JP7622580B2 - Side slip angle calculation device - Google Patents

Description

This disclosure relates to a sideslip angle calculation device for calculating the sideslip angle of a vehicle.

When a vehicle turns, a sideslip angle occurs. Yaw rate can only detect the direction the vehicle is facing, so in order to estimate the vehicle's direction of travel, it is necessary to estimate the vehicle's sideslip angle.

For this reason, for example, Non-Patent Document 1 shows a method of determining the sideslip angle by estimating the parameters required for estimating the sideslip angle using GNSS Doppler, which is the relative velocity between the satellite and the receiver.

"Research on GNSS/IMU Applicable in Urban Environments" by Aoki Takanose, Yoshinori Atsumi, Kanamu Takikawa, and Junichi Meguro, Transactions of the Society of Automotive Engineers of Japan, Vol. 51, No. 4, July 2020

However, the method described in Non-Patent Document 1 has the problem that in environments where GNSS signals cannot be received normally, the parameters required for estimating the sideslip angle cannot be estimated.

The present disclosure has been made in consideration of the above-mentioned points, and aims to provide a sideslip angle calculation device that can estimate parameters necessary for estimating sideslip angle, regardless of whether or not a GNSS signal is received.

In order to achieve the above object, a sideslip angle calculation device according to the present disclosure includes:
a sideslip angle estimation value calculation unit (14, 16, 20, 22) that receives a lateral acceleration (α _y ), a vehicle speed (V), and a rotational angular velocity (ω _yaw ) of a vehicle, and calculates a vehicle sideslip angle estimation value (β _est ) based on the received lateral acceleration (α _y ), vehicle speed (V), and rotational angular velocity (ω _yaw );
a multiplication unit (24) that calculates a multiplication result (Vω _yaw ) by multiplying a vehicle speed (V) and a rotational angular velocity (ω _yaw );
The control system further includes a parameter calculation unit (28) that calculates a parameter (K) that is a coefficient that approximates the sideslip angle estimated value (β _est ) calculated by the sideslip angle estimated value calculation unit and the multiplication result (Vω _yaw ) calculated by the multiplication unit.

The vehicle side slip angle can be calculated from the product (Vω _{yaw ) of the vehicle speed (V) and the rotational angular velocity (ω yaw )} and the parameter (K) calculated by the parameter calculation unit.

As described above, according to the sideslip angle calculation device of the present disclosure, the parameter (K) required for estimating the sideslip angle is calculated as a coefficient that approximates the sideslip angle estimated value (β _est ) calculated by the sideslip angle estimated value calculation unit (14, 16, 20, 22) and the multiplication result (Vω _yaw ) calculated by the multiplication unit (28). Therefore, it is possible to calculate the parameter (K) required for estimating the sideslip angle regardless of whether a GNSS signal is received or not.

The reference numbers in parentheses above are merely examples of the correspondence with specific configurations in the embodiments described below to facilitate understanding of this disclosure, and are not intended to limit the scope of this disclosure in any way.

In addition to the above-mentioned features, the technical features described in each claim of the present invention will become clear from the description of the embodiments and the attached drawings described below.

1 is a block diagram showing a configuration of a sideslip angle calculation device 10 according to a first embodiment. 1 is a waveform diagram showing an example of changes in traveling angular velocity α _y /V, which is obtained by dividing lateral acceleration α _y by vehicle speed V, and rotational angular velocity ω _yaw, when a vehicle turns right or left at an intersection. FIG. 11 is a waveform diagram showing an example of a change in a side slip angle differential value dβ from which an offset error dβ ₀ has been removed when a vehicle turns right or left at an intersection. FIG. 11 is a waveform diagram showing an example of a change in a sideslip angle estimated value β _est calculated by integrating a sideslip angle differential value dβ from which an offset error dβ ₀ has been removed when a vehicle turns right or left at an intersection. FIG. 5 is a waveform diagram showing, in superposition, the waveform of the estimated sideslip angle β _EST shown in FIG. 4 , the waveform of the estimated sideslip angle β _EST calculated by multiplying the waveform of the estimated sideslip angle β EST by the vehicle parameter K, the vehicle speed V, and the rotational angular velocity ω _yaw , respectively, and a waveform indicating the true sideslip angle. 4 is a flowchart showing a process for calculating an estimated slip angle β _EST in the side slip angle calculation device. 4 is a flowchart showing a method for calculating a vehicle parameter K in the first embodiment. 6A and 6B are waveform diagrams showing the temporal relationship between the change in the estimated side slip angle β _est and the side slip angle differential value dβ. 10 is a flowchart showing a method for calculating a vehicle parameter K in the second embodiment. FIG. 13 is a block diagram showing a configuration for implementing a method for calculating a vehicle parameter K according to a third embodiment. FIG. 13 is a block diagram showing a configuration according to a modified example.

Below, an embodiment of the side slip angle calculation device according to the present disclosure will be described in detail with reference to the drawings.

First Embodiment
FIG. 1 is a block diagram showing a configuration of a sideslip angle calculation device 10 according to a first embodiment. The sideslip angle calculation device 10 can be configured by, for example, a computer including at least one memory and one processor. The memory non-temporarily stores or memorizes computer-readable programs and data. The memory is realized by, for example, at least one type of non-transitory tangible storage medium among semiconductor memory, magnetic medium, optical medium, and the like. The memory stores a program for realizing at least a part of the functions of the sideslip angle calculation device 10 shown as a block in FIG. 1 .

The processor includes at least one of the following types of cores: a central processing unit (CPU), a graphics processing unit (GPU), and a reduced instruction set computer (RISC) CPU. The processor executes a number of instructions included in a program stored in memory to realize the various functions of the side slip angle calculation device 10 shown as blocks in FIG. 1. Some of the functions shown as blocks may be realized by hardware circuits.

The sideslip angle calculation device 10 receives signals from an acceleration sensor 1, a gyro sensor 2, a wheel speed sensor 3, and a GNSS (Global Navigation Satellite System) receiver 4. If necessary, the sideslip angle calculation device 10 may be configured to receive signals from other sensors in addition to or instead of the above sensors.

The acceleration sensor 1 detects a lateral acceleration _αy acting in the lateral direction (left-right direction) of a vehicle on which the sideslip angle calculation device 10 is mounted. The gyro sensor 2 detects the speed (yaw rate) _ωyaw of the rotational motion of the vehicle.

The detection axis of the acceleration sensor 1 is installed on the vehicle so that it is horizontal to the ground. Therefore, when the vehicle rolls while turning and the detection axis of the acceleration sensor 1 tilts from the horizontal direction, the acceleration sensor 1 detects the gravitational acceleration in addition to the acceleration acting in the lateral direction of the vehicle due to the motion of the vehicle. Therefore, the sideslip angle calculation device 10 has a gravitational component removal block 12. The gravitational component removal block 12 removes the gravitational component corresponding to the magnitude of the tilt of the vehicle from the horizontal direction from the lateral acceleration _αy detected by the acceleration sensor 1, based on the rotational angular velocity _ωyaw detected by the gyro sensor 2. This allows the sideslip angle calculation device 10 to obtain a highly accurate lateral acceleration _αy .

The wheel speed sensor 3 has, for example, a rotor with multiple teeth formed on its outer circumference and an electromagnetic pickup, and detects the speed at which the vehicle wheels rotate, i.e., the speed V at which the vehicle travels. Note that the wheel speed sensor 3 is not limited to the above-mentioned type, and other types of wheel speed sensors may also be used. The GNSS receiver 4 acquires vehicle position information and speed information based on signals from multiple positioning satellites.

The sideslip angle calculation device 10 has a vehicle speed correction block 18. The vehicle speed correction block 18 corrects the vehicle speed V detected by the wheel speed sensor 3 based on the speed information acquired by the GNSS receiver 4. For example, the vehicle speed V detected by the wheel speed sensor 3 may vary due to the influence of tire air pressure and the degree of tire wear. For this reason, the vehicle speed correction block 18 calculates a correction coefficient for correcting the vehicle speed V using accurate speed information acquired by the GNSS receiver 4. The vehicle speed correction block 18 corrects the vehicle speed V detected by the wheel speed sensor 3 using this correction coefficient. As a result, once the correction coefficient is calculated, the sideslip angle calculation device 10 can obtain a highly accurate vehicle speed V regardless of whether or not the speed information is acquired by the GNSS receiver 4. However, the GNSS receiver 4 and the vehicle speed correction block 18 may be omitted.

The sideslip angle calculation device 10 has bandpass filter blocks 14 and 16. The bandpass filter block 14 performs bandpass filtering on the lateral acceleration _αy output from the gravity component removal block 12. Furthermore, the bandpass filter block 16 performs bandpass filtering on the rotational angular velocity _ωyaw detected by the gyro sensor 2. In this manner, by performing bandpass filtering on the lateral acceleration _αy and the rotational angular velocity _ωyaw , high frequency noise and low frequency noise superimposed on the lateral acceleration _αy and the rotational angular velocity _ωyaw, respectively, can be removed.

By performing band-pass filtering on the lateral acceleration _αy and the rotational angular velocity _ωyaw , the same effect as performing band-pass filtering on the sideslip angle differential value dβ described later can be obtained. However, instead of or in addition to performing band-pass filtering on the lateral acceleration αy and the rotational angular velocity ωyaw, band-pass filtering may be performed on the sideslip angle differential value dβ.

参考として、図２に、車両が交差点で右左折するために旋回したときの、横加速度α_ｙを車速Ｖで除算した進行角速度α_ｙ／Ｖと、回転角速度ω_ｙａｗの変化の一例を示す。図２に示す進行角速度α_ｙ／Ｖから回転角速度ω_ｙａｗを減算することにより、横すべり角微分値ｄβが算出される。 The sideslip angle calculation device 10 has an error elimination calculation block 20. The error elimination calculation block 20 inputs the lateral acceleration α _y , the rotational angular velocity ω _yaw , and the vehicle speed V, and calculates a sideslip angle differential value dβ in accordance with Equation 1, which is a commonly known equation for sideslip angle differentiation.

For reference, Fig. 2 shows an example of changes in the travel angular velocity _αy /V, calculated by dividing the lateral acceleration _αy by the vehicle speed V, and the rotational angular velocity _ωyaw, when the vehicle turns to turn right or left at an intersection. The sideslip angle differential value dβ is calculated by subtracting the rotational angular velocity _ωyaw from the travel angular velocity _αy /V shown in Fig. 2.

If the output of each sensor contains an offset error due to temperature drift or the like, the influence of the offset error cannot be sufficiently removed by only using the above-mentioned band-pass filter blocks 14, 16. If the sideslip angle estimated value β _est is calculated by integrating the sideslip angle differential value dβ while the offset error is still contained, the calculated sideslip angle estimated value β _est will deviate significantly from the true sideslip angle β.

Therefore, the sideslip angle calculation device 10 includes a scene determination block 26 that determines whether the vehicle is moving straight or turning. For example, the scene determination block 26 can determine whether the vehicle is moving straight or turning based on the steering angle detected by the steering sensor and the magnitude of the rotational angular velocity ω _yaw detected by the gyro sensor 2. Then, based on the determination result of the scene determination block 26, the error elimination calculation block 20 obtains the sideslip angle differential value dβ calculated when the vehicle is moving straight before the vehicle starts turning as the offset error dβ _0. The error elimination calculation block 20 calculates the sideslip angle differential value dβ by subtracting the offset error dβ ₀ from the sideslip angle differential value dβ calculated according to Equation 1. In this manner, the error elimination calculation block 20 can output the sideslip angle differential value dβ from which the offset error dβ ₀ has been removed.

3 is a waveform diagram showing an example of a change in the sideslip angle differential value dβ with the offset error dβ ₀ removed when the vehicle turns to turn right or left at an intersection. As shown in FIG. 3, by removing the offset error dβ ₀ , the sideslip angle differential value dβ before the vehicle turns indicates an angular velocity of approximately zero.

The sideslip angle calculation device 10 has an integration block 22. The integration block 22 calculates a sideslip angle estimated value β _{est by integrating the sideslip angle differential value dβ output from the error removal calculation block 20. Fig. 4 is a waveform diagram showing an example of a change in the sideslip angle estimated value β est calculated} by the integration block 22 when the vehicle turns to turn right or left at an intersection.

5, the waveform of the estimated sideslip angle β _est shown in FIG 4 is superimposed on the waveform showing the true sideslip angle. As described above, by performing band-pass filtering on the lateral acceleration αy and the rotational angular velocity _ωyaw and removing the offset error _dβ0 from the sideslip angle differential dβ, it can be seen that the estimated sideslip angle β _est generally coincides with the true sideslip angle immediately after the start of turning.

However, errors that cannot be completely removed by the above-described band-pass filtering process or elimination of the offset error accumulate due to integration. As can be seen from FIG. 5, the deviation between the estimated side slip angle β _est and the true side slip angle increases as time passes.

Therefore, in this embodiment, the sideslip angle estimated value β _est is not used as the estimated sideslip angle β _EST as it is, but is used as a basis for determining a vehicle parameter K for calculating _{the estimated sideslip angle β EST .} The relationship between the vehicle parameter K and the sideslip angle estimated value β _est will be described below.

First, when a vehicle turns, the rotational centripetal force F acting on the vehicle is expressed by the following formula 2. Here, m is the vehicle weight, V is the speed of the vehicle in the direction of movement, and r is the turning radius.

The relationship between the sideslip angle β and the lateral force F is expressed by the following formula 3. Here, Cf indicates cornering power, which is a force generated per unit slip angle.

From Equation 2 and Equation 3, the following relational expression, Equation 4, is obtained regarding the vehicle parameter K and the estimated side slip angle value β _est .

In other words, the vehicle parameter K can be calculated as the ratio of the sideslip angle estimated value β _est to the multiplication result Vω _yaw of the vehicle speed V and the rotational angular velocity ω _yaw . It can also be said that the vehicle parameter K is a coefficient that approximates the sideslip angle estimated value β _est and the multiplication result Vω _yaw . For this reason, as shown in FIG. 1, the sideslip angle calculation device 10 has a multiplication block 24 that multiplies the vehicle speed V and the rotational angular velocity ω _yaw . Once the vehicle parameter K has been determined, the estimated sideslip angle β _EST can be calculated by multiplying the vehicle parameter K, the vehicle speed V, and the rotational angular velocity ω _yaw , respectively.

5 also shows the waveform of the estimated sideslip angle β _EST calculated by multiplying the vehicle parameter K, the vehicle speed V, and the rotational angular velocity ω _yaw . Since the estimated sideslip angle β _EST is not calculated by integration like the sideslip angle estimated value β _est , it can be seen that the error between the estimated sideslip angle β EST and the true sideslip angle becomes smaller over time as compared to the sideslip angle estimated value β _est .

The sideslip angle calculation device 10 has a vehicle parameter and estimated sideslip angle calculation block 28. As described above, the vehicle parameter and estimated sideslip angle calculation block 28 calculates the vehicle parameter K as the ratio of the sideslip angle estimated value β est to the multiplication result of the vehicle speed V and the rotational angular velocity ω _yaw detected when the vehicle turns. Furthermore, once the vehicle parameter K is determined, the sideslip angle calculation device 10 can calculate the estimated sideslip angle β _EST as the sideslip angle occurring when the vehicle is turning by multiplying the vehicle parameter K, the vehicle speed V, and the rotational angular velocity _{ω yaw} by each other.

The vehicle parameter and estimated sideslip angle calculation block 28 may be configured to calculate the vehicle parameter K and output the calculated vehicle parameter K to an external device that requires the sideslip angle (e.g., an automatic driving control device, a locator device, etc.). This is because if the vehicle parameter K is known, the external device can easily calculate the estimated sideslip angle β _EST .

Next, a process for calculating the estimated slip angle β _EST in the side slip angle calculation device 10 will be described with reference to the flowchart of FIG.

First, in step S100, the sideslip angle calculation device 10 inputs the lateral acceleration α _y , the rotational angular velocity ω _yaw , and the vehicle speed V, and calculates the sideslip angle differential value dβ according to the above-mentioned Equation 1. A predetermined number of the calculated sideslip angle differential values dβ are stored in memory. Note that, before calculating the sideslip angle differential value dβ, the lateral acceleration α _y is subjected to the above-mentioned gravity component removal and band-pass filter processing, the rotational angular velocity ω _yaw is subjected to band-pass filter processing, and the vehicle speed V is subjected to vehicle speed correction processing.

In step S110, it is determined whether or not the vehicle is turning (driving on a curve) based on the detection value of the steering sensor and/or the gyro sensor 2. When the vehicle starts turning and the determination result of step S110 is "YES", in step S120, the offset error _dβ0 is determined and stored in memory based on at least one side slip angle differential value dβ that has been calculated and stored in memory beforehand. On the other hand, when the determination result of step S110 is "NO", the process of step S100 is repeated until the determination result becomes "YES".

In step S130, it is determined whether the vehicle speed V is equal to or less than a predetermined value (e.g., 50 km/h). If the result of the determination in step S130 is "YES", the process proceeds to step S140, and if the result of the determination is "NO", the process returns to step S100.

When the vehicle speed increases, the vehicle's motion characteristics also change, and it is possible that a vehicle parameter K different from that calculated at low speeds is calculated. Situations in which it is highly necessary to calculate the side slip angle using the vehicle parameter K are, for example, situations in which the vehicle speed is relatively low, such as when the automatic driving control device accurately calculates the vehicle's traveling direction using the side slip angle when the vehicle turns to turn right or left at an intersection. For this reason, in this embodiment, the vehicle parameter K is calculated by the determination process of step S130, limited to a low speed range where the vehicle speed V is equal to or lower than a predetermined value. However, if it is necessary to calculate the side slip angle even in the medium speed range or high speed range, the vehicle parameter K may be calculated for each of a plurality of speed ranges, such as a low speed range and a medium-high speed range, or a low speed range, a medium speed range, and a high speed range.

In step S140, the sideslip angle estimated value β _est is calculated by integrating the sideslip angle differential value dβ from which the offset error dβ ₀ stored in the memory in the process of step S120 has been subtracted. In step S150, the multiplication result Vω _yaw is calculated by multiplying the vehicle speed V by the rotational angular velocity ω _yaw . The sideslip angle estimated value β _est and the multiplication result Vω _yaw are repeatedly calculated, for example, at predetermined time intervals while the vehicle is turning.

In step S160, a vehicle parameter K is calculated from the product _Vωyaw of the vehicle speed V and the rotational angular velocity _ωyaw and the estimated side slip angle _βest . An example of a method for calculating the vehicle parameter K will be described with reference to the flowchart of FIG.

In the first step S200, a maximum sideslip angle estimated value MAX(β _est ) that is the maximum value is identified among a plurality of sideslip angle estimated values β _est that are repeatedly calculated while the vehicle is turning. As shown in Figures 8A and 8B, the maximum sideslip angle estimated value MAX(β _est ) generally occurs at the timing when the sign of the sideslip angle differential value dβ reverses from positive to negative. Therefore, the sideslip angle estimated value β est calculated at the timing when the sign of the sideslip angle differential value dβ reverses from positive to negative may be identified as the maximum sideslip angle estimated value MAX(β _est ). Alternatively, the repeatedly calculated sideslip angle estimated values β _est may be compared in magnitude with each other, _and the sideslip angle estimated value β _est that is the largest value may be identified as the maximum sideslip angle estimated value MAX(β _est ).

In step S210, a maximum multiplication result MAX (Vω _yaw ) that indicates the maximum value is identified among the multiple multiplication results Vω _yaw of the vehicle speed V and the rotational angular velocity ω yaw that are repeatedly calculated while the vehicle is turning. With regard to the maximum multiplication result MAX (Vω _yaw ), the multiplication result Vω _yaw calculated at the same timing as the maximum sideslip angle estimated value MAX (β _{est )} is calculated may be identified as the maximum multiplication result MAX (Vω _yaw ). Alternatively, the repeatedly calculated multiplication results Vω _yaw may be compared in magnitude with each other, and the multiplication result Vω _yaw that indicates the largest value may be identified as the maximum multiplication result MAX (Vω _yaw ).

In step S220, the maximum sideslip angle estimated value MAX (β _est ) is divided by the maximum multiplication result MAX (Vω _yaw ) to calculate the vehicle parameter K. In other words, the vehicle parameter K is calculated as the ratio of the maximum value of the sideslip angle estimated value β _est to the maximum value of the multiplication result Vω _yaw obtained by multiplying the vehicle speed V and the rotational angular velocity ω _yaw . In this way, by using the respective maximum values, the S/N ratios of the sideslip angle estimated value β _est and the multiplication result Vω _yaw can be increased, and the vehicle parameter K can be calculated with the effects of noise reduced as much as possible.

Returning to the flowchart of FIG. 6, in step S170, the vehicle parameter K calculated in step S160 is used to calculate the side slip angle β, that is, the result of multiplication Vω _{yaw of the vehicle speed V and the rotational angular velocity ω yaw is} further multiplied by the vehicle parameter K. In step S180, it is determined whether the calculated side slip angle β is equal to or smaller than a predetermined upper limit value (for example, a value in the range of 3 to 5 degrees). This predetermined upper limit value corresponds to the upper limit of the side slip angle during normal vehicle running. Therefore, if it is determined in step S180 that the calculated side slip angle β is greater than the predetermined upper limit value, it is highly likely that the vehicle parameter K was not calculated correctly. For this reason, if the determination result in step S180 is "NO", the process returns to the process of step S100 without storing the calculated vehicle parameter K in the memory. On the other hand, if the determination result in step S180 is "YES", the process proceeds to step S190, where the calculated vehicle parameter K is stored in the memory. Then, the sideslip angle calculation device 10 calculates the estimated sideslip angle β _EST using the vehicle parameter K stored in the memory. The vehicle parameter K stored in the memory can be used to calculate the vehicle sideslip angle until a new vehicle parameter K is calculated.

As described above, according to the sideslip angle calculation device 10 of this embodiment, the vehicle parameter K required for estimating the sideslip angle β is calculated from the sideslip angle estimated value β _est calculated by integrating the sideslip angle differential value dβ and the multiplication result Vω _yaw of the vehicle speed V and the rotational angular velocity ω _yaw . Therefore, it is possible to calculate the vehicle parameter K required for estimating the sideslip angle regardless of whether or not a GNSS signal is received.

Second Embodiment
Next, a second embodiment of the sideslip angle calculation device 10 according to the present disclosure will be described with reference to the drawings.

In the first embodiment described above, the vehicle parameter K is calculated by dividing the maximum side slip angle estimated value MAX (β _est ) by the maximum multiplication result MAX (Vω _yaw ). However, the method of calculating the vehicle parameter K is not limited to the method described in the first embodiment, and other methods may be adopted. In this embodiment, a method of calculating the vehicle parameter K different from that in the first embodiment will be described.

9 is a flowchart showing a method for calculating the vehicle parameter K in this embodiment. In the first step S300, the sideslip angle estimated value β _est is repeatedly calculated while the vehicle is turning, thereby calculating the sideslip angle estimated value β _est multiple times. In step S310, the multiplication result Vω _yaw of the vehicle speed V and the rotational angular velocity ω _yaw is calculated multiple times in synchronization with the calculation of the sideslip angle estimated value β _est .

In step S320, a plurality of vehicle parameters K are calculated as a ratio between the sideslip angle estimated value β _est calculated a plurality of times and the multiplication result Vω _yaw of the vehicle speed V and the rotational angular velocity ω _yaw calculated a plurality of times, and are calculated synchronously. In step S330, one vehicle parameter K is determined by statistically processing the plurality of vehicle parameters K. The statistical processing may be, for example, a process of determining the most frequently occurring value of the plurality of vehicle parameters K. Alternatively, the statistical processing may be a process of determining an average of the plurality of vehicle parameters K after excluding obvious outliers.

In this way, the vehicle parameter K required for estimating the sideslip angle can be calculated by the method for calculating the vehicle parameter K in the second embodiment, as in the first embodiment.

Third Embodiment
Next, a third embodiment of the side slip angle calculation device 10 according to the present disclosure will be described with reference to the drawings. In this embodiment, as in the second embodiment, a method of calculating the vehicle parameter K that is different from that in the first embodiment will be described. Fig. 10 is a configuration diagram showing a configuration for implementing the method of calculating the vehicle parameter K according to this embodiment.

In FIG. 10, a control circuit 30 determines whether or not the vehicle is turning based on the rotational angular velocity ω _yaw detected by the gyro sensor 2, and outputs an enable signal to an adaptive filter 32 when it determines that the vehicle is turning.

The adaptive filter 32 is operable when an enable signal is output from the control circuit 30. When the adaptive filter 32 is in operation, it self-adapts the transfer function H(z) so that the error e between the waveform of the estimated sideslip angle value β _est and the waveforms of the vehicle speed V and the rotational angular velocity ω _yaw is minimized according to an optimization algorithm such as a least mean squares (LMS) algorithm or a recursive least squares (RLS) algorithm. From the self-adapted transfer function H(z), the vehicle parameter and estimated sideslip angle calculation block 28 can determine the vehicle parameter K.

In this way, the vehicle parameter K required for estimating the sideslip angle can be calculated by the method for calculating the vehicle parameter K in the third embodiment, as in the first embodiment.

Although the preferred embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments and can be modified in various ways without departing from the spirit of the present disclosure.

For example, in each of the above-described embodiments, as shown in FIG. 11, a road surface condition determination block 36 that determines the condition of the road surface on which the vehicle is traveling, and a K value table 38 that serves as a parameter storage unit that stores the vehicle parameters K calculated by the vehicle parameter and estimated sideslip angle calculation block 28 and updates the stored vehicle parameters K may be provided.

The road surface condition determination block 36, for example, performs image recognition processing on an image of the vehicle surroundings captured by a camera to determine whether the road surface on which the vehicle is traveling is a sunny road surface, a rainy road surface, or a snowy road surface. However, the road surface condition is not limited to image recognition, and may be determined based on, for example, the magnitude of the multiplication result _Vωyaw of the vehicle speed V and the rotational angular velocity _ωyaw when the vehicle turns, the lateral acceleration _αy , the magnitude of the rotational angular velocity _ωyaw , etc. In addition, at that time, the presence or absence of the wipers operation, the outside air temperature, etc. may be taken into consideration.

The K-value table 38 stores the vehicle parameters K in association with each road surface condition. In addition, when a new vehicle parameter K is calculated, the K-value table 38 updates the vehicle parameter K stored in association with the road surface condition for which the vehicle parameter K was calculated with the latest vehicle parameter K.

Vehicle parameter K varies depending on the number of occupants in the vehicle, the amount of luggage, the degree of tire wear, and road surface conditions. Of these variable factors, it is the road surface conditions that are most likely to change while the vehicle is traveling.

In this regard, as described above, if the vehicle parameter K is stored in the K value table 38 in association with each road surface condition, it becomes possible to select the vehicle parameter K appropriate for each road surface condition based on the result of the determination of the road surface condition on which the vehicle is traveling by the road surface condition determination block 36, and the multiplication block 40 can calculate the sideslip angle with high accuracy using the selected vehicle parameter K.

In addition, in each of the above-described embodiments, the vehicle parameter K is used as a coefficient for approximating the side slip angle estimated value β _est and the multiplication result Vω _yaw of the vehicle speed V and the rotational angular velocity ω _yaw , but it is also possible to use the cornering power Cf, since the vehicle parameter K and the cornering power Cf have a certain relationship as shown in Equation 4.

1: Acceleration sensor, 2: Gyro sensor, 3: Wheel speed sensor, 4: GNSS receiver, 10: Side slip angle calculation device, 12: Gravity component removal block, 14: Band pass filter block, 16: Band pass filter block, 18: Vehicle speed correction block, 20: Error removal calculation block, 22: Integration block, 24: Multiplication block, 26: Scene determination block, 28: Angle calculation block, 30: Control circuit, 32: Adaptive filter, 36: Road surface condition determination block, 38: K value table, 40: Multiplication block

Claims (10)

a sideslip angle estimation value calculation unit (14, 16, 20, 22) that receives a lateral acceleration (α _y ), a vehicle speed (V), and a rotational angular velocity (ω _yaw ) of a vehicle, and calculates a vehicle sideslip angle estimation value (β _est ) based on the received lateral acceleration (α _y ), vehicle speed (V), and rotational angular velocity (ω _yaw );
a multiplication unit (24) that calculates a multiplication result (Vω _yaw ) by multiplying a vehicle speed (V) and a rotational angular velocity (ω _yaw );
and a parameter calculation unit (28) that calculates a parameter (K) that is a coefficient that approximates the sideslip angle estimated value (β _est ) calculated by the sideslip angle estimated value calculation unit and the multiplication result (Vω _yaw ) calculated by the multiplication unit, wherein the vehicle sideslip angle is calculated from the multiplication result (Vω _yaw ) of the vehicle speed (V) and the rotational angular velocity (ω _yaw ) and the parameter (K) calculated by the parameter calculation unit. The sideslip angle estimated value calculation unit (14, 16, 20, 22) calculates a sideslip angle estimated value (β _est ) by integrating a sideslip angle differential value (dβ) obtained by subtracting a rotational angular velocity (ω _yaw ) from a division result (α _y /V) obtained by dividing a lateral acceleration (α _y ) by a vehicle speed (V);
2. The sideslip angle calculation device according to claim 1, wherein the sideslip angle estimated value calculation unit (14, 16, 20, 22) calculates the sideslip angle estimated value (β _est ) by integrating the sideslip angle differential value (dβ) from which the offset error has been removed, using a sideslip angle differential value (dβ) calculated before the vehicle starts turning and when the vehicle is traveling straight as an offset error (dβ ₀ ). The sideslip angle calculation device according to claim 2, wherein the sideslip angle estimated value calculation unit (14, 16, 20, 22) performs bandpass filtering on the sideslip angle differential value (dβ). 4. The sideslip angle calculation device according to claim 3, wherein the sideslip angle estimated value calculation unit performs bandpass filtering on at least a lateral acceleration (α _y ) and a rotational angular velocity (ω _yaw ) as the bandpass filtering on the sideslip angle differential value (dβ). A determination unit (26) is provided for determining whether the vehicle is turning,
5. The side slip angle calculation device according to claim 1, wherein the parameter calculation unit (28) specifies a maximum value of the vehicle side slip angle estimation value (β _est ) and a maximum value of the multiplication result (Vω _yaw ) of the vehicle speed (V) and the rotational angular velocity (ω _yaw ) while the vehicle is turning (S200, S210), and calculates a parameter (K) based on the specified maximum value of the vehicle side slip angle estimation value (β _est ) and the maximum value of the multiplication result (Vω _yaw ) of the vehicle speed (V) and the rotational angular velocity (ω _yaw ) (S220). A determination unit (26) is provided for determining whether the vehicle is turning,
The side slip angle estimation value calculation unit (14, 16, 20, 22) calculates the side slip angle estimation value (β _est ) a plurality of times while the vehicle is turning (S300, S310);
The multiplication unit (24) calculates a multiplication result (Vω _yaw ) of the vehicle speed (V) and the rotational angular velocity (ω _yaw ) multiple times in synchronization with the calculation of the side slip angle estimated value (β _est ) while the vehicle is turning (S320);
5. The side slip angle calculation device according to claim 1, wherein the parameter calculation unit (28) calculates a plurality of parameters (K) based on the side slip angle estimated value (β _est ) calculated a plurality of times and a multiplication result (Vω _yaw ) of the vehicle speed (V) and the rotational angular velocity (ω _yaw ) (S330), and calculates the parameter (K) by a most frequently occurring value of the plurality of parameters (K) or an average value after excluding outliers (S340). A determination unit (26) is provided for determining whether the vehicle is turning,
5. The sideslip angle calculation device according to claim 1, wherein the parameter calculation unit applies an adaptive filter to one of the sideslip angle estimated value (β _est ) calculated by the sideslip angle estimated value calculation unit and the multiplication result (Vω _yaw ) calculated by the multiplication unit while the vehicle is turning, adjusts a transfer function of the adaptive filter so that an output of the adaptive filter approximates the other of the sideslip angle estimated value (β _est ) calculated by the sideslip angle estimated value calculation unit and the multiplication result (Vω _yaw ) calculated by the multiplication unit, and calculates a parameter (K) from the adjusted transfer function. 8. The side slip angle calculation device according to claim 5, wherein the parameter calculation unit (28) calculates the parameter (K) on the condition that a vehicle speed (V) of the turning vehicle is equal to or lower than a predetermined reference speed (S130). 8. The sideslip angle calculation device according to claim 5, wherein the parameter calculation unit (28) is configured such that, when the vehicle sideslip angle calculated based on the calculated parameter (K) exceeds a predetermined upper limit value, the calculated parameter (K ) is not used for calculating the vehicle sideslip angle (S180). A road surface condition determination unit (36) for determining the condition of a road surface on which a vehicle is traveling;
a parameter storage unit (38) that stores the parameter (K) calculated by the parameter calculation unit or updates the stored parameter (K) according to the road surface condition determined by the road surface condition determination unit;
8. The sideslip angle calculation device according to claim 5, wherein a parameter (K) corresponding to a road surface condition is selected from the parameters (K) stored in the parameter storage unit, and the vehicle sideslip angle is calculated based on the selected parameter ( K ).

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