Remote Microphone ANC Group Delay Reduction
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Solution Overview
Problem
Active Noise Cancellation (ANC) systems, particularly those using remote microphone techniques, face challenges in adapting quickly to dynamic driving scenarios such as fast gear shifts and pavement transitions due to group delays caused by finite impulse response filters, which hinder effective noise cancellation performance.
Innovation Solution
The implementation of a system that includes a controller to bypass or modify the PathPR filter during fast-adapting events, such as changing engine orders or pavement transitions, by switching to a predetermined filter like an identity matrix, thereby reducing group delay and enhancing noise cancellation performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a finite impulse response filter (PathPR filter) is used in remote microphone ANC systems, then noise cancellation accuracy is improved, but group delay increases which slows adaptation rate
Solution Approach 1:
The system dynamically switches between two filter configurations based on driving conditions: during steady-state operation, the full PathPR filter is used for accurate noise cancellation, while during fast-adapting events (detected via accelerator pedal position rate of change), the filter is bypassed or reduced to minimize delay and enable faster adaptation to changing noise conditions
Solution Approach 2:
The system changes the filter parameters (order and complexity) based on the detected driving event state. The filter order is reduced or the filter is bypassed during fast-adapting events, and restored to full complexity during steady-state operation, thereby optimizing the balance between accuracy and adaptation speed
2Productivity
If the PathPR filter is bypassed during fast-adapting events, then adaptation speed is improved, but noise cancellation accuracy may be reduced
Solution Approach 1:
The system periodically evaluates the driving conditions (monitoring accelerator pedal position and rate of change) and adjusts filter configuration accordingly. During transient fast-adapting events, the filter is bypassed to enable rapid adaptation, then restored after the event concludes, ensuring both fast response when needed and accurate cancellation during steady-state operation
3Reliability
If the system continuously adapts to all changes, then noise cancellation performance is maintained, but system complexity and processing load increase
Solution Approach 1:
The adaptation process is segmented into different modes based on detected events: during fast-adapting events, the system uses a simplified adaptation path with reduced filter complexity, while during steady-state operation, the full adaptation path is active. This segmentation allows the system to maintain performance across different conditions without continuously operating at full complexity
Data Source
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AI summary
In at least one embodiment, an active noise cancellation (ANC) system is provided. The ANC system includes at least one microphone, a first filter, a first controllable filter, and at least one controller. The at least one microphone provides an error signal indicative of noise and an anti-noise sound within the cabin. The first filter modifies a transfer function between the at least one microphone and at least one remote microphone location to generate an estimated remote microphone error signal based at least on the error signal. The first controllable filter generates the anti-noise signal based on the estimated remote microphone error signal. The controller receives receive a first signal indicative of the vehicle exhibiting a fast-adapting event controls the first filter to execute a predetermined filter based on the first signal to reduce a group delay associated with the first filter.