JP2006131137A - Signal processing device for vehicle - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a signal processing device for a vehicle capable of estimating internal environment and external environment of the traveling of the vehicle by using only a signal detected during traveling. <P>SOLUTION: This device has a vibration detection means for detecting vibration of a prescribed direction of a tire under a vehicle spring, a reference frequency component extraction means for extracting a frequency component to be a reference value from a prescribed frequency band from the vibration detected in the vibration detection means, a comparison frequency component extraction means for extracting a frequency component to be a comparison value from the prescribed frequency band from the vibration detected in the vibration detection means, and an estimation means for estimating at least an environment of the internal environment and external environment of the traveling of the vehicle based on the combination of the frequency components including the frequency component to be the reference value and the frequency component to be the comparison value. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a vehicle signal processing apparatus that estimates an internal environment and an external environment related to traveling of a vehicle.

  In order to improve traveling safety of the vehicle, for example, a tire air pressure detection device disclosed in Patent Document 1 is used.

According to the tire pressure detecting device described in Patent Document 1, frequency detection is performed on the detection signal of the wheel speed sensor, and the resonance frequency in the vertical direction and the front-rear direction under the spring of the vehicle is calculated. Detect the state of. This is focused on the fact that when the tire air pressure decreases, both the vertical and longitudinal resonance frequencies decrease, and the resonance frequency is set in one or both directions and the normal tire pressure. Compared with the initial frequency being used, a warning is given of a decrease in tire air pressure.
Japanese Patent Laid-Open No. 5-133831

  However, the initial frequency set corresponding to the normal tire pressure varies depending on the type of tire. Therefore, in the tire air pressure detection device described in Patent Document 1, in order to improve detection accuracy, an initial frequency corresponding to a tire attached to a vehicle must be stored in advance. Further, when the user changes the tire, it is necessary to change the stored initial frequency by some means.

  The present invention has been made in view of such a problem, and is a vehicle signal processing device that can estimate an internal environment and an external environment related to running of a vehicle by using a signal detected during running of the vehicle. For the purpose of provision.

  According to the first aspect of the present invention, when the vehicle travels, the vibration detection means for detecting the vibration in the predetermined direction of the tire under the vehicle spring, and the frequency component serving as the reference value from the vibration detected by the vibration detection means is a predetermined frequency. Reference frequency component extracting means for extracting from a band, comparison frequency component extracting means for extracting a frequency component to be a comparison value from a predetermined frequency band from vibration detected by the vibration detecting means, and a frequency component to be a reference value and a comparison value The vehicle signal processing apparatus includes an estimation unit that estimates at least one of an internal environment and an external environment related to traveling of the vehicle based on a combination of frequency components including a frequency component. The vibration detection means detects vibrations in at least the first direction and the second direction, and the reference frequency component extraction means extracts a frequency component serving as a reference value from the vibration in the first direction from a predetermined frequency band, The comparison frequency component extraction unit may extract a frequency component serving as a comparison value from the vibration in the second direction from a predetermined frequency band.

  In this way, by combining the frequency components detected during vehicle travel, the environment can be accurately estimated without storing in advance the initial value that is changed in accordance with changes in the internal environment or the external environment. it can.

  Further, the direction may be any one of the vertical direction of the vehicle, the front-rear direction of the vehicle, the left-right direction of the vehicle, and the rotation direction of the tire. Further, in the vibration detection means, the vertical vibration is detected from one of an acceleration sensor attached to a non-rotating portion under the vehicle spring and outputting vertical acceleration and a wheel speed sensor. Alternatively, the vibration in the front-rear direction may be detected from any one of an acceleration sensor that is attached to a non-rotating part under the vehicle spring and outputs the acceleration in the front-rear direction, and a wheel speed sensor. The vibration in the left-right direction may be detected from the signal of the acceleration sensor that is attached to the non-rotating part under the vehicle spring and outputs the acceleration in the left-right direction. The vibration in the rotation direction is detected from the signal of the wheel speed sensor. May be.

  Thus, reliability can be improved by using the acceleration sensor attached to the non-rotating part under the vehicle spring. In addition, by using a conventionally used wheel speed sensor, a vehicle signal processing device can be provided at low cost.

  According to an eighth aspect of the present invention, vehicle speed detecting means for detecting the speed of the vehicle, reference value correcting means for correcting the frequency component serving as a reference value based on the vehicle speed, and a frequency component serving as a comparison value depending on the vehicle speed. And an estimation means for estimating the environment based on a combination of frequency components including the frequency component corrected by the reference value correction means and the frequency component corrected by the comparison value correction means. It is characterized by doing. Moreover, it has a vehicle speed detection means which detects the speed of a vehicle, and an estimation means may correct | amend estimation of an environment with the speed of a vehicle.

  Thereby, the estimation error resulting from the speed of the vehicle can be reduced.

  The invention according to claim 10 has vibration characteristic calculation means for calculating a substitute value from the frequency component, and the estimation means estimates the environment using the substitute value calculated by the vibration characteristic calculation means. It is characterized by.

  Thereby, the estimation accuracy of the environment can be improved and the time required for the estimation can be shortened.

  Further, the vibration characteristic calculation means may shorten the time length of the frequency component used for the calculation when the time elapsed until the environment changes is short, and lengthen the time length when the time passage is long.

  That is, some of the environments estimated in the present invention change rapidly, while others change over time. Therefore, it is possible to detect a rapid environmental change earlier by considering the time elapsed until the environment changes. On the other hand, when the estimation is performed with a longer time length, the noise is canceled and the estimation accuracy is improved.

  According to the twelfth aspect of the present invention, the estimation means may estimate at least one of a vehicle momentum, a vehicle posture, a vehicle body vibration, a tire grip, and a tire state as an internal environment. . The estimation means may estimate at least a road surface state where the vehicle travels as an external environment. Further, the estimating means may estimate at least one of a vehicle slip angle and a vehicle yaw rate as a vehicle momentum, and may determine a vehicle roll angle, a vehicle pitch angle, a vehicle height as a vehicle attitude. At least one of the above may be estimated, and as the grip of the tire, at least one of the grip force in the front-rear direction of the tire and the lateral force of the tire may be estimated. It is also possible to estimate at least one of air pressure, tire load, tire abnormality, tire wear, and tire type. Further, the estimation means may estimate any one of road surface unevenness, road surface shape, road surface gradient, and road surface friction coefficient as the road surface state.

  As described above, according to the present invention, it is possible to estimate various environments related to running of the vehicle using vibrations under the vehicle spring.

  The invention described in claim 19 is characterized by comprising storage means for storing a reference value and a comparison value corresponding to the environment.

  What values are used as the reference value and the comparison value may be different for each vehicle type, for example. Therefore, the environment estimation accuracy can be improved by storing appropriate reference values and comparison values in advance.

The invention according to claim 20 is the case where the same environment is estimated for each of the plurality of tires.
Comprehensive determination means for comprehensively determining the environment based on estimation of the environment for each of the plurality of tires.

  Thereby, the environment can be estimated more specifically.

  In the invention according to claim 21, in the case where the same environment is estimated for each of the plurality of tires, based on the estimation of the environment for each of the plurality of tires, whether or not the environment is an abnormal state that poses a danger to the running of the vehicle. First abnormality determining means for determining In addition, based on vibration in a direction different from each frequency component used for estimation in the estimation unit, second estimation unit for estimating the same environment as the environment estimated in the estimation unit, estimation of the environment in the estimation unit, and second Based on the estimation of the environment in the estimation means, and a second abnormality determination means for determining whether or not the environment is an abnormal state that poses a danger to the running of the vehicle, the second abnormality determination means is estimated in the estimation means If the environment is abnormal and the environment estimated by the second estimating means is abnormal, it is determined that the environment is abnormal and the environment estimated by the estimating means is not abnormal, or the second If the environment estimated by the estimation means is not in an abnormal state, it may be determined that the environment is not in an abnormal state.

  As a result, it is possible to reduce erroneous determination as to whether or not the estimated environment is an abnormal state that poses a danger to the traveling of the vehicle.

  According to a twenty-third aspect of the present invention, there is provided a warning means for warning the driver of the vehicle based on the environment estimated by the estimation means.

  Thereby, the estimated environment can be notified to the driver, and appropriate measures can be promoted.

  Furthermore, according to a twenty-fourth aspect of the present invention, the vehicle is characterized by further comprising a traveling control unit that controls the traveling of the vehicle based on the environment estimated by the estimating unit.

  Thereby, it is possible to take measures according to the estimated environment, and it is possible to contribute to the reduction of accident occurrence.

  A vehicle signal processing device according to an embodiment of the present invention will be described with reference to the drawings. In addition, this invention is not limited by the following Example, All the aspects which embody the idea of this invention are included.

  FIG. 1 is a configuration diagram of a vehicle signal processing device 100 according to the present embodiment. This shows only one arbitrary system among a plurality of tires attached to the vehicle. The vehicle signal processing device 100 includes a vibration detection unit 110 and a signal processing unit 120.

  The vibration detection unit 110 includes a vertical acceleration sensor 111 that detects vertical acceleration under a vehicle spring, a longitudinal acceleration sensor 112 that detects longitudinal acceleration, a lateral acceleration sensor 113 that detects lateral acceleration, and It is composed of a wheel speed sensor 114. Each sensor detects vibrations in the vertical direction, the front-rear direction, the left-right direction, and the rotation direction. However, the vibrations in the front-rear direction and the vertical direction may be extracted from the signal from the wheel speed sensor 114. As the wheel speed sensor, for example, a known electromagnetic pickup sensor or the like is used.

  The signal processing unit 120 includes a filter unit 131, a vibration characteristic calculation unit 141, a road surface state estimation unit 151, a tire state estimation unit 152, a vehicle motion estimation unit 153, a vehicle posture estimation unit 154, a vehicle body vibration estimation unit 155, and a grip estimation unit. 156. The filter unit 131 extracts a frequency component in a desired band from the vibration detected by the vibration detection unit 110 using a low-pass filter, a high-pass filter, or a band-pass filter. The vibration characteristic calculation unit 141 obtains a substitute value from the frequency component and calculates a substitute value in each frequency band.

  The estimation units 151 to 156 estimate each environment by combining two or more of the substitute values calculated by the vibration characteristic calculation unit 141. The road surface state estimation unit 151 estimates an environment related to a road surface state such as a road surface friction coefficient, road surface unevenness, road surface shape, and gradient. The tire state estimation unit 152 estimates a tire environment such as tire abnormality such as tread peeling or rupture, tire air pressure, tire load, tire type such as studless, and tire wear. The vehicle motion estimation unit 153 estimates an environment related to motion such as vehicle speed, longitudinal and lateral acceleration, slip angle, and yaw rate. The vehicle posture estimation unit 154 estimates an environment related to a posture such as a roll angle, a pitch angle, and a vehicle height. The vehicle body vibration estimation unit 155 estimates an environment related to vehicle body vibration such as vertical vibration. The grip estimation unit 156 estimates the environment related to the grip of the tire such as the wheel speed, the front and rear grip force of the tire, and the tire lateral force.

  Note that the vehicle signal processing apparatus 100 does not have to include all the sensors 111 to 114 and all the estimation units 151 to 156, and includes any one or two sensors and any one estimation unit. It only has to have. Hereinafter, in the present embodiment, a vehicle signal processing device 100 including the vertical acceleration sensor 111, the longitudinal acceleration sensor 112, the road surface state estimation unit 151, and the tire state estimation unit 152 will be described.

  FIG. 2 shows attachment positions of the vertical acceleration sensor 111 and the longitudinal acceleration sensor 112 with respect to an arbitrary tire 10. The acceleration sensors 111 and 112 are attached to the hub 21 fixed to the tire 10. The hub 21 is connected to the shaft 22 and the suspension 23. As described above, the vertical acceleration sensor 111 and the longitudinal acceleration sensor 112 are attached to the non-rotating portion below the vehicle suspension 23, that is, below the vehicle spring. For example, in the case of a four-wheeled vehicle, acceleration sensors 111 and 112 are attached to the positions shown in FIG. 2 for each of four tires or each of two non-drive wheels. Moreover, the left-right direction acceleration sensor 113 and the wheel speed sensor 114 are also attached at the same position. Note that the vertical acceleration sensor 111 and the longitudinal acceleration sensor 112 may be mounted integrally in the wheel speed sensor 114.

  The signal processing unit 120 is incorporated in an electronic control device (hereinafter referred to as ECU) (not shown), and acquires signals detected by the acceleration sensors 111 and 112 via the in-vehicle LAN.

  First, in this embodiment, the principle of estimating the tire air pressure, the road surface friction coefficient, and the like will be described. FIG. 3 shows a simplified feature of acceleration changes with respect to changes in tire or road surface conditions. When the tire air pressure decreases, the spring constant of the tire rubber portion decreases, so the vertical acceleration decreases, but the longitudinal acceleration increases due to tire distortion. Further, when an abnormality occurs in the tire, the acceleration in the vertical direction increases and the acceleration in the front-rear direction also increases. On the other hand, when the road surface friction coefficient decreases, the tire easily rotates, and the longitudinal acceleration decreases. Thus, the change in acceleration in the up-down direction and the front-rear direction has characteristics corresponding to changes in the tire and road surface environment, respectively.

  FIG. 4 shows simplified frequency characteristics of acceleration with respect to changes in the tire or road surface condition. When the road surface friction coefficient decreases, the vertical acceleration is characterized by low to medium frequency components, and the longitudinal acceleration is characterized by medium to high frequency components. Further, when the road surface shape changes, the vertical acceleration is characterized by a high frequency component, and the longitudinal acceleration is characterized by a low frequency component. On the other hand, when the tire air pressure decreases, the vertical acceleration is characterized by low to medium frequency components, and the longitudinal acceleration is characterized by low frequency components. Further, when the tire is worn, acceleration appears in the middle to high frequency components in both the vertical direction and the longitudinal direction. As described above, the frequency characteristics extracted from the acceleration in the vertical direction and the longitudinal direction also change in accordance with the change in the state of the tire and the road surface.

  Next, tire state and road surface state estimation processing in the present embodiment will be described. The tire state is an example of an internal environment related to traveling of the vehicle, and the road surface state is an example of an external environment. The internal environment refers to the environment related to the traveling vehicle itself, and the external environment refers to the surrounding environment other than the vehicle.

  FIG. 5 is a flowchart of signal processing executed in the signal processing unit 120. This process is repeated at predetermined timings while the vehicle is traveling. Since the signal processing unit 120 performs the same processing on each tire, in this embodiment, processing for an arbitrary tire 10 is shown.

  In step S <b> 1001, the signal processing unit 120 acquires acceleration in the vehicle vertical direction from the vertical acceleration sensor 111. In step S <b> 1002, the signal processing unit 120 acquires acceleration in the vehicle longitudinal direction from the longitudinal acceleration sensor 112. Then, the signal processing unit 120 performs filter processing (S1003) and vibration characteristic calculation processing (S1004) on the acceleration in the vertical direction. Similarly, the signal processing unit 120 performs the filter process (S1005) and the vibration characteristic calculation process (S1006) for the acceleration in the longitudinal direction.

  FIG. 6 is a flowchart of the filter processing (S1003, S1005). In S2001, the signal processing unit 120 cuts frequency components of 1 Hz or less and 200 Hz or more, which are greatly affected by noise, by passing the bandpass filter in S2002 with respect to the acceleration frequency components in a certain period. Further, in S2003 to S2005, the signal processing unit 120 extracts a low-frequency component, a high-frequency component, and a medium-frequency component of acceleration using a low-pass filter and a high-pass filter. Note that the frequency band may be further subdivided and extracted using a bandpass filter or the like. FIG. 7 is a graph showing an example of filter processing for acceleration. The horizontal axis represents time [sec], and the vertical axis represents acceleration [G]. FIG. 7A shows a vibration waveform after passing through a 1 Hz high-pass filter. (B) is a low-frequency component extracted by a 50 Hz moving average low-pass filter, and (c) is a high-frequency component extracted by a 50 Hz moving average high-pass filter.

  FIG. 8 is a flowchart of the vibration characteristic calculation processing (S1004, S1006). In step S3001, the signal processing unit 120 calculates an absolute average value, that is, an average value obtained by taking the absolute value, from the frequency component having a predetermined time length extracted by the filter processing. If it is determined negative in S3002, that is, if the calculation of absolute average values for the low frequency, high frequency, and medium frequency components extracted in S2003 to S2005 has not been completed, the process returns to S3001. On the other hand, if the determination in step S3002 is affirmative, the vibration characteristic calculation process ends. As a substitute value calculation method, the sum of squared deviation, variance, standard deviation, range (from minimum value to maximum value), distortion, sharpness, rank value (values in any rank when arranged in order of size) Etc. may be used.

  Then, the signal processing unit 120 performs estimation of the tire condition (S1007) and estimation of the road surface condition (S1008) using the substitute values of these frequency components in the vertical direction and the front-rear direction. In the present embodiment, description will be given by taking three environments, ie, tire abnormality, tire air pressure, and tire wear as tire conditions, and two environments as road surface irregularities and road friction coefficient as road conditions. Note that the signal processing unit 120 only needs to be able to estimate any one of these environments, but can also simultaneously estimate a plurality of environments as necessary.

  The signal processing unit 120 uses two substitute values according to the environment to be estimated among the substitute values of each frequency component for the vertical and longitudinal accelerations calculated in the vibration characteristic calculation processing (S1004, S1006). Here, which substitute value is used is statistically determined in advance from each frequency characteristic when the environment is changed. That is, among the frequency components with respect to the acceleration in the vertical direction and the longitudinal direction, a frequency component in which the fluctuation at the resonance point is remarkable when the environment changes or a frequency component without the fluctuation is used. Preferably, the frequency component having the strongest correlation with the actual measurement value is employed by combining the substitute values of the two frequency components. Each of the estimation units 123 to 128 stores the frequency component values employed as a table.

  FIG. 9 is an example of a table showing two substitute values (reference value and comparison value) according to the environment to be estimated. When estimating tire abnormality, the high frequency component X3 of the acceleration in the front-rear direction is set as a reference value, and the low frequency component X1 is set as a comparison value. When estimating the tire air pressure, the medium frequency component Z2 in the vertical direction acceleration is used as a reference value, and the medium frequency component X2 in the longitudinal direction acceleration is used as a comparison value. When estimating tire wear, the low frequency component Z1 of acceleration in the vertical direction is set as a reference value, and the medium frequency component Z2 is set as a comparison value. When estimating road surface unevenness, the low frequency component Z1 of acceleration in the vertical direction is used as a reference value, and the high frequency component Z3 is used as a comparison value. When estimating the road surface friction coefficient, the high frequency component Z3 of acceleration in the vertical direction is used as a reference value, and the high frequency component X3 of acceleration in the front and rear direction is used as a comparison value. Which is used as a reference value is arbitrary, and a frequency component with a small variation with respect to environmental changes may be used as the reference value. If the substitute value used as the reference value is a value that does not vary with changes in the environment, the substitute value itself can be stored in advance, and the process of calculating the reference value can be omitted. In addition, when the environment to be estimated is known, the estimation process can be simplified by extracting only the frequency components that are the reference value and the comparison value. In addition, it has been empirically found that the environment targeted by the present invention can be estimated by using a frequency component of 1 [Hz] to 200 [Hz] as shown in S2001.

  Here, the wheel speed in the rotation direction may be used instead of the acceleration in the front-rear direction. Since both frequency characteristics have many points in common, it is possible to derive a table similar to FIG. Further, in the vertical direction, the frequency component of the vertical vibration extracted from the signal of the wheel speed sensor 114 can be substituted.

  In addition, the number of frequency bands to be used as the reference value or comparison value for the longitudinal or vertical acceleration may vary depending on the environment, and the unsprung characteristics of each vehicle type It may be changed depending on. Thereby, estimation accuracy can be further improved. It is possible to derive a table as shown in FIG. 9 by statistically determining each vehicle type or correcting the frequency band determined for any vehicle type with the unsprung characteristics.

  The signal processing unit 120 estimates the environment using a correlation between the substitute value of the reference value and the comparison value and the actual measured value of the environment. For example, FIG. 10 is a graph showing the correlation between the ratio of the reference value substitute value Z3 and the substitute value substitute value X3 used for the estimation of the road surface friction coefficient and the measured value of the road surface friction coefficient. Under a single condition that the environment other than the road surface friction coefficient is constant, there is a correlation of a contribution rate of about 97% with the actually measured value. In addition, when there is a certain correlation by combining other than the reference value and the comparison value, a specific environment may be estimated comprehensively by combining three or more frequency components.

  Based on this correlation, the signal processing unit 120 estimates the road surface friction coefficient from the reference value substitute value Z3 and the comparison value substitute value X3. As the estimated value, the absolute value of the road surface friction coefficient can be obtained instead of the relative value from the initial value given in advance. FIG. 11 is a graph showing the relationship between the measured value and the estimated value of the road surface friction coefficient. The road surface friction coefficient can be estimated with an accuracy of approximately 80% in an environment (composite condition) in which not only the road surface friction coefficient but also the road surface shape, tire type, and tire wear state change.

  An external environment such as a road surface friction coefficient may be estimated from one arbitrary tire system shown in FIG. 1 or may be comprehensively determined from estimated values related to a plurality of tires. For example, the road surface friction coefficient near the center of the road may be determined from the estimated values regarding the right front wheel and the right rear wheel, and the road surface friction coefficient near the left end of the road may be determined from the estimated values regarding the left front wheel and the left rear wheel. Thereby, it is possible to estimate a road or the like where there is snow only at the left end. In this way, by comprehensively determining using estimations regarding a plurality of tires, it is possible to estimate the environment in more detail than when estimating the environment from one tire.

  By processing similar to the estimation of the road surface friction coefficient, the signal processing unit 120 uses the reference value and the substitute value of the comparison value shown in FIG. 9 to detect tire abnormality, tire pressure, tire wear, tire type, road surface. Estimate the environment such as unevenness. Further, the signal processing unit 120 determines whether the signal is from the acceleration sensors 111 and 112 attached to the tire of the right front wheel, the left front wheel, the right rear wheel, or the left rear wheel. The internal environment such as air pressure and tire wear can be estimated for each tire. The signal processing unit 120 can estimate not only one of these environments, but can simultaneously estimate a plurality of environments as necessary.

  As described above, the vehicle signal processing apparatus 100 can accurately estimate the internal environment and the external environment related to the traveling of the vehicle based on the combination of specific frequency components with respect to acceleration in a specific direction. Since the acceleration in the non-rotating part under the vehicle spring is used, the reliability is high and various environments related to the traveling of the vehicle can be estimated. Furthermore, the signal processing apparatus 100 for vehicles can also be provided cheaply by diverting the signal of the wheel speed sensor 114 conventionally used in the vehicle.

  In addition, since the signal processing unit 120 can estimate the tire state only from the value detected while the vehicle is running, it is not necessary to store the initial frequency corresponding to the tire in advance or to store it again every time the tire is replaced. Furthermore, since the signal processing unit 120 can estimate the absolute value of the environment, it is not necessary to previously store values in a steady state, for example, a road surface friction coefficient of dry asphalt or a tire state before starting running.

  Further, by using the substitute value, estimation using each frequency characteristic can be performed in a short time.

  In this embodiment, the estimation of the internal environment and the external environment related to the traveling of the vehicle is performed, but the vehicle signal processing device 100 may issue a warning to the driver based on the estimated value. For example, when the signal processing unit 120 estimates that the tire air pressure is below a certain value, the display device (not shown) installed in the passenger compartment displays that the tire air pressure has decreased. Warning. Thereby, it is possible to inform the driver in advance of a dangerous situation that may lead to an accident.

  The vehicle signal processing device 100 may control the traveling of the vehicle based on the estimated value. For example, when the signal processing unit 120 estimates that the road surface friction coefficient of the running road is small, the vehicle speed is suppressed so as not to exceed a certain value. Here, since the signal processing unit 120 can simultaneously estimate a plurality of environments such as a tire state and a road surface state, it is possible to perform more accurate traveling control.

  FIG. 12 is a configuration diagram of the vehicle signal processing device 101 according to the present embodiment. This shows only one arbitrary system among a plurality of tires attached to the vehicle. The same components as those in the previous embodiment are designated by the same reference numerals and the description thereof is omitted.

  The vehicle signal processing device 101 includes a vibration detection unit 110 and a signal processing unit 121. The signal processing unit 121 in this embodiment includes a filter unit 131, a vibration characteristic calculation unit 141, a road surface state estimation unit 151, a tire state estimation unit 152, a vehicle motion estimation unit 153, a vehicle posture estimation unit 154, a vehicle body vibration estimation unit 155, A grip estimation unit 156 and a correction unit 161 are included. The correction unit 161 corrects the data value after filtering using the vehicle speed. Note that the speed of the vehicle may be calculated by the correction unit 161, or the result calculated by the brake ECU (not shown) may be taken in.

  FIG. 13 shows a flowchart of signal processing executed in the signal processing unit 121. In S <b> 1001 and S <b> 1002, the signal processing unit 121 acquires accelerations in the vehicle vertical direction and the longitudinal direction from the vertical acceleration sensor 111 and the longitudinal acceleration sensor 112. Then, the signal processing unit 121 performs a filter process (S1003), a correction process (S1101), and a vibration characteristic calculation process (S1004) on the vertical acceleration. Similarly, the signal processing unit 121 performs filter processing (S1005), correction processing (S1102), and vibration characteristic calculation processing (S1006) for acceleration in the front-rear direction. Similar to the previous embodiment, the signal processing unit 121 performs estimation of the tire condition (S1007) and estimation of the road surface condition (S1008) using the substitute values of these frequency components in the vertical direction and the front-rear direction.

  FIG. 14 is a flowchart of the correction processing (S1101, S1102) according to the present embodiment. In step S4001, the signal processing unit 121 acquires a signal from the wheel speed sensor 114 and calculates the speed of the vehicle. In S4002, the signal processing unit 112 corrects the data after the filter processing (S1003, S1005) using the vehicle speed. The acceleration in the vertical direction is characterized by increasing in proportion to the square of the vehicle speed, while the acceleration in the longitudinal direction is characterized by a small change in the low frequency component due to the vehicle speed. Based on these features, the signal processing unit 112 corrects each frequency component of acceleration according to the speed of the vehicle.

As described above, by adding the correction processing (S1101, S1102), it is possible to accurately estimate the environment even when the vehicle speed changes.
In this embodiment, the correction process is performed after the filter process (S1003, S1005). However, in the estimation of the tire condition (S1007) and the estimation of the road surface condition (S1008), the correction is performed by the speed of the vehicle. It may be replaced. In this case, the signal processing unit 201 corrects the correlation between the substitute value of the reference value and the comparison value and the actual measured value of the environment, that is, the estimation formula, based on the vehicle speed. As a result, as described above, the estimation accuracy when the vehicle speed changes can be improved.

  In the present embodiment, a vibration characteristic calculation process different from the above-described embodiment will be described. The same components as those in the previous embodiment are designated by the same reference numerals and the description thereof is omitted.

  In S3001 shown in FIG. 8, when the signal processing unit 200 calculates the absolute average value as a substitute value, the time length of the frequency component used for the calculation, that is, the time length shown in FIG. 5 or FIG. Change the time interval for signal processing. For example, an environment such as a road surface friction coefficient changes instantaneously as the vehicle travels, while an environment such as tire wear changes over time. Since changes in the environment affect the running of the vehicle, the former needs to be detected quickly, but the latter may be detected over time.

  For example, when estimating the road surface friction coefficient that can be instantaneously changed with respect to the traveling of the vehicle, the signal processing unit 200 calculates a substitute value with a time length of 1 [sec] or less, and estimates the road surface friction coefficient. Thereby, although the estimation accuracy of each time falls, the sudden change of a road surface friction coefficient can be detected at an early stage. Similarly, when estimating an environment in which a change occurs in a short time such as tire abnormality or road surface unevenness, the estimation is performed with a short time length.

  On the other hand, when estimating an environment in which a change with time is small or unchanged, such as tire wear and tire type, a long time is taken. For example, the signal processing unit 200 calculates a substitute value with a time length of several tens [sec] to 100 [sec], and estimates tire wear and tire type. Further, when the change with time is moderate, such as tire air pressure, the signal processing unit 200 calculates a substitute value with a time length of several [sec] to 10 [sec].

  As described above, when the estimated environment changes in a short time, the change in the environment can be detected early by shortening the processing time. This makes it possible to quickly detect that the vehicle is in a dangerous state when traveling. On the other hand, when the environment to be estimated changes over time, it is possible to improve the estimation accuracy by lengthening the processing time and offsetting the affected noise.

  FIG. 15 is a configuration diagram of the vehicle signal processing device 102 according to the present embodiment. This shows only one arbitrary system among a plurality of tires attached to the vehicle. The same components as those in the previous embodiment are designated by the same reference numerals and the description thereof is omitted.

  The vehicle signal processing device 102 includes a vibration detection unit 110 and a signal processing unit 122. The signal processing unit 122 in this embodiment includes a frequency analysis unit 171, a road surface state estimation unit 181, a tire state estimation unit 182, a vehicle motion estimation unit 183, a vehicle posture estimation unit 184, a vehicle body vibration estimation unit 185, and a grip estimation unit 186. Consists of The frequency analysis unit 171 performs frequency analysis on the vibration output from the vibration detection unit 110. For example, frequency analysis is performed using a known fast Fourier transform (FFT). Each of the estimation units 181 to 186 estimates each environment from the resonance frequency obtained from the frequency analysis and the power spectral density (PSD) in each frequency band.

  16 and 17 are graphs showing frequency characteristics with respect to tire types (base tire, inch-up tire). In the present embodiment, estimation of the type of tire will be described as an example of an internal environment related to traveling of the vehicle. FIGS. 16A and 16B show the results of performing the FFT calculation on the vertical and longitudinal accelerations in the base tire. FIGS. 17A and 17B show the results of performing the FFT operation on the vertical and longitudinal accelerations of the inch-up tire.

  As described above, the result of frequency analysis varies depending on the type of tire. The inch up of the tire has a feature that the resonance point moves to the high frequency side. The tire condition estimation unit 182 estimates the type of tire from the result of frequency analysis based on such characteristics.

  As described above, the vehicle signal processing device 122 including the frequency analysis unit 171 can also estimate the internal environment and the external environment related to traveling of the vehicle.

  FIG. 18 is a configuration diagram of the vehicle signal processing device 200 according to the present embodiment. This shows all four tires attached to the four-wheeled vehicle. The same components as those in the previous embodiment are designated by the same reference numerals and the description thereof is omitted.

  The vehicle signal processing device 200 includes vibration detection units 110FL, 110FR, 110RL, and 110RR, signal processing units 120FL, 120FR, 120RL, and 120RR, a determination unit 210, an alarm unit 220, and a travel control unit 230. The vibration detection units and the signal processing units are the vibration detection unit 110 and the signal processing unit 120 for the left front wheel (FL), the right front wheel (FR), the left rear wheel (RL), and the right rear wheel (RR).

  The abnormality determination unit 210 determines whether or not an abnormality has occurred from the estimated values of the environment obtained from the signal processing units 120FL, 120FR, 120RL, and 120RR corresponding to each tire. The warning unit 220 issues a warning to the driver based on the estimated value and the determination result. For example, when it is determined that the tire air pressure is abnormal, an estimated value is displayed on a display device (not shown) to warn that the tire air pressure has decreased. The travel control unit 230 controls the travel of the vehicle based on the estimated value and the determination result. For example, when it is determined that the tire air pressure is abnormal, control is performed so that the speed of the vehicle does not increase above a certain value.

  The abnormality determination unit 210 compares the estimated values for a plurality of tires when an environmental change immediately poses a danger to the running of the vehicle, such as a tire abnormality, among the environments in which the abnormality can be estimated for each tire alone. . For example, when only the estimated value for the right front wheel (FL) reaches a predetermined abnormal value and the estimated values for other tires are within a predetermined normal value range, the estimated value for the right front wheel (FL) It is determined that an abnormality has occurred in the tire. Thereby, even when the signal processing unit 120FL makes a mistake in estimation due to noise or the like, it is possible to prevent the traveling control unit 230 from malfunctioning. On the other hand, when the degree of danger to the running of the vehicle is not high, such as tire wear, the estimated values for other tires do not have to be referred to.

  When determining the road surface friction coefficient, the abnormality determination unit 210 first uses the estimated values output from the signal processing units 120FL and 120FR of the left front wheel (FL) and the right front wheel (FR) to detect road surface abnormality. judge. Abnormality determination unit 210 determines that there is an abnormality when the estimated values of the road surface friction coefficients output from both signal processing units 120FL and 120FR are about the same. On the other hand, for example, when only the estimated value for the left front wheel (FL) is small, there is a possibility that the vehicle travels across different parts of the road surface friction coefficient, so the abnormality determination unit 210 determines the signal of the left rear wheel (RL). The estimated value output from the processing unit 120RL is also referred to. The abnormality determination unit 210 determines that an abnormality has occurred when the estimated value for the left rear wheel (RL) is also as small as the left front wheel (FL).

  As described above, the probability of erroneous determination can be reduced by considering which estimated value to use for each tire among the estimated values in accordance with the environment for determining abnormality. Therefore, excessive operation of the travel control and warning is also suppressed.

  Note that the alarm unit 220 and the travel control unit 230 in the present embodiment display an estimated value on a display device (not shown) based on each estimated value or perform a slight amount of traveling control even in an environment where it is not determined to be abnormal. It is possible to make minor modifications.

In the present embodiment, an abnormality determination process different from that in the fifth embodiment will be described. The same components as those in the previous embodiment are designated by the same reference numerals and the description thereof is omitted.

  In the present embodiment, the abnormality determination process determines an abnormal state of the environment based on a plurality of estimated values for one arbitrary tire system. When estimating the tire air pressure, the signal processing unit 120 uses signals from the acceleration sensor 111 in the vertical direction and the acceleration sensor 112 in the front-rear direction. Here, the signal processing unit 120 can also estimate the same environment using vibrations in different directions. For example, by calculating variations in wheel speed due to standard deviation, the resonance frequency by frequency analysis, and the power spectral density (PSD) of each frequency band by a bandpass filter from the signal of the wheel speed sensor 114, the tire air pressure is calculated. Can be estimated.

  Then, the abnormality determination unit 210 determines whether the environment is abnormal using the two estimated values for these different directions. FIG. 19 is a table showing the results of abnormality determination. First, the abnormality determination unit 210 determines whether the environment estimated from the signals of the acceleration sensors 111 and 112 and the environment estimated from the signals of the wheel speed sensor 114 are normal or abnormal. Next, when both the determination results are both in an abnormal state, it is determined as an abnormal state, and when both are in a normal state, the normal state is determined. If either one is in a normal state and the other is in an abnormal state, it is considered an indefinite state.

  Thereby, since the certainty of determination increases, it can suppress that the alarm part 220 and the traveling control part 230 act | operate excessively. In particular, the abnormality determination process in the present embodiment may be performed when determining an environment that instantly poses a danger to the traveling of the vehicle, such as a tire abnormality or a road surface friction coefficient.

  Further, the abnormality determination result may be reflected in the vibration characteristic calculation process shown in the third embodiment. The signal processing unit 200 acquires the determination result from the abnormality determination unit 210, and changes the time length of the frequency component used for the substitute value calculation, that is, the time interval for performing signal processing. If the determination result is an abnormal state, the signal processing unit 200 shortens the time interval and detects further deterioration of the environment at an early stage. On the other hand, when the determination result is indeterminate, the signal processing unit 200 performs the estimation with high accuracy by extending the time interval. When the determination result is normal, the time interval is not changed. Thereby, the estimated abnormal state of the environment can be detected early and accurately.

1 is a configuration diagram of a vehicle signal processing device according to Embodiment 1. FIG. It is a figure which shows the attachment position of an acceleration sensor. It is the figure which showed typically the characteristic of the acceleration with respect to the change of an environment. It is the figure which showed typically the characteristic of the frequency with respect to the change of an environment. It is a figure which shows the flowchart of the signal processing which concerns on Example 1. FIG. FIG. 6 is a flowchart illustrating filter processing according to the first embodiment. It is a figure which shows an example of a filter process. It is a figure which shows the flowchart of the vibration characteristic calculation process which concerns on Example 1. FIG. It is a figure which shows the example of a table of a reference value and a comparison value. It is a figure which shows the correlation with a reference value and a comparison value, and a road surface friction coefficient. It is a figure which shows the actual value and estimated value of a road surface friction coefficient. It is a block diagram of the vehicle signal processing apparatus which concerns on Example 2. FIG. FIG. 10 is a flowchart illustrating signal processing according to the second embodiment. FIG. 10 is a flowchart illustrating a correction process according to the second embodiment. FIG. 6 is a configuration diagram of a vehicle signal processing device according to a fourth embodiment. It is a figure which shows the frequency characteristic of a base tire. It is a figure which shows the frequency characteristic of an inch-up tire. FIG. 10 is a configuration diagram of a vehicle signal processing device according to a fifth embodiment. It is a figure which shows the result of abnormality determination.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Tire 21 Hub 22 Shaft 23 Suspension 100,101,102,200 Vehicle signal processing apparatus 110 Vibration detection part 111 Vertical direction acceleration sensor 112 Longitudinal direction acceleration sensor 113 Horizontal direction acceleration sensor 114 Wheel speed sensor 120, 121, 122 Signal processing Unit 131 filter unit 141 vibration characteristic calculation unit 151 to 156, 181 to 186 estimation unit 161 correction unit 171 frequency analysis unit 210 abnormality determination unit 220 alarm unit 230 travel control unit

Claims (24)

Vibration detecting means for detecting vibration in a predetermined direction of the tire under the vehicle spring when the vehicle travels;
A reference frequency component extracting means for extracting a frequency component serving as a reference value from a predetermined frequency band from the vibration detected by the vibration detecting means;
Comparison frequency component extraction means for extracting a frequency component to be a comparison value from a predetermined frequency band from the vibration detected by the vibration detection means;
Estimating means for estimating at least one of an internal environment and an external environment related to traveling of the vehicle based on a combination of frequency components including the frequency component serving as the reference value and the frequency component serving as the comparison value; A vehicle signal processing apparatus. The vibration detecting means detects vibrations in at least a first direction and a second direction;
The reference frequency component extracting means extracts a frequency component serving as a reference value from the vibration in the first direction from a predetermined frequency band,
2. The vehicle signal processing apparatus according to claim 1, wherein the comparison frequency component extraction unit extracts a frequency component serving as a comparison value from the vibration in the second direction from a predetermined frequency band. 3. The vehicle signal processing according to claim 1, wherein the direction is one of a vertical direction of the vehicle, a longitudinal direction of the vehicle, a lateral direction of the vehicle, and a rotational direction of the tire. apparatus. In the vibration detection means,
The vertical vibration is detected from any one of an acceleration sensor attached to a non-rotating portion under the vehicle spring and outputting the vertical acceleration and a wheel speed sensor. The vehicle signal processing device according to claim 3. In the vibration detection means,
The vibration in the front-rear direction is detected from any one of an acceleration sensor that is attached to a non-rotating portion under the vehicle spring and outputs the acceleration in the front-rear direction, and a wheel speed sensor. The signal processing device for vehicles according to claim 3 or 4. In the vibration detection means,
6. The vehicle according to claim 3, wherein the vibration in the left-right direction is detected from a signal of an acceleration sensor that is attached to a non-rotating portion under the vehicle spring and outputs the acceleration in the left-right direction. Signal processor. In the vibration detection means,
The vehicle signal processing device according to claim 3, wherein the vibration in the rotational direction is detected from a signal from a wheel speed sensor. Vehicle speed detection means for detecting the speed of the vehicle;
Reference value correction means for correcting the frequency component serving as the reference value according to the speed of the vehicle;
A comparison value correction means for correcting the frequency component to be the comparison value according to the speed of the vehicle,
The estimation unit estimates the environment based on a combination of frequency components including a frequency component corrected by the reference value correction unit and a frequency component corrected by the comparison value correction unit. Item 8. The vehicle signal processing device according to any one of Items 1 to 7. Vehicle speed detecting means for detecting the speed of the vehicle,
The vehicle signal processing apparatus according to claim 1, wherein the estimation unit corrects the estimation of the environment based on a speed of the vehicle. Vibration characteristic calculating means for calculating a substitute value from the frequency component,
The vehicle signal processing device according to claim 1, wherein the estimation unit estimates the environment using a substitute value calculated by the vibration characteristic calculation unit. The vibration characteristic calculating means shortens the time length of the frequency component used for calculation when the time elapsed until the environment changes is short, and lengthens the time length when the time is long. The vehicle signal processing device according to claim 10. The estimation unit estimates, as the internal environment, at least one of a momentum of the vehicle, a posture of the vehicle, a vehicle body vibration of the vehicle, a grip of the tire, and a state of the tire. The signal processing apparatus for vehicles in any one of 1 thru | or 11. The vehicle signal processing apparatus according to claim 1, wherein the estimation unit estimates, as the external environment, at least a state of a road surface on which the vehicle travels. 13. The vehicle signal processing apparatus according to claim 12, wherein the estimation means estimates at least one of a slip angle of the vehicle and a yaw rate of the vehicle as a momentum of the vehicle. The vehicle signal according to claim 12, wherein the estimation means estimates at least one of a roll angle of the vehicle, a pitch angle of the vehicle, and a height of the vehicle as the posture of the vehicle. Processing equipment. 13. The vehicle signal processing device according to claim 12, wherein the estimation means estimates at least one of a grip force in the front-rear direction of the tire and a lateral force of the tire as the grip of the tire. 13. The estimation means estimates at least one of the tire air pressure, the tire load, the tire abnormality, the tire wear, and the tire type as the state of the tire. The vehicle signal processing device according to claim 1. The said estimation means estimates at least any one of the unevenness | corrugation of the said road surface, the shape of the said road surface, the gradient of the said road surface, and the friction coefficient of the said road surface as the state of the said road surface. Vehicle signal processing device. The vehicle signal processing device according to claim 1, further comprising a storage unit that stores the reference value and the comparison value corresponding to the environment. When estimating the same environment for each of multiple tires,
The vehicle signal processing apparatus according to claim 1, further comprising: a comprehensive determination unit that comprehensively determines the environment based on the estimation of the environment for each of the plurality of tires. When estimating the same environment for each of multiple tires,
21. First abnormality determining means for determining whether or not the environment is in an abnormal state that poses a danger to travel of the vehicle based on the estimation of the environment for each of the plurality of tires. The signal processing apparatus for vehicles in any one. Second estimation means for estimating the same environment as the environment estimated by the estimation means based on vibration in a direction different from each frequency component used for estimation in the estimation means;
Second abnormality determining means for determining whether or not the environment is in an abnormal state that poses a danger to the traveling of the vehicle based on the estimation of the environment in the estimation means and the estimation of the environment in the second estimation means; Have
The second abnormality determination means includes
When the environment estimated by the estimating means is the abnormal state and the environment estimated by the second estimating means is the abnormal state, the environment is determined to be the abnormal state;
The environment estimated by the estimating unit is not the abnormal state, or when the environment estimated by the second estimating unit is not the abnormal state, it is determined that the environment is not the abnormal state. The vehicle signal processing device according to any one of 1 to 21. 23. The vehicle signal processing device according to claim 1, further comprising alarm means for warning a driver of the vehicle based on an environment estimated by the estimation means. 24. The vehicle signal processing apparatus according to claim 1, further comprising a travel control unit that controls travel of the vehicle based on an environment estimated by the estimation unit.

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