Application of Multi-Objective Optimization techniques for improved emissions and fuel economy over transient manoeuvres 2019-01-1177
This paper presents a novel approach to augment existing engine calibrations to deliver improved engine performance during a transient through the application of multi-objective optimization techniques to the calibration of the Variable Valve Timing (VVT) system of a 1.0 litre gasoline engine. Current mature calibration approaches for the VVT system are predominantly based on steady state techniques which fail to consider the engine dynamic behaviour in real world driving, which is heavily transient.
In this study the total integrated fuel consumption and engine out NOx emissions over a 2min segment of the transient Worldwide Light-duty Test Cycle are minimised in a constrained multi-objective optimisation framework to achieve an updated calibration for the VVT control. The cycle segment was identified as an area with high NOx emissions. The optimisation framework was developed around a Mean Value Engine Model with representative engine controls which was validated against an engine tested on a dynamometer. The aim of this study was to demonstrate a practical benefit without having to significantly change the existing engine control strategy. Offline optimization with the MVEM model allows exploitation of workstation computational performance to effectively explore the calibration space, reducing both time and investment in engine testing.
The initial optimization results show a strong dominance of both fuel and NOx objectives with a potential reduction in fuel consumption and engine out NOx emissions of up to 5% and 18% respectively compared to the original steady-state based VCT calibration. Engine experimental results have confirmed that NOx emissions can be significantly reduced without any significant detriment to fuel economy over this 2min transient.
Samuel David Le Corre, Byron Mason, Thomas Steffen, Edward Winward, Zhijia Yang, Thomas Childs, Mark Cary, Robert Lygoe
Loughborough University, Ford Motor Co Ltd