The sound quality of the vehicle interior response and fuel efficiency are two important considerations that influence customer purchase decision. However, these two objectives often have opposing design requirements. The reason is because a more fuel efficient vehicle generally requires lower overall weight. On the other hand, to achieve a quieter vehicle with premium sound quality inside the passenger compartment using traditional passive noise control strategy typically leads to a more massive body structure. In recent years, as a response to the need to further improve vehicle interior sound quality, a number of patents on active noise control (ANC) begin to appear. The proposed patented systems basically use a destructive sound wave form to treat the unwanted noise. This approach is gaining popularity as an alternative way to design a quieter car without the cost of weight penalty. This is made possible with recent rapid development of high performance signal processing software and hardware systems. The existing, patented active noise control systems are most effective for suppressing low frequency noise as compared to the traditional passive control applications. Even though the active vehicle noise control technology is not fully matured yet, the number of investigations and related patents in the open literature has risen over the years. Hence, there is merit to review the existing patents on active control of vehicle systems, and to provide a candid discussion on the direction and trend of this capability in the future.
Active noise control, active noise reduction, active noise suppression, acoustic noise tuning, vehicle noise control, vehicle interior response, fuel efficiency, NVH, filtered-x least mean square, FxLMS, signal processing unit, internal model controller, IMC algorithm, adaptive filter, signal generator, limiting amplifier, abnormal acoustic noise, adaptive notch filters, finite impulse response, secondary path filter, filtered reference signal, sinusoidal waveform generator, Bluebird, virtual microphone arrangement, the remote microphone technique, feedforward difference prediction tech-nique, adaptive LMS virtual microphone technique, Kalman filtering virtual sensing method, stochastically optimal tonal diffuse field virtual sensing technique
Mechanical Engineering, School of Dynamic Systems, 598 Rhodes Hall, P.O. Box 210072, University of Cincinnati, Cincinnati, OH 45221-0072, USA.