The OEM was using traditional approaches to calibrate individual components and full engine models with large numbers of calibration parameters. This process takes a large number of simulation runs and a large amount of engineering time. Despite the effort, this process can result in poor model fit and doesn’t produce model form error information.
SmartUQ ran a proof of concept demonstrating advance statistical and Bayesian calibration techniques for a cylinder combustion model. This also involved the construction of a predictive model and construction of discrepancy maps.
SmartUQ succeeded in generating accurate calibration parameters and discrepancy maps using a fraction of the simulation runs used with prior methods. This reduced the computation time substantially and allowed model form errors to be investigated. The success of this project lead to purchase and ongoing efforts towards full engine model calibration.
