Adaptive calibration of Diesel engine injection for minimising fuel consumption with constrained N O x emissions in actual driving missions

Abstract

This article proposes a method for fuel minimisation of a Diesel engine with constrained $\mathrm{N}{\mathrm{O}}_{\mathrm{x}}$ emission in actual driving mission. Specifically, the methodology involves three developments: The first is a driving cycle prediction tool which is based on the space-variant transition probability matrix obtained from an actual vehicle speed dataset. Then, a vehicle and an engine model is developed to predict the engine performance depending on the calibration for the estimated driving cycle. Finally, a controller is proposed which adapts the start-of-injection calibration map to fulfil the $\mathrm{N}{\mathrm{O}}_{\mathrm{x}}$ emission constraint while minimising the fuel consumption. The calibration is adapted during a predefined time window based on the predicted engine performance on the estimated cycle and the difference between the actual and the constraint on engine $\mathrm{N}{\mathrm{O}}_{\mathrm{x}}$ emissions. The method assessment was done experimentally in the engine test set-up. The engine performace using the method is compared with the state-of-the-art static calibration method for different $\mathrm{N}{\mathrm{O}}_{\mathrm{x}}$ emission limits on real driving cycles. The online implementation of the method shows that the fuel consumption can be reduced by 3%–4% while staying within the emission limits, indicating that the estimation method is able to capture the main driving cycle characterstics.