Selection Families of Optimal Engine Designs Using Nonlinear Programming and Parametric Sensitivity Analysis

A controls optimization methodology for advanced diesel engines, as they are utilized in a specific driving cycle, is addressed in this work. The technique illustrated here accounts for realistic engine use regimes encountered during the FTP driving schedule and finds the maximum foreseeable fuel economy improvement, with the introduction of advanced technologies, to a baseline engine design. Outputs from the optimization procedure are analyzed from a numerical standpoint, yielding insights into the general topology of the engine’s design domain. Control variable histories through the specified driving cycle are determined and discussed with specific regard to the thermodynamic mechanisms producing the associated fuel economy improvements. Guidelines for the practical design of engine components, along with the assumptions made for these studies, are detailed. These techniques are directly applicable to other types of automotive internal combustion engines, vehicles, and driving patterns.

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Selection Families of Optimal Engine Designs Using Nonlinear Programming and Parametric Sensitivity Analysis

Cited by 5 publications

References 13 publications

Performance assessment of a multi-objective parametric optimization algorithm with application to a multi-physical engineering system

Performance assessment of a multi-objective parametric optimization algorithm with application to a multi-physical engineering system

Surrogate-assisted constraint-handling technique for parametric multi-objective optimization

Optimization of Advanced Engine Controls for Conventional Vehicles: A Driving Cycle Perspective

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