JP2006056388A - Estimation method of road surface friction coefficient - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an estimation method of a road surface μ capable of easily calculating the road surface μ and securing the practical accuracy. <P>SOLUTION: The estimation method of the road surface friction coefficient estimating the road surface coefficient μ is composed of the step detecting the steering angle by a steering angle sensor, the step detecting the lateral acceleration by a lateral acceleration sensor, the step calculating an approximate μ, and the step fine-adjusting the road surface μ so that the difference between the estimated lateral acceleration and the lateral G detected by the lateral acceleration sensor becomes zero based on the approximate μ. The step calculating the approximate μ based on the road surface μ corresponding to the region in a plurality of road surface μi (i=1 to n) refers to the road surface μ determination table wherein the region composed of the steering angle and the lateral acceleration are defined for respective road surface μi (i=1 to n) and finds the region corresponding to the steering angle detected by the steering angle sensor and the lateral acceleration detected by the lateral acceleration sensor based on the boundary line derived from the lower limit of the lateral acceleration about respective steering angles in the combination of the steering angle and the lateral acceleration in respective road surface μi about a plurality of road surface μi (i=1 to n, wherein n is an integer of 2 or more). <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a method for estimating a road surface friction coefficient (hereinafter, road surface μ). In particular, the present invention relates to a method for estimating the road surface μ that is easy to calculate and can ensure practical accuracy.

  Conventionally, when controlling the motion state of a vehicle such as a turning motion, the optimal torque distribution control of the vehicle is performed using an angle (hereinafter referred to as a slip angle β) formed by the vehicle traveling direction and the center line of the vehicle longitudinal direction. The control which improves exercise | movement performance by performing etc. is known.

  Conventionally, as a method of estimating the slip angle β, a method of estimating the slip angle using a lateral force acting on the rear wheel in the lateral direction based on a tire dynamic model is described in Patent Document 1 as follows. Yes.

  Proportional / integral so that the difference between the lateral G detected by the lateral acceleration (lateral G) sensor and the lateral G estimated value estimated from the previous estimated slip angle differential value β ′, vehicle speed V, and yaw rate r becomes zero. An adjustment value for adjusting the initial value of the road surface μ is calculated by differentiation (PID) operation, and the road surface μ is estimated by adding the initial value of the road surface μ having the vicinity of 1 to the adjusted value.

A lateral force acting on the rear wheel (hereinafter referred to as tire lateral force Y _r ) is calculated based on the tire dynamic model from the estimated road surface μ and the slip angle β estimated immediately before, and the vehicle center of gravity detected by the yaw rate sensor is calculated. The rotational angular velocity about the vertical axis (hereinafter referred to as the yaw rate r), its differential value r ′, and the vehicle speed V detected by the vehicle speed sensor are substituted into the following equation (1) to differentiate the slip angle β in the time direction (slip The angular differential value β ′) is estimated.

β ′ = − 2 (L _f + L _r ) Y _r / mVL _f + Ir ′ / mVL _f −r−M / mVL _f
(1)
Where L _f is the distance from the vehicle center of gravity to the front wheel side axle, L _r is the distance from the vehicle center of gravity to the rear wheel side axle, Y _r is the tire lateral force, r ′ is the yaw rate differential value, m is the total mass of the vehicle, I is the yawing moment of inertia and M is the yawing moment.

The estimated slip angle derivative β ′ is integrated over time to estimate the current slip angle β. The lateral acceleration is estimated using the current estimated slip angle differential value β ′, the next estimated tire lateral force Y _r is calculated using the current estimated slip angle β recursively, and this tire lateral force Y _r is used. Thus, the slip angle differential value β ′ and the slip angle β are estimated.
JP 2003-306092 A

  As described above, when the road surface μ is estimated, the integration is performed by the integrator provided in the PID adjuster, and when the slip angle β is estimated, the integration of the slip angle differential value β ′ is performed by the integrator. It uses two integrators.

  Since the integrated signal includes the sensor signal from the vehicle, the integration result includes noise and error, and these are accumulated by integration, which may greatly deteriorate the estimation accuracy. In particular, since two integrators are used for estimating each of the road surface μ and the slip angle and each integration result is used for the estimation of the other, both the slip angle β and the road surface μ are mathematically true. It is also possible that the value does not converge.

  When the slip angle β cannot be accurately estimated, there is a problem that the motion state of the vehicle controlled using the slip angle cannot be accurately controlled.

  Therefore, it can be said that it is desirable not to use the value of the slip angle β estimated for the estimation of the road surface μ or to increase the influence even if it is used.

  The present invention has been made in view of the above problems, and an object of the present invention is to provide a method for estimating the road surface μ, which can easily calculate the road surface μ and can ensure practical accuracy.

  According to the first aspect of the present invention, in the road surface friction coefficient estimating method for estimating the road surface friction coefficient μ, a step of detecting a steering angle by a steering angle sensor, a step of detecting a lateral acceleration by a lateral acceleration sensor, and a plurality of steps For road surface μi (i = 1 to n, n is an integer of 2 or more), a boundary line derived from the lower limit value of the lateral acceleration for each rudder angle in the combination of the rudder angle and lateral acceleration on each road surface μi Based on the road surface μi (i = 1 to n), with reference to the road surface μ determination table in which a region composed of the steering angle and the lateral acceleration is defined, the steering angle detected by the steering angle sensor and the lateral Obtaining a region corresponding to the lateral acceleration detected by the acceleration sensor, and calculating an approximate μ based on the road surface μ corresponding to the region among the plurality of road surfaces μi (i = 1 to n). Characterized by A method for estimating a road surface friction coefficient is provided.

  According to the second aspect of the present invention, the step of finely adjusting the road surface μ based on the approximate μ so that the lateral acceleration difference between the estimated lateral acceleration and the lateral acceleration detected by the lateral acceleration sensor is zero. The road surface friction coefficient estimation method according to claim 1 is provided.

  According to a third aspect of the present invention, the step of calculating the approximate μ is more delayed in signal relative to the steering angle detected by the steering angle sensor than to the lateral acceleration detected by the lateral acceleration sensor. 3. A road surface friction coefficient estimating method according to claim 1, wherein a filtering process having a large characteristic is performed.

  According to a fourth aspect of the present invention, the method includes a step of detecting a vehicle speed by a vehicle speed sensor, wherein the road surface μ determination table includes a plurality of tables set for each vehicle speed according to the vehicle speed detected by the vehicle speed sensor. As a steering angle used when calculating properly or μ, the steering angle detected by the steering angle sensor is corrected with a correction coefficient corresponding to the vehicle speed detected by the vehicle speed sensor. The estimation method of the road surface friction coefficient in any one of Claims 1-3 characterized by the above-mentioned is provided.

  According to a fifth aspect of the present invention, the method includes the step of detecting the vehicle speed by a vehicle speed sensor, wherein the step of calculating the approximate μ is an approximate μ when the vehicle speed detected by the vehicle speed sensor is equal to or less than a specified value. The method of estimating a road surface friction coefficient according to any one of claims 1 to 4 is provided.

  According to a sixth aspect of the present invention, the step of calculating the approximate μ includes a steering angle detected by the steering angle sensor and a lateral acceleration detected by the lateral acceleration sensor rather than the currently estimated approximate μ. 6. The method according to claim 1, further comprising a step of reducing the approximate value of μ when the road surface μ corresponding to the region corresponding to is continued in a region where the road surface μ is small for a predetermined time or more. A method for estimating the road surface friction coefficient is provided.

  According to the invention of claim 7, the plurality of road surfaces μi (i = 1 to n) are defined with a constant step size, and the step of finely adjusting the road surface μ includes an upper limit value and a lower limit of a fine adjustment value. The method for estimating a road surface friction coefficient according to claim 2, wherein an absolute value of the value is equal to or larger than the step size.

  According to an eighth aspect of the present invention, the step of finely adjusting the road surface μ performs fine adjustment when the lateral acceleration detected by the lateral acceleration sensor is equal to or larger than a predetermined multiple of the current estimated value of μ. A method for estimating a road surface friction coefficient according to claim 2 or 7 is provided.

  According to the ninth aspect of the present invention, the step of finely adjusting the road surface μ includes a step of determining whether or not the value of the approximate μ has changed, and a fine adjustment value when the value of the approximate μ has changed. The method for estimating the road surface friction coefficient according to any one of claims 7 to 9 is provided.

  The road surface friction according to any one of claims 7 to 9, wherein the step of finely adjusting the road surface μ stops the fine adjustment when a counter steer is detected. A coefficient estimation method is provided.

  According to an eleventh aspect of the present invention, the step of calculating the approximate μ includes a step of detecting a straight traveling state, and a step of increasing the value of the approximate μ when a straight traveling state of a certain time or more is detected. Furthermore, the estimation method of the road surface friction coefficient in any one of Claims 1-10 characterized by the above-mentioned is provided.

  According to a twelfth aspect of the present invention, the step of calculating the approximate μ increases the approximate μ value when the lateral acceleration detected by the lateral acceleration sensor becomes larger than the current approximate μ value. A method for estimating a road surface friction coefficient according to any one of claims 1 to 11 is provided.

  According to the first aspect of the present invention, since the approximate μ that is relatively close to the road surface μ that is running is calculated without using the estimated value of the slip angle β of the vehicle body, both the slip angle and the road surface μ are estimated using integration. As a result, the estimation accuracy can be prevented from deteriorating, and the road surface μ can be estimated easily.

  According to the second aspect of the present invention, since the estimation result of the slip angle β is only used as a fine adjustment for estimating the road surface μ, the estimation result of the slip angle β does not greatly affect the estimation of the road surface μ. Accuracy is maintained.

  According to the third aspect of the invention, the delay characteristic of the lateral acceleration with respect to the rudder angle originally possessed by the vehicle characteristic is canceled by performing the filter process having a larger signal delay characteristic than the lateral acceleration with respect to the rudder angle. As a result, it is possible to mitigate the deterioration of the estimation accuracy in the case of sudden steering or the like.

  According to the fourth aspect of the invention, the method includes the step of detecting the vehicle speed by the vehicle speed sensor, and the road surface μ determination table uses a plurality of tables set for each vehicle speed according to the vehicle speed detected by the vehicle speed sensor. By increasing the number of tables to be set, the accuracy of the approximate μ can be improved, and as the steering angle used when calculating the approximate μ, the steering angle detected by the steering angle sensor is adjusted by the vehicle speed sensor. By using a corrected value corresponding to the detected vehicle speed, it is possible to easily create a table and calculate the approximate μ with high accuracy.

  According to the fifth aspect of the present invention, when the vehicle speed detected by the vehicle speed sensor is equal to or lower than the specified value, the approximate μ change is paused. For example, even if the steering angle is cut in a stopped state, the lateral G sensor Since the lateral acceleration detected by is kept at 0, it can be avoided that the estimated μ is reduced to the minimum value by stopping the estimation.

  According to the invention described in claim 6, the step of estimating the approximate μ corresponds to the steering angle detected by the steering angle sensor and the lateral acceleration detected by the lateral acceleration sensor rather than the currently estimated approximate μ. When the road surface μ corresponding to the area continues for a certain period of time in a small area, the approximate μ value is reduced, so the influence of sensor noise and the influence of the driving method can be avoided, and the approximate μ can be accurately calculated. Can be estimated.

  According to the seventh aspect of the present invention, the plurality of road surfaces μi (i = 1 to n) are defined with a constant step size, and the step of finely adjusting the road surface μ includes the upper limit value and the lower limit value of the fine adjustment value. Since the absolute value is equal to or larger than the step size, the range of the fine adjustment value is reduced, and the estimation accuracy of the road surface μ can be improved.

  According to the invention of claim 8, when the lateral acceleration detected by the lateral acceleration sensor is equal to or more than a predetermined multiple of the current estimated value of μ, the influence of the nonlinearity of the tire is large, and there is an effect of μ fine adjustment, In other cases, a significant decrease in accuracy can be prevented by stopping the fine adjustment.

  According to the ninth aspect of the present invention, when the approximate value of μ changes, the fine adjustment value is reset to 0, so that the accuracy when the approximate μ changes is improved.

  According to the tenth aspect of the present invention, since the accuracy of the estimated lateral acceleration is greatly deteriorated at the time of counter steer, fine adjustment of μ cannot be expected. Deterioration of estimation accuracy can be prevented.

  According to the eleventh aspect of the present invention, when the straight traveling state for a certain time or longer is detected, the estimated value of μ is increased. Therefore, it is possible to prevent the estimated value of the estimated μ from becoming too small. Deterioration of estimation accuracy can be prevented.

  According to the twelfth aspect of the present invention, since a lateral acceleration larger than the road surface μ cannot normally occur, when the lateral acceleration detected by the lateral acceleration sensor becomes larger than the current estimated μ value, the estimated By increasing the value of μ, an underestimation of the approximate μ can be prevented.

  FIG. 1 is a diagram showing a schematic configuration of a power transmission device for a four-wheel drive vehicle based on a front engine / front drive (FF) vehicle in which the vehicle body slip angle estimation method of the present invention can be implemented. As shown in FIG. 1, the power transmission system includes a front differential device 6 in which power from an engine 2 disposed in front of the vehicle is transmitted from an output shaft 4a of the transmission 4, and power from the front differential device 6 is transmitted from the vehicle. It mainly includes a speed increasing device (transmission device) 10 that is transmitted through a propeller shaft 8 that is a front and rear shaft, and a rear differential device 12 to which power from the speed increasing device 10 is transmitted.

The front differential device 6 has a conventionally known structure, and the power from the output shaft 4a of the transmission 4 is transmitted to the left and right front wheel drive shafts 20 and 22 via the plurality of gears 14 and the output shafts 16 and 18 in the differential case 6a. By transmitting, each front wheel is driven. Torque control of the left and right wheels 29 _FR and 29 _FL of the front wheels is controlled by, for example, an electromagnetic actuator.

The rear differential device 12 includes a pair of planetary gear sets and a pair of electromagnetic actuators that respectively control the engagement of a multi-plate brake mechanism (multi-plate clutch mechanism). The left and right rear wheel drive shafts are controlled by controlling the electromagnetic actuator. The rear wheels 29 _RR and 29 _RL are driven by transmitting the power to the rear wheels 29 _RR and 29 _RL .

Wheel speed sensors 30 are provided for the front wheels 29 _FL and 29 _FR and the rear wheels 29 _RR and 29 _RL , respectively, and the rotational speed of each wheel is detected. The vehicle speed sensor 32 detects a vehicle speed (vehicle speed V) from each wheel speed detected by the plurality of wheel speed sensors 30 and outputs an electric signal corresponding to the vehicle speed V, for example, a voltage level.

The lateral G sensor 33 detects a lateral acceleration G _y that is an acceleration applied to the vehicle in the lateral direction, and outputs an electrical signal corresponding to the magnitude of the detection result, for example, a voltage level. The yaw rate sensor 34 is, for example, an electrical signal according to the magnitude of the yaw rate r, such as a piezoelectric element or a gyro sensor that detects an angle change amount of the inclination angle with respect to the vehicle direction or the vertical direction in a horizontal plane, for example, Output voltage level.

  The yaw rate differential value calculation unit 36 time-differentiates the yaw rate r output from the yaw rate sensor 34 to calculate the yaw rate differential value r ′. The engine ECU 40 calculates drive torque and the like from the rotational speed of the engine 40. The steering angle sensor 38 includes, for example, a rotary encoder provided on the steering shaft, and outputs an electrical signal corresponding to the direction and magnitude of the steering angle input by the driver, for example, a voltage signal indicating a sign and a level. .

  The counter steer detection device 40 is a device that detects a counter steer in which the direction of the lateral G and the direction of the steering angle are opposite to each other, and outputs a counter steer flag CS indicating whether or not it is a counter steer. For example, when the direction of the lateral G detected by the lateral G sensor 33 and the direction of the steering angle detected by the steering angle sensor 38 are opposite, that is, when the signs of the lateral G and the steering angle are opposite, it is a counter steer. And the counter steer flag CS is output.

  FIG. 2 is an apparatus block diagram related to the control of the motion state of the vehicle. The vehicle body slip angle estimating device 42 estimates the road surface μ, and recursively uses the estimated vehicle slip angle immediately before calculating the estimated road surface μ and the current estimated vehicle body slip angle based on the vehicle dynamic model. An apparatus for carrying out a vehicle body slip angle estimation method for estimating a slip angle.

In the present embodiment, as will be described later, the lateral acceleration G _y detected by the lateral acceleration sensor 33, the yaw rate r detected by the yaw rate sensor 34, the yaw rate differential value r ′ calculated by the yaw rate differential calculation unit 36, The road surface μ is estimated so that the difference from the estimated lateral acceleration G _ye estimated based on the vehicle speed V detected by the vehicle speed sensor 32 becomes zero. Then, based on the tire dynamic model, the current slip angle β is estimated by using the estimated road surface μ and the estimated value of the previous slip angle β recursively.

The engine ECU 44 calculates drive torque and the like from the rotational speed of the engine 2. The target distribution torque setting device 46 includes a slip angle β estimated by the slip angle estimation device 42, a vehicle yaw rate r detected by the yaw rate sensor 34, a vehicle lateral acceleration G _y detected by the lateral G sensor 33, a vehicle speed. From the vehicle speed V detected by the sensor 32, the counter steer flag CS output by the counter steer detection device 40, and the drive torque calculated by the engine ECU 44, the left and right wheels 29 _FL , 29 _FR , 29 _RR , 29 on the front and rear sides of the vehicle The target value of the distribution torque distributed to _RL is set, and the calculated left and right wheel torques before and after are output to the target distribution torque control device 48.

The target distribution torque control device 48 applies the left and right wheels 29 _FL , 29 _FR , 29 _RR , and 29 _RL to the front and rear wheels so as to match the target torque based on the left and right wheel torque output from the target distribution torque control device 46. The current flowing through the corresponding electromagnetic actuator is controlled.

  FIG. 3 is a block diagram of the slip angle estimation device 42. The slip angle estimation device 42 includes a lateral acceleration estimation unit 60, a subtractor 62, an approximate μ estimation calculation unit 64, a μ fine adjustment calculation unit 66, an adder 68, a tire lateral force calculation unit 70, and a slip angle differential value calculation unit 72. , An integrator 74 and a slip angle β storage means 76.

The lateral acceleration estimation unit 60 substitutes the slip angle differential value β ′, the vehicle speed V, and the yaw rate r input from the slip angle differential value calculation unit 72 into the following equation (2) to obtain the estimated lateral acceleration G _ye of the vehicle. Calculate and output to the subtractor 52.

G _ye = V (r + β ′) (2)
Subtractor 62, the lateral G from the lateral acceleration (lateral G) G _y input from the sensor 33 by subtracting the estimated lateral acceleration G _ye inputted from the lateral acceleration estimation unit 60, fine adjustment of the subtraction result μ calculating section 66 Output to.

  The road surface μ estimation method according to the present embodiment does not estimate the road surface μ by PID calculation based on the initial value road surface μ, but obtains an approximate μ from an approximate μ estimation table 86 to be described later. Further, μ is finely estimated by the μ fine adjustment calculation unit 66.

  FIG. 4 is a block diagram of the approximate μ estimation calculation unit 64 according to the first embodiment of the present invention. The approximate μ estimation calculation unit 64 includes a multiplier 80, a correction table 82, a delay correction unit 84, an absolute value unit 85, an approximate μ determination table 86, a timer 88, an approximate μ initial value setting unit 90, and an approximate μ change. It has a pause control means 91, an approximate μ decrease control means 92, an approximate μ increase control means 94, and an approximate μ storage means 96.

The multiplier 80 detects that the lateral G detected by the lateral G sensor 36 increases as the vehicle speed V increases even if the steering angle detected by the steering angle sensor 34 is the same. In order not to depend, the correction table 82 is referred to, a correction coefficient corresponding to the vehicle speed V is obtained, and the steering angle is corrected by multiplying the steering angle by the correction coefficient. The correction coefficient is determined with respect to the steering angle θ _{REF with} respect to the steering angle θ _REF that is the same lateral G _{V at} the reference vehicle speed V _REF for the combination of the steering angle θ _V and the lateral G _{V at} the vehicle speed V, with a certain vehicle speed as the reference V _REF (reference vehicle speed). which is the ratio of the angle θ _V.

FIG. 5 is a diagram showing the correction table 82. The horizontal axis indicates the vehicle speed, and the vertical axis indicates the correction coefficient. As shown in FIG. 5, the correction table 82 stores a correction coefficient corresponding to each vehicle speed with a correction coefficient corresponding to the reference vehicle speed V _{REF set} to 1. As the vehicle speed increases, the lateral G increases even at the same steering angle, so the correction coefficient increases monotonously with respect to the vehicle speed.

  The delay correcting means 84 usually has a slight delay in the behavior of the vehicle with respect to the steering even at the maximum road surface μ, so that the lateral G detected by the lateral G sensor 33 is detected by the steering angle sensor 38 during sudden steering. Since the tracking to the steering angle is delayed, the output of the lateral G sensor 33 is caused to follow the steering angle detected by the steering angle sensor 33, and the delay characteristic between the steering angle and the lateral G is cancelled.

  Thereby, for example, the value of the lateral G detected by the lateral G sensor 33 during sudden steering becomes smaller when compared with the same steering angle value as the lateral G value when there is no vehicle delay. Thereby, it is possible to prevent the approximate μ obtained from the relationship between the lateral G and the steering angle, which will be described later, from becoming too small.

  FIG. 6 is a diagram showing an example of the delay correction means 84 in FIG. The delay correction unit 84 includes low-pass filters 100 # 1 and 100 # 2. The low-pass filter 100 # 1 delays the output of the steering angle sensor 38. The low-pass filter 100 # 2 delays the output of the lateral G sensor 33.

  Since the output of the lateral G sensor 33 is delayed with respect to the output of the steering angle sensor 38, the delay time of the low-pass filter 100 # 1 is shorter than the delay time of the low-pass filter 100 # 2, In order to cancel the delay with respect to the steering angle, the cutoff frequency of the low-pass filter 100 # 1 is smaller than the cutoff frequency of the low-pass filter 100 # 2. Note that other delay elements may be used instead of the low-pass filters 100 # 1 and 100 # 2. The absolute value means 85 takes an absolute value with respect to the lateral G and the steering angle input from the delay correction means 84.

  For each road surface μ, the absolute value of the travel data is plotted in the first quadrant (the steering angle and the lateral G are positive) with the steering angle as the horizontal axis and the horizontal G as the vertical axis. The boundary line is derived. This boundary line is unique for the road surface μ and shifts upward as the value of the road surface μ increases.

The approximate μ determination table 86 is a plurality of road surfaces μi (i = 1 to n, n is an integer of 2 or more, μi> μ (i + 1), μi−μ (i + 1) = at a predetermined step at the reference speed V _REF . S (i = 1 to n−1)) is a table in which areas A1 to An including steering angles and lateral accelerations are defined based on the boundary lines on the respective road surfaces μi (i = 1 to n).

  FIG. 7 is a diagram showing an example of the approximate μ determination table 86. The approximate μ determination table 86 is a range Ai (i = 1 to 1) hatched with a hatching type corresponding to the road surface μi (i = 1 to 5) with respect to a plurality of road surfaces μi (i = 1 to 5). 5) is a preset table. In FIG. 7, [mu] 1> [mu] 2> [mu] 3> [mu] 4> [mu] 5, and the range A1-A5 is set in a certain step S (S = [mu] i- [mu] (i + 1) (i = 1-4)).

  Regarding the ranges A1 to A5, the boundary line between the ranges Ai and A (i + 1) (i = 1 to 4) is the boundary line on the road surface μi. Thereby, in the range Aj (j> i), there is no combination of the steering angle and the lateral G on the road surface μ (μi ≦ μ), and the steering angle and the lateral G in the range Aj (j> i) It is estimated that the road surface μ is smaller than μi. That is, it is estimated that the road surface μ is equal to or less than μi for the steering angle and the lateral G in the range A (i + 1).

  For example, when μ1 = 1.0, μ2 = 0.8, μ3 = 0.6, μ4 = 0.4, μ5 = 0.2, and S = 0.2, the road surface μ ≦ 1. 0, in the range A3, it is estimated that the road surface μ ≦ 0.8, in the range A4, the road surface μ ≦ 0.6, and in the range A5, the road surface μ ≦ 0.4. That is, μ in each range Ai (i = 2 to 5) is μ ≦ μi + 0.2.

  Each range Ai (i = 1 to 4) may include a road surface μ smaller than (μi−S) due to the relationship between the steering angle and the lateral G with respect to the road surface μ. Since the upper limit of the μ fine adjustment value adjusted by the adjustment calculation unit 66 is set to S and the lower limit is set to −S, the estimation accuracy is improved. For example, the lower limit of the estimation range of μ in each range Ai is set to (μi -S). A road surface μ smaller than (μi−S) included in the range Ai is estimated in the range Aj (j> i). The estimated range of μ in the range Ai (i = 2 to 5) is μi−S ≦ μ ≦ μi + S.

  The timer 88 in FIG. 4 is used to determine whether or not a predetermined time is in a region of μ smaller than the current estimated μ estimated value, and whether or not a straight traveling state is detected for a specified time or more. This is to prevent erroneous determination due to sensor error.

  The approximate μ initial value setting means 90 is a means for setting an approximate initial value of μ, for example, a dry road surface μ (= 1) when the ignition is ON.

  The approximate μ change pause control means 91 pauses the change of the approximate μ when the vehicle speed detected by the speed sensor 32 is equal to or less than a specified value. For example, since the value of the lateral G sensor 33 remains 0 even if the steering angle is turned in a stopped state, the estimated μ is reduced to the minimum value unless the estimation is stopped. In order to avoid the above, the estimation at low speed is paused. Further, since the problem in behavior due to the decrease in the road surface μ is not as great as the medium speed or higher at low speeds, this treatment is possible. The specified value is about 10 km / h, for example.

  The approximate μ reduction control means 92 sets the approximate μ by reducing it by one step when it is in a region of μ smaller than the current approximate μ estimate value for a longer time than the specified time. When the vehicle is in a region of μ smaller than the current estimated value of μ, as described above, since the road surface μ that is currently traveling is less than or equal to the upper limit road surface μ estimated by this region, the approximate μ is set to 1. Reduce the step to reduce the lower limit of the estimated range of μ after fine adjustment.

  The approximate μ increase control means 94 increases the approximate μ by one step and sets it when the approximate μ is smaller than the value of the lateral G sensor 33 when the straight traveling state is detected for a longer time than the specified time. When traveling straight, there is no significant difference between the lateral G and the rudder angle due to the difference in μ. Therefore, it is difficult to estimate μ when traveling straight, and the estimated μ tends to decrease due to the approximate μ reduction means 92. Since there is a possibility that the approximate μ is underestimated, in order to prevent the underestimation of μ, μ is increased when going straight.

  In the straight traveling state, for example, the value of the lateral G detected by the lateral G sensor 33 is in the vicinity of 0, the yaw rate detected by the yaw rate sensor 34 is in the vicinity of 0, or the value of the lateral G is 0. And the yaw rate is near zero.

  Also, a lateral G larger than the normal road surface μ cannot occur. In this case, since it is considered that the road surface μ is underestimated, the underestimation of μ is avoided by increasing the approximate μ estimated value by one step. The reason why the estimated μ is not increased by one step when it is in the region of μ that is longer than the estimated value of the estimated current for a longer time than the specified time is as follows.

  From the general characteristics of the vehicle, the relationship between the rudder angle and the lateral G does not vary greatly when the vehicle is traveling stably on any road surface. In other words, it is possible to travel in an approximate μ region larger than the actual road surface μ. For this reason, if the estimated μ is increased when the estimated μ is in a larger region than the current value, there is a risk of overestimating μ. The approximate μ storage means 96 is a memory for storing the approximate μ.

  FIG. 8 is a block diagram of the μ fine adjustment calculation unit 66 in FIG. The μ fine adjustment calculation unit 66 adjusts μ within a certain range based on the approximate μ stored in the approximate μ storage unit 96 to estimate the road surface μ, and the μ fine adjustment value reset unit 110. , Μ fine adjustment value reset control means 112, μ fine adjustment control means 114, μ fine adjustment means 116, μ fine adjustment upper / lower limit regulation means 118, and μ fine adjustment value storage means 120.

  The μ fine adjustment value resetting unit 110 resets the μ fine adjustment value to zero according to the instruction of the μ fine adjustment value reset control unit 112. The μ fine adjustment value reset control means 112 instructs the μ fine adjustment value reset means 110 to reset the μ fine adjustment value when there is an approximate μ variation stored in the approximate μ storage means 96. If the approximate μ fluctuates, the μ fine adjustment value fluctuates. Therefore, the accuracy at the time of fluctuation can be improved by resetting in accordance with the fluctuation of the approximate μ.

  When the approximate μ × K stored in the approximate μ storage unit 96 is larger than the value of the lateral G sensor 33, the μ fine adjustment control unit 114 counters the counter steer flag CS output from the counter steer detection device 40. When the steering is instructed, the μ fine adjustment means 116 is instructed to stop fine adjustment.

  When the approximate value of μ × K ≧ the lateral G sensor 33 is satisfied, the tire is considered to run in a linear region, and therefore the effect of fine adjustment is small, and the accuracy is reduced by stopping μ fine adjustment. Can be prevented. Further, since the accuracy of the lateral G detected by the lateral G sensor 33 is greatly deteriorated at the time of counter steering, fine adjustment of μ cannot be expected. Therefore, the deterioration of accuracy can be prevented by stopping the fine adjustment.

As will be described later, the μ fine adjustment means 116 calculates the lateral acceleration G _y and the estimated lateral acceleration G _ye by a proportional-integral-derivative (PID) operation based on the approximate μ stored in the approximate μ storage means 96. An adjustment value for finely adjusting the estimated road surface μ is calculated so that the difference becomes zero.

  The μ fine adjustment upper / lower limit regulating means 118 regulates the upper and lower limits of the adjustment value finely adjusted by the μ fine adjustment control means 116 to step S of μi (i = 1 to n) defined in the approximate μ determination table 86. And stored in the μ fine adjustment value storage means 120. The absolute values of the upper and lower limits to be regulated may be S or more. The μ fine adjustment value storage means 120 is a memory for storing the μ fine adjustment value and outputs it to the adder 68.

  The adder 68 in FIG. 3 adds the μ fine adjustment value input from the μ fine adjustment calculation unit 66 and the approximate μ output from the approximate μ estimation calculation unit 64, and adds the addition result μ to the estimated road surface μ. Is output to the tire lateral force calculation unit 70.

Tire lateral force calculating section 70, the following equation is derived from the tire dynamic model (3), on the basis of (4), calculates the tire lateral force Y _r, and outputs the slip angle differential value calculation unit 72.

但し、式（３），（４）において、Ｗは接地重量であり、例えば、車両荷重の測定値を前後及び横加速度で補正した値あるいは懸架装置に設けたロードセルの出力から求めた値、Ｋはコーナリングパワーであり、予め設定された所定のマップ、例えば、摩擦係数μ及び接地荷重Ｗに応じて変化するコーナリングパワーのマップより求めた値、Ｘは前後力であり、例えば、加速度から推定、あるいは、制動液圧又はエンジン出力から求めた値、βは直前の推定スリップ角であり、μは推定路面μであり、加算器６８の出力である。

However, in the formulas (3) and (4), W is a ground contact weight, for example, a value obtained by correcting a measured value of the vehicle load with the longitudinal and lateral accelerations or a value obtained from an output of a load cell provided in the suspension device, K Is a cornering power, and is a value determined from a predetermined map set in advance, for example, a cornering power map that changes in accordance with the friction coefficient μ and the contact load W, X is a longitudinal force, for example, estimated from acceleration, Alternatively, the value obtained from the brake fluid pressure or the engine output, β is the previous estimated slip angle, μ is the estimated road surface μ, and is the output of the adder 68.

The slip angle differential value calculation unit 72 converts the lateral force of the vehicle and the balanced equation of the moment about the vertical axis of the vehicle into the lateral force Y _f acting on the front tire and the lateral force Y _r acting on the rear tire. The slip angle differential value β ′ is calculated by substituting into the following equation (7) obtained by eliminating the lateral force Y _f acting on the front tire from the following equations (5) and (6) described based on the above equation. .

mV (r + β ′) = − 2Y _f −2Y _r (5)
_{Ir '= - 2Y f L f} + 2Y r L r + M ··· (6)
β ′ = − 2 (L _f + L _r ) Y _r / mVL _f + Ir ′ / mVL _f −r−M / mVL _f
(7)
Where L _f is the distance from the vehicle center of gravity to the front wheel side axle, L _r is the distance from the vehicle center of gravity to the rear wheel side axle, Y _r is the tire lateral force, r ′ is the yaw rate differential value, m is the total mass of the vehicle, I is the yawing moment of inertia and M is the yawing moment.

  The integrator 74 integrates the slip angle differential value β ′ input from the slip angle differential value calculation unit 72 on the time axis, and outputs the integral value β to the tire lateral force calculation unit 70 and the slip angle β storage unit 76. .

  FIG. 9 is a flowchart illustrating an approximate μ estimation method according to an embodiment of the present invention. In step S2, when the ignition is ON, an approximate estimated μ, for example, an initial value of μ = 1 corresponding to a dry road surface is set in the approximate μ storage unit 96. In step S4, the following approximate μ change pause control is performed.

  FIG. 10 is a flowchart showing the approximate μ change suspension control. In step S9, the approximate μ change suspension control means 91 determines whether or not the vehicle speed detected by the vehicle speed sensor 32 is greater than a specified value. When the vehicle speed is higher than the specified value, the process returns to step S6 in FIG. When the vehicle speed is less than or equal to the specified value, the process returns to step S9. In step S6 in FIG. 9, the following approximate μ reduction control is performed.

  FIG. 11 is a flowchart showing the approximate μ reduction control. FIG. 12 is a diagram showing an approximate reduction control of μ for travel data. The steering angle is corrected by the multiplier 80, the delay of the lateral G output from the lateral G sensor 33 with respect to the steering angle is canceled by the delay correcting means 84, and the absolute values of the steering angle and the lateral G are taken by the absolute value means 85.

  In step S <b> 10, the approximate μ reduction control unit 92 obtains the approximate μ corresponding to the corresponding region with reference to the approximate μ determination table 86 for the steering angle and the lateral G input from the absolute value unit 85. Then, it is determined whether or not the area is smaller than the current estimated μ estimated value stored in the estimated μ storage means 96.

  If it is a region of μ smaller than the current approximate μ estimated value, the process proceeds to step S14. If it is not an area of μ smaller than the current estimated μ estimated value, the process proceeds to step S12. In step S12, the timer 88 is stopped (time reset), and the process returns to step S10.

  In step S14, it is determined whether or not the timer 88 has started. If the timer 88 has not started, the process proceeds to step S16. In step S16, the timer 88 is started (time reset).

  If the timer 88 has started, the process proceeds to step S18. In step S18, it is determined whether the specified time has been exceeded. If the specified time is exceeded, the process proceeds to step S20. If the specified time has not been exceeded, the process returns to step S10. In step S20, the approximate μ is reduced by one step and set in the approximate μ storage means 96, the timer 88 is stopped (time reset), and the process returns to step S8 in FIG.

  For example, with respect to the traveling data indicated by the symbol b in FIG. 12, in the symbol c that is determined that the region A2 of the approximate μ2 that is smaller than the approximate μ1 from the approximate μ1 of the region A1 has exceeded the specified time, The approximate μ is reduced from μ1 to μ2. In step S8 in FIG. 9, the following approximate μ increase control is performed.

  FIG. 13 is a flowchart showing an approximate increase control of μ. In step S30, the approximate μ increase control means 94 determines whether or not a straight traveling state is detected based on the lateral G, yaw rate, lateral G and yaw rate. If a straight traveling state is detected, the process proceeds to step S32. In step S32, it is determined whether or not the timer 88 has started.

  If the timer 88 has not started, the process proceeds to step S34. In step S34, the timer 88 is started (time reset), and the process proceeds to step S36. If the timer 88 has started, the process proceeds to step S36. In step S36, it is determined whether or not a specified time has been exceeded.

  If the specified time has not been exceeded, the process returns to step S30. If the specified time is exceeded, the process proceeds to step S38. In step S38, the approximate μ is increased by one step and set in the approximate μ storage means 96, and the timer 88 is stopped (time reset), and the process proceeds to step S46.

  In step S40, the timer 88 is stopped (time reset). In step S42, it is determined whether or not approximate μ <value of the lateral G sensor 33. If approximate μ <value of the lateral G sensor 33, the process proceeds to step S44. If approximate μ <value of the lateral G sensor 33 is not satisfied, the process proceeds to step S46. In step S44, the approximate μ is increased by one step, set in the approximate μ storage means 96, and the process proceeds to step S46.

  In step S46, it is determined whether or not the vehicle is in a non-straight running state. If it is a non-straight running state, the process returns to step S4 in FIG. If it is a straight traveling state, the process returns to step S46. As a result, when the estimated μ is increased by one step in the straight traveling state, the estimated μ is not increased until the non-straight traveling state is detected even if the straight traveling state continues thereafter. By continuing, it is possible to prevent the approximate μ from becoming excessive.

  FIG. 14 is a flowchart showing the μ fine adjustment method according to the embodiment of the present invention. In step S50, the μ fine adjustment value resetting unit 110 resets the μ fine adjustment value (PID reset) and stores it in the μ fine adjustment value storage unit 120. In step S <b> 52, the μ fine adjustment control unit 116 determines whether or not approximate μ × K <value of the lateral G sensor 33. If approximate μ × K <value of the lateral G sensor 33 is not reached, the process returns to step S52. If approximate μ × K <value of the lateral G sensor 33, the process proceeds to step S54.

  In step S54, the μ fine adjustment control means 114 determines whether or not the counter steer is based on the counter steer flag CS. If it is counter steer, the process returns to step S52. If not the counter steer, the μ fine adjustment control unit 114 instructs the μ fine adjustment unit 116 to perform the μ fine adjustment, and the process proceeds to Step S56.

In step S56, the μ fine adjustment unit 116 calculates the difference between the lateral acceleration G _y and the estimated lateral acceleration G _ye by a proportional integral differential (PID) operation based on the approximate μ stored in the approximate μ storage unit 96. Μ fine adjustment value for fine adjustment of the estimated road surface μ is calculated so that becomes zero.

  In step S58, the μ fine adjustment upper / lower limit restricting means 118 limits the upper and lower limits of the μ fine adjustment value so that the lower limit of the μ fine adjustment value calculated in step S56 is −S and the upper limit value is + S. And stored in the μ fine adjustment value storage means 120.

  In step S <b> 60, the μ fine adjustment value reset control unit 112 determines whether or not there is a change in the approximate μ stored in the approximate μ storage unit 96. If there is an approximate change in μ, the μ fine adjustment value reset means 110 is instructed to reset, and the process returns to step S50. In step S <b> 50, the μ fine adjustment value reset unit 110 resets the μ fine adjustment value to zero and stores it in the μ fine adjustment value storage unit 120. If there is no approximate μ variation, the process returns to step S52. Steps S50 to S60 are repeated, and the accuracy of the road surface μ estimated by the addition value of the μ fine adjustment value and the approximate μ is improved.

The adder 68 in FIG. 3 adds the μ fine adjustment value input from the μ fine adjustment calculation unit 66 and the approximate μ output from the approximate μ estimation calculation unit 64, and the addition result μ is determined as the tire lateral force. The result is output to the calculation unit 70. Tire lateral force calculating section 70, the formula derived from the tire dynamic model (3), on the basis of (4), calculates the tire lateral force Y _r, and outputs the slip angle differential value calculation unit 72.

The slip angle differential value calculation unit 72 converts the lateral force of the vehicle and the balanced equation of the moment about the vertical axis of the vehicle into the lateral force Y _f acting on the front tire and the lateral force Y _r acting on the rear tire. The slip angle differential value β ′ is calculated by substituting the lateral force Y _f acting on the front tire into the above equation (7) obtained from the above equations (5) and (6) described based on the above equation. . The integrator 74 integrates the slip angle differential value β ′ input from the slip angle differential value calculation unit 72 on the time axis, and outputs the integral value β to the tire lateral force calculation unit 70 and the slip angle β storage unit 76. .

Thus, since the road surface μ is estimated from the accuracy, the accuracy of the slip angle differential value β ′ and the slip angle β is improved. The slip angle β estimated by the slip angle estimation device 42, the vehicle yaw rate r detected by the yaw rate sensor 34, the vehicle lateral acceleration G _y detected by the lateral G sensor 33, and the vehicle speed V detected by the vehicle speed sensor 32. From the counter steer flag CS output by the counter steer detection device 40 and the drive torque calculated by the engine ECU 44, the target distribution torque setting device 46 converts the front and rear wheels 29 _FL , 29 _FR , 29 _RR , 29 _RL to the left and right wheels of the vehicle. A target value of the distributed torque to be distributed is set.

Further, the left and right wheels 29 _FL , 29 _FR , 29 _RR , 29 _RL of the front and rear wheels are matched with the target torque by the target distribution torque control device 48 based on the left and right wheel torque output from the target distribution torque control device 46. Since the current flowing through the electromagnetic actuator provided corresponding to is controlled, the motion state of the vehicle can be controlled with high accuracy.

  FIG. 15 is a block diagram of the approximate μ estimation calculation unit 64 according to the second embodiment of the present invention. Components that are substantially the same as those in FIG. 4 are denoted by the same reference numerals. As shown in FIG. 15, the approximate μ estimation calculation unit 64 of the present embodiment is different from that in FIG. 4 in that the multiplier 80 and the correction table 82 are eliminated, and the approximate μ determination table 200 is the approximate in FIG. Unlike the μ determination table 86, the approximate μ decrease control means 202 and the approximate μ increase control means 204 are different from the approximate μ control means 92 and the approximate μ increase control means 204 in FIG.

  FIG. 16 is a configuration diagram of the approximate μ determination table 200 in FIG. As shown in FIG. 16, the approximate μ determination table 200 includes road surface μi (i = 1 to 5) for a plurality of vehicle speeds in a coordinate space in which the steering angle at the vehicle speed is the horizontal axis and the horizontal G is the vertical axis. Range Ai (i = 1 to 5) is defined.

  For example, as shown in FIG. 16, an approximate μ determination table is defined for vehicle speeds V1 to V4. The steering angle in FIG. 16 is not the steering angle corrected with respect to the reference vehicle speed as in the approximate μ determination table 86 in FIG. 8, but the steering angle detected by the steering angle sensor 38. By increasing the number of vehicle speeds to be defined, the region corresponding to the steering angle and the lateral G can be accurately detected, and the estimation accuracy of the approximate μ is improved.

  The approximate μ reduction means 202 refers to the approximate μ determination table 200 defined for the vehicle speed closest to the vehicle speed V detected by the vehicle speed sensor 32, and the steering angle and lateral input from the absolute value means 85. Approximate μ is calculated from the range corresponding to G. The other processes of the approximate μ reduction means 202 are the same as those of the approximate μ reduction means 92.

  The approximate μ increase means 204 refers to the approximate μ determination table 200 defined for the vehicle speed closest to the vehicle speed V detected by the vehicle speed sensor 32, and the steering angle and lateral input from the absolute value means 85. Approximate μ is calculated from the range corresponding to G. The other processes of the approximate μ increase means 204 are the same as those of the approximate μ increase means 94.

  In this way, the approximate μ determination table 200 is created for each vehicle speed without correcting the rudder angle detected by the rudder angle sensor 38 in accordance with the reference speed, and the highest vehicle speed V detected by the vehicle speed sensor 32 is obtained. It is also possible to calculate the approximate μ from the range corresponding to the steering angle and the lateral G output from the absolute value means 85 with reference to the approximate μ determination table 200 defined for the near vehicle speed.

It is the schematic which shows the power transmission system of a four-wheel drive vehicle. It is a block diagram concerning the movement state control of a vehicle. It is a functional block diagram of the vehicle body slip angle estimation apparatus by embodiment of this invention. FIG. 3 is a block diagram of an approximate μ estimation calculation unit according to the first embodiment of the present invention. It is a figure which shows the correction table in FIG. It is a block diagram of the delay correction means in FIG. FIG. 4 is a diagram illustrating an approximate μ determination table in FIG. 3. FIG. 4 is a block diagram of a μ fine adjustment calculation unit in FIG. 3. 5 is a flowchart showing an approximate μ estimation method. It is a flowchart which shows rough mu change pausing control. It is a flowchart which shows rough micro reduction control. It is a figure which shows rough micro reduction control about driving | running | working data. It is a flowchart which shows rough (micro | micron | mu) increase control. 5 is a flowchart showing a μ fine adjustment method. FIG. 10 is a block diagram of an approximate μ estimation calculation unit according to a second embodiment of the present invention. FIG. 16 is a diagram illustrating an approximate μ determination table in FIG. 15.

Explanation of symbols

10 Speed increaser (transmission)
12 Rear differential devices 24, 26 Rear axle 32 Vehicle speed sensor 33 Lateral acceleration sensor 34 Yaw rate sensor 36 Yaw rate differential value calculation unit 38 Steering angle sensor 40 Counter steer detection device 42 Car body slip angle estimation device 60 Lateral acceleration estimation unit 64 Approximate μ estimation Calculation unit 70 Tire lateral force calculation unit 72 Slip angle differential value calculation unit 74 Integrator

Claims (12)

In the road friction coefficient estimation method for estimating the road surface friction coefficient μ,
Detecting a rudder angle with a rudder angle sensor;
Detecting lateral acceleration by a lateral acceleration sensor;
With respect to a plurality of road surfaces μi (i = 1 to n, n is an integer of 2 or more), among the combinations of the steering angle and the lateral acceleration on each of the road surfaces μi, it was derived with the lower limit value of the lateral acceleration for each steering angle. The steering angle detected by the steering angle sensor with reference to the road surface μ determination table in which a region composed of the steering angle and the lateral acceleration is defined for each road surface μi (i = 1 to n) based on the boundary line, and Obtaining a region corresponding to the lateral acceleration detected by the lateral acceleration sensor, and calculating an approximate μ based on the road surface μ corresponding to the region among the plurality of road surfaces μi (i = 1 to n); A method for estimating a road surface friction coefficient.   The method further comprises the step of finely adjusting the road surface μ based on the approximate μ so that a lateral acceleration difference between the estimated lateral acceleration and the lateral acceleration detected by the lateral acceleration sensor is zero. The road surface friction coefficient estimation method according to 1.   In the step of calculating the approximate μ, the steering angle detected by the steering angle sensor is subjected to a filtering process having a larger signal delay characteristic than the lateral acceleration detected by the lateral acceleration sensor. The method for estimating a road surface friction coefficient according to any one of claims 1 and 2. Detecting vehicle speed with a vehicle speed sensor,
The road surface μ determination table uses a plurality of tables set for each vehicle speed depending on the vehicle speed detected by the vehicle speed sensor, or uses the steering angle sensor as a steering angle used when calculating an approximate μ. The road friction coefficient estimation method according to any one of claims 1 to 3, wherein the steering angle detected by the vehicle speed sensor is corrected with a correction coefficient corresponding to the vehicle speed detected by the vehicle speed sensor.   A step of detecting a vehicle speed by a vehicle speed sensor, and the step of calculating the approximate μ pauses the change of the approximate μ when the vehicle speed detected by the vehicle speed sensor is equal to or less than a specified value. The road friction coefficient estimation method according to any one of claims 1 to 4.   The step of calculating the approximate μ is a road surface μ corresponding to a region corresponding to the rudder angle detected by the rudder angle sensor and the lateral acceleration detected by the lateral acceleration sensor rather than the currently estimated rough μ. 6. The method for estimating a road surface friction coefficient according to claim 1, further comprising a step of reducing the approximate value of μ when the value is continued in a small region for a predetermined time or more.   The plurality of road surfaces μi (i = 1 to n) are defined with a constant step size, and the step of finely adjusting the road surface μ includes an upper limit value of a fine adjustment value and an absolute value of a lower limit value as the step size. The method for estimating a road surface friction coefficient according to claim 2, wherein the road surface friction coefficient is equal to or greater than that.   3. The step of finely adjusting the road surface μ performs fine adjustment when the lateral acceleration detected by the lateral acceleration sensor is equal to or more than a predetermined multiple of the current estimated value of μ. 7. The road surface friction coefficient estimation method according to 7.   The step of finely adjusting the road surface μ includes a step of determining whether or not the value of the approximate μ has changed, and a step of resetting the fine adjustment value to 0 when the value of the approximate μ has changed. The method for estimating a road surface friction coefficient according to any one of claims 7 to 8.   The method for estimating a road surface friction coefficient according to any one of claims 7 to 9, wherein the step of finely adjusting the road surface μ stops fine adjustment when a counter steer is detected.   The step of calculating the approximate μ further includes a step of detecting a straight traveling state, and a step of increasing the value of the approximate μ when a straight traveling state of a predetermined time or longer is detected. The estimation method of the road surface friction coefficient in any one of 1-10.   The step of calculating the approximate μ includes the step of increasing the approximate μ value when the lateral acceleration detected by the lateral acceleration sensor becomes larger than the current approximate μ value. The estimation method of the road surface friction coefficient in any one of Claims 1-11.

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