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 generally rely on hot gas bench-measured maps to characterize their performance. Such discrete map data is inherently too sparse to be used directly in simulation, and so a pre-processing algorithm interpolates and extrapolates the data to generate a wider and 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 for the fact that they often operate on input map data in SAE standard format. Indeed, for decades it has been common practice for turbocharger suppliers to share performance data with their engine OEM customers in this form. This paper describes a compressor map interpolation technique that has a basis in the nondimensional compressor flow and loading coefficients, instead of SAE-format data. It compares the difference in compressor operating point prediction accuracy seen when using this method against the standard approach based on dimensional parameters. This is done by removing a speed line from an existing dataset, interpolating for the removed speed using the two methods, and then comparing their accuracy to the original data. It is found that using speed lines cast in the nondimensional coefficients improves interpolation accuracy over a method employing data in physical or reduced formats; in some cases, the sum of squares of residuals between interpolated data points and the original data demonstrated an order of magnitude improvement when using the loading coefficient. This work shows how the employment 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.