Interior Acoustic Control System Using Boundary Vibration with Giant Magnetostrictive Actuator: Fundamental Consideration on the Control Algorithm

Abstract

Ultra-compact electric vehicles (EVs) have been becoming increasingly popular recently. These vehicles have advanced characteristics such as compactness, light body, and low environmental impact. However, it is serious problem with interior noise which are from outside such as road noise and wind noise. Therefore, we have been studying an active noise control (ANC) system for ultra-compact EV by using the giant magnetostrictive actuator. In this paper, we propose a control system using an adaptive filter by least mean square (LMS) algorithm which is updating a filter coefficient continuously and brings the reduce noise. Furthermore, we studied fundamental considerations on simulation and noise reduction experiments for the development new ANC system using the giant magnetostrictive actuator. We performed noise reduction simulation using LMS algorithm and conducted low frequency noise simulated road noise reduction experiment by wall surface vibration using the giant magnetostrictive actuator. From the result of the simulation, the sound power became to close 0 Pa in the noise control system limitlessly by giving an appropriate step size parameter. Furthermore, in the noise reduction experiment, the sound pressure level of 200 Hz was reduced to 5.8 dB by controlling the noise. Comparing the results with the simulation, it was possible to reduce the noise level at the position of the driver's ears.