Adaptive multi-objective optimization for personal sound zones in vehicles considering passenger-induced scattering

Personal sound zone (PSZ) systems aim to create distinct acoustic zones within a vehicle to enhance the listening experience for passengers. However, existing PSZ systems often rely on a fixed acoustic transfer function (ATF), which cannot account for the dynamic nature of passenger movement, leading to reduced performance. Optimizing key metrics such as acoustic contrast (AC), signal distortion (SD), and array effort (AE) simultaneously in such systems is difficult, often involving trade-offs. The adaptive genetic weighting with scattering adjustment algorithm (AGW–SA) is proposed to overcome these limitations. This method adapts to dynamic passenger movement and incorporates real-time scattering effect estimation through a small number of microphones positioned outside the sound field. Simulation and experimental results show that the AGW–SA method significantly improves sound field zone partitioning, achieving better optimization of AC, SD, and AE compared to traditional methods. The method also demonstrates robust performance across various scenarios.