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In order to improve the interior sound quality of Electric Vehicles (EV), solve the problem of low sense of power and comfort of the interior sound as well as the large electromagnetic excitation order noise of motor and the sharp interior sound, this article designs a dynamic active sound control system for EV under accelerated driving conditions. Firstly, by comparing and analyzing the sound spectrum characteristics of fuel vehicle (FV) and EV during acceleration, a short-time Fourier transform (STFT) is adopted to extract and synthesize the engine sound. Secondly, the influence of the engine order composition and the energy distribution in the frequency domain on the sound quality of the vehicle is analyzed, and an active control system for sound quality is proposed. And the software and hardware development of the active control sound system is completed. Finally, through real-vehicle testing and verification, the sense of comfort and power of the EV interior sound has been greatly improved during acceleration, and the total value of interior sound can meet the requirement. The sound pressure level and loudness of interior sound have been increased, and the sharpness of the sound inside the vehicle has been improved, with a maximum reduction of 1.0acum. [ABSTRACT FROM AUTHOR]

The conflict of filtered-x least mean square (FxLMS) algorithm between convergence speed and steady-state misalignment restricts the performance of the adaptive system. The convex combination approach can successfully avoid this contradiction as it combines two adaptive filters that adopt different step sizes. Firstly, the generalized versoria function is applied as the cost function to develop the filtered-x maximum versoria criterion (FxMVC) algorithm, which has good performance in the face of impulsive noise and performs better than the FxLMS algorithm. Then, inspired by the convex combination approach, C-FxMVC is developed by combining the FxLMS algorithm with the FxMVC algorithm to obtain better behavior, and the FxLMS algorithm is employed in the fast filter. To further optimize the performance of the presented algorithm, we use the method of amplitude-constraint, and the amplitude of e (n) and X (n) are restrained nicely. Numerous simulations are employed to verify the effectiveness and rationality of the presented algorithm, where the impulsive noise required for the simulation environment is consistent with symmetric α -stable (S α S) distribution model. Simulation results demonstrate that the proposed C-FxMVC algorithm can possess better efficacy in terms of convergence speed and noise reduction. [ABSTRACT FROM AUTHOR]