Methods to Reduce Air-charge Characterization Data for High Degree of Freedom Engines
Current methods of storing critical engine operating parameters often rely on lookup interpolation functions. A drawback to lookup interpolations is that as the number of independent variables increases, the function's dimensions increase from tables to cubes to hypercubes of data. A sparser collection of data may serve if the strict orthogonal structure of lookup functions is not required. Instead of forming a matrix of data for every combination of input variables, a few critical data points are stored with their independent variables. The available data can be used to estimate parameters at new input values (typically from current measurements) by relating the available data by its distance from the new inputs. An inverse distance weighting scheme is used to calculate the output of the function.