Apparatus for controlling noise road noise via trained model and method thereof

1 . An apparatus for controlling noise, the apparatus comprising:

a memory configured to store computer-executable instructions; and

at least one processor operatively connected to the memory and configured to access the memory to execute the instructions,

wherein the at least one processor is configured to:

obtain a primary virtual road noise and a noise weight by applying an error input signal of a target time point to a trained noise control model;

obtain a target road noise by applying the primary virtual road noise and a secondary virtual road noise obtained at a time point different from the target time point to a primary path;

obtain a target control noise by applying the noise weight and a noise weight obtained at a time point different from the target time point to a secondary path; and

perform noise control on the error input signal based on the target road noise and the target control noise.

2 . The apparatus of claim 1 , wherein the at least one processor is further configured to:

obtain a first weight and a second weight related to noise removal of the target time point, based on an error input signal of a time point different from the target time point and an error output signal of a time point different from the target time point.

3 . The apparatus of claim 2 , wherein the at least one processor is further configured to:

generate a first virtual road noise by applying the first weight to the primary virtual road noise;

generate a second virtual road noise by applying the second weight to the secondary virtual road noise obtained at the time point different from the target time point; and

obtain the target road noise by applying the first virtual road noise and the second virtual road noise to the primary path.

4 . The apparatus of claim 2 , wherein the at least one processor is further configured to:

generate a first target weight by applying the first weight to the noise weight;

generate a second target weight by applying the second weight to the noise weight obtained at the time point different from the target time point; and

obtain the target control noise by applying the first target weight, the second target weight, and the primary virtual road noise to the secondary path.

5 . The apparatus of claim 4 , wherein the at least one processor is further configured to:

obtain a third target weight from an adaptive filter at the target time point; and

obtain the target control noise by applying the first target weight, the second target weight, the third target weight, and the primary virtual road noise to the secondary path.

6 . The apparatus of claim 1 , wherein the at least one processor is further configured to:

obtain an estimation error signal by applying an estimation road noise measured from an acceleration sensor mounted in a vehicle to a feedforward active noise control (ANC) model;

remove an internal noise of the vehicle based on the estimation road noise and an estimation weight; and

generate a training input including the estimation error signal and a training output in which the estimation road noise and the estimation weight are paired, based on removal of the internal noise by a predetermined amount of noise.

7 . The apparatus of claim 6 , wherein the at least one processor is further configured to:

train the noise control model based on the training input and the training output.

8 . The apparatus of claim 7 , wherein the at least one processor is further configured to:

train the noise control model based on the training input in which a road flag representing each of at least one road condition and the estimation error signal are paired, and the training output.

9 . The apparatus of claim 1 , wherein the at least one processor is further configured to:

obtain an error output signal based on the target road noise and the target control noise; and

set the error output signal as an error input signal at a time point subsequent to the target time point.

10 . The apparatus of claim 9 , wherein the at least one processor is further configured to:

obtain the error output signal by subtracting the target control noise from the target road noise.

11 . A method of controlling noise, the method comprising:

obtaining, by at least one processor, a primary virtual road noise and a noise weight by applying an error input signal of a target time point to a trained noise control model;

obtaining, by the at least one processor, a target road noise by applying the primary virtual road noise and a secondary virtual road noise generated obtained at a time point different from the target time point to a primary path;

obtaining, by the at least one processor, a target control noise by applying the noise weight and a noise weight obtained at a time point different from the target time point to a secondary path; and

performing, by the at least one processor, noise control on the error input signal based on the target road noise and the target control noise.

12 . The method of claim 11 , further including:

obtaining, by the at least one processor, a first weight and a second weight related to noise removal of the target time point, based on an error input signal of a time point different from the target time point and an error output signal of a time point different from the target time point.

13 . The method of claim 12 , wherein the obtaining of the target road noise includes:

generating a first virtual road noise by applying the first weight to the primary virtual road noise;

generating a second virtual road noise by applying the second weight to the secondary virtual road noise obtained at the time point different from the target time point; and

obtaining the target road noise by applying the first virtual road noise and the second virtual road noise to the primary path.

14 . The method of claim 12 , wherein the obtaining of the target control noise includes:

generating a first target weight by applying the first weight to the noise weight;

generating a second target weight by applying the second weight to the noise weight obtained at the time point different from the target time point; and

obtaining the target control noise by applying the first target weight, the second target weight, and the primary virtual road noise to the secondary path.

15 . The method of claim 14 , wherein the obtaining of the target control noise includes:

obtaining a third target weight from an adaptive filter at the target time point; and

obtaining the target control noise by applying the first target weight, the second target weight, the third target weight, and the primary virtual road noise to the secondary path.

16 . The method of claim 11 , wherein the obtaining of the road noise and the weight includes:

obtaining an estimation error signal by applying an estimation road noise measured from an acceleration sensor mounted in a vehicle to a feedforward active noise control (ANC) model;

removing an internal noise of the vehicle based on the estimation road noise and an estimation weight; and

generating a training input including the estimation error signal and a training output in which the estimation road noise and the estimation weight are paired, based on removal of the internal noise by a predetermined amount of noise.

17 . The method of claim 16 , further including:

training, by the at least one processor, the noise control model based on the training input and the training output.

18 . The method of claim 17 , further including

training, by the at least one processor, the noise control model based on the training input in which a road flag representing each of at least one road condition and the estimation error signal are paired, and the training output.

19 . The method of claim 11 , further including:

obtaining, by the at least one processor, an error output signal based on the target road noise and the target control noise; and

setting, by the at least one processor, the error output signal as an error input signal at a time point subsequent to the target time point.

20 . The method of claim 19 , wherein the obtaining of the error output signal includes:

obtaining, by the at least one processor, the error output signal by subtracting the target control noise from the target road noise.