Vehicle Active Road Noise Control With MIMO FxLMS Coupling
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Solution Overview
Problem
Existing active noise control systems for vehicle road noise, particularly those using the FxLMS algorithm, suffer from slow convergence and inaccuracies due to the neglect of channel coupling in multi-channel applications.
Innovation Solution
The proposed method employs a multi-channel normalized FxLMS (MIMO MNFxLMS) algorithm that normalizes the convergence factor and considers channel coupling, enabling faster convergence and improved accuracy in reducing vehicle road noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the traditional FxLMS algorithm is used for active noise control, then the system is simple to implement and computationally efficient, but the convergence speed is slow and accuracy is limited due to neglect of channel coupling
Solution Approach 1:
The patent transforms the scalar convergence factor into a diagonal matrix of convergence factors, where each diagonal element corresponds to a different channel. This parameter change allows independent optimization of convergence for each channel while maintaining computational efficiency, thereby improving noise reduction accuracy without excessively increasing algorithm complexity
Solution Approach 2:
The patent segments the multi-channel system into independent channel components by using a diagonal convergence factor matrix. This segmentation allows the algorithm to handle channel coupling effects through separate per-channel normalization while avoiding the full complexity of completely coupled multi-channel optimization, balancing accuracy and computational load
2Measurement precision
If the multi-channel FxLMS algorithm is used to address channel coupling, then the noise reduction accuracy improves, but the convergence speed becomes slower due to increased computational complexity
Solution Approach 1:
The patent introduces channel-specific convergence factors through diagonal matrix normalization, where each channel can have its own optimized convergence rate. This allows faster convergence for individual channels while maintaining overall system accuracy, resolving the trade-off between convergence speed and noise reduction precision in multi-channel applications
3Ease of manufacture
If passive noise control methods are used, then the structural design is simple and costs are controlled, but the noise reduction effect on low-frequency road noise is poor
Solution Approach 1:
The patent replaces passive mechanical noise control methods with active electronic noise control using the MIMO MNFxLMS algorithm. The system uses microphones to detect road noise and speakers to generate anti-noise signals, substituting mechanical damping and isolation structures with an electronic feedback system that is particularly effective for low-frequency noise cancellation
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The MIMO MNFxLMS algorithm achieves faster convergence and more accurate noise reduction compared to traditional multi-channel FxLMS algorithms, effectively addressing the limitations of existing systems.
Implementation Method 1
The active noise reduction solution utilizes the vehicle-mounted audio system to establish a reverse signal of the noise signal, and form a secondary sound wave to cancel out the noise in a target area
Data Source
AI summary
Disclosed are a method and system for controlling vehicle road noise based on active noise reduction. The method includes: acquiring a multi-channel reference signal of vehicle road noise; generating a control signal based on a coefficient of a filter at a current time and the multi-channel reference signal, and feeding to a sound reproduction device of the vehicle; acquiring acoustical signals at a plurality of sampling positions inside a compartment of the vehicle to obtain a vector of an error signal; filtering the reference signal to obtain a filtered reference signal; writing the filtered reference signal in a matrix form; and updating the coefficient of the filter. The method actively reduces the road noise caused by friction between vehicle tires and road surface, reduces interior noise pollution, and has a relatively fast convergence speed and relatively high accuracy.