This paper presents the development of an Analytical Target Cascading (ATC) Multidisciplinary Design Optimization (MDO) framework for a steady-state engine calibration optimization problem. The implementation novelty of this research is the use of the ATC framework to formulate the complex multi-objective engine calibration problem, delivering a considerable enhancement compared to the conventional 2-stage calibration optimization approach [1]. A case study of a steady-state calibration optimization of a Gasoline Direct Injection (GDI) engine was used for the calibration problem analysis as ATC. The case study results provided useful insight on the efficiency of the ATC approach in delivering superior calibration solutions, in terms of “global” system level objectives (e.g. improved fuel economy and reduced particulate emissions), while meeting “local” subsystem level requirements (such as combustion stability and exhaust gas temperature constraints). The ATC structure facilitated the articulation of engineering preference for smooth calibration maps via the ATC linking variables, with the potential to deliver important time saving for the overall calibration development process.

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