Abstract Compared with traditional finite element analysis and statistical energy analysis, the energy finite element analysis (EFEA) has the advantages of small computations and solving local responses in large-scale complex structures. In this paper, the structural sound insulation effect is introduced to EFEA for predicting and analyzing interior noise responses of extruded structures in a high-speed train. Firstly, the carriage structure and cavity models are established based on EFEA theory, and model parameters are obtained through experiments and effective simulations. Mechanical and acoustic excitation sources of the high-speed train are extracted through multi-body dynamic simulation, acoustic finite element method and nonlinear acoustic solution. The reliability of predicted excitations is validated by verifying the amplitude peak frequency bands. The interior noise responses at several observations are obtained and in good agreement with on-site test results, and the EFEA prediction model of interior noise is verified accurately. Secondly, the energy contribution of exterior excitation sources to interior noise responses is analyzed based on EFEA model. The results indicate that acoustic excitations dominate the acoustic energy in the frequency bands above 800 Hz, and the energy contribution of mechanical excitations and acoustic excitations is relatively close in the frequency bands below 600 Hz. The contribution of aerodynamic noise excitations is predominantly concentrated in the frequency bands below 500 Hz, while that of wheel-rail noise excitations is concentrated in the frequency bands above 800 Hz. In the frequency bands below 1250 Hz, the energy contribution of rail noise excitations is much more important than that of wheel noise excitations, while their contribution gets gradually close in the frequency bands above 1600 Hz. Besides, the acoustic excitations at the bottom of the carriage are quite important sources. Finally, wheel-rail noise excitations are optimized with spoke-shielding damping wheels and dynamic vibration absorbers, and the sound pressure level in the amplitude peak bands is reduced by about 8 dB. The interior noise responses are reduced by about 3–5 dB in the frequency bands above 800 Hz, and total loudness, sharpness and roughness at different locations are decreasing by more than 1 sone, 0.05 acum and 0.03 asper respectively. Therefore, wheel-rail noise optimizations have good reduction effects on interior noise responses in the high frequency bands.