汽车行驶车内噪声优化控制算法研究

Research on Optimal Control Algorithm for Vehicle Driving Interior Noise

研究汽车行驶车内噪声主动控制技术,可有效降低以低频噪声为主的汽车车内噪声,其难点在于如何改进汽车行驶车内噪声主动控制算法。针对经典的汽车行驶车内噪声主动控制算法——LMS算法无法同时兼顾算法收敛速度和稳态误差的固有缺陷,通过建立步长因子μ(n)与误差信号e(n)之间的非线性函数关系,提出一种多项式函数的变步长LMS算法。通过将采用LMS算法和变步长LMS算法的汽车车内噪声主动控制结果进行对比,结果表明,利用多项式函数的变步长LMS算法解决了LMS算法的固有缺陷,具有更快的算法收敛速度和较小的稳态误差,可优化控制汽车行驶车内噪声。

Active noise control technology is an effective method in reducing the vehicle driving interior noise which is usually low-frequency noise based. The difficulty in using the active noise control technology is how to improve the active noise control algorithm for vehicle driving interior noise. Aiming at the inherent defect of classical active noise control algorithm for vehicle driving interior noise LMS algorithm, i.e. , consideration cannot be given to both algorithm convergence speed and steady state error, the non-linear function relationship between step factor μ（n） and error signal e （n） is constructed to establish the polynomial function based variable-step LMS algorithm. Comparison of active noise control results which are obtained by using the LMS algorithm and variable-step LMS algorithm shows that the polynomial function based variable-step LMS algorithm overcomes the inherent defect of LMS algorithm and has a faster convergence rate and a smaller steady state error.