Road-surface friction coefficient estimation device, road-surface friction coefficient estimation method, and program

Abstract

To provide a road-surface friction coefficient estimation device, a road-surface friction coefficient estimation method, and program which can accurately estimate a road-surface friction coefficient and facilitate performing control adjustment.SOLUTION: A road-surface friction coefficient estimation device comprises: a lateral acceleration calculator configured to calculate a lateral acceleration using a wheel speed detected by a wheel speed sensor mounted in a vehicle, a vehicle-body roll angular velocity detected by an angular velocity sensor mounted in the vehicle, and vehicle-body lateral velocity and yaw rate calculated from a geometrical relationship; a coordinate converter configured to convert an acceleration detected by an acceleration sensor mounted in the vehicle to a measured lateral acceleration subjected to ground coordinate conversion; and a road-surface friction coefficient estimator configured to estimate a road-surface friction coefficient by using a road-surface friction model based on the calculated lateral acceleration and the converted lateral actual measurement acceleration.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a road surface friction coefficient estimation device, a road surface friction coefficient estimation method, and a program. [Background technology]

[0002] In recent years, efforts to provide access to sustainable transport systems that take into consideration vulnerable transport participants have become more active. To achieve this, we are focusing on research and development into driver assistance to further improve road safety and convenience.

[0003] In the field of driving assistance, two-wheeled vehicles equipped with an IMU (Inertial Measurement Unit) for detecting the vehicle state and performing stabilization control are known (see, for example, Patent Document 1). In order to detect changes in roll moment, which can cause two-wheeled vehicles to tip over, it is necessary to estimate the road friction coefficient.

[0004] For example, the road surface friction coefficient estimated value μ_estm, which is an estimate of the road surface friction coefficient μ, is calculated using δ1_sens, δ2_sens, γ_sens, γdot_sens, and Accy_sens from the detection values ​​of the observation target quantities generated by the observation target quantity detection means, the total road surface reaction force resultant translational force vector estimated value ↑Fg_total_estm and the total road surface reaction force resultant yaw moment estimated value Mgz_total_estm calculated by the vehicle model calculation means, and the vehicle center of gravity longitudinal speed estimated value Vgx_estm from the vehicle motion state quantity estimated values ​​calculated by the vehicle model calculation means (see, for example, Patent Document 2). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent Publication No. 2021-54184 [Patent Document 2] Patent No. 5185873 Summary of the Invention [Problem to be solved by the invention]

[0006] However, in the conventional technology, when estimating the sideslip angle and road friction coefficient, the sideslip angle is used to estimate the road friction coefficient, and the road friction coefficient is used to estimate the sideslip angle. In this way, in the conventional technology, the sideslip angle and the road friction coefficient are interdependent, making it difficult to adjust the control.

[0007] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a road surface friction coefficient estimation device, a road surface friction coefficient estimation method, and a program that can accurately estimate a road surface friction coefficient and facilitate control adjustment, thereby contributing to the development of a sustainable transportation system. [Means for solving the problem]

[0008] (1) In order to achieve the above-mentioned object, a road surface friction coefficient estimation device according to one embodiment of the present invention is a road surface friction coefficient estimation device including: a lateral acceleration calculation unit that calculates lateral acceleration using wheel speeds detected by wheel speed sensors mounted on a vehicle, a vehicle body roll angular velocity detected by an angular velocity sensor mounted on the vehicle, and a vehicle body lateral velocity and yaw rate calculated from a geometric relationship; a coordinate conversion unit that converts the acceleration detected by an acceleration sensor mounted on the vehicle into an actual measured lateral acceleration converted into ground coordinates; and a road surface friction estimation unit that estimates a road surface friction coefficient using a road surface friction model based on the calculated lateral acceleration and the converted actual measured lateral acceleration.

[0009] (2) In the road surface friction coefficient estimation device according to the aspect of (1) above, the lateral acceleration calculation unit may calculate the lateral acceleration under a condition where no slip occurs.

[0010] (3) In the road surface friction coefficient estimation device according to the aspect (1) or (2) above, the road surface friction estimation unit may estimate the road surface friction coefficient without using an estimated side slip angle value.

[0011] (4) The road surface friction coefficient estimation device according to any one of the above (1) to (3) may be provided with a control unit that uses the estimated road surface friction coefficient and sideslip angle to control the roll moment caused by acceleration from the inertial coordinate system.

[0012] (5) In order to achieve the above object, one embodiment of the present invention provides a road surface friction coefficient estimation method, in which a lateral acceleration calculation unit calculates lateral acceleration using a wheel speed detected by a wheel speed sensor mounted on a vehicle, a vehicle body roll angular velocity detected by an angular velocity sensor mounted on the vehicle, and a vehicle body lateral velocity and yaw rate calculated from a geometric relationship, a coordinate conversion unit converts the acceleration detected by an acceleration sensor mounted on the vehicle into an actual lateral acceleration converted into ground coordinates, and a road surface friction estimation unit estimates a road surface friction coefficient using a road surface friction model based on the calculated lateral acceleration and the converted actual lateral acceleration.

[0013] (6) In order to achieve the above object, a program according to one embodiment of the present invention causes a computer of a road surface friction coefficient estimation device to calculate lateral acceleration using wheel speeds detected by wheel speed sensors mounted on a vehicle, vehicle body roll angular velocity detected by angular velocity sensors mounted on the vehicle, and vehicle body lateral velocity and yaw rate calculated from a geometric relationship; converts the acceleration detected by an acceleration sensor mounted on the vehicle into measured lateral acceleration converted to ground coordinates; and estimates a road surface friction coefficient using a road surface friction model based on the calculated lateral acceleration and the converted measured lateral acceleration. [Effects of the Invention]

[0014] According to the above (1) to (6), the road surface friction coefficient can be estimated with high accuracy, and control adjustment can be easily performed. According to the above (4), it is possible to control the roll moment caused by the acceleration from the inertial coordinate system. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a diagram showing an example of the external shape of a saddle-ride type vehicle; [Figure 2] 1 is a diagram illustrating an example of the configuration of a road surface friction coefficient estimation system according to an embodiment; [Figure 3] FIG. 10 is a diagram for explaining the dynamics of a road surface friction coefficient model. [Figure 4] FIG. 10 is a diagram illustrating an example of a geometric model, which is used to calculate the ground lateral acceleration ay_model. [Figure 5] FIG. 10 is a diagram for explaining signs and the like used in calculating the ground lateral acceleration ay_model. [Figure 6] FIG. 10 is a diagram for explaining symbols and the like used in calculating an actual wheel radius. [Figure 7] 10 is a flowchart illustrating an example of a processing procedure of a control device according to the embodiment. [Figure 8] 10A and 10B are diagrams illustrating examples of actual measured values ​​and estimated results of lateral acceleration during slalom running. [Figure 9] FIG. 10 is a diagram showing an example of the results of road surface friction coefficient estimation. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the drawings used in the following description, the scale of each component is appropriately changed so that each component can be recognized. In all the drawings for explaining the embodiments, the same reference numerals are used for components having the same functions, and repeated explanations will be omitted. Furthermore, in this application, "based on XX" means "based on at least XX," and includes cases where it is based on other elements in addition to XX. Furthermore, "based on XX" is not limited to cases where XX is used directly, but also includes cases where it is based on XX that has been calculated or processed. "XX" is any element (for example, any information).

[0017] <Vehicle exterior> Fig. 1 is a diagram showing an example of the exterior shape of a saddle-ride type vehicle. Fig. 1 shows a scooter-type two-wheeled vehicle 1 having a floor portion (low floor portion) on which a rider (driver) places his / her feet as an example of the saddle-ride type vehicle, but the saddle-ride type vehicle is not limited to this. The vehicle 1 includes, for example, front wheels 3 which are steerable wheels, rear wheels 4 which are drive wheels, a seat 5 in which the driver sits, a front body FB connected to the front of the floor section, a rear body RB connected to the rear of the floor section, a control device 6 (road surface friction coefficient estimation device), an IMU 71, a steering angle sensor 72, and a wheel speed sensor 73.

[0018] The front wheels 3 can be steered by a bar handle (steering handle) 2. A pair of left and right grip portions 2a that are gripped by the rider with the left and right hands are provided on the left and right sides of the handlebar bar 2. The periphery of the handlebar bar 2 is covered with a handlebar cover 2b except for the left and right grip portions 2a. For example, the control device 6 and the IMU 71 are housed inside the front body FB. A steering angle sensor 72 and a wheel speed sensor 73 are attached to the front and rear wheels, respectively.

[0019] <Road surface friction coefficient estimation system> 2 is a diagram showing an example of the configuration of a road surface friction coefficient estimation system according to this embodiment. The road surface friction coefficient estimation system includes, for example, an IMU 71, a steering angle sensor 72, a wheel speed sensor 73, and a control device 6. The control device 6 includes, for example, a vehicle body roll angular velocity acquisition unit 601, a vehicle body lateral velocity calculation unit 602, a yaw rate calculation unit 603, a wheel speed calculation unit 604, a ground lateral acceleration calculation unit 605 (lateral acceleration calculation unit), a coordinate conversion unit 606, a road surface friction coefficient estimation unit 607 (road surface friction coefficient unit), a sideslip angle estimation unit 608, a control unit 609, and a memory unit 610. The IMU 71 includes, for example, an acceleration sensor 711 and an angular velocity sensor 712 .

[0020] The acceleration sensor 711 detects, for example, acceleration in the front-rear direction of the vehicle 1, the up-down direction of the vehicle 1, and the left-right direction of the vehicle 1. The angular velocity sensor 712 detects, for example, the angular velocity in each of the pitch direction of the vehicle 1, the roll direction of the vehicle 1, and the yaw direction of the vehicle 1.

[0021] The steering angle sensor 72 detects, for example, the steering angle of the front wheels and the steering angle of the rear wheels. The wheel speed sensor 73 detects, for example, the wheel speed of the front wheels and the wheel speed of the rear wheels.

[0022] The control device 6 is, for example, an ECU (Engine Control Unit).

[0023] The vehicle body roll angular velocity acquisition unit 601 acquires the vehicle body roll angular velocity ((-hφ ·· b )(cosφ b )) to get the

[0024] The vehicle lateral velocity calculation unit 602 calculates the vehicle lateral velocity V using a geometric model of the vehicle that is assumed to be free of slip. · oy_geo Calculate.

[0025] The yaw rate calculation unit 603 calculates the yaw rate ω using a geometric model of the vehicle that assumes no slip. z_geo Calculate.

[0026] The wheel speed calculation unit 604 calculates the wheel speeds V of the front and rear wheels based on the values ​​detected by the wheel speed sensors 73. ox_wheel Calculate.

[0027] The ground lateral acceleration calculation unit 605 calculates the ground lateral acceleration a using the vehicle body roll angular velocity, vehicle body lateral velocity, wheel speed, and yaw rate as shown in the following equation (1). y_model Calculate.

[0028]

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[0029] The coordinate conversion unit 606 calculates the lateral acceleration using the acceleration detected by the IMU 71. The coordinate conversion unit 606 performs earth coordinate conversion by removing the gravitational acceleration component from the calculated lateral acceleration.

[0030] The road surface friction coefficient estimation unit 607 adjusts the parameters m, k, d, and c in the following equations (2) and (3) using, for example, data obtained when the vehicle 1 is actually traveling. Note that the signs in equation (2) and the dynamics of the road surface friction coefficient model will be described later. Note that F is a y_act and a y_model The value is determined by comparing the values ​​of the dead zone and the dead zone. y_act is the acceleration converted by the coordinate conversion unit 606. c is a positive integer. The road friction coefficient estimation unit 607 is a model that uses the dynamics of the road friction coefficient model, and is constructed based on, for example, a disturbance observer configuration of the lateral acceleration. The ground lateral acceleration a calculated by the ground lateral acceleration calculation unit 605 is y_model (acceleration model) and the absolute value of a converted by the coordinate conversion unit 606 y_act The road friction coefficient μ is estimated by comparing the absolute value of

[0031]

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[0032]

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[0033] A sideslip angle estimation unit 608 estimates the sideslip angle using the road surface friction coefficient estimated by the road surface friction coefficient estimation unit 607 and the detection values ​​of the IMU 71, steering angle sensor 72, and wheel speed sensor 73. An example of the configuration and processing of the sideslip angle estimation unit 608 will be described later.

[0034] The control unit 609 uses the estimated road friction coefficient and sideslip angle to control the roll moment caused by acceleration from the inertial coordinate system. The control unit 609 controls the roll moment caused by movement of the mass point position and contact point movement based on the steering angles of the front and rear wheels.

[0035] The storage unit 610 stores mathematical formulas, predetermined values, processing algorithms, etc. used by each unit.

[0036] <Dynamics of road friction coefficient model> Figure 3 is a diagram for explaining the dynamics of the road friction coefficient model. Reference symbol g11 denotes the road surface, reference symbol g12 denotes the mass, reference symbol g13 denotes the spring, and reference symbol g14 denotes the damper. The length EL is the natural length, which is the length at which the mass is balanced by the spring and damper. Here, the natural length is set to 1. m is the mass of the mass, k is the spring coefficient, d is the damper coefficient, and μ is the road friction coefficient. F is the force acting on the mass, and is calculated using equation (3). Note that the dead zone in equation (3), Deadzone, is determined, for example, by actual measurement or simulation.

[0037] The dynamics of the road friction coefficient model is calculated by the road friction coefficient estimation unit 607. y_model and the absolute value of a converted by the coordinate conversion unit 606 y_act Compared with the absolute value of |a y_act |<|a y_model The road friction coefficient μ is reduced when |a y_act |≧|a y_model In the case of |, the road friction coefficient μ is increased. Ideally, |a y_act | and |a y_model If they do not match, the road friction coefficient is assumed to be not 1 and is adjusted as described above. In the model, the road friction coefficient μ is set to 1 as the initial value.

[0038] <Ground lateral acceleration a y_model Calculation of> Figure 4 shows an example of a geometric model. y_modelδ' is a diagram illustrating an example of elements used in calculating (acceleration model value). L is the distance between the front and rear wheels, Lf is the distance from the center (or center of gravity) position g21 of L to the front wheels, and Lr is the distance from the center (or center of gravity) position g21 of L to the rear wheels. f is the inclination angle of the front wheels of the vehicle 1 relative to the traveling direction, and is also the angle between the road surface passing through the turning center O and the front wheels passing through the turning center O. r is the tilt angle of the rear wheels of the vehicle 1 relative to the direction of travel, and is also the angle between the road surface passing through the turning center O and the rear wheels passing through the turning center O. ox_wheel are the wheel speeds of the front and rear wheels, respectively.

[0039] Figure 5 shows the lateral acceleration a y_model 6 is a diagram for explaining symbols and the like used in the calculation of the actual wheel radius. In Figures 5 and 6, δ i is the steering angle of the front or rear wheels, and δ i ' is the actual steering angle (actual yaw angle) of the front or rear wheels, and φ i is the roll angle of the front or rear wheels, and ω i is the angular velocity of the front or rear wheel, and R i is the radius of the front or rear wheel, and R S_i is the cross-sectional radius of the front or rear wheel, and θ ci is the caster angle of the front or rear wheels. Note that i is the front wheel f (front) and the rear wheel r (rear). Also, R i is the radius of the front or rear wheel, and h is the height from the road surface to the center of gravity m, for example.

[0040] Here, in equation (1), V · oy_geo is a geometrically computable V oy_geo is calculated, for example, by pseudo-differentiation.

[0041]

number

[0042] Also, V ox_wheelis the following equation (5), and φ i is the following equation (6), and δ i ' is the following equation (7).

[0043]

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[0044]

number

[0045]

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[0046] In addition, in formula (5), (R i -R S_i (1-cosφ i ) is the actual wheel radius. Also, in equation (1), ω z_geo is calculated using the following equation (8).

[0047]

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[0048] In the prior art (see, for example, Japanese Patent No. 5208831), a tire model is used to calculate the acceleration model value, and the tire lateral force F yf and rear tire lateral force F yr The tire lateral force Fy is calculated by dividing the sum of the road friction coefficient and the sideslip angle by the vehicle weight. Note that the calculation of tire lateral force Fy requires the road friction coefficient and the sideslip angle. In this way, in the conventional technology, the estimation of the road friction coefficient and the estimation of the sideslip angle are mutually dependent. When these are mutually dependent, there are cases where it is not possible to uniquely identify the parameters for the road friction coefficient and the parameters for estimating the sideslip angle.

[0049] In contrast, in this embodiment, the ground lateral acceleration a y_modelis calculated as shown in equation (1) using a geometric model, assuming no slip, without using the estimated sideslip angle.

[0050] <Estimation of sideslip angle> Next, the estimation of the sideslip angle will be described. The sideslip angle is estimated, for example, by the method described in Patent Document 2. In this case, unlike the method described in Patent Document 2, the present embodiment does not use the sideslip angle estimated in estimating the road surface friction coefficient.

[0051] <Example of processing procedure> FIG. 7 is a flowchart showing an example of a processing procedure of the control device according to this embodiment.

[0052] (Step S1) The vehicle body roll angular velocity acquisition unit 601 acquires the vehicle body roll angular velocity ((-hφ)) from the IMU 71. ·· b )(cosφ b )) to get the

[0053] (Step S2) The vehicle lateral velocity calculation unit 602 calculates the vehicle lateral velocity V using a geometric model of the vehicle that is assumed to be slip-free. · oy_geo Calculate.

[0054] (Step S3) The yaw rate calculation unit 603 calculates the yaw rate ω using a geometric model of the vehicle that is assumed to have no slip. z_geo Calculate.

[0055] (Step S4) The wheel speed calculation unit 604 calculates the wheel speeds V of the front and rear wheels based on the values ​​detected by the wheel speed sensors 73. ox_wheel Calculate.

[0056] (Step S5) The ground lateral acceleration calculation unit 605 calculates the ground lateral acceleration a using the vehicle body roll angular velocity, the vehicle body lateral velocity, the wheel speed, and the yaw rate as shown in Equation (1). y_model Calculate.

[0057] (Step S6) The coordinate conversion unit 606 calculates the lateral acceleration using the acceleration detected by the IMU 71. Subsequently, the coordinate conversion unit 606 performs ground coordinate conversion by removing the gravitational acceleration component from the calculated lateral acceleration.

[0058] (Step S7) The road surface friction coefficient estimation unit 607 calculates the ground lateral acceleration a calculated by the ground lateral acceleration calculation unit 605. y_model (acceleration model) and the absolute value of a converted by the coordinate conversion unit 606 y_act The road friction coefficient μ is estimated by comparing the absolute value of

[0059] (Step S8) The sideslip angle estimating unit 608 estimates the sideslip angle using the road surface friction coefficient estimated by the road surface friction coefficient estimating unit 607 and the detection values ​​of the IMU 71, steering angle sensor 72, and wheel speed sensor 73.

[0060] (Step S9) The control unit 609 uses the estimated road surface friction coefficient and sideslip angle to control the roll moment caused by the acceleration from the inertial coordinate system. The control unit 609 controls the roll moment caused by the movement of the mass point position and the contact point movement based on the steering angles of the front and rear wheels.

[0061] The control device 6 repeats the above process while the vehicle 1 is traveling. The above-described processing procedures are merely examples, and are not limiting. For example, some processes may be performed in parallel.

[0062] <Example of evaluation results> FIG. 8 shows an example of the actual measured value and the estimated result of the lateral acceleration during slalom running. The horizontal axis is time (s), and the vertical axis is the lateral acceleration a y (m / s 2 ) The evaluation was performed on a dry road surface with the vehicle 1 traveling at a speed of 15 km / h. Line g201 represents actual measured values, and line g202 represents values ​​calculated by the ground lateral acceleration calculation unit 605 of this embodiment. As shown in Fig. 8, it was confirmed that on dry roads, the measured and estimated lateral acceleration values ​​were almost identical.

[0063] FIG. 9 is a diagram showing an example of the results of road surface friction coefficient estimation. The horizontal axis is time (s) and the vertical axis is road surface friction coefficient μ(-). Line g211 represents the lateral acceleration a y_act =a y_act The line g212 is an example of a virtual lateral acceleration value halved. y_act =0.5a y_act This is an example of the case where As shown by line g211, when driving on a dry road, the road friction coefficient is approximately 1, which allows for an accurate estimation. When the lateral acceleration is virtually halved, as shown by line g212, the road friction coefficient becomes approximately 0.5, which is an appropriate estimate. As described above, it was confirmed that the method of this embodiment can appropriately calculate the road surface friction coefficient.

[0064] In the above example, the vehicle 1 has been described as having two wheels, but the present invention is not limited to this. The vehicle 1 may have, for example, three or four wheels. The vehicle 1 may also be driven by an engine, an engine and a motor, or a motor.

[0065] In the above example, the IMU 71 is used as an example of a sensor for detecting acceleration and angular velocity, but the present invention is not limited to this. The sensor for detecting acceleration and angular velocity may be a six-axis sensor or a combination of an acceleration sensor and an angular velocity sensor.

[0066] A program for implementing some or all of the functions of the control device 6 of the present invention may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be loaded into a computer system and executed to perform all or part of the processing performed by the control device 6. Note that the term "computer system" as used herein includes hardware such as an OS and peripheral devices. The term "computer system" also includes a WWW system equipped with a homepage provision environment (or display environment). The term "computer-readable recording medium" refers to portable media such as flexible disks, optical magnetic disks, ROMs, and CD-ROMs, as well as storage devices such as hard disks built into computer systems. The term "computer-readable recording medium" also includes devices that retain a program for a certain period of time, such as volatile memory (RAM) within a computer system that acts as a server or client when the program is transmitted via a network such as the Internet or a communication line such as a telephone line. Alternatively, some or all of these components may be realized by LSI (Large Scale Integration) such as ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), GPU (Graphics Processing Unit), or SOC (System On Chip) or hardware (including circuitry), or may be realized by a combination of software and hardware.

[0067] The program may also be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by transmission waves in the transmission medium. Here, the "transmission medium" that transmits the program refers to a medium that has the function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may also be a program that realizes part of the above-mentioned functions. Furthermore, the program may be a so-called differential file (differential program) that can realize the above-mentioned functions in combination with a program already recorded in the computer system.

[0068] The above describes the form for carrying out the present invention using an embodiment, but the present invention is not limited to such an embodiment, and various modifications and substitutions can be made within the scope that does not deviate from the gist of the present invention. [Explanation of symbols]

[0069] 1...vehicle, 71...IMU, 72...steering angle sensor, 73...wheel speed sensor, 6...control device, 601...vehicle body roll angular velocity acquisition unit, 602...vehicle body lateral velocity calculation unit, 603...yaw rate calculation unit, 604...wheel speed calculation unit, 605...ground lateral acceleration calculation unit, 606...coordinate conversion unit, 607...road surface friction coefficient estimation unit, 608...side slip angle estimation, 609...control unit, 610...storage unit, 711...acceleration sensor, 712...angular velocity sensor

Claims

1. a lateral acceleration calculation unit that calculates a lateral acceleration using a wheel speed detected by a wheel speed sensor mounted on the vehicle, a vehicle body roll angular velocity detected by an angular velocity sensor mounted on the vehicle, and a vehicle body lateral velocity and yaw rate calculated from a geometric relationship; a coordinate conversion unit that converts the acceleration detected by the acceleration sensor mounted on the vehicle into a measured acceleration in a lateral direction that has been converted to a ground coordinate; a road surface friction estimating unit that estimates a road surface friction coefficient using a road surface friction model based on the calculated lateral acceleration and the converted actual measured lateral acceleration; A road surface friction coefficient estimation device comprising:

2. the lateral acceleration calculation unit calculates the acceleration in the lateral direction under a condition where no slip occurs. The road surface friction coefficient estimation device according to claim 1 .

3. the road surface friction estimation unit estimates the road surface friction coefficient without using an estimated sideslip angle value; 3. The road surface friction coefficient estimation device according to claim 1 or 2.

4. a control unit that controls a roll moment caused by acceleration from an inertial coordinate system using the estimated road surface friction coefficient and sideslip angle; The road surface friction coefficient estimation device according to claim 1 or 2, comprising:

5. a lateral acceleration calculation unit that calculates a lateral acceleration using a wheel speed detected by a wheel speed sensor mounted on the vehicle, a vehicle body roll angular velocity detected by an angular velocity sensor mounted on the vehicle, and a vehicle body lateral velocity and yaw rate calculated from a geometric relationship; a coordinate conversion unit converting the acceleration detected by the acceleration sensor mounted on the vehicle into an actual measured acceleration in a lateral direction by ground coordinate conversion; a road surface friction estimation unit that estimates a road surface friction coefficient using a road surface friction model based on the calculated lateral acceleration and the converted actual measured lateral acceleration; Method for estimating road surface friction coefficient.

6. The computer of the road friction coefficient estimation device calculating a lateral acceleration using a wheel speed detected by a wheel speed sensor mounted on the vehicle, a vehicle body roll angular velocity detected by an angular velocity sensor mounted on the vehicle, and a vehicle body lateral velocity and yaw rate calculated from a geometric relationship; converting the acceleration detected by an acceleration sensor mounted on the vehicle into a measured lateral acceleration that has been converted to a ground coordinate system; a road friction coefficient is estimated using a road friction model based on the calculated lateral acceleration and the converted actual measured lateral acceleration; program.

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