JP2006161921A - Active vibration control device - Google Patents

Abstract

An active vibration control device that shortens the convergence time of parameters of an adaptive filter (7).
Parameters of a physical quantity related to vibration or noise of a vehicle body, an actuator that generates distortion in a floor panel, and an adaptive filter 7 for controlling the actuator are repeatedly updated to an optimum value, and the physical quantity is updated. An adaptive filter controller 4 that cancels vibration or noise transmitted to the vehicle body by controlling the actuator based on the above, a seating sensor that detects that an occupant is seated in the seat, and an initial value set of parameters of the adaptive filter 7 are stored. The database includes an initial value set of parameters of a plurality of adaptive filters 7 that differ depending on the number and arrangement of occupants, and the adaptive filter controller 4 is based on the number and arrangement of occupants detected by the seating sensor. The selected adapter To start the update from the set of initial values for the parameters of Ibufiruta 7.
[Selection] Figure 8

Description

  The present invention relates to an active vibration control device, and more particularly to an active vibration control device using adaptive filter technology.

Conventionally, a signal from a vibration detector that has detected vibrations from a vibration source is used as a reference signal, a cancellation signal having an opposite phase to the vibration in the vehicle interior based on the reference signal is generated by an adaptive FIR digital filter, and the speaker is driven. 2. Description of the Related Art An active vibration control device that detects a cancellation error between a cancellation vibration generated from a speaker and a vibration in a vehicle interior based on a vibration source with a microphone and changes an adaptive parameter of an adaptive FIR digital filter based on an output signal of the microphone is known. (For example, refer to Patent Document 1).
JP-A-10-169700

  The advantage of active vibration control equipment (AVC) using adaptive filter technology is that it is not necessary to specify the vibration source (system), and the parameters of the adaptive filter reduce the cancellation error. Automatically updated.

  For example, the parameters of the adaptive filter are updated online from the initial value set to the optimum value. Usually, the initial set of parameters is set to zero for simplicity. In this case, the parameters of the adaptive filter converge from zero to the optimum value. The convergence time required for convergence from the initial value set to the optimum value becomes longer due to an increase in the parameters of the adaptive filter and an increase in actuators (speakers).

  The present invention has been made to solve the above-mentioned problems, and an object thereof is to provide an active vibration control device that shortens the convergence time of parameters of an adaptive filter by using an initial value set that is more suitable than zero. That is.

  A first feature of the present invention is a sensor that measures a physical quantity related to vibration or noise of a vehicle body, an actuator that is arranged on the floor panel of the vehicle body and generates distortion in the floor panel, and an adaptive filter for controlling the actuator The adaptive filter controller that cancels vibration or noise transmitted to the vehicle body by repeatedly updating the parameters to the optimal value and controlling the actuator based on the physical quantity, and detecting that the passenger is seated in the vehicle seat where the passenger sits An active vibration control device comprising a seating sensor and a database storing an initial value set of adaptive filter parameters, wherein the database includes initial values of a plurality of adaptive filter parameters that differ depending on the number and arrangement of passengers. The set is accumulated and the adaptive filter Controller is summarized in that initiating the update from the set of initial values for the parameters of the adaptive filter selected based on the number and arrangement of an occupant seating sensor detects.

  The second feature of the present invention is that a sensor for measuring a physical quantity related to vibration or noise of a vehicle body, an actuator arranged on the floor panel of the vehicle body to generate distortion in the floor panel, and an adaptive filter for controlling the actuator The adaptive filter controller that cancels vibration or noise transmitted to the vehicle body by repeatedly updating the parameters to the optimum value and controlling the actuator based on the physical quantity, and detecting that the occupant is seated in the seat where the occupant sits The acoustic model, which is a conversion function from the actuator to the sensor, based on the number and location of the occupants detected by the seating sensor, and the database that stores the initial value set of parameters of the adaptive filter An active vibration control device comprising a control unit for Dapu Restorative filter controller uses an acoustic model controller has modified, and summarized in that updating the parameters of the adaptive filter.

  The third feature of the present invention is a sensor that measures a physical quantity related to vibration or noise of a vehicle body, an actuator that is disposed on the floor panel of the vehicle body and generates distortion in the floor panel, and an adaptive filter that controls the actuator The adaptive filter controller that cancels vibration or noise transmitted to the vehicle body by repeatedly updating the parameters to the optimal value and controlling the actuator based on the physical quantity, and detecting that the passenger is seated in the vehicle seat where the passenger sits The acoustic model, which is a conversion function from the actuator to the sensor, based on the number and location of the occupants detected by the seating sensor, and the database that stores the initial value set of parameters of the adaptive filter An active vibration control device comprising a control unit, The control unit calculates an initial value set of parameters of a plurality of adaptive filters that differ depending on the number and arrangement of occupants from one initial value set accumulated in the database. The gist is to start updating from the initial value set calculated by the control unit using the model.

  ADVANTAGE OF THE INVENTION According to this invention, the active-vibration control apparatus which shortens the convergence time of the parameter of an adaptive filter by using the initial value set more suitable than zero can be provided.

  Embodiments of the present invention will be described below with reference to the drawings. In the description of the drawings, the same or similar parts are denoted by the same or similar reference numerals.

(First embodiment)
As shown in FIG. 1, in the active vibration control apparatus according to the first embodiment of the present invention, the sensor 1 measures the physical quantity related to the vibration or noise of the vehicle body 5, and the physical quantity measured by the sensor (1, 2). Based on the above, the actuator 3 is distorted to generate distortion in the vehicle body. The actuator 3 continuously distorts the vehicle body 5, whereby control vibration is transmitted to the vehicle body 5. By causing the control vibration to interfere with the vibration and noise transmitted from the outside of the vehicle body 5 to the inside of the vehicle, the vibration and noise are offset and reduced. Here, the physical quantity related to the vibration of the vehicle body (system) 5 measured by the sensors (1, 2) includes vibration and noise transmitted from the outside of the vehicle body 5 to the inside of the vehicle via the tires 10a, 10b. Moreover, the acceleration sensor 1 and the microphone 2 are demonstrated as an example of a sensor.

  The active vibration control apparatus according to the first embodiment of the present invention is disposed on the floor panel 6 of the vehicle body 5 and the sensors (1, 2) that measure the physical quantity related to the vibration or noise of the vehicle body 5. The actuator 3 that generates distortion in 6 and the parameters of the adaptive filter 7 for controlling the actuator 3 are repeatedly updated to the optimum values, and the actuator 3 is controlled based on physical quantities related to vibration or noise of the vehicle body 5. A database that stores an adaptive filter controller 4 that cancels vibrations or noise transmitted to the vehicle body 5 by means of, a seating sensor that detects that an occupant is seated in the seat of the vehicle body 5 on which the occupant sits, and an initial value set of parameters of the adaptive filter 7 With.

  There are various controllers for reducing vibration and noise, but the adaptive filter controller 4 is one of the most frequently used controllers. The adaptive filter controller 4 achieves a predetermined purpose by updating parameters of the adaptive filter 7 online. The predetermined purpose here is to cancel vibration or noise transmitted to the vehicle body 5. The parameter is updated according to the adaptive row 8 described later.

  The adaptive filter controller 4 includes an adaptive filter 7 that transmits a control signal to the actuator 3 and an adaptive row 8. The adaptive filter controller 4 requires two types of signals measured by the two types of sensors (1, 2). One is a signal related to a disturbance that causes noise transmitted in the vehicle. For example, the signal from the acceleration sensor (G-sensor) 1 that measures vibration transmitted from the road surface 11 to the wheels (tires 10a and 10b). A signal is included. The other is a signal related to the noise level in the vehicle, and includes, for example, a signal from the microphone 2 mounted in the vehicle. That is, in the active vibration control apparatus using the adaptive filter 7, the sensor (acceleration sensor 1) that measures the disturbance and the vibration or noise caused by the disturbance and the control vibration by the actuator 3 interfere with each other and are transmitted to the vehicle. Two types of sensors are required: a sensor for measuring noise (microphone 2). The actuator 3 is fixed under the floor panel 6 in the vehicle body 5 and generates distortion in the floor panel 6 by being distorted by itself, thereby generating control vibration in the vehicle body 5 to generate vibration or noise due to disturbance. cancel. As the actuator 3, a piezo-electric actuator using a piezo effect (piezoelectric effect) that generates a strain proportional to the electric field when an electric field is applied to the crystal can be used. When an electric field is applied to both surfaces of the actuator 3, the actuator 3 is distorted.

  As shown in FIG. 3, the floor panel 6 of the vehicle body 5 to which the actuator 3 of FIG. 1 is fixed can be divided into three main parts. Specifically, the floor panel 6 includes a flat cabin floor 15 located under a seat on which an occupant sits, a tank panel 16 to which a fuel tank is fixed, and a spare tire panel under the spare tire and the trunk. 17. The cabin floor 15 is located between the engine room and the tank panel 16. The spare tire panel 17 is located between the tank panel 16 and the rear end of the vehicle body 5.

  As shown in FIG. 4, on the floor panel 6 of FIG. 3, vertical members 18a to 18d extending in the vertical direction toward the traveling direction of the vehicle and horizontal members 19a to 19d extending in the horizontal direction are arranged. Yes. Since the floor panel 6 is formed in a thin flat plate shape to reduce the weight of the vehicle body, sufficient rigidity cannot be obtained with the floor panel 6 alone. The bar-shaped vertical members 18a to 18d and the horizontal members 19a to 19d having higher rigidity than the floor panel 6 are fixed on the floor panel 6 to increase the rigidity of the floor panel 6. The vertical members 18 a to 18 d and the horizontal members 19 a to 19 d are formed thicker than the floor panel 6. The vertical members 18a to 18d and the horizontal members 19a to 19d may be fixed only to one surface (front surface or back surface) side of the floor panel 6, or may be fixed to both surfaces (front and back surfaces).

  As shown in FIG. 2, the system 9 is divided into a vibration model W (z) 20 and an acoustic model C (z) 21. The system 9 shows a superordinate concept including the vehicle body 5 of FIG. 1 through which residual vibration, noise, or control vibration is transmitted. The vibration model 20 can be expressed in, for example, a transfer function form corresponding to transmission of vibration from the disturbance source x to the actuator 3. The acoustic model 21 can be expressed in, for example, a transfer function format corresponding to the transmission of sound waves from the actuator 3 to the microphone 2. The acoustic model 21 represents a period from the generation of sound by the actuator 3 to the measurement of the noise level in the vehicle by the microphone 2.

  It is generally difficult to accurately measure or evaluate the vibration model W (z) 20. This is because it is difficult to accurately know the number and arrangement of the disturbance sources x. However, it is possible to determine the acoustic model C (z) 21 accurately. This is because the number and arrangement of the actuators 3 can be accurately known, and the arrangement of the acceleration sensor 1 or the microphone 2 for measuring the sound level can also be accurately known. The main advantage of the adaptive filter controller 4 is that it is not necessary to measure the vibration model W (z) 20. The vibration model W (z) 20 is evaluated online from the signal x of the disturbance source and the signal e corresponding to the sound level.

  A signal y (n) is output from the adaptive filter 7, and the signal y (n) is combined with the vibration ω (n) via the actuator 3 to become a vibration u (n). The vibration u (n) becomes the acoustic e (n) via the acoustic model C (z) 21. The sound e (n) corresponds to the noise level in the passenger compartment and is measured by the microphone 2. Similarly, the signal measured by the acceleration sensor 1 attached to the vehicle body 5 also corresponds to the noise level in the passenger compartment.

The adaptive filter W ′ (z) is generally represented by an FIR filter as shown in the equation (1). Let I be the number of parameters w ′ _i of the adaptive filter W ′ (z).

Here, z ⁻ⁱ is a variable of Z conversion, and is expressed by equation (2). In equation (2), h (n) is a sample signal.

Therefore, the output y (n) of the adaptive filter W ′ (z) is expressed by the equation (3).

The sound level signal e (n) in FIG. 2 is expressed by equation (4).

The acoustic model C (z) can be expressed not only by the FIR filter but also by the IIR filter. When the acoustic model C (z) is an FIR filter having J parameters, the acoustic model C (z) is expressed by Expression (5).

The reference value J in the expression (5) minimized by the adaptive row 8 is defined by the expression (6).

The parameters γ _e and γ _y are fixed by the user. When the differential value of the reference value J shown in the equation (7) becomes zero, the reference value J reaches the minimum value.

Here, the signal r (ni) is defined by the equation (8).

  Thus, the acoustic model C (z) is represented by the FIR filter.

The adaptive row 8 updates the parameter w ′ _i of the adaptive filter W ′ (z) from (n) to (n + 1) according to the equation (9). Here, n indicates the number of updates, and K is fixed by the user.

Equation (9) can be further rewritten into Equation (10).

にそれぞれ等しく、１よりも小さい。パラメータαは、アダプティブフィルタＷ’(ｚ)の最適値への収束速度を固定するパラメータであり、パラメータβは、収束安全性を固定するパラメータである。 In equation (10), parameters α and β are set by the user, respectively.

Each equal to and less than 1. The parameter α is a parameter for fixing the convergence speed of the adaptive filter W ′ (z) to the optimum value, and the parameter β is a parameter for fixing the convergence safety.

In general, the initial value set w ′ _i (0) of the parameter w ′ _i of the adaptive filter W ′ (z) is all set to zero for simplification and generalization. The simplification, which means that to omit 'and special memory for saving the _i (0), the initial value set w' initial value set w means for calculating / evaluate _i (0). Generalization means that the state of the vehicle varies depending on the type of vehicle, and the parameter w ′ _i converges toward an optimum value corresponding to J (optimum value) corresponding to the minimum value of the noise level in the passenger compartment. To do.

In the embodiment of the present invention, the update is started from the initial value set w ′ _i (0) of the predetermined parameter w ′ _i . The initial value set w ′ _i (0) here is a numerical value set closer to the optimum value that is not zero as described above. Thereby, the update of the parameter w ′ _i can be started from a numerical set close to the optimum value, and the convergence time of the adaptive row 8 is shortened compared to the conventional method in which the initial value set w ′ _i (0) is started from zero. I can do it. In other words, the noise level in the passenger compartment can be quickly reduced.

The initial value set w ′ _i (0) is calculated and evaluated off-line and stored in the memory. There are as many initial value sets w ′ _i (0) of the parameters w ′ _i as there are combinations of the number of passengers and arrangements detected by the seating sensor. This is because the optimum value at which the parameter w ′ _i converges differs depending on the combination of the number of passengers and the arrangement detected by the seating sensor, and there are as many combinations.

In FIG. 5, a case where the adaptive filter W ′ (z) includes two parameters w ′ ₀ and w ′ ₁ will be described in order to simplify the description. However, the same applies to the case where the adaptive filter W ′ (z) includes three or more parameters.

The optimum value 24 corresponds to a state where the noise level in the passenger compartment is minimal. Conventionally, since the initial value set (0, 0) of the parameters w ′ ₀ and w ′ ₁ is both zero, the parameter w ′ ₀ is converged from the origin of the graph of FIG. 5 toward the optimum value 24 as a start point. And w ′ ₁ update. On the other hand, in the present application, the initial value set (w ′ ₀ (0), w ′ ₁ (0)) of the parameters w ′ ₀ and w ′ ₁ is not zero but closer to the optimum value 24. Therefore, rather than the conventional convergence path 22 from the initial value set (0,0) to the optimum value 24, the initial value set (w ′ ₀ (0), w ′ ₁ (0)) changes to the optimum value 24. The convergence path 23 is shorter. That is, the convergence time can be shortened.

Of course, when the state of the vehicle is exactly equal to the state indicated by the initial value set (w ′ ₀ (0), w ′ ₁ (0)) stored in the memory, the optimum value 24 is the initial value set (w ′ ₀ (0), w ′ ₁ (0)), and the parameters w ′ ₀ and w ′ ₁ need not be updated. When the state of the vehicle is different from the state indicated by the initial value set (w ′ ₀ (0), w ′ ₁ (0)), the parameters w ′ ₀ and w ′ ₁ need to be updated, but are necessary for the update. The time (convergence time) is shorter than before.

However, in practice, the optimum value of the parameter w ′ _i varies depending on the state of the vehicle and the environment. If the disturbance source x (n) or the vibration model W (n) changes, it is not necessary to change the update algorithm described above in order to reach a new optimal value. However, when the actual acoustic model C ′ (z) changes and becomes different from the acoustic model C (z) used for updating the parameter w ′ _i , the updating algorithm should be left as it is. Is not desirable. This is because, as shown in the equations (10) and (8), updating the parameter w ′ _i requires knowing an accurate acoustic model C (z), and the convergence to the optimum value is C ′ ( This is realized only when z) = C (z), and even if the minimum value of the noise level in the passenger compartment is obtained with C ′ (z) not equal to C (z), This is because the noise level is different from the minimum value. That is, it is not the minimum value.

The main factor that changes the actual acoustic model C ′ (z), which is the acoustic transfer function from the actuator 3 to the microphone 2, is the state of the air in the passenger compartment. The air condition can be controlled by the temperature of the air in the passenger compartment. As shown in FIG. 6, when the actual acoustic model C ′ (z) changes, the optimum values of the parameters w ′ ₀ and w ′ ₁ also change. The optimum value 24b indicates a case where only the driver is present in the passenger compartment, and the optimum value 24a indicates a case where passengers are present in the driver seat and the passenger seat respectively in the passenger compartment. Thus, the actual acoustic model C ′ (z) varies depending on the number and arrangement of passengers in the vehicle interior.

In the first embodiment, an initial value set (w ′ ₀ (0),..., Parameter w ′ _i of a plurality of adaptive filters W ′ (z) that differ depending on the number and arrangement of passengers is stored in the database. w ′ _I-1 (0)) is accumulated, and the adaptive filter controller 4 sets the initial value of the parameter w ′ _i of the adaptive filter W ′ (z) selected based on the number and arrangement of passengers detected by the seating sensor. Update of the parameter w ′ _i shown in the equation (10) is started from the set (w ′ ₀ (0),..., W ′ _I−1 (0)). In the first embodiment, it is assumed that the acoustic model C (z) does not change according to the number and arrangement of passengers.

Since the initial value set (w ′ ₀ (0),..., W ′ _I-1 (0)) as many as the number of occupants and the number of combinations is stored in the memory, the number of occupants Depending on the arrangement, the initial value set (w ′ ₀ (0),..., W ′ _I-1 (0)) closest to the optimum value can be prepared online, and the initial value set (w ′ Update can be started from ₀ (0),..., W ′ _I-1 (0)). Therefore, the parameter w ′ _i can be converged to the optimum value in a short time. That is, the convergence time can be shortened.

In the first embodiment, an initial value set (w ′ ₀ (0),..., W ′ _I-1 (0)) as many as the number of occupants and the number of arrangement combinations is stored. Storage capacity is required. The required storage capacity increases with increasing number I of parameters w ′ _i of the adaptive filter W ′ (z) and combinations of occupant numbers and arrangements. For example, as shown in FIG. 7, for a vehicle having five seats, the number S of passengers and the number of arrangement combinations S is calculated as 16 according to the equation (11). In addition, (12) Formula is a formula which shows the calculation method in the parenthesis of (11) Formula.

  The first term of the equation (11) indicates a case where there is one occupant. There is no seat where one passenger can sit other than the driver's seat while driving. Therefore, there are only one combination of occupant arrangements in this case. The second term shows the case where there are two passengers. As shown in FIG. 7, it is conceivable that the first person sits in the driver's seat S1 and the second person sits in any one of S2 to S5. Therefore, there are four arrangement combinations. The third term shows the case where there are three passengers. It is conceivable that the first person sits in the driver's seat S1, the second person sits in any of the four seats S2 to S5, and the second person sits in any of the remaining three seats S2 to S5. Therefore, there are six arrangement combinations. The fourth term shows a case where there are four passengers. In this case, since there are five seats in total, one seat is vacant. Therefore, there are four arrangement combinations. The fifth term shows a case where there are five passengers. In this case, since there are five seats in total, there is one arrangement combination. Therefore, 1 + 4 + 6 + 4 + 1 = 16.

Therefore, 16 initial value sets (w ′ ₀ (0),..., W ′ _I−1 (0)) are stored in the memory. The number and arrangement of the occupants are detected by a seating sensor that detects that the occupants are sitting on the seat. The seating sensor is preferably a pressure sensor disposed in the seat. Alternatively, the seating sensor may be an acceleration sensor that is disposed on the floor panel 6 and measures the acceleration of the floor panel 6 when an occupant sits on the seat. The vibration of the floor panel 6 does not spread over a large range. Vibration when the occupant is sitting in the seat S _k is, not spread up to the seat S _{k + 1} next to it. Therefore, the vibration that is measured by the seating sensor arranged corresponding to the seat S _k is due only to the occupant sitting on the seat S _k.

  As shown in FIG. 8, in the active vibration control apparatus according to the first embodiment of the present invention, the database in the control unit 25 includes parameter values of a plurality of adaptive filters 7 that differ depending on the number and arrangement of passengers. Initial value sets # 1 to # 16 are accumulated. First, the seating sensor detects the number and arrangement of passengers sitting on the seats S1 to S5 of the vehicle in FIG. The selection unit 26 selects an initial value set of parameters of the adaptive filter 7 based on the number and arrangement of occupants detected by the seating sensor. The adaptive filter controller 4 starts updating from the initial value set of the parameters of the adaptive filter 7 selected by the selection unit 26 according to the equation (10).

(Second Embodiment)
As described above, the actual acoustic model C ′ (z) that is the acoustic transfer function from the actuator 3 to the microphone 2 varies depending on the air condition in the passenger compartment, and as shown in FIG. When '(z) changes, the optimum value of the parameter w' _i of the adaptive filter 7 also changes. In the first embodiment, the acoustic model C (z) is not changed according to the number and arrangement of passengers. However, in order to shorten the convergence time, it is desirable to update the acoustic model C (z) according to the number and arrangement of occupants so as to approach the actual acoustic model C ′ (z).

In the second embodiment, the initial value set w ′ _i (0) of the parameter w ′ _i of the adaptive filter 7 is set to zero, and the parameter w ′ _{i in} the expression (10) is updated as shown in FIG. Start from the initial value (0,0). However, as shown in the equation (10), the correction (acoustic model C (z) of the acoustic model C (z) used to update the parameter w ′ _i is made closer to the actual acoustic model C ′ (z). Modify).

Since a part of the system 9 is considered to be linear, in order to obtain an actual acoustic model C ′ (z) corresponding to 16 different arrangement combinations, 5 terms corresponding to a vehicle with 5 seats Only C ₁ (z) to C ₅ (z) are required. That is, the acoustic model C (z) includes five seat models C ₁ (z) to C ₅ (z) corresponding to the five seats of the vehicle body on which the occupant sits. The seat model C _k (z) indicates the air condition when an occupant is seated in the k-th seat. The acoustic model C (z) in this case is shown in equation (13), and further generalized equation (13) is shown in equation (14).

Here, the coefficient δ _k is, when you are sitting occupant in the k-th seat S _k is "1", when the occupant is not sitting in the k-th seat S _k is "0".

An IIR filter is used for the acoustic model C (z) in order to reduce the capacity of the memory for storing the data of the seat model C _k (z) and the calculation amount for updating the acoustic model C (z). By using the IIR filter, the number of parameters can be reduced as compared with the FIR filter.

As shown in FIG. 9, the active vibration control apparatus according to the second embodiment of the present invention is different in the configuration of the control unit 25 from that in FIG. 8, and the other configurations are the same. The control unit 25 includes a memory that stores data of the seat model C _k (z), and a coefficient calculation unit 27 that calculates δ _k in Expression (13) from the occupant arrangement information. First, the seating sensor detects the number and arrangement of occupants sitting on the seats S1 to S5 of the vehicle in FIG. 7, and the occupant transfers position information. The coefficient calculation unit 27 calculates δ _k based on the number and arrangement of passengers detected by the seating sensor. Then, the control unit 25 uses the coefficient δ _k calculated by the coefficient calculation unit 27 and the data of the seat model C _k (z) stored in the memory to calculate the acoustic model C (z) according to the equation (13). The actual model C ′ (z) is corrected. The adaptive filter controller 4 starts updating from the initial value set (0, 0) of the parameters of the adaptive filter 7 according to the equation (10) using the actual model C ′ (z).

The control unit 25 adds the seat model C _k (z) corresponding to the seat on which the occupant is seated to add the acoustic model C (z) to the reality as shown in the equation (13). To the model C ′ (z).

  As described above, according to the second embodiment, the convergence time is improved by correcting the acoustic model C (z) according to the number and arrangement of passengers and bringing it closer to the actual acoustic model C ′ (z). Can be shortened.

(Third embodiment)
In the third embodiment, an active vibration control device combining the first embodiment and the second embodiment will be described.

Here, as the initial value set w ′ _k (0) of the parameter w ′ _k of the adaptive filter 7, all initial value sets w ′ _k (0) corresponding to the combination of the number of passengers and the arrangement are stored in the memory. Without updating, the parameter w ′ _k is updated using the initial value set w ′ _k (0) close to the optimum value and using the actual model C ′ (z) as the acoustic model C (z). Further, another initial value set w ′ _k (0) is calculated online from one initial value set w ′ _k (0) stored in the memory.

As shown in FIG. 10, when there are two combinations of the number and arrangement of occupants including case #i and case #j, the optimum value sets 24i and 24j are different in case #i and case #j. In the third embodiment, the initial value set 26j of the other case (case #j) is calculated from the initial value set 26i of one case (case #i) stored in the memory. For example, consider the case where there are three passengers. The update of the parameters w ′ _{k, # j} is performed by _changing the initial value set (w ′ _{0, # j} (0),..., W ′ _{I−1, #} ) rather than the initial value set (0,..., 0). _j (0)) has a shorter convergence time. Therefore, as shown in FIG. 11, the calculation initial values (w ′ _{0, # j} (0),..., W ′ _{I−1, # j} (0)) are used as reference initial values stored in the memory. (W ′ _{0, # i} (0),..., W ′ _{I−1, # i} (0)). Here, the reference initial value (w ′ _{0, # i} (0),..., W ′ _{I−1, # i} (0)) is an initial value set w of the parameter w ′ _k corresponding to case #i. ' _k (0).

In the calculation of the initial operation value (w ′ _{0, # j} (0),..., W ′ _{I−1, # j} (0)) in case #j, equation (15) modified from equation (10) Is used.

Here, r ′ (ni) is expressed by equation (16).

Here, the filter C _#i (z) of the acoustic model C (z) corresponds to the case #i. When only the driver is in the vehicle in case #i, C _#i (z) = C ₁ (z). The coefficient η is calculated as large as possible to approach the optimum value of case #j, but protects the stability of the algorithm. The equation (17) can be used to fix the coefficient η.

Here, I indicates the number of parameters w ′ _k of the active filter W ′ (z), and x ² is the root mean square value of the signal x (n).

Reference initial values (w ′ _{0, # i} (0),..., W ′ _{I−1, # i} (0)) are initial values corresponding to case #i, and other initial values are initially calculated. It is used when calculating according to equation (15) as a value. The most common configuration for the number and arrangement of passengers is the case where only the driver is on board. This is case # 1. Therefore, it is desirable to use the initial value set (w ′ _{0, # 1} (0),..., W ′ _{I−1, # 1} (0)) of case _{# 1} as the reference initial value. Of course, cases other than the case # 1 in which only the driver is in the vehicle may be set as the reference initial value.

Consider a case where the adaptive filter 7 includes two parameters w ′ ₀ and w ′ ₁ and updates the parameters w ′ ₀ and w ′ ₁ of the three cases #i, #j and #k. In the three cases #i, #j, and #k, there are initial value sets of the parameters w ′ ₀ and w ′ ₁ corresponding to the combination of the number of passengers and the arrangement, respectively. As shown in FIG. 12, there is a distance d _{# i, # k} between the initial value set 26k of case #k and the initial value set 26i of case #i. There is a distance d _{# j, # k} between the initial value set 26k of #k and the initial value set 26j of case #j. Between the initial value set 26i of case #i and the initial value set 26j of case #j Has a distance d _{# i, # j} . These distances (for example, distance d _{#i, #j} ) are defined by equation (18).

Between the initial value sets of three or more cases, there is a case where the distance between the initial value sets with other cases is the smallest. For example, as shown in FIG. 12, the initial value set of case #i has the shortest distance to the initial value sets of the other two cases #j and #k. Therefore, in this case, only the initial value set 26i of the case # 1 is stored in the memory as the reference initial value, and the initial value sets of the other two cases #j and #k are the reference initial values according to the equation (15). 26i is calculated. The calculated initial value set 26j of case #j and initial value set 26k of case #k are values close to the respective optimum values. Accordingly, the time required for updating the parameter w ′ _k of the active filter W ′ (z) can be shortened, and at the same time, the number of initial values stored in the memory can be reduced to one. Can be reduced.

On the other hand, the acoustic model C (z) includes N seat models C ₁ (z) to C _N (z) corresponding to the N seats of the vehicle body on which the occupant sits, as shown in FIG. The seat model C _k (z) indicates the air condition when an occupant is seated in the k-th seat. The acoustic model C (z) in this case is shown in equation (14). The coefficient calculation unit 27 calculates δ _k based on the number and arrangement of passengers detected by the seating sensor. Then, the control unit 25 uses the coefficient δ _k calculated by the coefficient calculation unit 27 and the data of the seat model C _k (z) stored in the memory to calculate the acoustic model C (z) according to the equation (14). The actual model C ′ (z) is corrected.

In addition, when additional information is obtained, the additional information is used. For example, as shown in FIG. 13, if it is possible to know the weight of the occupant sitting on the seat S _k using a pressure sensor embedded in the seat, the parameters of the seat model _{C 1 (z) ~C N (} z) You may change according to a passenger | crew's weight.

Thus, by improving the accuracy of the seat models C ₁ (z) to C _N (z), the acoustic model C (z) is improved, and further, the parameter w ′ _k of the active filter W ′ (z). Updates are also improved. That is, the convergence time required for updating the parameter w ′ _k is shortened.

  With reference to FIG. 14, the processing procedure of the active vibration control apparatus according to the third embodiment will be described.

  (A) In step S01, the seating sensor detects the number and arrangement of occupants sitting on the seats S1 to S5 of the vehicle shown in FIG. In step S02, it is determined whether the current number and arrangement of passengers are the same as the previous number and arrangement. If the current number of passengers and arrangement are the same as the previous time (YES in step S02), the process proceeds to step S03, and if the current number of passengers and arrangement is not the same as the previous time (NO in step S02), the process proceeds to step S04.

(B) The initial value is set to 1 in step S03, and the initial value is set to 0 in step S04. Thereafter, the process proceeds to S05 step, measuring the weight of the occupant sitting on the seat S _k using a pressure sensor embedded in the seat. In step S06, a seat model C _k (z) is calculated. In S07 step, the coefficient calculating unit 27 calculates the [delta] _k based on the number and arrangement of an occupant seating sensor detects. In step S08, the control unit 25 uses the coefficient δ _k calculated by the coefficient calculation unit 27 and the seat model C _k (z) to convert the acoustic model C (z) to the actual model C ′ ( Modify to z).

  (C) In step S09, it is determined whether or not the update is on. If the update is on (YES in step S09), the process proceeds to step S10. If the update is off (NO in step S09), the process proceeds to step S15. In step S10, it is determined whether or not the initial value is zero. If the initial value is zero (YES in step S10), the process proceeds to step S11. If the initial value is not zero (NO in step S10), the process proceeds to step S15.

(D) In step S11, the reference initial value 29 of FIG. 11 of the parameter w ′ _i is called from the memory. In step S12, it is determined whether or not the current number and arrangement of occupants are the same as the number and arrangement of occupants corresponding to the reference initial value 29. When the current number and arrangement of passengers are the same as the reference initial value 29 (YES in step S12), the process proceeds to step S13, and the initial value is set to 1. When the current number and arrangement of passengers are different from the reference initial value 29 (NO in step S12), the process proceeds to step S14, and the calculation initial value 28 is calculated using the reference initial value 29. Then, it progresses to S13 stage.

(E) Thereafter, in step S15, the adaptive filter controller 4 repeatedly updates the parameter w ′ _i from the calculation initial value 28 according to the equation (10). It is determined whether or not the condition shown in step S16 is satisfied. If it is satisfied (YES in step S16), the process proceeds to step S17, and the update is set to an off state. If not satisfied (NO in step S16), the process proceeds to step S18, and the update is set to an on state.

  As described above, the present invention has been described according to the first to third embodiments. However, it should not be understood that the description and drawings constituting a part of this disclosure limit the present invention. From this disclosure, various alternative embodiments, examples and operational techniques will be apparent to those skilled in the art. That is, it should be understood that the present invention includes various embodiments not described herein. Therefore, the present invention is limited only by the invention specifying matters according to the scope of claims reasonable from this disclosure.

It is a block diagram which shows the adaptive filter controller mounted in the vehicle as an example of the active vibration control apparatus concerning the 1st Embodiment of this invention. 1 is a block diagram showing an entire active vibration control apparatus according to an embodiment of the present invention. It is sectional drawing which shows the vehicle by which the active vibration control apparatus of FIG. 1 is mounted, and a top view which shows the floor panel part of a vehicle. It is a top view which shows the member arrange | positioned on the floor panel of FIG. Parameter w _'i is a graph showing a path that converges in the active vibration control apparatus according to the first embodiment. It is a graph which shows the change of the optimal value of the parameter of an active filter when actual acoustic model C '(z) changes. It is a top view which shows a vehicle provided with five seats. 1 is a block diagram showing an entire active vibration control apparatus according to a first embodiment of the present invention. It is a block diagram which shows the whole active vibration control apparatus concerning the 2nd Embodiment of this invention. It is a graph which shows two initial values and optimal value corresponding to two combinations from which the number of passengers and arrangement differ. It is a block diagram which shows the whole active vibration control apparatus concerning 3rd Embodiment. It is a graph showing the distance between the active filter W plurality of initial values of _k 'parameter w of (z)'. It is a block diagram which shows the whole active vibration control apparatus concerning the modification of 3rd Embodiment. It is a flowchart which shows the process sequence of the active vibration control apparatus concerning 3rd Embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Acceleration sensor 2 ... Microphone 3 ... Actuator 4 ... Adaptive filter controller 5 ... Car body 6 ... Floor panel 7 ... Adaptive filter 8 ... Adaptive low 9 ... System 10a ... Tire 11 ... Road surface 15 ... Cabin floor 16 ... Tank panel 17 ... Spare Tire panel 18a-18d ... Vertical member 19a-19d ... Horizontal member 20 ... Vibration model 21 ... Acoustic model 22, 23 ... Convergence path 24, 24a, 24b, 24i, 24j ... Optimal value set 25 ... Control unit 26 ... Selection unit 26i , 26j, 26k ... initial value set 27 ... coefficient calculation unit 28 ... calculation initial value

Claims (9)

A sensor for measuring a physical quantity related to vibration or noise of the vehicle body;
An actuator disposed on a floor panel of the vehicle body and generating distortion in the floor panel;
An adaptive filter controller that repeatedly updates an adaptive filter parameter for controlling the actuator toward an optimum value and cancels the vibration or noise transmitted to the vehicle body by controlling the actuator based on the physical quantity; and
A seating sensor for detecting that the occupant is seated in a seat of the vehicle body on which the occupant sits;
A database for storing an initial value set of parameters of the adaptive filter,
The database stores an initial value set of a plurality of parameters of the adaptive filter that differ depending on the number and arrangement of the occupants,
The said adaptive filter controller starts an update from the initial value set of the parameter of the said adaptive filter selected based on the number and arrangement | positioning of the said passenger | crew which the said seating sensor detects, The active vibration control apparatus characterized by the above-mentioned.   The active vibration control device according to claim 1, wherein the seating sensor is a pressure sensor disposed in the seat.   The active vibration control device according to claim 1, wherein the seating sensor is an acceleration sensor disposed on the floor panel and measuring an acceleration of the floor panel when the occupant sits on the seat. . A sensor for measuring a physical quantity related to vibration or noise of the vehicle body;
An actuator disposed on a floor panel of the vehicle body and generating distortion in the floor panel;
An adaptive filter controller that repeatedly updates an adaptive filter parameter for controlling the actuator toward an optimum value and cancels the vibration or noise transmitted to the vehicle body by controlling the actuator based on the physical quantity; and
A seating sensor for detecting that the occupant is seated in a seat on which the occupant of the vehicle body sits;
A database for storing an initial set of parameters of the adaptive filter;
A controller that corrects an acoustic model, which is a conversion function from the actuator to the sensor, into an actual model based on the number and arrangement of the occupants detected by the seating sensor;
The said adaptive filter controller updates the parameter of the said adaptive filter using the said acoustic model which the said control part corrected, The active vibration control apparatus characterized by the above-mentioned.   The acoustic model includes a plurality of seat models corresponding to the plurality of seats of the vehicle body on which the occupant sits, and the control unit adds all of the seat models corresponding to the seats on which the occupant is sitting. The active vibration control device according to claim 4, wherein the acoustic model is corrected to the actual model.   The active vibration control device according to claim 5, wherein the seat model corresponding to the seat on which the occupant is seated is modified according to the weight of the occupant. A sensor for measuring a physical quantity related to vibration or noise of the vehicle body;
An actuator disposed on a floor panel of the vehicle body and generating distortion in the floor panel;
An adaptive filter controller that repeatedly updates an adaptive filter parameter for controlling the actuator toward an optimum value and cancels the vibration or noise transmitted to the vehicle body by controlling the actuator based on the physical quantity; and
A seating sensor for detecting that the occupant is seated in a seat of the vehicle body on which the occupant sits;
A database for storing an initial set of parameters of the adaptive filter;
A controller that corrects an acoustic model, which is a conversion function from the actuator to the sensor, into an actual model based on the number and arrangement of the occupants detected by the seating sensor;
The control unit calculates an initial value set of a plurality of adaptive filter parameters that differ depending on the number and arrangement of the occupants from the one initial value set accumulated in the database,
The adaptive filter controller starts updating from the initial value set calculated by the control unit using the acoustic model corrected by the control unit.   The one initial value set stored in the database is an initial value set having a shortest distance from another initial value set that varies depending on the number and arrangement of the occupants. 8. The active vibration control device according to 7.   The control unit changes parameters of a plurality of seat models constituting the acoustic model based on the number and arrangement of the occupants detected by the seating sensor when the acoustic model is corrected to the actual model. 9. The active vibration control device according to claim 7 or 8, wherein:

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