JP3278180B2 - Vehicle noise control device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle noise control device for reducing noise in a vehicle cabin caused by engine vibration and the like. More specifically, the present invention relates to noise collected by a microphone or the like and a reference signal corresponding to engine vibration and the like. The present invention relates to a vehicle noise control device for outputting a sound for reducing the noise from a speaker using an adaptive filter, and more particularly to an adaptive algorithm for coefficients of the adaptive filter.

[0002]

2. Description of the Related Art Noise in the interior of a motor vehicle increases the fatigue of drivers and other occupants and causes discomfort.

[0003] Such an in-vehicle noise is generally 200 H
There are low frequency (muffled sound) of z ~ 300Hz or less, and medium and high wave sounds such as engine noise, exhaust radiation, road noise and wind noise.

[0004] Among them, engine noise and road noise have a great influence on people inside the vehicle, and the occupant's discomfort increases as the noise increases.

[0005] The rate at which these noises travel through the body or the like and reach the interior of the vehicle is greater than the rate of direct emission from the engine or road surface into the interior of the vehicle, and there is a limit to soundproofing measures using sound insulation members. Active noise reduction measures are attracting attention, as it outputs sound in phase opposite to engine noise or road noise and actively cancels noise, making people in the car feel as if there is no engine noise or road noise. ing.

[0006] As a conventional technique relating to such a positive soundproofing measure, there is known a technique in which a loudspeaker mounted in a vehicle is used on the basis of noise collected by a microphone mounted near a passenger's headrest and a reference signal synchronized with the engine speed. There is a known type that outputs a sound having a phase opposite to that of the vehicle interior noise to cancel the engine noise (Japanese Patent Application Laid-Open No. 1-501344).

That is, as shown in FIG. 8, a plurality of microphones 112 for collecting vehicle interior noise and two speakers 111 constituting a secondary sound source are installed at a predetermined position in a vehicle interior 110, as shown in FIG. Have been. The noise collected by the microphone 112 is converted into an electric signal and transmitted to the control unit 113.

On the other hand, based on an engine rotation detection signal synchronized with the rotation speed of the engine 102, a reference signal generator
At 114, a reference signal is generated. Control unit 11
In 3 the input reference signal and microphone 112
The two speakers 111 are driven in accordance with the electric signal from the first and second speakers 111 so as to output a sound for canceling the vehicle interior noise (a sound having a phase opposite to the noise).

By the way, as a noise control algorithm in such a noise control device, an LMS (Least Mean Meaning) method is used.
Square Method) is known. FIG. 9 is a block diagram showing a noise control device using a noise control algorithm based on the LMS method. In FIG. 9, the number of reference signals, the number of speakers, and the number of microphones are all one for convenience of explanation.

The control unit 113 contains a filter F116 and a filter H ° 117. These two filters F, H ° 116 and 117 are FIR filters (Finite Inpul
se Response filter), of which filter H °
Reference numeral 117 denotes a model of an acoustic signal transfer characteristic H from the speaker 111 to the microphone 112.

In the LMS method, the mean square of the error signal J = E
[E (k) ² ] (e (k) is the k-th sample value of e, e
Is a coefficient vector <f> of the filter F116 (using the steepest descent method) so that the error between the control output Z from the speaker 111 and the noise d at the position of the microphone 112 is minimized. In (2), if a vector is represented, a symbol <> is added to the code.).

Here, the coefficient vector of the filter H ° 117 is
Assuming that <h>, the algorithm for updating the coefficient vector <f> is represented by the following recurrence formula (1).

[0013]

<F> (k + 1) = <f> (k) −μ <r> (k) · e (k) (1) where <f> = [f ₀ , f ₁ , ^{_{......, f I] T, <}} r> (k) = [r (k), r (k-1), ......, r (kI)] T, r (k) = <h> T <x> (k), <h> = [h ₀ , h ₁ ,..., h _J ] ^T , <x> (k) = [x (k), x (k−1),..., x (kJ) ^T and μ are constants that determine the convergence speed of the recurrence formula (1). In this algorithm, a filter H having a transfer characteristic equal to the transfer characteristic H between the speaker and the microphone is used.
° must be used. For this reason, there is a trouble that the transfer characteristic H between the speaker and the microphone must be measured in advance, and there is a problem that if the transfer characteristic H between the speaker and the microphone fluctuates greatly during the noise control, the control effect is reduced.

In order to solve such a problem, it is conceivable to use a simplex method, which is a kind of nonlinear optimization method, instead of the LMS method as a noise control algorithm. That is, as shown in FIG. 10, when the simplex method is used, it is not necessary to provide the filter H ° 117, and the above-described problem when the LMS method is used is solved.

Hereinafter, an adaptation algorithm using the simplex method will be described.

If the noise d and the reference signal x are in a stationary process (statistical properties are constant) and the transfer characteristic H between the speaker and the microphone is constant, the error signal 2
Since the root mean square J is simply considered to be a function of the filter coefficient <f>, it is expressed again as J (<f>). Also, I +
A set of two filter coefficient vectors ⁰ <f>, ¹ <f>, ..., ^{I + 1}
Prepare <f>.

Here, an algorithm for updating the coefficient vector <f> of the filter F116A is obtained by repeating the following processes (i) to (viii).

(I) The filter coefficients ⁰ <f>, ¹ <f>,.
^{I + 1} <f> are sequentially set as the above filter coefficients, and each time the error signal square mean (evaluation function value) J ( ⁰ <f>), J (
¹ <f>), ..., J ( ^{I + 1} <f>). (ii) The measured mean squared error signals J ( ⁰ <f>), J
( ¹ <f>), ..., J ( ^{I + 1} <f>)
( ^{I *} <f>). At this time, ^{i *} <f> is updated according to the following equation.

[0019]

(Equation 2)

(Iii) ^{i *} <f> updated in the above process (ii)
, The error signal mean square J ( ^{i *} <f>) is measured again.

(Iv) After the processing of (iii), the measured J ( ^{i *} <f>) is the average of all error signal square means J ( ⁰ <f>).
), J ( ¹ <f>),..., J ( ^{I + 1} <f>), ^{i *} <f> is updated again according to the following equation.

[0022]

(Equation 3)

(V) ^{i *} <f> updated in the above process (iv)
, The error signal mean square J ( ^{i *} <f>) is measured again.

(Vi) If the measured J ( ^{i *} <f>) after the process of (iii) is larger than the J ( ^{i *} <f>) before the update, ^{i *} Update <f>.

[0025]

(Equation 4)

(Vii) ^{i *} <f> updated in the above process (vi)
, The error signal mean square J ( ^{i *} <f>) is measured again.

(Viii) Return to the above process (ii).

[0028]

To achieve the above object, the present invention has the following configuration. That is, a sound collecting means for collecting noise in the vehicle interior, a speaker for outputting a sound capable of reducing the noise in the vehicle interior, a reference signal generating means for generating a reference signal corresponding to the noise vibration, and the reference signal Adaptive filter means for generating a control error signal by filtering; and, based on the reference signal and the error signal, filtering the noise from the speaker to reduce noise in the vehicle cabin at a position where the sound collecting means is disposed. Control means for controlling output of a canceling sound, wherein the adaptive filter means performs an operation of minimizing a mean square value of a difference between the noise signal collected by the sound collecting means and the control error signal. It is configured as follows.

That is, in the above-mentioned simplex method, the evaluation function values J ( ⁰ <f>) to J, which are the squared error signals, are used.
All of ( ^{I + 1} <f>) must be measured accurately, and if it is not measured accurately, the convergence of the control will be significantly slowed down or worsened.

Therefore, when a sound other than the noise to be controlled and a sound in an unsteady process (for example, a voice of an occupant or an audio sound) is mixed into the output signal from the microphone, the measured value of the evaluation function is large. An error occurs and smooth noise control cannot be performed.

The present invention has been made in view of the above circumstances,
It is an object of the present invention to provide a vehicle noise control device capable of accurately controlling only noise to be controlled, even when sound of an unsteady process is mixed in a microphone signal with sound other than noise to be controlled. It is the purpose.

[0032]

SUMMARY OF THE INVENTION A first noise control device for a vehicle in the present invention comprises a sound collecting means for collecting vehicle interior noise, and a speaker for outputting a sound capable of reducing the noise in the vehicle interior. A reference signal generating means for generating a reference signal corresponding to the noise and vibration; and an arrangement position of the sound collecting means based on the noise collected by the sound collecting means and the reference signal generated by the reference signal generating means. Control means for controlling the speaker to output a sound for canceling the noise in order to reduce the noise in the vehicle interior, wherein the control means includes an output of the sound collection means. A signal extraction unit for extracting a signal having a high correlation with the reference signal from the signals; and a signal extraction unit for extracting a signal having a high correlation with the reference signal based on an output of the signal extraction unit and the reference signal. It can and is characterized by comprising a filter unit for generating the speaker drive signal corresponding to the sound to cancel the noise.

The above-mentioned filter means a filter using an FIR filter (Finite Impulse Response filter).

[0034]

According to the above arrangement, the control error signal is generated by filtering the reference signal by the adaptive filter means.

Since the reference signal is a signal that is a source of noise to be controlled, the reference signal includes, among the sounds collected by the sound collecting means, sounds other than the noise to be controlled.
Even when a sound in an unsteady process, for example, a human voice or an audio sound is mixed, it is possible to extract a sound component mainly caused by a behavior of a noise source to be controlled.

The control means controls the output of noise reduction sound from the speaker based on the reference signal and the control error signal. At this time, the adaptive filter means is operated so as to minimize the mean square value of the difference between the noise signal collected by the sound collecting means and the control error signal.

As a result, the evaluation function values J ( ⁰ <f>) to J ( ^{I + 1} <f>) corresponding to the above-described filter coefficients can be accurately measured. Thus, only the noise to be controlled can be appropriately controlled.

[0038]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 6 is a schematic diagram showing a state in which the vehicle noise control device according to the embodiment of the present invention is mounted inside a vehicle.

That is, this apparatus comprises a microphone 2 embedded at the position of a headrest 1 of each seat, an electric signal obtained by converting the sound collected by the microphone 2 and an ignition pulse detector 3 (hereinafter referred to as IG).
A controller 4 to which an ignition pulse signal (hereinafter, referred to as an IG pulse signal) transmitted from a pulse detector 3 is input, and an audio front speaker driven by the controller 4 to output a sound for canceling noise in the vehicle. It consists of five.

The microphones 2 are arranged at positions corresponding to the positions of both ears of each occupant, so that an electric signal corresponding to the sound actually heard by each occupant is input to the controller 4. Becomes

The IG pulse detector 4 extracts a signal synchronized with the engine rotation. For example, the IG pulse detector 4 outputs, as an IG pulse signal, a signal obtained by detecting rotation of a crankshaft or detecting ignition timing from an igniter. is there.

Further, a switch 4a is provided near the front panel of the driver's seat for appropriately switching the type of noise that the occupant turns on / off or cancels out.

The loudspeaker 5 is a general audio loudspeaker for converting a sound signal from a CD, a magnetic tape, a tuner or the like into a sound and outputting the sound. The loudspeaker 5 simultaneously outputs such a sound and the noise canceling sound. , Or only one of them.

FIG. 7 is a block diagram showing the internal configuration of the controller 4.

That is, according to FIG. 7, the IG pulse signal transmitted from the IG pulse detector 3 and the electric signal carrying the noise information transmitted from the microphone 2 are amplified by the amplifier 6, and the A / D The signal is converted into a digital signal by the conversion circuit 7 and input to the CPU 8. This CPU 8
Although a DSP (Digital Signal Processor) is used as this, other general microprocessors can also be used.

The memory circuit 9 connected to the CPU 8 stores a program representing a predetermined algorithm relating to noise control. The CPU 8 performs predetermined signal processing on the input signal based on the program. , And outputs a predetermined speaker drive signal.

This speaker drive signal is supplied to the D / A conversion circuit 10
Is converted into an analog signal, amplified by the amplifier 11, and applied to each speaker 5. As a result, the sound to cancel the noise in the vehicle at the position of each occupant's ear is output from each speaker 5.

The controller 113 sends a clock signal having a constant period (500 μs to 1 ms) to the CPU 8 in order to increase the accuracy of the operation timing in the CPU 8.
And a clock circuit 12 for outputting to

FIG. 1 is a block diagram conceptually showing a noise control algorithm stored in the controller 113B (actually, the memory circuit 9).

That is, in this block diagram, the speaker 11
The microphone signal ε output from the microphone 112 based on the control output Z from 1 and the noise d, and the reference signal x
Is input, and the speaker 111 is set based on a predetermined algorithm.
The controller 113B which outputs the speaker drive signal y is shown in FIG.

The controller 113B includes a filter G120 whose filter coefficient is adjusted by a second adaptive algorithm 119 using a signal ε-e obtained by subtracting the error signal e from the microphone signal ε and a reference signal x, and a reference signal. x is a first adaptive algorithm 118 using an error signal e obtained by signal conversion by the filter G120.
A filter F116B whose filter coefficient is adjusted by B is provided, and the reference signal x is applied to the filter F116B.
Is converted into a speaker drive signal y by the
Is output to

In this embodiment, the simplex method is used as the first adaptive algorithm 118B. In this simplex method, the evaluation function value J ( ⁰ <f>)
~ J ( ^{I + 1} <f>) must be accurately measured,
If a sound other than the noise to be controlled and a sound of an unsteady process (for example, a voice of a passenger or an audio sound) is mixed into the microphone signal ε, a large error occurs in the evaluation function value, and as a result, the error is smooth. Noise control cannot be performed.

In order to avoid such a situation, it is necessary to remove from the microphone signal ε a component that is not caused by the sound to be controlled.

Therefore, in this embodiment, based on the following ideas (i) and (ii), as shown in FIG. 1, a second algorithm 119 for generating an error signal e and a filter G120
Is provided.

(I) An error signal e is generated by filtering a reference signal x obtained from a noise source.

(Ii) In the above (i), the parameters of the filter G120 are adjusted so that the mean square of the difference between the microphone signal ε and the error signal e is minimized.

The filter G120 is composed of an FIR filter. If the filter coefficient vector is <g>, the second adaptive algorithm 119 is an LMS (a so-called Filtered-XL used for noise control, which is used for noise control).
In the case of using the LMS method in which the reference signal does not need to be processed in advance, instead of the MS), the updating equation of the filter coefficient vector <g> is represented by the following equation.

[0059]

<G> (k + 1) = <g> (k) + α · <x> ′ (k) {ε (k) −e (k)} where <g> = [g ₀ , g ₁ ,..., G _I ′] ^T , <x> ′ (k) = [x (k), x (k−1),..., X (kI ′)] ^{T In} the above equation, α is It is a constant that determines the convergence speed of the recurrence formula.

The above equation is the equation in the prior art described above.
Although based on the LMS method as in (1), equation (1)
Since the signals to be handled are different from the above, there is no practical problem which is a problem in the equation (1).

According to the above-described embodiment, it is possible to extract a component caused only by the behavior of the noise source by the second adaptive algorithm 119 and the filter G120, whereby a stable noise reduction effect can be obtained.

Hereinafter, a program representing the above-described noise control algorithm will be described with reference to the flowcharts of FIGS.

FIG. 2 is a main flowchart showing the entire program. In this embodiment, the number of speakers 5 is M, and the filter coefficient vector to be adjusted for each speaker 5 is <f> 1, <f> 2,..., <F> M
Of M. One of the filter coefficient vectors
Focusing on <f> m, adjusting <f> m is actually I + 2 of ⁰ <f> m, ¹ <f> m, ..., ^{I + 1} <f> m since it is possible to update calculation using a set of coefficient vector (the set is referred to as Fm), F _1, F ₂ as shown in the end view 1, ..., it should be updated sequentially F _M.

[0064] That is, as shown in FIG. 1, first update the filter coefficient vector F ₁ (S1), then updates the filter coefficient vector F ₂ (S2), and further updates the filter coefficient vector followed by the last to update the filter coefficient vector F _M to (S3).

[0065] When the filter coefficient vector F _M the updated end, returns to Step 1 (S1), again sequentially updating the filter coefficient vector from the filter coefficient vector F _1.

[0066] Figure 3 is a flowchart showing a program for updating the F _m.

First, in step 4 (S4), imax, ^imax <f representing the largest filter coefficient vector
> m, the evaluation function value Jmax (Jmax = J ( ^imax <f>
m)) and

[0068]

(Equation 6)

Next, in step 5 (S5), i = 0
far.

Thereafter, in step 6 (S6), <f> m
^{Is set} to ⁱ <f> m, and J ( ⁱ <f> m) is obtained. Step 7
In (S7), this J ( ⁱ <f> m)
It is determined whether or not the value is the maximum value. If the result is the maximum value, the process proceeds to step 8 (S8), and i at this time is set to ima
Set x and J as Jmax, and proceed to step 9 (S9). If it is not the maximum, step 9 (S8) is skipped without step 8 (S8).
Proceed to 9).

In step 9 (S9), the current

[0072]

(Equation 7)

Add ⁱ <f> m to <c> and replace it with <c>.

Thereafter, i is incremented (S10). If i is I + 2 in step 11 (S11), the process proceeds to step 12 (S12).
Returning to (S6), the processing of each step of S6 to S11 is performed again.

Next, in step 12 (S12), ^imax <f> m is subtracted from <c>, and this is set as <c>.

Thereafter, ^imax <f> m is updated according to the following equation.

[0077]

(Equation 8)

Thereafter, ⁰ <f> m, ¹ <f> m,... ^{I + 1} <f> m again
Are set in order, J ( ⁰ <f> m), J ( ¹ <f> m),
.., J ( ^{I + 1} <f> m) will be measured. That is, in step 14 (S14), imax ', Jmax',
Initialize imin, Jmin, etc. Further steps
In step 15 (S15), i = 0 is set.

Next, in step 16 (S16), <f> m is
ⁱ put the <f> m determine the ^{J (i <f> m)} . Step 17 (S
In 17), it is determined whether or not this J ( ⁱ <f> m) is the largest among the values of J obtained so far. If the result is the largest, the process proceeds to step 18 (S18). I for imax
', J are set to Jmax', and the routine proceeds to step 19 (S19). If it is not the maximum, the process proceeds to step 19 (S19) without passing through step 18 (S18).

In step 19 (S19), step
It is determined whether J ( ⁱ <f> m) obtained in 16 (S16) is the smallest of the values of J obtained so far. If the result is the minimum, the process proceeds to step 20 (S20). I at this time is i
Min and J are set to Jmin, and the process proceeds to step 21 (S21). If it is not the minimum, step 21 is skipped without step 20 (S20).
Proceed to (S21).

Next, i is incremented in step 21 (S21).

Thereafter, in step 22 (S22), it is determined whether or not i is I + 2. If i is 2, the process proceeds to step 23 (S23). If not, the process returns to step 16 (S16). , S16 to S22 are performed again.

As described above, by the processing of S14 to S22,
Each measured J value J ( ⁰ <f> m), J ( ¹ <f> m), ..., J
( ^{I + 1} <f> m), the maximum value Jmax 'is Jmax' = J (
^imax ′ <f> m), and the minimum value Jmin is Jmin = J ( ^imin <f> m)
It is put.

Thereafter, in step 23 (S23), ima
It is determined whether or not x and imax 'are equal. If the result is equal, the process proceeds to step 24 (S244), and according to the following equation:
Update ^imax <f> m and end the program processing. Here, <ε> represents a small error.

[0085]

(Equation 9)

The results imax and imax of step 23 (S23)
'Are not equal, the flow advances to step 25 (S25), and it is determined whether imax and imin are equal. If they are equal, the flow advances to step 26 (S26), and according to the following equation:
Update ^imax <f> m and end the program processing.

[0087]

(Equation 10)

In the above program processing,
When imax is equal to imax 'in step 23 (S23),
When updating ^imax <f> m in step 24 (S24),
^imax <ε> is added. This is for the following reason.

That is, as the updating process of the filter coefficients by the simplex method progresses, the values of the filter coefficients gradually approach, and there is a possibility that all of them eventually become the same coefficient vector. Once in this state,
Even if the curve shape of the evaluation function J changes and the value of <f> that minimizes the function J changes, this cannot be accommodated.

Therefore, each filter coefficient vector ⁰ <f> m, ¹
For <f> m, ..., ^{I + 1} <f> m, the corresponding vectors that are linearly independent and have small absolute values ⁰ <ε>, ¹ <ε>, ..., ^{I + 1}
<ε> is added as a small error to avoid the above-described problem, that is, the filter coefficients are not all the same coefficient vector.

As described above, according to the program shown in FIG. 3, the simplex method can be used to optimize the filter coefficient vector.

FIG. 4 is a flowchart showing a program for obtaining the evaluation function J.

First, in step 41 (S41), q is set to 0 and J is set to 0, and initialization is performed.

Next, in step 42 (S42), an error signal vector <e> is obtained. Note that <e> = [e ₁ , e ₂ ,
..., e _M ] ^T.

Subsequently, in step 43 (S43),

[0096]

[Equation 11]

Is set to J. Here, M indicates the number of microphones 2 installed.

Next, at step 44 (S44), the value of q is incremented, and at step 45 (S45), it is determined whether or not q is equal to Q. As a result, q
If is not equal to Q, the flow returns to step 42 (S42), and the above processing is repeated. On the other hand, if the result q is equal to Q, the program for obtaining the evaluation function J with J / Q as J ends in step 46 (S46).

When the evaluation function J is obtained, the value of Σe _m (k) ² is obtained a plurality of times instead of the operation described above.
The average value may be obtained.

Next, a program for obtaining <e> in step 42 (S42) will be described with reference to FIG.

In the program for obtaining <e>,
In step 51 (S51), it is determined whether or not the clock signal from the clock circuit 12 has been input to the CPU 8.

If the input of the clock signal is confirmed, the reference signal <x> (k) is sent to the CPU in step 52 (S52).
Enter 8 Subsequently, in step 53 (S53),
n = 1,2, ......, to calculate the ^{<F> n T · <x} > (k) for each of the N, put each result y _n. Where <x> (k) = [x
(k), x (k-1),..., x (kI)] ^T.

Next, in step 54 (S54), the CPU 8 outputs the respective speaker drive signals y _{1 to} y _N.
Finally, in step 55 (S55), each microphone 2
The error signals ε _{1 to} ε _M are input to the CPU 8.

Next, in step 56 (S56), the above-mentioned second adaptive algorithm 119 is executed based on the following equation. That is, the following equation is calculated for m = 1, 2,..., M.

[0105]

<E> _m ← <g> _m ^T · <x> ′ (k) <g> _m ← <g> _m + α · <x> ′ (k) (ε _m −e _m ) where <x> ′ (k) = [x (k), x (k−1),..., x (kI)] ^T α is a convergence coefficient The program for obtaining <e> is completed.

The first adaptive algorithm shown in FIG.
All programs that correspond to parts other than 118B
Is shown in the program shown in FIG. However, each calculation formula is represented as having a plurality of speakers 111 and microphones 112 respectively.

The noise control device for a vehicle according to the present invention is not limited to the above-described embodiment, and various other modifications can be made.

For example, in the above-described embodiment, the case where the simplex method is used as the first adaptive algorithm and the LMS method is used as the second adaptive algorithm is described. However, other algorithms can be used as each adaptive algorithm. is there. For example, the Powell method can be used as the first adaptive algorithm.

In the above-described embodiment, the case where the engine noise in the vehicle compartment is reduced has been described. However, the present invention is applicable to the case where other noises (for example, road noise and exhaust noise) are reduced. Of course you can.

The numbers of microphones and speakers can be appropriately selected.

If the mode is switchable so that the user can appropriately select a desired reference signal from the plurality of reference signals by the switch 4a shown in FIG. 6, an in-car sound field according to the user's preference is formed. Is possible.

In the present embodiment, the microphone 2 for the sensor is attached to the ears of all the occupants, and noise control is performed for all the occupants. However, only a specific occupant, for example, the driver or the driver and the occupant in the front passenger seat It is also possible to perform noise control only for the specific occupant. In this case, a signal from the microphone 2 at the ear of the specific occupant may be input to the controller 4.

[Brief description of the drawings]

FIG. 1 is a block diagram conceptually showing an adaptive algorithm used in an apparatus according to an embodiment of the present invention.

FIG. 2 is a flowchart showing an entire program of an adaptive algorithm used in the apparatus according to the embodiment of the present invention;

FIG. 3 shows Fm used in the overall program shown in FIG.
Flowchart showing a program for updating

FIG. 4 is a flowchart showing a program for obtaining J used in the program shown in FIG. 3;

FIG. 5 is a flowchart showing a program for obtaining <e> used in the program shown in FIG. 4;

FIG. 6 is a schematic diagram showing a mounting position of the vehicle noise control device according to one embodiment of the present invention.

FIG. 7 is a block diagram showing the inside of the controller shown in FIG. 6;

FIG. 8 is a block diagram for explaining a conventional technique.

FIG. 9 is a block diagram showing an outline of a vehicle noise control device when the LMS method is used.

FIG. 10 is a block diagram showing an outline of a vehicle noise control device when the simplex method is used.

[Explanation of symbols]

 2,112 microphone 3 ignition pulse detector 4,113,113 A, 113 B controller (control unit) 5,111 speaker 6,11 amplifier 7 A / D conversion circuit 8 CPU 9 memory circuit 10 D / A conversion circuit 116, 116 A, 116 B, 117 Filter F 118, 118 A, 118 B First adaptive algorithm 119 Second adaptive algorithm 120 Filter G

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-4-262012 (JP, A) JP-A-4-272416 (JP, A) JP-A-5-30585 (JP, A) JP-A-5-205 6185 (JP, A) (58) Field surveyed (Int. Cl. ⁷ , DB name) G10K 11/178 B60R 11/02 F01N 1/00 F01N 1/06

Claims (1)

(57) [Claims] And 1. A sound collecting means for collecting the interior noise, and a speaker for outputting a sound that can reduce the noise of the vehicle interior, and a reference signal generating means for generating a reference signal corresponding to the noise vibrations, the By filtering the reference signal
Adaptive filter means for generating a control error signal; and a sound for canceling the noise from the speaker for reducing the noise in the cabin at an arrangement position of the sound collecting means based on the reference signal and the error signal. Control means for controlling the noises collected by the adaptive filter means.
Minimizing the mean square value of the difference between the signal and the control error signal
A noise control device for a vehicle, wherein the noise control device is configured to perform an operation .