal engine parameter sets need to be searched in the high dimensionality. Traditional calibration methods are too complicated, expensive and timeconsuming. The model-based optimisation is of critical importance for engine fuel efficiency improvement and exhaust emissions reduction. The optimisation highly depends on the model accuracy. In this paper, a multi-layer modelling method is proposed, which can be used to generate the engine model at arbitrary operating points in real time with high accuracy. An enhanced heuristic-algorithm-based optimiser is combined with the real-time modelling method to perform a parallel optimisation. The proposed modelling and optimisation strategy
can achieve the minimal fuel consumption fast and accurately. This strategy has been successfully verified using experimental data sets.
Funding
The work was cofunded by the Digital Engineering and Test Centre (DETC), under a grant for the virtually connected hybrid vehicle. DETC is a unique joint industry-academic centre, also as an Advanced Propulsion Centre spoke. It develops and uses virtual engineering tools and techniques to accelerate the development, test and manufacture of automotive propulsion systems. This work was also supported by the Engineering and Physical Sciences Research Council of U.K. under the EPSRC-UKRI Innovation Fellowship scheme (EP/S001956/1)
History
School
Aeronautical, Automotive, Chemical and Materials Engineering
Department
Aeronautical and Automotive Engineering
Published in
American Control Conference
Pages
5544 - 5549
Citation
GU, W., ZHAO, D. and MASON, B., 2019. Real-time modelling and parallel optimisation of a gasoline direct injection engine. Presented at the American Control Conference (ACC), Philadelphia, PA, USA, 10-12 July 2019.
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.