抄録
Ultra-compact electric vehicles (EVs) have gained popularity due to their compact size, lightweight design, affordability, and environmental friendliness. However, significant interior noise, mainly from road and wind noise, remains a challenge. To address this, we developed an active noise cancellation (ANC) system using a giant magnetostrictive actuator installed on the roof to generate counteracting sound waves through roof panel vibrations. This study employed a variant of the least mean squares (LMS) algorithm, the Filtered-X LMS algorithm, to achieve real-time noise cancellation by continuously updating the coefficients of the FIR adaptive filter. In addition, the influence of introducing and not introducing a secondary path estimation module in the noise reduction system on the overall noise reduction performance was also studied. Furthermore, this study analyzed the effects of different excitation points on noise reduction performance and proposed using the power spectral density method to examine the sound spectra and power density at various excitation points, aiming to explore the reasons behind how the actuator’s fixed position influences noise reduction performance. Finally, experiments on ANC of simulated road noise were conducted on an ultra-compact EV, and the results verified the effectiveness of incorporating secondary path characteristics and selecting an appropriate excitation point in enhancing active noise cancellation performance.
