Interior Acoustic Control System Using Boundary Vibration with Giant Magnetostrictive Actuator: Improving Noise Reduction Through Actuator Placement and Secondary Path Construction
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.
Authors
- Taro Kato (ORCID: https://orcid.org/0000-0003-4083-3659)
- Kentaro Sawada (ORCID: https://orcid.org/0000-0001-7952-2765)
- Ayato ENDO (ORCID: https://orcid.org/0000-0001-6454-2245)
- Hideaki KATO (ORCID: https://orcid.org/0000-0002-3546-8936)
- Yudai Tanaka (ORCID: https://orcid.org/0000-0002-4142-7268)
- Ikkei Kobayashi
- Koichi Ikeda (ORCID: https://orcid.org/0009-0002-6562-7472)
- Daigo Uchino
- Kazuki Ogawa (ORCID: https://orcid.org/0009-0007-1229-4906)
- Takayoshi NARITA (ORCID: https://orcid.org/0000-0001-7150-6672)
- Jumpei Kuroda
- W. Wu
Institutions
- Fukuoka Institute of Technology (JP)
- Hokkaido University of Science (JP)
- Tokai University (JP)
- Tokyo University of Technology (JP)
- National Institute of Technology, Numazu College (JP)
- Aichi University of Technology (JP)
Publication Details
- Journal
- Journal of Advanced Computational Intelligence and Intelligent Informatics
- Published
- 2025-09-19
- DOI
- https://doi.org/10.20965/jaciii.2025.p1117
- Primary Topic
- Advanced Adaptive Filtering Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00