A robust error sensing strategy for global active noise control in car cabins.

Abstract

Global active noise control (ANC) systems reduce noise over the entire car cabin with robust performance even as the human head moves; however, they have not been implemented in real-world applications. A robust error sensing strategy is proposed in this paper that is based on which a feasible global ANC system is realized in an electric car, and real-time ANC experiments demonstrate its effectiveness. Simulations based on measured road noise show that using evenly distributed error sensors is a robust error sensing strategy for different car speeds and the upper limit frequency of 3 dB global control is inversely proportional to the equivalent distance between error sensors. Real-time experiments with a 5-seat A-class sedan demonstrate that an average noise reduction of 3.8 dB was achieved between 50 and 250 Hz with 12 evenly distributed error sensors using the four standard car audio loudspeakers as secondary sources. Virtual sensing techniques can be integrated to constitute a more practical system without obstructing the movement of human heads. The findings in this study establish a benchmark for global noise control in car cabins and can be a starting point for future optimization of the system and implementation of adaptive algorithms.