JP3201282B2 - Vehicle yaw rate estimation device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a vehicle yaw rate estimating apparatus, and more particularly to a vehicle yaw rate estimating apparatus for correcting a yaw rate using a Kalman filter.

[0002]

2. Description of the Related Art In recent years, various technologies for assisting a driver, such as a navigator system, have been developed for automobiles. Further, technology development relating to automatic driving for automatically performing driving operation on behalf of the driver has been developed. Is also underway. The driving operation by the driver controls the vehicle speed and performs steering according to the grasped road conditions and driving conditions while grasping the road conditions and the driving conditions of the vehicle. Various functions need to be computerized or mechanized.

For example, in order to automatically control the speed and traveling direction of a vehicle, mechanical functions for performing throttle operation, brake operation and steering operation instead of the driver (ie, throttle actuator, brake actuator and steering actuator) are required. Needless to say, various functions for controlling the operation of these actuators are required.

In order to grasp the running condition of the vehicle, it is necessary to provide various sensors on the vehicle. One of these sensors is a yaw rate sensor for detecting the yaw rate of the vehicle. With this yaw rate sensor, the turning state of the vehicle can be known, and the direction of the vehicle can be estimated by integrating (time integrating) the detection values of the yaw rate sensor.

[0005]

Incidentally, a yaw rate sensor, like an acceleration sensor or the like, generally has a configuration in which a movement in the yaw direction is sensed and converted into a voltage and output. Assuming that the yaw motion in the rotation direction is the positive direction and the yaw motion in the right rotation direction is the negative direction, the output voltage value at the neutral point (that is, the yaw rate is 0) is V2. Is lower than the neutral point output voltage value V2 (that is, V1 <V2), and the output voltage V3 at the time of the yaw motion in the counterclockwise direction (positive direction) is higher than the neutral point output voltage value V2 (that is, the neutral point output voltage value V2). V2 <V3).

[0006] However, the output voltage value at the neutral point is not always V2 and varies due to various factors. That is, the voltage value at the neutral point generally undergoes a change due to a temporal change (DC offset). In addition, the yaw rate sensor is generally easily affected by the temperature similarly to the acceleration sensor and the like. For the same yaw rate, the output voltage value increases in a high temperature atmosphere, and conversely, the output voltage value decreases in a low temperature atmosphere. For example, the output value changes depending on the temperature.

Therefore, it is necessary to correct such a change over time (DC offset) and a change corresponding to temperature (temperature drift). For example, Japanese Unexamined Patent Publication No. 6-174741 discloses that if the yaw rate detection value of a vehicle is accumulated, it should be zero.
A technique for correcting the neutral point of the yaw rate sensor based on the assumption that However, if the yaw rate detection value of the vehicle is accumulated, it does not always become 0, and the accuracy of the neutral correction is not satisfactory.

Japanese Patent Application Laid-Open No. 7-2131 discloses a technique for correcting the output value of the yaw rate sensor when the vehicle travels straight to be at the neutral point of yaw rate 0. However, it is difficult to accurately determine the straight running of the vehicle, and the accuracy of the neutral correction is still not satisfactory. Further, a method of correcting the output value of the yaw rate sensor at the time of stop to be a neutral point of the yaw rate 0 can be considered. However, the correction cannot be performed during traveling, and it is possible to cope with the neutral point fluctuation occurring during traveling. Can not.

SUMMARY OF THE INVENTION The present invention has been made in view of the above-described problems, and has a high yaw rate information for a vehicle in which even if the output value of the yaw rate sensor changes due to a change in temperature or a change with time, highly accurate yaw rate information can be obtained. An object is to provide an estimation device.

[0010]

According to a first aspect of the present invention, there is provided a vehicle yaw rate estimating apparatus for detecting a yaw rate of a vehicle, a geomagnetic sensor for detecting geomagnetism from the vehicle, and a yaw rate sensor. A sensor and a Kalman filter that processes each detected value of the geomagnetic sensor and outputs a yaw rate estimated value. The Kalman filter corrects the yaw rate estimated value with a geomagnetic detected value and time-integrates the corrected value and the geomagnetic sensor. The yaw rate estimation value is calculated by correcting the yaw rate detection value of the yaw rate sensor by a value obtained by multiplying the first gain K1 by the time integral value of the difference from the geomagnetic detection value detected in the step (1). It is characterized by being constituted.

According to a second aspect of the present invention, there is provided a vehicle yaw rate estimating apparatus for detecting a yaw rate of a vehicle, a wheel speed sensor detecting left and right wheel speeds of the vehicle, and a yaw rate sensor detecting the yaw rate of the vehicle. A yaw rate calculating means for calculating a yaw rate of the vehicle from the left and right wheel speeds; and a Kalman filter for processing a yaw rate detected value by the yaw rate sensor and a yaw rate calculated value by the yaw rate calculating means to output a yaw rate estimated value. A first processing unit that corrects the yaw rate detection value with a time integral value related to the yaw rate detection value, multiplies the corrected value by a predetermined coefficient, and outputs the first processing unit; and calculates the yaw rate calculation value by the yaw rate detection value and the yaw rate detection value. A second processing unit that corrects and outputs the time integration value related to the yaw rate calculation value; And a third processing unit that performs a weighted average of the output values of the second processing unit and the output value of the second processing unit at a predetermined ratio, performs a time integration process on the weighted average value, and outputs the result as a yaw rate estimated value. It is characterized by having.

[0012]

Embodiments of the present invention will be described below with reference to the drawings. First, a first embodiment will be described. FIGS. 1 and 2 show a yaw rate estimating device for a vehicle as a first embodiment of the present invention.
This vehicle yaw rate estimating device, as shown in FIG.
A yaw rate sensor 61 for detecting a yaw rate of the vehicle,
A terrestrial magnetism sensor 62 for detecting terrestrial magnetism from a vehicle, and a Kalman filter 63 for processing each detection value of the yaw rate sensor 61 and the terrestrial magnetism sensor 62 and outputting an estimated yaw rate value
It is composed with and. The terrestrial magnetism detection value detected by the terrestrial magnetism sensor 62 corresponds to the azimuth in the reference direction of the vehicle (for example, in front of the vehicle body), and may be referred to as an azimuth sensor.

In the Kalman filter 63, the time integral value of the yaw rate of the vehicle (hereinafter, the time integral value is simply referred to as the integral value) corresponds to the geomagnetism detected from the vehicle, that is, the azimuth in the reference direction (front of the vehicle body) of the vehicle. It is used by paying attention to it. The Kalman filter 63 calculates the yaw rate correction amount K1 · C, and calculates the yaw rate correction amount K1.
· Correcting the yaw rate estimated value detected yaw rate detected value YR _I by the yaw rate sensor 61 by C (corrected yaw rate) yaw rate estimated value for calculating the YR _O calculating section 6
3A and an azimuth estimating unit 63B for calculating an azimuth estimation value D _O for obtaining the yaw rate correction amount K1 · C based on the yaw rate estimation value YR _O.

That is, the Kalman filter 63 has addition functions (addition sections) 64 and 65, a deviation calculation function (deviation calculation section) 66, time integration functions (integration sections) 67 and 68, and a weighting function (gain multiplication section). The yaw rate estimation value calculation unit 63A includes an integration unit 67, a gain multiplication unit 69, and an addition unit 64, and the azimuth estimation unit 63B includes an addition unit 65, an integration unit 68, and a deviation. Calculation unit 6
6 and a gain multiplying unit 70.

[0015] Then, the yaw rate estimated value calculation section 63A, the adding section 64, a detection value YR _I from the yaw rate sensor 61, the correction amount calculated in the manner described below (K1 ·
C), and these YR _I and (K1 · C) are added, and the calculated value is output as an estimated yaw rate value YR _O of the vehicle. The correction amount (K1 · C) is
A value C obtained by time-integrating (hereinafter simply referred to as “integration”) a difference (D _I −D ₀ ) between an azimuth angle estimation value D ₀ and an azimuth angle detection value D _I described later is calculated by a gain multiplication unit. It is obtained by multiplying the first gain K1 by 69. The difference (D _I -D ₀ ) between the estimated azimuth angle value D ₀ and the detected azimuth angle value D _I is calculated by the deviation calculator 66.

The azimuth estimating section 63B includes a deviation calculating section 66
The difference (D _I -D ₀ ) between the estimated azimuth angle value D ₀ and the detected azimuth angle value D _I calculated in ( ₂ ) is calculated by the gain multiplication unit 70 as the second gain K
2 and the resulting value [K2 · (D _I -D
_0)] and 'to give _{[= YR O + K2 · (D} I -D 0) ], this value YR _O' sum YR _O by adding the yaw rate estimated value YR _O by an adder 64 by an integrator section 68 and it outputs the integrated value as azimuth estimate D _0.

Incidentally, the first gain K1 and the second gain K2 are set by the following equations (1) and (2), respectively. K1 = (2πf) ² (1) K2 = 2√2πf (2) Note that f is a predetermined frequency in the yaw rate fluctuation frequency range.

[0018] In such a Kalman filter 63, the detection value YR _I, of D _I, so a predetermined frequency f or less of the variation component corresponding to the set of values of gain K1, K2 are removed. That is, only the fluctuation component of the yaw rate detection value having a frequency higher than the frequency f can be extracted. Here, the frequency f will be described.

[0019] That is, the change in the value of the yaw rate YR _I of the vehicle detected by the yaw rate sensor 61 outputs (output voltage), in addition to those due to the vehicle yaw, the sensor output caused by temperature change or variation with time, as described above Occurs due to a change in characteristics or the like. When a change in the detected value (output voltage) of the yaw rate sensor 61 is subjected to frequency analysis, for example, a characteristic as shown in FIG. 2 appears.

FIG. 2 shows theoretical characteristics assumed when the detected value (output voltage) of the yaw rate sensor 61 is Fourier-transformed. The frequency is plotted on the horizontal axis (the higher the frequency on the right).
f, the vertical axis represents the spectrum amount (the upper side is larger). A high frequency corresponds to a case where the output voltage of the yaw rate sensor 61 changes rapidly, and a low frequency corresponds to a case where the output voltage of the yaw rate sensor 61 changes gradually.

For example, the change (DC offset) of the sensor output due to a change over time is extremely slow and concentrates on an extremely low frequency as shown in FIG. The change (temperature drift) of the sensor output due to the temperature change is faster than the change over time (DC offset), but is still slightly slower, and occurs in a slightly lower frequency region as shown in FIG. The change in the sensor output due to the yaw ink of the vehicle body is the steepest, and occurs in a high frequency region as shown in FIG.

A predetermined frequency f (referred to as fn) among the fluctuation frequencies of the yaw rate detection value is set, and the first frequency fn is calculated from the predetermined frequency fn according to the above equations (1) and (2). The gain K1 and the second gain K2 are set. Here, as shown in FIG. 2, when the frequency f1 is set as the predetermined frequency f, the first gain K1 and the second gain
The gain K2 is set as follows.

K1 = (2πf1) ² (1 ′) K2 = 2√2πf1 (2 ′) With such a gain setting, the fluctuation frequency of the yaw rate detection value depends on the DC offset. Temperature drift is eliminated, and a yaw rate YR _O which is not affected by aging or temperature change can be obtained.

The vehicle yaw rate estimating apparatus according to the first embodiment of the present invention is configured as described above.
Among the fluctuating frequencies of the yaw rate detection value detected by the yaw rate sensor 61, those due to the DC offset and those due to the temperature drift are removed, and the neutral point correction relating to aging or temperature change is performed. There is an advantage that a yaw rate estimated value YR _{O which} is not affected by a change over time or a temperature change can be obtained.

The azimuth estimation value D obtained by the azimuth estimation unit 63B using the yaw rate estimation value YR _O is also used.
_{In the case of 0} , the variation due to the DC offset and the variation due to the temperature are removed from the fluctuation frequency of the detected value, and there is an advantage that the azimuth estimation value D _{O which} is not affected by the aging or the temperature change can be obtained. In this device,
By setting the predetermined frequency fn according to the setting of the first gain K1 and the second gain K2, it is possible to perform filtering for a desired frequency region.

According to the present apparatus, the delay of the estimated value is reduced and a stable estimation result can be obtained as compared with the processing of a general first-order filter. It is considered that this can contribute to improving the accuracy of the estimated value. Next, a second embodiment will be described. FIG. 3 shows a vehicle yaw rate estimating apparatus as a second embodiment of the present invention.

As shown in FIG. 3, the vehicle yaw rate estimating apparatus includes a yaw rate sensor 61 for detecting the yaw rate of the vehicle, a wheel speed sensor 71 for detecting the left and right wheel speeds of the vehicle, and a wheel speed sensor 71 for detecting the yaw rate. Yaw rate calculating means 72 for calculating the yaw rate of the vehicle from the determined left and right wheel speeds
And a Kalman filter 73 that processes the yaw rate detection value YR _I detected by the yaw rate sensor 61 and the yaw rate calculation value CYR _I calculated by the yaw rate calculation means 71 and outputs a yaw rate estimated value YR _O. The yaw rate calculating means 71 calculates the yaw rate from the detected difference between the left and right wheel speeds and the tread width of the vehicle, but may further calculate the yaw rate with high accuracy in consideration of the detected value of the steering angle. .

The Kalman filter 73 is configured to correct a yaw rate detection value detected by the yaw rate sensor with a yaw rate calculation value obtained from left and right wheel speeds. The Kalman filter 73, the yaw rate detection value YR _I is corrected by the time integration value C1 regarding the yaw rate detection value YR _I outputs a value after the correction (YR _I + C1) factor multiplication (k1 times) by a predetermined coefficient k1 to 1 a processing unit 73A, a second processing unit 73B to output the corrected yaw rate calculation value CYR _I in yaw rate detection value YR _I and the yaw rate calculation value CYR _I with respect to time integral value C2, the output from the first processing section 73A Value [k1 · (YR _I + C
1)] and the output value (CYR _I + C) from the second processing unit 73B.
2) the weighted average, the third processing unit 73C outputs the weighted average time integration process to the yaw rate estimated value YR _O
It is composed of

That is, the Kalman filter 73 includes deviation calculating functions (deviation calculating sections) 74 and 75, an adding function (adding section) 76, time integrating functions (integrating sections) 77 and 78, and a weighting function (gain multiplying section). The first processing unit 73A includes a deviation calculating unit 74, a gain multiplying unit 79, and an integrating unit 77, and the second processing unit 73B includes a deviation calculating unit 75. , The third processing unit 73C includes gain multiplication units 80 and 81, an addition unit 76, and an integration unit 78.

Then, the first processing unit 73A calculates a deviation.
The yaw rate detection value (the yaw rate sensor detection
Value) YR_IFrom the yaw rate detection value YR_IIntegral with respect to
The value (correction amount) C1 is subtracted and corrected, and the corrected value is obtained.
(YR_I+ C1) to a predetermined coefficient k1 by the gain multiplication unit 79.
A calculated value [k1 · (Y
R _I+ C1)] is output. The correction amount C1 is
Calculated value [k1 · (YR_I+ C1)] by the integration unit 77
Is obtained.

The second processing section 73B includes a deviation calculating section 75
The yaw rate calculation value (the yaw rate calculated from the difference between the left and right wheel speeds)
Ito) CYR_IFrom the yaw rate calculation value detection value CYR_I
Is calculated by subtracting the integral value (correction amount) C2 related to
Value (CYR_I-C2) is output. The correction amount C2
Is a yaw rate estimated value (corrected yaw rate) Y described later.
R _OIt is.

The third processing section 73C includes a gain multiplying section 80
And the output value from the first processing unit 73A [k1 · (YR _I + C
1)] is multiplied by a coefficient k2 (where 0 <k2 <1). On the other hand, the second processing unit 73B
Calculated value from (CYR _I -C2) to be multiplied by a coefficient (1-k2), by an adder 76, these output values [i.e., the value k
2 · k1 · (YR _I + C1) and value (1−k2) · (C
YR _I -C2)]. That is, the gain multiplying unit 8
0, 81 and the adding unit 76, the output value [k1 · (YR _I + C1)] from the first processing unit 73A and the second processing unit 73B
And the output value (CYR _I -C2) from the weighting ratio k2:
Weighted averaging is performed by (1-k2). And this A
Average value k2 · k1 · (YR _I + C1) obtained by
+ (1−k2) · (CYR _I −C2)] is integrated by the integration section 78 to obtain a yaw rate estimated value (corrected yaw rate) YR _O.

The vehicle yaw rate estimating apparatus according to the second embodiment of the present invention is configured as described above.
Coefficient (gain) k1, coefficient (gain related to weight ratio) K
By appropriately setting 2, the yaw rate detection value detected by the yaw rate sensor 61 can be corrected by the yaw rate calculation value calculated based on the difference between the left and right wheel speeds. Yaw rate estimation value YR _O which is not affected by aging or temperature change
There are advantages that can be obtained.

The vehicle yaw rate estimating apparatus of the present invention as described above can be used as one of means for grasping the running condition of the vehicle. For example, it can be used for a vehicle navigation system, automatic driving control of a vehicle, and the like. Can be used.

[0035]

As described in detail above, according to the vehicle yaw rate estimating apparatus of the first aspect of the present invention, the yaw rate detection value is filtered while utilizing the detection value of the geomagnetic sensor. Unnecessary frequency components in the yaw rate detection value can be removed,
For example, there is an advantage that the neutral point correction relating to a change over time or a change in temperature can be accurately performed, and the estimation accuracy of the yaw rate in the vehicle can be improved.

As described in detail above, according to the vehicle yaw rate estimating apparatus of the present invention, the yaw rate detection value is filtered using the yaw rate calculation value based on the detection value of the left and right wheel speed sensors. With such a simple configuration, it becomes possible to remove unnecessary frequency components from the detected yaw rate value.For example, it is possible to accurately correct a neutral point with respect to a change over time or a temperature change. There is an advantage that the estimation accuracy can be improved.

[Brief description of the drawings]

FIG. 1 is a block diagram schematically showing a configuration of a vehicle yaw rate estimating apparatus as a first embodiment of the present invention.

FIG. 2 is a diagram illustrating gain setting of the vehicle yaw rate estimating apparatus according to the first embodiment of the present invention.

FIG. 3 is a block diagram schematically showing a configuration of a vehicle yaw rate estimating apparatus as a second embodiment of the present invention.

[Explanation of symbols]

 Reference Signs List 61 Yaw rate sensor 62 Geomagnetic sensor (azimuth angle sensor) 63 Kalman filter 63A Yaw rate estimation value calculation unit 63B Azimuth angle estimation unit 64, 65 Addition unit 66 Deviation calculation unit 67, 68 Integration unit 69, 70 Gain multiplication unit 71 Wheel speed sensor 72 Yaw rate Calculation means 73 Kalman filter 73A First processing unit 73B Second processing unit 73c Third processing unit 74, 75 Deviation calculation function (deviation calculation unit) 76 Addition function (Addition unit) 77, 78 Time integration function (Integration unit) 79, 80 , 81 weighting function (gain multiplication unit) K1 first gain K2 second gain k1 predetermined coefficient (gain) k2 gain (gain related to weight ratio)

──────────────────────────────────────────────────続 き Continuation of the front page (56) References JP-A-5-208608 (JP, A) JP-A-6-174741 (JP, A) JP-A-7-2131 (JP, A) JP-A 9-208 2317 (JP, A) JP-A-3-188316 (JP, A) JP-A-4-238221 (JP, A) JP-A-5-71964 (JP, A) (58) Fields investigated (Int. ⁷ , DB name) B62D 6/00

Claims (2)

(57) [Claims] 1. A yaw rate sensor for detecting a yaw rate of a vehicle, a geomagnetic sensor for detecting geomagnetism from the vehicle, and a Kalman filter for processing each detected value of the yaw rate sensor and the geomagnetic sensor to output a yaw rate estimated value. The Kalman filter calculates a deviation between a value obtained by correcting the estimated yaw rate value with a terrestrial magnetism detection value and time-integrating the corrected value and a terrestrial magnetism detection value detected by the terrestrial magnetism sensor. A yaw rate estimating device for a vehicle, wherein a yaw rate estimation value is calculated by correcting a yaw rate detection value by the yaw rate sensor by a value multiplied by one gain K1. 2. A yaw rate sensor for detecting a yaw rate of a vehicle, a wheel speed sensor for detecting left and right wheel speeds of the vehicle, and a yaw rate for calculating a yaw rate of the vehicle from left and right wheel speeds detected by the wheel speed sensors. Calculating means for processing a yaw rate detected value by the yaw rate sensor and a Kalman filter for processing a yaw rate calculated value by the yaw rate calculating means to output a yaw rate estimated value, wherein the Kalman filter converts the yaw rate detected value to a time related to the yaw rate detected value. A first processing unit for correcting the integrated value, multiplying the corrected value by a predetermined coefficient and outputting the corrected value, and correcting the yaw rate calculated value with the time integrated value related to the detected yaw rate value and the calculated yaw rate value and outputting the corrected value. Second
A processing unit, a weighted average of an output value from the first processing unit and an output value from the second processing unit at a preset ratio, and time-integrating the weighted average value to output a yaw rate estimation value Third
A yaw rate estimating device for a vehicle, comprising: a processing unit.