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Hsing, P. Bertrand
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An Engineering Method for Part-load Engine Simulation

General Motors Corporation-P. Bertrand Hsing, Jia-Shiun Chen, H.Y. Isaac Du
Published 2007-10-29 by SAE International in United States
This work provides an effective engineering method of building a part-load engine simulation model from a wide-open throttle (WOT) engine model and available dynamometer data. It shows how to perform part-load engine simulation using optimizer for targeted manifold absolute air pressure (MAP) on a basic matrix of engine speed and MAP. Key combustion parameters were estimated to cover the entire part-load region based on affordable assumptions and limitations. Engine rubbing friction and pumping friction were combined to compare against the motoring torque. The emission data from GM dynamometer laboratory were used to compare against engine simulation results after attaching the RLT sensor to record emission data in the engine simulation model.
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Formulation of Robustness in a CAE Design Model

Epcom Corp.-Xu Han
General Motors-P. Bertrand Hsing
Published 2005-04-11 by SAE International in United States
As the computer efficiency and capability increase, so as the Computer Aided Engineering (CAE) technologies improve. Recently Robust Design or Reliability Based Design Optimization (RBDO) technologies have been utilized in all sorts of industries including automotive. The process generally involves identifying key input design variables and key performance output variables, determining a sampling plan for CAE simulations, building a response surface model (RSM), analyzing the results, and finding the optimized design that meets the reliability criteria. Yet little was addressed on the robustness of a CAE design model in the process. A systematic method of defining Robustness in a CAE design model was developed. How robust a CAE model is and how far away an optimized design is from the More Robust Region (MRR) are addressed in this paper. This method provides a clear measure of determining if a robust design within the performance variance is achievable in this CAE model and the size and location of the MRR in the design space. Numerical examples are used to illustrate the methodology.
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