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Source identification applied to a truck engine and using inverse numerical acoustics is presented. The approach is based on acoustic transfer vectors (ATV) and truncated singular value decomposition (SVD). Acoustic transfer vectors are arrays of transfer functions between surface normal velocity and acoustic pressure at response points. They can be computed using boundary element methods (indirect, direct or multi-domain direct formulations) or finite element methods (in physical or modal coordinates). Regularization techniques such as the so-called L-curve approach are used to identify the optimum SVD truncation. To increase the reliability of the source identification, the approach can use velocity measurements on the boundary surface as well as the standard nearfield pressure measurements. It also allows for linear or spline interpolation of the acoustic transfer vectors in the frequency domain, to increase computational speed.