Fentanyl substance abuse and death cases frequently occur worldwide, and the detection and identification of fentanyl substances in the human body are becoming increasingly important. After some time in the human body, some of the fentanyl substances are still discharged with urine, so the history of drug abuse can be reflected by detecting fentanyl substances in the urine. Surface Enhanced Raman Spectroscopy ( SERS ) is fast, sensitive and easy to operate, which is suitable for the field detection and analysis of fentanyl in urine. However, the background peaks of urea and other substances in urine are highly coincident with the SERS characteristic peaks of fentanyl, and the characteristic peaks of fentanyl are covered by the background peaks of urine, which causes great interference with the spectral identification of fentanyl in urine.In this paper, the spectral peak analysis model is established based on the Voigt line, and the spectral peak analysis of the overlapping part of urine and fentanyl is carried out. Because of the interference of SERS spectral noise and fluorescence on the peak analytical model, the unconstrained Nelder-Mead algorithm is used to optimize and calculate the model. The algorithm is insensitive to the initial value of iterative parameters to improve the accuracy of the peak analytical model. According to the characteristics of the half-peak width of the SERS spectrum, the analytical peak set was screened, and the urine background peak of the SERS spectrum was deducted to restore the spectral peak characteristics of the fentanyl SERS spectrum at 1 000 and 1 030 cm-1.The experimental results and phenomena show that the spectral peak analysis model established by the Voigt line shape has a fitting degree of more than 99% for the SERS spectrum of fentanyl in urine and can restore the SERS spectrum characteristics of fentanyl in urine through the screening of the peak solution set. The characteristics of the half-peak width and peak ratio of the reduced spectrum and the characteristic peaks of fentanyl are highly consistent. When the SERS spectrum of blank urine is analyzed, the analytical peak set does not contain the characteristic peaks of fentanyl substances, which can effectively distinguish blank urine from urine containing fentanyl substances. The reduced spectral fragment (935~1 100 cm-1) was identified by the hit quality index (HQI), which can effectively distinguish Ofentanyl, Furanyl and Acetylfentanyl in urine and improve the discrimination between spectra. This analytical model is expected to provide a way to solve practical problems for the identification and judgment of fentanyl in urine.