JP4909644B2 - Road surface friction coefficient determination method and apparatus, and road surface friction coefficient determination program - Google Patents

Description

  The present invention relates to a method and apparatus for determining a friction coefficient of a road surface, and a program. More specifically, a road surface friction coefficient determination method and apparatus capable of improving the performance and safety of the vehicle by determining the road surface friction coefficient between the road surface and the tire using rotation information of four tire wheels, and The present invention relates to a road surface friction coefficient determination program.

  Conventionally, by utilizing the fact that the relationship between the slip ratio and acceleration of a tire of a four-wheel vehicle changes, the relationship between the slip ratio and acceleration is obtained from the primary regression calculation result, so that the road surface friction coefficient between the road surface and the tire is obtained. A determination method has been proposed (see, for example, Patent Document 1).

  However, in this method, since the regression calculation is performed according to the least square approximation method, even if the road surface state changes within the sampling time for performing the regression calculation, only an averaged regression line can be obtained. There was a problem that an accurate regression line corresponding to each road surface condition could not be obtained. In addition, the primary regression calculation method used in Patent Document 1 has a problem that the number of calculations is large, and that many of them include multiplication and division with a large load on the computer.

JP 2001-253334 A

  The present invention provides a method capable of reducing the number of calculations for obtaining a linear regression line of slip ratio and acceleration, and capable of accurately detecting a road surface friction coefficient even when the road surface state is not constant. With the goal.

  The present invention includes a step of detecting the rotational speed of four tires of a vehicle, a step of calculating vehicle speed, vehicle acceleration, and slip ratio from the tire rotational speed, a step of accumulating vehicle acceleration and slip ratio, A road surface including a step of obtaining a first-order regression coefficient with the slip ratio, and a step of determining a friction coefficient between the road surface and the tire by comparing the first-order regression coefficient with a preset threshold value In the friction coefficient determination method, when the accumulated slip rate and vehicle acceleration sample data continuously change with a change amount within a certain range, one or more points near the start point of the sample data. The present invention relates to a road surface friction coefficient determination method for calculating the primary regression coefficient based on an average value and an average value of one or more sample data near the end point.

  It is preferable to include a step of detecting the absolute speed of the vehicle, and calculate the slip ratio from the absolute speed and the tire rotation speed.

  Preferably, the method includes a step of detecting the absolute speed of the vehicle, and the vehicle acceleration is calculated from the absolute speed.

  The present invention includes a step of detecting rotational speed and wheel torque information of four tires of a vehicle, a step of calculating a slip ratio from the rotational speed, a step of accumulating the slip ratio and wheel torque, and a slip ratio and wheel torque. A method for determining a road surface friction coefficient, including a step of obtaining a primary regression coefficient of each other, and a step of determining a friction coefficient between the road surface and a tire by comparing the primary regression coefficient with a preset threshold value. When the accumulated slip rate and vehicle acceleration sample data continuously change with a change amount within a certain range, an average value of one or more points near the start point of the sample data, and The present invention relates to a road surface friction coefficient determination method for calculating the primary regression coefficient based on an average value of one or more sample data near an end point.

  It is preferable to include a step of detecting the absolute speed of the vehicle, and to calculate the slip ratio from the absolute vehicle speed and tire rotation information.

  The present invention provides means for detecting the rotational speed of four tires of a vehicle, means for calculating vehicle speed, vehicle acceleration, and slip ratio from the tire rotational speed, means for accumulating vehicle acceleration and slip ratio, vehicle acceleration, Road surface including means for obtaining a first-order regression coefficient with respect to the slip ratio, and means for determining a friction coefficient between the road surface and the tire by comparing the first-order regression coefficient with a preset threshold value In the friction coefficient determination device, when the accumulated slip rate and vehicle acceleration sample data continuously change with a change amount within a certain range, one or more points near the start point of the sample data The present invention relates to a road surface friction coefficient determination apparatus that calculates the primary regression coefficient based on an average value and an average value of one or more sample data near an end point.

  The present invention includes a computer for detecting a rotational speed of four tires of a vehicle, a procedure for calculating a vehicle speed, a vehicle acceleration, and a slip ratio from the tire rotational speed, a procedure for accumulating the vehicle acceleration and the slip ratio, Procedure for obtaining a first-order regression coefficient between vehicle acceleration and slip ratio, and a procedure for determining a friction coefficient between a road surface and a tire by comparing the first-order regression coefficient with a preset threshold value Is a program for determining the friction coefficient of the road surface, and when the accumulated sample data of the slip ratio and the vehicle acceleration continuously change with a change amount within a certain range, 1 near the start point of the sample data. The primary regression coefficient is calculated based on the average value of the points or two or more points, and the average value of one or more sample data near the end point. On the road surface friction coefficient determination program.

  The present invention relates to means for detecting rotational speed and wheel torque information of four tires of a vehicle, means for calculating a slip ratio from the rotational speed, means for storing a slip ratio and wheel torque, slip ratio and wheel torque. A road surface friction coefficient determination device including means for obtaining a primary regression coefficient of each other, and means for determining a friction coefficient between the road surface and the tire by comparing the primary regression coefficient with a preset threshold value When the accumulated slip rate and vehicle acceleration sample data continuously change with a change amount within a certain range, an average value of one or more points near the start point of the sample data, and The present invention relates to a road surface friction coefficient determination apparatus that calculates the primary regression coefficient based on an average value of one or more sample data near an end point.

  The present invention relates to a procedure for detecting the rotational speed and wheel torque information of four wheels of a vehicle, a procedure for calculating a slip ratio from the rotational speed, a procedure for accumulating the slip ratio and the wheel torque, and a slip ratio and a wheel torque. Road surface friction for causing each other to obtain a primary regression coefficient, and a procedure for determining a friction coefficient between the road surface and the tire by comparing the primary regression coefficient with a preset threshold value. A coefficient determination program, wherein when the accumulated slip rate and vehicle acceleration sample data continuously change with a change amount within a certain range, an average of one or more points near the start point of the sample data Road surface friction coefficient determination program for calculating the first-order regression coefficient based on the average value of one point or two or more sample data near the end point On-time.

  According to the method of the present invention, when determining the relationship between the slip ratio and the acceleration, the number of calculations can be reduced as compared with the conventional linear regression calculation, and the road surface is accurately obtained even when the road surface condition is not constant. It becomes possible to detect the friction coefficient.

  Hereinafter, a road surface friction coefficient determination method and apparatus and a road surface friction coefficient determination program according to the present invention will be described with reference to the accompanying drawings.

  As shown in FIG. 1, a road surface friction coefficient determination apparatus according to an embodiment of the present invention includes four tires FL, FR, RL and RR (hereinafter collectively referred to as Wi) provided in a four-wheel vehicle. And i = 1-4, 1: front left tire, 2: front right tire, 3: rear left tire, 4: rear right tire).

  As the rotation information detecting means 1, a wheel speed sensor that generates a rotation pulse using an electromagnetic pickup or the like and measures the wheel speed (rotation speed) of the rotation speed information from the number of pulses can be used. The output of the rotation information detecting means 1 is given to a control unit 2 which is a computer such as ABS. Connected to the control unit 2 are an alarm display 3 which is a display means composed of a liquid crystal display element, a plasma display element or a CRT for informing the road surface condition, and an initialization switch 4 operated by a driver.

  As shown in FIG. 2, the control unit 2 stores an I / O interface 2a necessary for signal exchange with an external device, a CPU 2b functioning as a center of arithmetic processing, and a control operation program for the CPU 2b. The ROM 2c and the RAM 2d into which data is temporarily written or the written data is read when the CPU 2b performs a control operation.

  The present embodiment includes a rotation information detection unit 1 that detects rotation information of each tire Wi, a calculation processing unit that calculates wheel speed, vehicle acceleration, and front and rear wheel slip ratios from the rotation information of each tire Wi, respectively. Storage means for accumulating vehicle acceleration and front and rear wheel slip ratios, arithmetic processing means for obtaining primary regression coefficients of vehicle acceleration and front and rear wheel slip ratios, and the primary regression coefficients are preset. Road surface friction coefficient determining means for determining a friction coefficient between the road surface and the tire by comparing the threshold values.

  The program for determining the road surface friction coefficient in the present embodiment is a calculation processing procedure for calculating the wheel speed, the vehicle acceleration, and the front and rear wheel slip ratios from the tire rotation information. An accumulation procedure for accumulating the slip ratio, an arithmetic processing procedure for obtaining a linear regression coefficient between the vehicle acceleration and the slip ratio of the front and rear wheels, and comparing the primary regression coefficient with a preset threshold value Thus, a road surface friction coefficient determination procedure for determining the friction coefficient between the road surface and the tire is executed.

  As the vehicle speed, for example, an absolute speed of the vehicle detected by a GPS device or the like may be used. As the GPS device, for example, VBOX (trade name) manufactured by RACELOGIC can be used. Since this VBOX employs a position specifying method called Kinematic GPS that corrects using the phase difference of the carrier wave of the satellite radio wave, the position can be specified with high accuracy. It is more preferable for the GPS device to be able to calculate the vehicle speed with high accuracy using the Doppler effect of the carrier wave.

  In this case, the slip ratio may be calculated from the detected absolute speed and the tire rotation speed, and a primary regression coefficient of the slip ratio and the vehicle acceleration may be obtained, or the vehicle acceleration may be calculated from the absolute speed. Alternatively, a linear regression coefficient between the vehicle acceleration and the slip ratio may be obtained.

  As another embodiment of the present invention, rotation information detection means and wheel torque information detection means for detecting the rotation information of each tire Wi, and the slip ratio of the front and rear wheels are calculated from the rotation information of each tire Wi. Arithmetic processing means, storage means for accumulating wheel torque and front and rear wheel slip ratios, arithmetic processing means for obtaining first order regression coefficients of wheel torque and front and rear wheel slip ratios, and the first order regression coefficients And road surface friction coefficient determining means for determining a friction coefficient between the road surface and the tire by comparing a preset threshold value.

  A program for determining a road surface friction coefficient in another embodiment includes a procedure for detecting the rotation speed information and wheel torque information of the tire in the control unit 2, and a calculation for calculating the slip ratio of the front and rear wheels from the rotation speed information. Processing procedure, accumulation procedure for accumulating wheel torque and front and rear wheel slip ratios, calculation processing procedure for obtaining first order regression coefficients of wheel torque and front and rear wheel slip ratios, and the first order regression coefficients. The road surface friction coefficient determination procedure for determining the friction coefficient between the road surface and the tire by comparing the threshold values is executed.

  Here, the wheel torque can be calculated and calculated from engine torque, engine speed, accelerator sensitivity, and the like.

  Next, the procedure of the road surface friction coefficient determination method of the present invention will be described.

  First, as shown in FIG. 3, after taking the rotation information, the wheel speed is calculated (steps S1 and S2), and then the vehicle acceleration and the slip ratio of the front and rear wheels are calculated from the wheel speeds of the four wheels (step S3). Then, the obtained vehicle acceleration and slip ratio are accumulated (step S4).

  Next, a primary regression coefficient (regression coefficient of the slip ratio of the front and rear wheels with respect to the vehicle acceleration) K1 is obtained (a specific method will be described later) (step S5). This primary regression coefficient (hereinafter also simply referred to as a regression coefficient) K1 is the relationship between the vehicle acceleration and the slip ratio here, and this regression coefficient K1 is used as a judgment value for the road surface friction coefficient.

  Next, a predetermined number N (for example, 20) of the regression coefficients during traveling of the vehicle are accumulated (step S6), and a determination value of the regression coefficient is obtained as an average value (step S7).

  The determination value is compared with a preset threshold value (step S8). When it is determined that the road surface is low μ, an alarm is issued by the alarm indicator 3. The threshold value is set in advance by conducting an experiment for each vehicle.

  Hereinafter, the operation procedure of the road surface friction coefficient determination apparatus according to the present embodiment will be described along (1) to (6).

(1) The wheel speeds (V1n, V2n, V3n, V4n) are calculated from the rotational speeds of the four-wheel tires FL, FR, RL and RR of the vehicle. For example, the wheel speed data at a certain point of each wheel tire FL, FR, RL, RR of the vehicle obtained from a sensor such as an ABS sensor is set as wheel speeds V1n, V2n, V3n, V4n.

(2) Next, the average wheel speed (Vfn, Vdn) of the driven wheel and the drive wheel is calculated. In the case of front wheel driving, the average wheel speeds Vfn and Vdn of the driven wheel and driving wheel at a certain time are obtained by the following equations (1) and (2).
Vfn = (V3n + V4n) / 2 (1)
Vdn = (V1n + V2n) / 2 (2)

(3) The vehicle acceleration (that is, the average wheel acceleration / deceleration of the driven wheel) Afn is calculated. Assuming that the average wheel speed Vfn−1 is obtained from the wheel speed data immediately before the average wheel speed Vfn of the driven wheel, the vehicle acceleration Afn is obtained by the following equation (3).
Afn = (Vfn−Vfn−1) / Δt / g (3)
Here, Δt is the time interval (sampling time) between the wheel speeds Vfn and Vfn−1 calculated from the wheel speed data, and g is the gravitational acceleration. The sampling time needs to be 0.1 second or less in order to reduce the variation in data and to determine in a short time. More preferably, it is 0.05 second or less. Note that the absolute speed of the vehicle may be detected using a GPS device or the like, and the vehicle acceleration may be calculated from the absolute speed.

(4) The slip ratio of the front and rear wheels is calculated according to the value of the vehicle acceleration Afn. First, when the vehicle is slipping with the driving wheel locked in the acceleration state (Vdn = 0, Vfn ≠ 0), or when the vehicle is stopped and the driving wheel is causing a wheel spin in the deceleration state (Vfn). = 0, Vdn ≠ 0) is assumed to be impossible, and the slip ratio Sn is calculated from the following equations (4) and (5).
Sn = (Vfn−Vdn) / Vdn when Afn ≧ 0 and Vdn ≠ 0
... (4)
Sn = (Vfn−Vdn) / Vfn when Afn <0 and Vfn ≠ 0
... (5)
In other cases, Sn = 1 is set.

(5) Accumulate the slip ratio and vehicle acceleration to obtain the regression coefficient.

(6) The procedure so far is repeated until the count starts from zero and is repeated 20 times, for example. Then, when the count reaches 20, the judgment value of the regression coefficient is obtained as an average value of 20 and compared with a preset threshold value, and the road surface information (such as slippery) is warned to the driver.

  In the procedure (5), the primary regression coefficient of the slip ratio and the vehicle acceleration is calculated by the following method.

  When the sample of the slip ratio or the vehicle acceleration changes continuously, a straight line connecting the sampling start point (point group) and the end point (point group) is defined as a primary regression line. Here, the “point group” is used because the accuracy of the regression depends on the detection accuracy of the sampling start point and end point. For example, a total of three points including the start point and two points before and after (time) thereof. When the average coordinate is used as a starting point, the regression accuracy can be improved. Specifically, the straight line connecting the start point and the end point may be used as the primary regression line when the vehicle acceleration changes continuously for 10 samples or more and the change amount between them is 0.02G or more. it can.

  Further, in order to adjust the regression accuracy, the amount of change of each sample is obtained, and it is determined how long samples with the same tendency are continuous. For example, the change from the previous sample to the latest sample is Δ1, the change from the previous sample to the previous sample is Δ2, and the x-axis direction and the y-axis direction are taken into account, Δ1x, If expressed as Δ1y, Δ2x, and Δ2y, the positive and negative signs of Δ1x and Δ2x and the positive and negative signs of Δ1y and Δ2y are determined. If both are the same, two changes are continuous (they have the same tendency). ). Furthermore, the signs of Δ1x and Δ1y may be the same. In order to increase the reliability of the result, not only the positive and negative signs but also the Δ1x and Δ2x magnitudes and the Δ1y and Δ2y magnitudes are provided with certain limits, and the limits may be adjusted. For example, a certain threshold value is provided, and it may be adopted as a sample only when each change amount is equal to or greater than the threshold value (or less than the threshold value).

  Next, a specific example will be described. For example, consider a case where the slope of a linear regression line is calculated from (x, y) of 10 sets of samples that change with the same tendency continuously. In the conventional method, the slope of the primary regression line is obtained from the sum of x, the sum of y, the sum of squares of x, the sum of squares of y, and the sum of products of x and y according to the following formula (6) (formula N indicates the number of samples). Here, the addition is 9 times to obtain the sum, 18 times in total with x and y, the multiplication is 10 times to obtain the sum of squares, the addition is 9 times, 19 times in total, 38 times in total with x and y, x In order to obtain the sum of the product of y and y, the product is 10 times, the sum is 9 times, a total of 19 times, and convenience is required 75 times (45 additions, 30 multiplications).

  On the other hand, in the method of the present invention, the slope of the linear regression line is obtained from the coordinates of the start point (point group) and end point (point group). Here, if the start point coordinates are (x1, y1), the end point coordinates are (x2, y2), the start point is determined by the average coordinates of the three start point groups, and the end point is determined by the average coordinates of the three end point groups. To determine the x coordinate of a point, two additions, one division, and 12 x and y coordinates of the start and end points are required. Since the slope is obtained by (y2−y1) ÷ (x2−x1), 2 subtractions, 1 multiplication, and 15 convenient operations are required (8 additions, 2 subtractions, 5 divisions).

  Furthermore, a separate calculation for determining the continuity of sample changes is required. In order to check whether the change from the previous sample to the latest sample has the same tendency as the change from the previous sample to the previous sample, the amount of change in the X-axis direction (subtraction) and the change in the Y-axis direction A total of 48 subtractions are required to verify the continuity because the subtraction of the amount (subtraction) is 2 times each, and the total of 4 subtractions and 2 comparison operations occur 8 times from the 3rd sample to the 10th sample. It becomes. In addition to this, assuming that a point group consisting of 3 points (3 samples) is used to calculate the value corresponding to the slope of the regression line, a total of 63 calculations are required (8 additions, 34 subtractions). , 5 divisions, 16 comparisons).

  In a computer, since the load of multiplication / division is larger than addition / subtraction and comparison, according to the present invention, it can be said that the effect of reduction of multiplication / division is greater than the reduction of the number of calculations.

  The number of samples does not need to be fixed, and the number of samples and the size of the sampling start point (point group) and sampling end point (point group) in the x-axis direction and the y-axis direction are determined as guidelines. (For example, 7 or more).

  When using the conventional regression calculation, it is difficult to optimize the number of samples to be used for the regression calculation according to the situation. However, depending on the number of samples used for regression calculation, only an averaged result may be obtained. When the number of samples is fixed, the sampling time is fixed. For example, if the sampling time is fixed at 10 seconds, the slipperiness on the road surface of the tire should be constant over the entire period of 10 seconds. However, if the slipperiness of the tire on the road surface is not constant, such as changing from asphalt to ice in 10 seconds, the slipperiness of the tire on the asphalt and the slipperiness of the tire on the ice surface Only slipperiness with respect to the road surface of the tire included in proportion to the included time length can be obtained.

  When the road surface on which two regression lines as shown in FIG. 4 are obtained is halved during the sampling time, for example, when the sampling time is 10 seconds, the road surface travels 5 seconds on the asphalt, and 5 seconds on the ice. The linear regression line obtained from the sampling data is the average of a (asphalt) and b (ice) (dotted line c in FIG. 4). On the other hand, the method of the present invention provides separate regression lines on ice and on asphalt. By obtaining an average value for each obtained regression line, the accuracy of the regression calculation result is not inferior.

  The present invention will be described below based on examples, but the present invention is not limited to such examples.

  The difference in accuracy according to the tendency of the sample data was examined in the case of using the primary regression coefficient calculation method and the general least square method in the present invention.

Example 1
Twenty sets of sample data (x, y) = (A, B) were collected, sample data 1 to 10 were defined as section 1, and sample data 11 to 20 were defined as section 2 (Table 1).

In section 1, the average value of the sample data 1 to 3 was set as the start point, the sample data 8 to 10 was set as the end point, and a straight line equation connecting the start point and the end point was obtained. Similarly, in section 2, the average value of the sample data 11 to 13 is set as the start point, the sample data 18 to 20 is set as the end point, and a straight line connecting the start point and the end point is obtained. Moreover, about the sample data 1-20, the formula of the linear regression line was calculated | required using the least square method. The results are shown in FIG.
Section 1: y = 1.032x-0.823
Section 2: y = 1.075x-0.951
Least square method: y = 1.09x-0.333

  In Table 1, coefficient C is a value obtained by estimating coefficient B from coefficient A using a linear regression coefficient obtained by the method of least squares, and error D is the difference between coefficient B and coefficient C. The coefficient C ′ is a value obtained by estimating the coefficient B from the coefficient A using the linear regression coefficient obtained by the method of the present invention, and the error D ′ is the difference between the coefficient B and the coefficient C ′.

Example 2
Twenty sets of sample data (x, y) = (A, B) different from Example 1 were collected (Table 2), and a linear regression line equation was similarly obtained. The results are shown in FIG.
Section 1: y = 0.954x + 0.293
Section 2: y = 2.253x−2.546
Least squares method: y = 1.443x + 0.388

  As in the first embodiment, when the change amount of each sample data (corresponding to the vehicle acceleration and the slip ratio) does not change so much in the data of the fixed number of samples, the method of the present invention uses the conventional method. There was no difference in accuracy compared to the least square method. On the other hand, it can be seen that when the tendency of the amount of change in the sample data changes remarkably from a certain point in time as in Example 2, a regression line can be obtained with higher accuracy than the least square method.

It is a block diagram which shows one Embodiment of the road surface friction coefficient determination apparatus of this invention. It is a block diagram which shows the electric constitution of the road surface friction coefficient determination apparatus in FIG. It is a figure which shows the flowchart of the road surface friction coefficient determination program of this invention. It is a schematic diagram of the linear regression line showing the slipperiness with respect to the road surface of a tire. (A) It is a figure which shows the linear regression line in Example 1. FIG. (B) It is a figure which shows the linear regression line in Example 2. FIG.

Explanation of symbols

1 Rotation information detection means 2 Control unit 3 Alarm indicator 4 Initialization switch

Claims (9)

A step of detecting the rotational speed of the four tires of the vehicle, a step of calculating the vehicle speed, the vehicle acceleration, and the slip ratio from the tire rotational speed, a step of accumulating the vehicle acceleration and the slip ratio, and the vehicle acceleration and the slip ratio, A method for determining a road surface friction coefficient, including a step of obtaining a primary regression coefficient of each other, and a step of determining a friction coefficient between the road surface and a tire by comparing the primary regression coefficient with a preset threshold value. Because
In the case where the accumulated sample data of the slip ratio and the vehicle acceleration continuously change with a change amount within a certain range, one or more average values near the start point of the sample data and 1 near the end point A road friction coefficient determination method for calculating the first-order regression coefficient based on an average value of sample data of two or more points. The road surface friction coefficient determination method according to claim 1, further comprising a step of detecting an absolute speed of the vehicle, and calculating a slip ratio from the absolute speed and the tire rotation speed. The road surface friction coefficient determination method according to claim 1, further comprising a step of detecting an absolute speed of the vehicle, wherein the vehicle acceleration is calculated from the absolute speed. A step of detecting rotational speed and wheel torque information of four tires of the vehicle, a step of calculating a slip ratio from the rotational speed, a step of accumulating the slip ratio and the wheel torque, and a mutual primary of the slip ratio and the wheel torque A method for determining a friction coefficient of a road surface, and a method for determining a friction coefficient between a road surface and a tire by comparing the primary regression coefficient with a preset threshold value,
In the case where the accumulated sample data of the slip ratio and the wheel torque continuously change with a change amount within a certain range, the average value of one point or two or more points near the start point of the sample data, and 1 near the end point A road friction coefficient determination method for calculating the first-order regression coefficient based on an average value of sample data of two or more points. 5. The road surface friction coefficient determination method according to claim 4, further comprising a step of detecting an absolute speed of the vehicle, and calculating a slip ratio from the absolute vehicle speed and tire rotation information. Means for detecting the rotational speed of four tires of the vehicle, means for calculating vehicle speed, vehicle acceleration and slip ratio from the tire rotational speed, means for storing vehicle acceleration and slip ratio, vehicle acceleration and slip ratio, A road surface friction coefficient determination device including means for obtaining a primary regression coefficient of each other, and means for determining a friction coefficient between the road surface and the tire by comparing the primary regression coefficient with a preset threshold value Because
In the case where the accumulated sample data of the slip ratio and the vehicle acceleration continuously change with a change amount within a certain range, one or more average values near the start point of the sample data and 1 near the end point A road surface friction coefficient determination device that calculates the primary regression coefficient based on an average value of sample data of two or more points. Procedures for detecting the rotational speed of the four tires of the vehicle in the computer, procedures for calculating the vehicle speed, vehicle acceleration and slip ratio from the tire rotational speed, procedures for accumulating the vehicle acceleration and slip ratio, vehicle acceleration and slip In order to execute a procedure for obtaining a first-order regression coefficient with a rate, and a procedure for determining a friction coefficient between a road surface and a tire by comparing the first-order regression coefficient with a preset threshold value A road surface friction coefficient determination program of
In the case where the accumulated sample data of the slip ratio and the vehicle acceleration continuously change with a change amount within a certain range, one or more average values near the start point of the sample data and 1 near the end point A road surface friction coefficient determination program that calculates the primary regression coefficient based on an average value of sample data of two or more points. Means for detecting rotational speed and wheel torque information of four tires of vehicle, means for calculating slip ratio from the rotational speed, means for accumulating slip ratio and wheel torque, mutual primary of slip ratio and wheel torque A road surface friction coefficient determination device including means for determining a regression coefficient of the road surface, a means for determining a friction coefficient between the road surface and a tire by comparing the primary regression coefficient with a preset threshold value,
In the case where the accumulated sample data of the slip ratio and the wheel torque continuously change with a change amount within a certain range, the average value of one point or two or more points near the start point of the sample data, and 1 near the end point A road surface friction coefficient determination device that calculates the primary regression coefficient based on an average value of sample data of two or more points. Procedure for detecting rotational speed and wheel torque information of four tires of vehicle, procedure for calculating slip ratio from the rotational speed, procedure for accumulating slip ratio and wheel torque, mutual primary of slip ratio and wheel torque A road surface friction coefficient determination program for executing a procedure for determining a friction coefficient between a road surface and a tire by comparing the primary regression coefficient with a preset threshold value. There,
In the case where the accumulated sample data of the slip ratio and the wheel torque continuously change with a change amount within a certain range, the average value of one point or two or more points near the start point of the sample data, and 1 near the end point A road surface friction coefficient determination program that calculates the primary regression coefficient based on an average value of sample data of two or more points.

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