Benefiting from Sobol Sequences Experiment Design Type for Model-based Calibration

Design of Experiments (DOE) introduces a number of design types such as space filling design and optimal design. However, optimal design type is best for a system with high prior knowledge. Meanwhile, space-filling design is good for unknown systems, which is normal for engine calibration. It would be best to have a design that can support constructive model building, where a block of engine test is run for most of the day and followed by engine modeling at the end of the day. However, this needs separate space filling design for each day and separate design is susceptible to redundant test points. Among of the five space-filling design type, Sobol sequences and Halton sequences can support constructive model building due to the deterministic random sequence characteristic. When the model is good enough for system prediction, the remaining engine test can stop and proceed to model optimization. This made is possible because Sobol sequences is a quasi-random sequence, in which test points are scattered in a purely random manner. This behavior supports progressive augmentation of test sequences. Sobol sequences is typically use in statistical engine modeling. This paper discussed the fundamental building block of the Sobol sequences in experimental point of view in which the design benefits calibration engineers.