# US 12,217,733 B2 · Road noise cancellation shaping filters

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- Number: US 12,217,733 B2
- Document ID: US12217733B2
- Status: Granted
- Kind: B2
- Application number: 17/592,861
- Filed: 2022-02-04
- Published: 2023-08-10
- Granted: 2025-02-04
- Earliest claimed: 2022-02-04
- Assignees: Harman International Industries, Incorporated
- Applicants: Harman International Industries, Incorporated
- Inventors: Tao Feng; Kevin J. Bastyr
- Web page: https://patentgrep.com/patent/US12217733B2

## CPC

- G10K 11/17823: {Reference signals, e.g. ambient acoustic environment}
- G10K 11/17854: {the filter being an adaptive filter}
- G10K 11/17817: {between the output signals and the error signals, i.e. secondary path}
- G10K 11/17825: {Error signals}
- G10K 11/17837: {by retaining part of the ambient acoustic environment, e.g. speech or alarm signals that the user needs to hear}
- G10K 11/17881: {the reference signal being an acoustic signal, e.g. recorded with a microphone}
- G10K 2210/12821: Rolling noise; Wind and body noise
- G10K: SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR

## Abstract

A road noise cancellation (RNC) system is provided with at least one loudspeaker to project anti-noise sound within a passenger cabin of a vehicle in response to an anti-noise signal; and a controller. The controller is programmed to: determine a coherence value between a noise signal indicative of road induced noise and an error signal indicative of noise and the anti-noise sound within the passenger cabin; estimate a noise reduction value based on the coherence value; filter the noise signal and the error signal based on the estimated noise reduction value; and generate the anti-noise signal based on the filtered noise signal and the filtered error signal.

## Claims

### Claim 1

A road noise cancellation (RNC) system comprising:
at least one loudspeaker to project anti-noise sound within a passenger cabin of a vehicle in response to an anti-noise signal; and
a controller programmed to:
determine a noise signal indicative of road induced noise using an output signal measured by a force gauge;
determine a coherence value between the noise signal and an error signal indicative of noise and the anti-noise sound within the passenger cabin;
estimate a noise reduction value based on the coherence value;
filter the noise signal and the error signal based on the estimated noise reduction value; and
generate the anti-noise signal based on the filtered noise signal and the filtered error signal.

### Claim 2 (depends on 1)

The RNC system of claim 1, wherein the controller is further programmed to:
determine shaping filter parameters based on the estimated noise reduction value using a non-linear least square solver; and
filter the noise signal and the error signal using the shaping filter parameters,
wherein the noise reduction value is frequency-dependent.

### Claim 3 (depends on 2)

The RNC system of claim 2, wherein the controller is further programmed to:
initialize an objective function with a target value based on the estimated noise reduction value; and
determine the shaping filter parameters based on the objective function using the non-linear least square solver.

### Claim 4 (depends on 1)

The RNC system of claim 1, wherein the controller is further programmed to:
smooth the filtered noise signal and the filtered error signal using artificial intelligence; and
generate the anti-noise signal based on the smoothed and filtered noise signal and the smoothed and filtered error signal.

### Claim 5 (depends on 1)

The RNC system of claim 1, wherein the controller is further programmed to:
select at least one peak filter based on the estimated noise reduction value; and
filter the noise signal and the error signal using the at least one peak filter.

### Claim 6 (depends on 1)

The RNC system of claim 1, wherein the controller is further programmed to filter the noise signal and the error signal based on the estimated noise reduction value over a frequency range.

### Claim 7 (depends on 1)

The RNC system of claim 1 further comprising at least one microphone for measuring the noise and the anti-noise sound within the passenger cabin and providing the error signal.

### Claim 8 (depends on 1)

The RNC system of claim 1 further comprising a vibration sensor for providing the noise signal indicative of the road induced noise within the passenger cabin.

### Claim 9 (depends on 1)

The RNC system of claim 1, wherein the controller further comprises:
an adaptive filter controller to determine the coherence value and to estimate the noise reduction value; and
a controllable filter to generate the anti-noise signal.

### Claim 10

A method for automatically adjusting a road noise cancellation (RNC) shaping filter comprising:
projecting anti-noise sound within a passenger cabin of a vehicle in response to an anti-noise signal;
receiving a noise signal indicative of road induced noise within the passenger cabin, wherein the noise signal is determined using vibration data measured via a vibration sensor including a linear variable differential transformer;
receiving an error signal indicative of noise and the anti-noise sound within the passenger cabin;
determining a coherence value between the noise signal and the error signal;
estimating a noise reduction value based on the coherence value;
filtering the noise signal and the error signal based on the estimated noise reduction value; and
generating the anti-noise signal based on the filtered noise signal and the filtered error signal.

### Claim 11 (depends on 10)

The method of claim 10 further comprising:
initializing an objective function with a target value based on the estimated noise reduction value;
determining shaping filter parameters based on the objective function using a non-linear least square solver; and
filtering the noise signal and the error signal using the shaping filter parameters.

### Claim 12 (depends on 10)

The method of claim 10 further comprising:
smoothing the filtered noise signal and the filtered error signal using artificial intelligence; and
generating the anti-noise signal based on the smoothed and filtered noise signal and the smoothed and filtered error signal.

### Claim 13 (depends on 10)

The method of claim 10 further comprising:
selecting at least one peak filter based on the estimated noise reduction value; and
filtering the noise signal and the error signal using the at least one peak filter.

### Claim 14

A road noise cancellation (RNC) system comprising:
at least one loudspeaker to project anti-noise sound within a passenger cabin of a vehicle in response to an anti-noise signal;
at least one microphone to provide an error signal indicative of the noise and the anti-noise sound within the passenger cabin; and
a controller programmed to:
determine a noise signal indicative of road induced noise using an output signal measured via a load cell;
determine a coherence value between the noise signal and an error signal indicative of noise and the anti-noise sound within the passenger cabin;
estimate a noise reduction value based on the coherence value;
filter at least one of the noise signal and the error signal based on the estimated noise reduction value; and
generate the anti-noise signal based on the at least one of the filtered noise signal and the filtered error signal.

### Claim 15 (depends on 14)

The RNC system of claim 14, wherein the controller is further programmed to:
determine shaping filter parameters based on the estimated noise reduction value using a non-linear least square solver; and
filter at least one of the noise signal and the error signal using the shaping filter parameters.

### Claim 16 (depends on 14)

The RNC system of claim 14, wherein the controller is further programmed to:
smooth the at least one of the filtered noise signal and the filtered error signal using artificial intelligence; and
generate the anti-noise signal based on the at least one of the smoothed and filtered noise signal and the smoothed and filtered error signal.

### Claim 17 (depends on 14)

The RNC system of claim 14, wherein the controller is further programmed to:
select at least one peak filter based on the estimated noise reduction value; and
filter the noise signal and the error signal using the at least one peak filter.

### Claim 18 (depends on 14)

The RNC system of claim 14, wherein the controller is further programmed to filter the noise signal and the error signal based on the estimated noise reduction value over a frequency range.

### Claim 19 (depends on 14)

The RNC system of claim 14 further comprising a vibration sensor to provide the noise signal indicative of the road induced noise within the passenger cabin.

### Claim 20 (depends on 14)

The RNC system of claim 14, wherein the controller further comprises:
an adaptive filter controller to determine the coherence value and to estimate the noise reduction value; and
a controllable filter to generate the anti-noise signal.