Realization And Experimental Research Of Vehicle Active Noise Control System Based On DSP

With the development of economy and society,people have higher and higher requirements for the comfort of the car,and the low-frequency noise in the car is one of the important factors affecting the ride comfort.The traditional noise reduction methods are mainly for sound insulation and sound absorption for high-and medium-frequency noise,but they are not effective for low-frequency noise.Active noise reduction technology has become a compelling solution thanks to its good control of low-frequency noise.However,when the technology is applied in a vehicle,there are still problems such as slow convergence,poor stability,and poor control of low-bandwidth noise.This has also become one of the problems that restricts the development of active noise reduction technologies.In order to improve the performance of active noise attenuation technology in car interior noise,this paper mainly focuses on the performance and implementation of control algorithms.According to the acoustic wave linear equation and superposition principle,the single-channel feedforward active noise reduction system is taken as the research object,and its main composition and working principle are analyzed.In order to solve the problem of acoustic feedback,the non-acoustic signal is used as the reference signal in this paper.The vibration acceleration signal of the engine,vehicle roof,and cockpit pedals is used as the input signal.The driver's right ear is the predicted output signal and trained by BP neural network algorithm.In-car noise prediction model.In the control algorithm,three kinds of common algorithms,FXLMS algorithm,variable step size LMS algorithm and convex combination algorithm,are analyzed and deduced in terms of stability and convergence,and in order to improve the convergence of the algorithm.Sex and stability,that is,to improve the variable step size LMS algorithm and convex combination algorithm,proposed a new variable step size LMS algorithm based on fractional functions(abbreviated as VXLMS algorithm)and based on sigmoid function fast convex combination of the minimum mean square algorithm(abbreviated SCLMS algorithm)new algorithm.After theoretical analysis,the new algorithm reduces the amount of computation.At the same time,in the MATLAB software,the BP neural network program and the new algorithm program are combined to form a simulation system.The simulation analysis shows that the system speeds up the convergence and improves the system robustness.The last is to build the experimental platform and the required hardware design.The digital processing chip used in the system is TMS320F28335.In order to reduce the computational control algorithm,the VXLMS algorithm is used.The DSP chip combines the AIC23 audio chip,ADC digital conversion unit,I2 C bus,and multi-channel cache.The serial port and other peripherals complete the signal acquisition and processing transmission function of the active noise elimination system.Write the control algorithm to the DSP through CCS5.5,and then connect the audio equipment,sensors,sensor bracket and signal conditioning circuit to finally complete the construction of the active noise elimination system..The experimental analysis of the active noise reduction system effectively reduces the engine noise.