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A model for the evaporation of a multi-component fuel droplet is presented that takes account of temperature dependent fuel and vapour properties, evolving droplet internal temperature distribution and composition, and enhancement to heat and mass transfer due to droplet motion. The effect on the internal droplet mixing of non-ideal fluid diffusion is accounted for. Activity coefficients for vapour-liquid equilibrium and diffusion coefficients are determined using the UNIFAC method. Both well-mixed droplet evaporation (assuming infinite liquid mass diffusivity) and liquid diffusion-controlled droplet evaporation (iteratively solving the multi-component diffusion equation) have been considered. Well-mixed droplet evaporation may be applicable with slow evaporation, for example early gasoline direct injection; diffusion-controlled droplet evaporation must be considered when faster evaporation is encountered, for example when injection is later, or when the fuel mixture is non-ideal.

This paper presents the development and implementation of an Analytical Target Cascading (ATC) Multi-disciplinary Design Optimisation (MDO) framework for the steady state engine calibration optimisation problem. The case is made that the ATC offers a convenient framework for the engine calibration optimisation problem based on steady state engine test data collected at specified engine speed / load points, which is naturally structured on 2 hierarchical levels: the ‘Global’ level, associated with performance over a drive cycle, and ‘Local’ level, relating to engine operation at each speed / load point. The case study of a diesel engine was considered to study the application of the ATC framework to a calibration optimisation problem. The paper describes the analysis and mathematical formulation of the diesel engine calibration optimisation as an ATC framework, and its Matlab implementation with gradient based and evolutionary optimisation algorithms.