Internal combustion engines are routinely developed using 1D engine simulation tools. A well-known limitation is the accuracy of the turbocharger compressor and turbine sub-models, which rely on hot gas bench-measured maps to characterize performance. Such discrete map data is inherently too sparse to be used directly in simulation, and so a preprocessing algorithm interpolates and extrapolates the data to generate a wider, more densely populated map. Methods used for compressor map interpolation vary. They may be mathematical or physical in nature, but there is no unified approach, except that they typically operate on input map data in SAE format. For decades it has been common practice for turbocharger suppliers to share performance data with engine OEMs in this form. This paper describes a compressor map interpolation technique based on the nondimensional compressor flow and loading coefficients, instead of SAE-format data. It compares the difference in compressor operating point prediction accuracy when using this method against the standard approach employing dimensional parameters. This is done by removing a speed line from a dataset, interpolating for the removed speed using the two methods, and comparing their accuracy to the original data. Three maps corresponding to compressor diameters of 54, 88, and 108 mm were evaluated. In some cases, the residual sum of squares between the interpolated and original data demonstrated an order of magnitude improvement when using the nondimensional coefficients. When evaluated in a simple engine model, this manifests as a slight shift in interpolated turbocharger speed, resulting in a difference in predicted compressor efficiency of up to 0.89 percentage points. This paper shows how the use of truly nondimensional interpolation techniques can improve the accuracy of processed turbocharger compressor maps, and consequently the value of 1D engine simulations as a reliable performance development tool, at virtually no additional effort or cost.