Adaptive Noise Control With Dynamic Leakage Factors

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Solution Overview

Problem

Active noise control systems in vehicles face challenges with stability and processor load due to varying secondary path transmission functions, especially in dynamic environments, which affect the overall performance and convergence speed of adaptive filtering.

Innovation Solution

The method involves determining time-dependent control parameters such as vehicle speed, tire pressure, and audio levels to dynamically adjust adaptation step sizes and leakage factors for updating filter coefficients in adaptive filtering, improving stability and convergence speed by using frequency-dependent adaptation step sizes and leakage matrices.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If adaptive filtering is used to reduce noise in vehicle compartments, then noise suppression performance is improved, but system stability deteriorates due to varying secondary path transmission functions

Engineering Contradiction:
Improvenoise levelsVSAvoidsystem stability
Core Design Contradiction:
Object-affected harmful factorsVSReliability

Solution Approach 1:

The patent applies dynamics by making the adaptation step size variable rather than constant. The step size adapts based on the correlation between reference and error signals, allowing the system to respond dynamically to changing secondary path transmission functions while maintaining stability. This resolves the contradiction by enabling noise suppression performance improvement without sacrificing system stability.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent implements feedback mechanisms where the error signal from the noise control system is used to adjust the adaptation step size. This feedback loop allows the system to monitor its own performance and adjust parameters accordingly, maintaining stability while improving noise suppression. The step size is increased when correlation is high (good noise cancellation) and decreased when correlation is low (potential instability), creating a self-regulating system.

Inventive Principle:
Principle #23Feedback

2Object-affected harmful factors

If adaptive filtering with frequent updates is used to track varying noise conditions, then noise suppression performance is improved, but processor load increases

Engineering Contradiction:
Improvenoise suppression performanceVSAvoidprocessor load
Core Design Contradiction:
Object-affected harmful factorsVSUse of energy by moving object

Solution Approach 1:

The patent applies partial action by selectively updating filter coefficients only when necessary. Instead of continuously updating at maximum rate, the system adjusts the adaptation step size based on actual need (correlation between signals). This reduces unnecessary computational operations while maintaining effective noise suppression, thereby lowering processor load without sacrificing performance.

Inventive Principle:
Principle #16Partial or excessive action

Solution Approach 2:

The patent changes the parameter of adaptation step size dynamically based on system conditions. By modifying this parameter rather than maintaining a fixed high update rate, the system achieves effective noise suppression only when needed, reducing overall computational burden and processor load while maintaining performance where required.

Inventive Principle:
Principle #35Parameter changes

3Device complexity

If constant adaptation step size is used for simplicity, then device complexity is reduced, but convergence speed deteriorates under varying vehicle conditions

Engineering Contradiction:
Improvefiltering algorithm complexityVSAvoidconvergence speed
Core Design Contradiction:
Device complexityVSSpeed

Solution Approach 1:

The patent transitions from a static (constant step size) to a dynamic (variable step size) approach. The step size becomes a function of the correlation between reference and error signals, allowing the system to converge quickly when conditions are favorable and maintain stability when conditions change. This dynamic adaptation improves convergence speed under varying vehicle conditions without significantly increasing overall system complexity.

Inventive Principle:
Principle #15Dynamics

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

This approach enhances the stability and speed of adaptive filtering in active noise control systems, effectively reducing noise levels in vehicle compartments by dynamically adjusting filter coefficients based on real-time vehicle conditions, leading to improved in-vehicle communication and entertainment quality.

Implementation Method 1

The compensation signal has amplitude and frequency components that are equal to those of the noise signal; however, it is phase shifted by 180°. As a result, the compensation sound signal destructively interferes with the noise signal, thereby eliminating or damping the noise signal at least at certain positions within the listening environment.

Methodology Applied
Scientific EffectDestructive interference: Interference

Data Source

PatentEP3182407B1Active noise control by adaptive noise filtering
Publication Date: 2020.03.11 HARMAN BECKER AUTOMOTIVE SYST GMBH
  • EP3182407B1 patent drawingFigure 1
  • EP3182407B1 patent drawingFigure 2
  • EP3182407B1 patent drawingFigure 3

AI summary

The present invention relates to a method of noise reduction, comprising the steps of filtering reference signals, representing noise by an adaptive filtering means comprising adaptive filter coefficients to obtain actuator driving signals, outputting the actuator driving signals by loudspeakers to obtain loudspeaker signals, detecting the loudspeaker signals by microphones, filtering the reference signals by estimated transfer functions representing the transfer of the loudspeaker signals output by the loudspeakers to the microphones to obtain filtered reference signals and updating the filter coefficients of the adaptive filtering means based on the filtered reference signals and previously updated filter coefficients of the adaptive filtering means multiplied by leakage factors.