Engine Order Cancellation Pre-Seeding for Fast Gear Shift Noise Control
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Solution Overview
Problem
Existing Engine Order Cancellation (EOC) systems in vehicles take time to adapt to large changes in engine RPM during gear shifts, leading to delayed noise cancellation performance.
Innovation Solution
A pre-characterization method is employed to store the magnitude and phase of adaptive filters in a lookup table, allowing for 'pre-seeding' of these values during and after gear shifts, using an absolute phase reference from the 'missing tooth' of the analog RPM crank signal, thereby enabling faster convergence of the EOC system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous adaptation of adaptive filters is used in EOC systems, then noise cancellation performance is optimized under normal conditions, but adaptation time increases during gear shifts causing delayed noise cancellation
Solution Approach 1:
The system performs preliminary characterization of the vehicle's acoustic environment across different RPM ranges and stores optimal filter coefficients in lookup tables before gear shifts occur. During gear shifts, the system quickly retrieves pre-computed coefficients corresponding to the new RPM range, eliminating the need for time-consuming real-time adaptation and enabling immediate noise cancellation performance.
Solution Approach 2:
The continuous RPM range is divided into multiple discrete segments or bins, each with pre-characterized acoustic transmission paths and optimal filter coefficients. This segmentation allows the system to quickly identify which segment the current RPM falls into and retrieve the corresponding pre-computed coefficients, rather than continuously adapting through the entire RPM range during gear transitions.
2Adaptability or versatility
If real-time adaptive filtering is implemented, then noise cancellation adapts to changing engine conditions, but computational complexity and processing time increase during rapid RPM changes
Solution Approach 1:
The system performs comprehensive real-time adaptive filtering and acoustic characterization during normal operation to build and update lookup tables of optimal filter coefficients for different RPM segments. This preliminary computational work is stored for quick retrieval during gear shifts, reducing the computational burden during rapid RPM changes while maintaining adaptability to engine conditions.
Solution Approach 2:
Instead of performing complex real-time adaptive filtering during gear shifts, the system copies pre-computed filter coefficients from the lookup tables that were generated during normal operation. This copying approach maintains the adaptability benefits of real-time filtering during steady-state operation while dramatically reducing computational complexity during transient gear shift events.
Data Source
AI summary
In at least one embodiment, an active noise cancellation (ANC) system is provided. The ANC system includes at least one loudspeaker, at least one microphone and at least one controller. The at least one loudspeaker projects anti-noise sound within a cabin of a vehicle based at least on an anti-noise signal. The at least one microphone provides an error signal indicative of noise and the anti-noise sound within the cabin. The at least one controller is programmed to receive the error signal and a reference signal indicative of a gear shift that occurs over a predetermined time interval and to adapt at least one adaptive filter with pre-stored filter coefficients for the predetermined time interval to generate the anti-noise signal based at least on the error signal and the reference signal.