Vehicle control device and vehicle control method

Abstract

To provide a vehicle control device and a vehicle control method capable of allowing vehicle behavior control to appropriately intervene even in understeer behavior in which autorotation of a vehicle stops during turning.SOLUTION: According to the vehicle control device and the vehicle control method of the present invention, in one aspect, a target yaw moment is obtained based on a steering angle yaw rate deviation, which is a difference between an actual yaw rate and a steering angle yaw rate that is a yaw rate obtained based on a steering angle and a vehicle speed, and an estimated road surface friction coefficient, and a target deceleration is obtained based on a yaw rate deviation, which is a difference between an actual yaw rate and a yaw rate estimated based on a physical quantity indicating a traveling state of the vehicle, and a braking / driving force difference of each wheel applies a yaw moment to the vehicle based on the target yaw moment. The turning motion of the vehicle is controlled, and the speed of the vehicle is controlled based on the target deceleration.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a vehicle control device and a vehicle control method. [Background technology]

[0002] The vehicle behavior control device of Patent Document 1 performs yaw moment control by applying braking force to the inside wheel of a turn to generate a yaw moment for the vehicle when the deviation between the target lateral acceleration and the actual lateral acceleration is less than a predetermined deviation, and performs deceleration control by applying braking force to all four wheels to generate a deceleration for the vehicle when the deviation is equal to or greater than the predetermined deviation. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-058211 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when the front and rear wheels skid toward the outside of the turn during a turn, causing the vehicle to stop spinning and resulting in an understeer behavior, the actual lateral acceleration does not decrease even though the actual yaw moment decreases. Therefore, in vehicle behavior control based on the deviation between the target lateral acceleration and the actual lateral acceleration, it is difficult to establish the conditions for deceleration control, and there is a possibility that understeer behavior cannot be sufficiently suppressed.

[0005] Therefore, an object of the present invention is to provide a vehicle control device and a vehicle control method that can appropriately intervene in vehicle behavior control even when the vehicle experiences understeer behavior in which the rotation of the vehicle is stopped during cornering. [Means for solving the problem]

[0006] In one aspect, the vehicle control device and vehicle control method according to the present invention calculate a target yaw moment based on a steering angle yaw rate deviation, which is the difference between an actual yaw rate generated in the host vehicle and a steering angle yaw rate, which is a yaw rate calculated based on the actual steering angle and vehicle speed of the host vehicle, and an estimated road surface friction coefficient of the roadway on which the host vehicle is traveling; calculate a target deceleration based on the yaw rate deviation, which is the difference between the actual yaw rate and an estimated yaw rate calculated based on physical quantities that indicate the traveling state of the host vehicle, and the estimated road surface friction coefficient; apply a yaw moment to the host vehicle based on a difference between braking / driving forces of each wheel of the host vehicle based on the target yaw moment, thereby controlling the turning movement of the host vehicle; and control the speed of the host vehicle based on the target deceleration. [Effects of the Invention]

[0007] According to the present invention, even if the vehicle experiences an understeer behavior in which the rotation of the vehicle is stopped during cornering, vehicle behavior control can be appropriately intervened. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing a vehicle control system having a function of vehicle behavior control. [Figure 2] 3 is a flowchart showing a basic flow of vehicle behavior control. [Figure 3] FIG. 2 is a block diagram showing details of vehicle behavior control. [Figure 4] FIG. 4 is a diagram showing the characteristics of a first deceleration gain. [Figure 5] 6 is a flowchart showing the flow of a process for calculating a target yaw moment and a first target deceleration. [Figure 6] FIG. 10 is a diagram showing the characteristics of a second deceleration gain. [Figure 7] 10 is a flowchart showing the flow of a process for calculating a target deceleration. [Figure 8] FIG. 1 is a diagram illustrating an example of a driving situation in which oversteer changes to understeer. [Figure 9]9 is a time chart illustrating changes in yaw rate, lateral acceleration deviation, and yaw rate deviation in the driving situation of FIG. 8. [Figure 10] FIG. 1 is a diagram illustrating an example of a driving situation in which understeer changes to four-wheel skidding. [Figure 11] 11 is a time chart illustrating changes in yaw rate, lateral acceleration deviation, and yaw rate deviation in the driving situation of FIG. 10. [Figure 12] FIG. 10 is a diagram illustrating an example of the correlation between vehicle position within a lane and lane departure risk. [Figure 13] FIG. 10 is a diagram illustrating an example of a future vehicle position and a braking state due to yaw moment control when there is an oversteer tendency. [Figure 14] FIG. 10 is a diagram showing a future vehicle position with a neutral steering tendency. [Figure 15] FIG. 10 is a diagram illustrating an example of a future vehicle position and a braking state due to yaw moment control when there is a slight understeer tendency. [Figure 16] 10A and 10B are diagrams illustrating examples of future vehicle positions and braking states due to yaw moment control and deceleration control when there is a strong understeer tendency; [Figure 17] 4 is a time chart illustrating the characteristics of a yaw moment control amount and a deceleration control amount in a manual driving mode. [Figure 18] 4 is a time chart illustrating the characteristics of a yaw moment control amount and a deceleration control amount in an automatic driving mode; [Figure 19] 5 is a time chart illustrating the characteristics of a yaw moment control amount and a deceleration control amount in a driving assistance mode; DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of a vehicle control device and a vehicle control method according to the present invention will be described with reference to the accompanying drawings. FIG. 1 is a block diagram showing a vehicle control system 100 equipped with a vehicle 10 and having a function of controlling vehicle behavior. The vehicle 10 is a four-wheeled automobile and includes a pair of left and right front wheels 11, 12 and a pair of left and right rear wheels 13, 14.

[0010] The vehicle control system 100 includes an external environment recognition unit 200, a vehicle momentum sensor unit 300, a driving operation sensor unit 400, a vehicle control device 500, and an actuator unit 600. The external environment recognition unit 200 recognizes external environment information of the vehicle 10, which is the vehicle itself, in other words, is a device for detecting the surrounding situation of the vehicle 10.

[0011] The external environment recognition unit 200 includes, for example, a GPS (Global Positioning System) receiving unit 210, a map database 220, a camera 230, a radar 240, and the like. The external environment recognition unit 200 is a device used for automatic driving and driving assistance of the vehicle 10, and the vehicle 10 is driven in one of the following driving modes: a manual driving mode, an automatic driving mode, and a driving assistance mode (semi-automatic driving mode) that uses ADAS (Advanced Driver-Assistance Systems) or ACC (Adaptive Cruise Control).

[0012] The vehicle motion quantity sensor unit 300 is a device for detecting physical quantities related to the motion of the vehicle 10, and includes a wheel speed sensor 310, a lateral acceleration sensor 320, a longitudinal acceleration sensor 330, a yaw rate sensor 340, and the like. The wheel speed sensor 310 is a sensor that detects the rotation speed of each of the wheels 11-14 of the vehicle 10, and the detection result of the wheel speed sensor 310 is used to estimate the vehicle speed Vc (vehicle speed) of the vehicle 10. The lateral acceleration sensor 320 detects the lateral acceleration αy of the vehicle 10 , the longitudinal acceleration sensor 330 detects the longitudinal acceleration αx of the vehicle 10 , and the yaw rate sensor 340 detects the yaw rate γ of the vehicle 10 .

[0013] The driving operation amount sensor unit 400 is a device that detects physical amounts related to the driving operation of the vehicle 10 by the driver. In detail, the driving operation amount sensor unit 400 includes an accelerator pedal sensor 410 that detects an accelerator operation amount ACC, which is the amount of operation of the accelerator pedal, a brake pedal sensor 420 that detects a brake operation amount BR, which is the amount of operation of the brake pedal, and a steering angle sensor 430 that detects an actual steering angle θ of the front wheels 11, 12, which are steered wheels.

[0014] The actuator section 600 has actuators for driving the vehicle 10, such as a steering device 610, a driving device 620, and a braking device 630. The steering device 610 may be a steer-by-wire system that steers the steered wheels (front wheels 11, 12) of the vehicle 10 that are mechanically separated from the steering wheel, or an electric power steering device that has an electric motor that generates a steering assist force that assists the movement of a rack bar or pinion gear that is mechanically connected to the steering wheel.

[0015] The drive unit 620 has an internal combustion engine, a motor, etc., and is a device in which the drive force applied to the drive wheels is electronically controlled. The braking device 630 has a hydraulic brake capable of controlling the increase and decrease of supplied hydraulic pressure, an electric caliper, a regeneratively operated motor, etc., and is a device capable of electronically controlling the braking force applied to each of the wheels 11-14 individually.

[0016] The vehicle control device 500 is an electronic control device equipped with a microcomputer 500A as a control unit that performs calculations based on acquired information and outputs the calculation results, and the microcomputer 500A functions as a vehicle behavior control controller that executes vehicle behavior control. The microcomputer 500A estimates the behavior of the vehicle 10 from the vehicle momentum detected by the vehicle momentum sensor unit 300 and the driving operation amount detected by the driving operation amount sensor unit 400, and when a disturbance occurs in the vehicle behavior, it calculates a target yaw moment and a target deceleration to converge the disturbance. The microcomputer 500A then outputs a request command according to the target yaw moment and the target deceleration to the actuator unit 600 to control the braking / driving force applied to each wheel, thereby controlling the yaw moment and deceleration generated in the vehicle 10.

[0017] FIG. 2 is a flowchart showing the basic flow of vehicle behavior control by the microcomputer 500A. First, in step S601, microcomputer 500A performs input processing to apply low-pass filtering to the longitudinal acceleration signal, lateral acceleration signal, yaw rate signal, etc. output by vehicle momentum sensor unit 300 to remove disturbances such as noise components.

[0018] Next, in step S602, the microcomputer 500A performs a process of estimating the vehicle behavior state. Here, the microcomputer 500A estimates the vehicle body speed Vc as a vehicle behavior state based on the rotation speed signals of the wheels 11-14 output by the wheel speed sensors 310. Furthermore, the microcomputer 500A calculates the steering angle yaw rate θγ*, which is the yaw rate as a vehicle behavior state, based on the actual steering angle θ of the front wheels 11, 12 and the estimated vehicle body speed V.

[0019] Furthermore, the microcomputer 500A estimates the road surface friction coefficient μ based on the output of the vehicle momentum sensor unit 300 and the braking / driving force by the actuator unit 600. Then, the microcomputer 500A determines the vehicle behavior (understeer US, oversteer OS) based on the estimated vehicle behavior state.

[0020] Furthermore, in step S603, the microcomputer 500A performs a process of estimating the vehicle traveling state. Here, the microcomputer 500A calculates the trajectory yaw rate Rγ*, which is the yaw rate that occurs when the vehicle 10 travels according to the target trajectory and target vehicle speed, based on the target trajectory and target vehicle speed set in automatic driving or driving assistance. In addition, the microcomputer 500A estimates the distance from the vehicle 10 to the road edge from images from the camera 230, location information of the vehicle 10 from the GPS receiver 210, and road shape information from the map database 220, and from the information on the distance to the road edge, estimates the lane departure risk COR, which is the risk that the vehicle 10 will go off course in the future.

[0021] After estimating the vehicle running state, the microcomputer 500A performs vehicle behavior control in step S604. Here, the microcomputer 500A obtains the steering angle yaw rate deviation θγ_err, which is the difference between the actual yaw rate and the steering angle yaw rate, and calculates the target yaw moment M* and the first target deceleration θαx* from the steering angle yaw rate deviation θγ_err.

[0022] Furthermore, the microcomputer 500A obtains the trajectory yaw rate deviation Rγ_err, which is the difference between the actual yaw rate γ and the trajectory yaw rate Rγ*, and calculates the second target deceleration Rαx* from the trajectory yaw rate deviation Rγ_err. Then, the microcomputer 500A calculates the final target deceleration αx* according to the driving condition (automatic driving, manual driving, semi-automatic driving) based on the first target deceleration θαx*, the second target deceleration Rαx*, and the lane departure risk COR.

[0023] Next, in step S605, the microcomputer 500A performs output signal processing. Here, microcomputer 500A calculates the required braking / driving force for each wheel based on target yaw moment M* and target deceleration αx* calculated in the vehicle behavior control in step S604, and outputs a signal of the required braking force to braking device 630. In other words, the microcomputer 500A controls the turning movement of the vehicle 10 by applying a yaw moment to the vehicle 10 based on the target yaw moment M* by the difference between the braking and driving forces of each wheel of the vehicle 10, and also controls the speed of the vehicle 10 based on the target deceleration αx*.

[0024] FIG. 3 is a functional block diagram showing the functions and data flow of the microcomputer 500A. The driving operation detection unit 501 and the vehicle behavior detection unit 502 are functional units that execute the input process of step S601 in the flowchart of FIG.

[0025] The driving operation detector 501 detects the driver's driving operations of the vehicle 10, including the actual steering angle θ of the front wheels 11, 12, the accelerator operation amount ACC, and the brake operation amount BR, from the output signal of the driving operation amount sensor 400. The vehicle behavior detection unit 502 detects the wheel speed Vw, the yaw rate γ [rad / s], the longitudinal acceleration αx [m / s], and the vehicle speed Vw, yaw rate γ [rad / s], and the longitudinal acceleration αx [m / s] from the output signal of the vehicle momentum sensor unit 300. 2 ], lateral acceleration αy[m / s 2 ] is detected.

[0026] 2. The vehicle behavior estimation unit 503 is a functional unit that executes the process of estimating the vehicle behavior state in step S602 in the flowchart of FIG. The vehicle behavior estimation unit 503 acquires the output signals (θ, ACC, BR) of the driving operation detection unit 501 and also acquires the output signals (Vw, γ, αx, αy) of the vehicle behavior detection unit 502. Then, the vehicle behavior estimation unit 503 calculates the steering angle yaw rate θγ*, the vehicle speed Vc, and the road surface friction coefficient μ.

[0027] Specifically, the vehicle behavior estimation unit 503 estimates the vehicle body speed Vc (vehicle speed) based on the signal of the wheel speed Vw of each wheel. Furthermore, the vehicle behavior estimation unit 503 estimates the friction coefficient μ of the road surface on which the vehicle 10 is traveling (the friction coefficient μ between the tires of the vehicle 10 and the road surface) from the longitudinal acceleration αx, the wheel speed Vw, and the braking / driving force.

[0028] Then, the vehicle behavior estimation unit 503 calculates the steering angle yaw rate θγ* [rad / s], which is the yaw rate estimated from the actual steering angle θ [rad] and the vehicle speed Vc [m / s], according to Equation 1. In Equation 1, L is the wheelbase [m] and A is the stability factor, which are given as constant values.

number

[0029] 2. The steering angle yaw rate deviation calculation unit 504, the target yaw moment calculation unit 505, and the first target deceleration calculation unit 506 are functional units that execute the vehicle behavior control in step S604 in the flowchart of FIG. The steering angle yaw rate deviation calculation unit 504 acquires a signal of the steering angle yaw rate θγ* [rad / s] from the vehicle behavior estimation unit 503 and also acquires a signal of the actual yaw rate γ [rad / s] from the vehicle behavior detection unit 502.

[0030] Then, the steering angle yaw rate deviation calculation unit 504 calculates the steering angle yaw rate deviation θγ_err [rad / s], which is the absolute value of the deviation between the steering angle yaw rate θγ* and the actual yaw rate γ, according to Equation 2.

number

[0031] In addition, the steering angle yaw rate deviation calculation unit 504 determines that the vehicle behavior is understeer US and outputs an understeer determination signal, for example, when the actual yaw rate γ is smaller than the steering angle yaw rate θγ* and the steering angle yaw rate deviation θγ_err is equal to or larger than the understeer determination threshold USth. Here, the steering angle yaw rate deviation calculation unit 504 variably sets the understeer determination threshold USth based on the estimated road surface friction coefficient μ and vehicle body speed Vc, thereby accurately determining the occurrence of understeer even under conditions where the road surface friction coefficient μ and vehicle body speed Vc are different. The vehicle behavior estimating unit 503 can estimate a vehicle slip angle β from the lateral acceleration αy, the yaw rate γ, and the vehicle speed Vc, and perform understeer determination based on the vehicle slip angle β.

[0032] The target yaw moment calculation unit 505 acquires signals of the steering angle yaw rate deviation θγ_err [rad / s], the estimated road surface friction coefficient μ, and the vehicle speed Vc [m / s], and further acquires an understeer determination signal. When understeer is occurring, the target yaw moment calculation unit 505 calculates the yaw moment gain GM from the estimated road surface friction coefficient μ and vehicle speed Vc according to Equation 3, and further calculates the target yaw moment M* from the steering angle yaw rate deviation θγ_err and the yaw moment gain GM.

number

[0033] That is, the target yaw moment calculation unit 505 calculates the yaw moment gain GM based on a function F1(μ, Vc) with the estimated road surface friction coefficient μ and vehicle speed Vc as variables, and multiplies the steering angle yaw rate deviation θγ_err by the yaw moment gain GM to calculate the target yaw moment M*. When understeer is not occurring, target yaw moment calculation section 505 sets target yaw moment M* to zero.

[0034] The first target deceleration calculation unit 506 acquires the estimated road surface friction coefficient μ, the vehicle speed Vc, and the understeer determination signal. When understeer occurs, the first target deceleration calculation unit 506 calculates the first target deceleration θαx*[m / s 2 ] is calculated. In addition, in Equation 4, γ limit [rad / s] is the limit yaw rate, Nθγ_err is a dimensionless signal of the steering angle yaw rate deviation θγ_err calculated by Equation 2, and GD is a first deceleration gain that is set in accordance with the dimensionless signal Nθγ_err.

[0035]

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[0036] In other words, the first target deceleration calculation unit 506 calculates the first deceleration gain GD based on a function F2(Nθγ_err) that uses the non-dimensional signal Nθγ_err as a variable, and multiplies the estimated road surface friction coefficient μ by the first deceleration gain GD to calculate the first target deceleration θαx*. When understeer is not occurring, first target deceleration calculation section 506 sets first target deceleration θαx* to zero.

[0037] FIG. 4 is a diagram illustrating the correlation between the dimensionless signal Nθγ_err of the steering angle yaw rate deviation θγ_err and the first deceleration gain GD (0≦GD). Here, the first target deceleration calculation section 506 increases the first deceleration gain GD in response to an increase in the non-dimensional signal Nθγ_err. In the example shown in Figure 4, the first deceleration gain GD starts to increase when the non-dimensional signal Nθγ_err is less than 1.0, reaches an intermediate value when the non-dimensional signal Nθγ_err is 1.0, and continues to increase in accordance with the increase in the non-dimensional signal Nθγ_err even after the non-dimensional signal Nθγ_err exceeds 1.0, until it reaches its maximum value of 1.0.

[0038] FIG. 5 is a flowchart showing the flow of the calculation process of target yaw moment M* and first target deceleration θαx* by target yaw moment calculation section 505 and first target deceleration calculation section 506, which are functional components of microcomputer 500A. In step S611, the microcomputer 500A calculates the steering angle yaw rate θγ* in accordance with Equation 1 based on the actual steering angle θ, the vehicle speed Vc, and the like.

[0039] In addition, in step S612, the microcomputer 500A calculates a steering angle yaw rate deviation θγ_err, which is the absolute value of the deviation between the steering angle yaw rate θγ* and the actual yaw rate γ, according to Equation 2. Next, in step S613, the microcomputer 500A determines whether or not understeer US of the vehicle 10 is occurring based on a comparison between the steering angle yaw rate θγ* and the actual yaw rate γ.

[0040] If the microcomputer 500A determines that understeer US is not occurring, the process proceeds to step S614, where it sets the target yaw moment M* to zero and also sets the first target deceleration θαx* to zero. On the other hand, if the microcomputer 500A determines that understeer US is occurring, the process proceeds to step S615, where the target yaw moment M* is calculated according to equation 3, and in step S616 the first target deceleration θαx* is calculated according to equation 4.

[0041] The control configuration including the above-mentioned driving operation detection unit 501, vehicle behavior detection unit 502, vehicle behavior estimation unit 503, steering angle yaw rate deviation calculation unit 504, target yaw moment calculation unit 505, and first target deceleration calculation unit 506 constitutes a functional configuration that determines the target yaw moment and target deceleration by feedback control after the occurrence of vehicle behavior. On the other hand, the running state detection unit 511, running state calculation unit 512, trajectory yaw rate deviation calculation unit 513, and second target deceleration calculation unit 514 described below constitute a functional configuration that controls vehicle behavior by feedforward control based on the running state.

[0042] The running state detection unit 511 is a functional unit that executes the input process of step S601 in the flowchart of FIG. The driving state detection unit 511 acquires a target trajectory, which is set in automatic driving or driving assistance, and a target vehicle speed when the vehicle 10 is driven along the target trajectory.

[0043] The running state calculation unit 512 is a functional unit that performs the process of estimating the vehicle running state in step S603 in the flowchart of FIG. 2, and acquires signals of the target trajectory and target vehicle speed Vctg (target vehicle speed) from the running state detection unit 511. Then, the driving state calculation unit 512 calculates the trajectory yaw rate Rγ* [rad / s], which is the yaw rate estimated based on the turning radius R [m] of the target trajectory and the target vehicle speed Vctg [m / s], according to Equation 5, with the road surface friction coefficient μ = 1.0.

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[0044] In addition, the driving condition calculation unit 512 calculates the distance from the vehicle 10 to the left and right road edges (curbs, lane boundaries) at a future time (a predetermined time after) from images from the camera 230, etc., and sets a lane departure risk COR, which represents the magnitude of the risk that the vehicle 10 will deviate from its lane in the future, based on the distance. The trajectory yaw rate deviation calculation unit 513 and the second target deceleration calculation unit 514 are functional units that execute the vehicle behavior control in step S604 in the flowchart of FIG.

[0045] The trajectory yaw rate deviation calculation unit 513 acquires the trajectory yaw rate Rγ* calculated by the driving state calculation unit 512 and the actual yaw rate γ detected by the vehicle behavior detection unit 502, and calculates the trajectory yaw rate deviation Rγ_err [rad / s], which is the absolute value of the deviation between the trajectory yaw rate Rγ* and the actual yaw rate γ, according to Equation 6.

number

[0046] The second target deceleration calculation unit 514 acquires the estimated road surface friction coefficient μ, the target vehicle speed Vctg, and the understeer determination signal, and calculates the second target deceleration Rαx*[m / s 2 ] is calculated according to Equation 7. In addition, in Equation 7, γ limit [rad / s] is the limit yaw rate, NRγ_err is a dimensionless signal of the trajectory yaw rate error Rγ_err calculated by Equation 6, and GC is a second deceleration gain that is set in accordance with the dimensionless signal NRγ_err.

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[0047] That is, the second target deceleration calculation unit 514 calculates the second deceleration gain GC based on a function F3(NRγ_err) that uses the non-dimensional signal NRγ_err as a variable, and calculates the second target deceleration Rαx* by multiplying the estimated road surface friction coefficient μ by the second deceleration gain GC. It should be noted that, when understeer is not occurring, second target deceleration calculation section 514 sets second target deceleration Rαx* to zero.

[0048] FIG. 6 is a diagram illustrating an example of the correlation between the dimensionless signal NRγ_err of the trajectory yaw rate error Rγ_err and the second deceleration gain GC. Here, the second target deceleration calculation unit 514 increases the second deceleration gain GC in response to an increase in the non-dimensional signal NRγ_err. In the example shown in FIG. 6, the second deceleration gain GC starts to increase when the non-dimensional signal NRγ_err is less than 1.0, and reaches the maximum value of 1.0 when the non-dimensional signal Nθγ_err is 1.0.

[0049] The target deceleration calculation unit 521 is a functional unit that executes the vehicle behavior control in step S604 in the flowchart of FIG. 2, and calculates the final target deceleration αx*. The target deceleration calculation unit 521 acquires a signal of the first target deceleration θαx* from the first target deceleration calculation unit 506, acquires a signal of the second target deceleration Rαx* from the second target deceleration calculation unit 514, acquires a signal of the target yaw moment M* from the target yaw moment calculation unit 505, and further acquires a signal of the lane departure risk COR from the driving state calculation unit 512.

[0050] When the target yaw moment M* is zero and yaw moment control is not executed, the target deceleration calculation unit 521 sets the target deceleration αx* to zero. On the other hand, when the target yaw moment M* is not zero and yaw moment control is executed, the target deceleration calculation unit 521 sets the first target deceleration θαx* as the final target deceleration αx* in manual driving mode by the driver, sets the second target deceleration Rαx* as the final target deceleration αx* in automatic driving mode, and determines the final target deceleration αx* by weighting the first target deceleration θαx* and the second target deceleration Rαx* in driving assistance mode (semi-automatic driving mode).

[0051] Here, the weighting of the first target deceleration θαx* and the second target deceleration Rαx* in the driving assistance mode is set according to the lane departure risk COR, and the higher the lane departure risk COR, the greater the weighting of the second target deceleration Rαx* and the relatively smaller the weighting of the first target deceleration θαx*. The lane departure risk COR is expressed as 1.0 when the vehicle 10 has the highest risk of deviating from the road edge on the outside of the turn, and as 0.0 when the vehicle 10 has the lowest risk of deviating from the road edge on the outside of the turn, and gradually increases as the forward gaze point of the vehicle 10 approaches the road edge on the outside of the turn.

[0052] Then, the target deceleration calculation unit 521 calculates the final target deceleration αx* in the driving assistance mode according to Equation 8.

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[0053] FIG. 7 is a flowchart showing the flow of the calculation process of the target deceleration αx* by the target deceleration calculation unit 521, which is a functional component of the microcomputer 500A. The calculation process of the target deceleration αx* is based on the assumption that the vehicle 10 is being driven in either a manual driving mode, an automatic driving mode, or a driving assistance mode, and the target deceleration αx* is switched depending on which of these driving modes the vehicle is being driven in.

[0054] In step S621, the microcomputer 500A determines whether the target yaw moment M* is zero, in other words, whether the state is such that yaw moment control is being executed to apply a yaw moment to the vehicle 10 to control the turning movement of the vehicle 10. Then, if the target yaw moment M* is zero and yaw moment control is not being executed, the microcomputer 500A proceeds to step S622 and cancels the deceleration control of the vehicle 10 based on the target deceleration αx* by setting the target deceleration αx* to zero. In other words, deceleration control based on the target deceleration αx* is executed when yaw moment control is being executed.

[0055] On the other hand, if the target yaw moment M* is not zero and yaw moment control is being executed, the microcomputer 500A proceeds to step S623 and determines whether the vehicle 10 is in an automatic driving mode in which it is driven automatically, in other words, whether it is in automatic driving mode. If the vehicle is in the automatic driving mode (during automatic driving), the microcomputer 500A proceeds to step S624 and sets the value of the second target deceleration Rαx* calculated from the target trajectory in automatic driving as the target deceleration αx* as is.

[0056] Also, if the vehicle 10 is not in the automatic driving mode, the microcomputer 500A proceeds to step S625 and determines whether the vehicle 10 is in the manual driving mode in which the vehicle 10 is manually driven based on the driver's operation, in other words, whether the vehicle 10 is being manually driven. If the vehicle is in the manual driving mode (during manual driving), the microcomputer 500A proceeds to step S626 and sets the value of the first target deceleration θαx* calculated from the amount of driving operation by the driver as the target deceleration αx*.

[0057] On the other hand, if the vehicle is not in the manual driving mode, it is in the driving assistance mode, one of the three driving modes of the automatic driving mode, the manual driving mode, and the driving assistance mode, in other words, it is in the driving assistance mode. Then, if the driving assistance mode (driving assistance in progress) is selected, the microcomputer 500A proceeds to step S627 and performs calculations according to equation 8 to weight the first target deceleration θαx* and the second target deceleration Rαx* according to the lane departure risk COR to set the target deceleration αx*.

[0058] Here, the greater the lane departure risk COR and the greater the possibility that the vehicle 10 will depart from the road edge on the outside of the turn due to understeer US, the closer the target deceleration αx* will be to the second target deceleration Rαx*. Conversely, the smaller the lane departure risk COR and the lower the possibility that the vehicle 10 will deviate from the road edge on the outside of the turn due to understeer US, the closer the target deceleration αx* will be to the first target deceleration θαx*.

[0059] As described above, the microcomputer 500A has a functional configuration as a target yaw moment calculation unit, and calculates the target yaw moment M* based on the steering angle yaw rate deviation θγ_err, which is the difference between the actual yaw rate γ generated in the vehicle 10 and the steering angle yaw rate θγ*, which is the yaw rate calculated based on the actual steering angle θ of the vehicle 10 and the vehicle speed Vc, and the estimated road surface friction coefficient μ of the road on which the vehicle 10 is traveling. In addition, the microcomputer 500A has a functional configuration as a target deceleration calculation unit, and calculates the target deceleration (first target deceleration θαx*, second target deceleration Rαx*) based on the yaw rate deviation (steering angle yaw rate deviation θγ_err, trajectory yaw rate deviation Rγ_err), which is the difference between the actual yaw rate γ and the estimated yaw rate (steering angle yaw rate θγ*, trajectory yaw rate Rγ*) calculated based on physical quantities indicating the running state of the vehicle 10, and the estimated road surface friction coefficient μ.

[0060] The target braking force calculation unit 522 and the target value calculation unit 523, which are functional units that execute the output signal processing of step S605 in the flowchart of Figure 2, control the braking / driving force difference of each wheel of the vehicle 10 based on the target yaw moment M* to apply a yaw moment to the vehicle 10, thereby controlling the turning movement of the vehicle 10 and also controlling the speed of the vehicle 10 based on the target deceleration αx*. That is, the microcomputer 500A has a target braking force calculation unit 522 and a target value calculation unit 523, which are functional components serving as a yaw moment control unit and a deceleration control unit.

[0061] The target braking force calculation unit 522 calculates the target braking force for each wheel from the braking force target for applying the target yaw moment M* to the vehicle 10 based on the braking / driving force difference between each wheel, and the braking force target for realizing the target deceleration αx*. Then, for example, when a regenerative brake and a friction brake are used in combination, the target value calculation unit 523 outputs a regenerative brake torque request (minimum required braking force of the drive wheels multiplied by the number of drive wheels) to the regenerative brake of the actuator unit 600, and outputs a braking force request (required braking force of each vehicle minus the regenerative brake allocation) to the friction brake of the actuator unit 600.

[0062] FIG. 8 shows the behavior of the vehicle 10 when the rear wheels 13, 14 skid and become oversteer OS while the vehicle 10 is turning (see (3) in FIG. 8), and then the front wheels 11, 12 come onto a road surface with a low coefficient of friction μ, such as an icy road surface, causing the front wheels 11, 12 to also skid and become understeer US (see (3') in FIG. 8). FIG. 9 shows the changes in the actual yaw rate γ, lateral acceleration deviation, and yaw rate deviation when the vehicle changes from oversteer OS to understeer US during cornering as shown in FIG.

[0063] FIG. 10 also shows the behavior of the vehicle 10 when the front wheels 11, 12 skid and understeer US while the vehicle 10 is turning (see (3) in FIG. 10), and then the front wheels 11, 12 come onto a road surface with a low friction coefficient μ, such as an icy road surface, causing the front wheels 11, 12 to skid more and enter a four-wheel skid state (a sideways jump state) (see (3') in FIG. 10). FIG. 11 shows the changes in the actual yaw rate γ, the lateral acceleration deviation, and the yaw rate deviation when the understeer US shown in FIG. 10 occurs.

[0064] In both the vehicle behaviors shown in Figures 8 and 10, when all four wheels skid (state (3') in Figures 8 and 10), the vehicle behavior changes in a direction that stops the rotation of the vehicle 10, and the actual yaw rate γ decreases and approaches 0 [rad / s]. As the actual yaw rate γ decreases, the steering angle yaw rate deviation θγ_err, which is the absolute value of the deviation between the steering angle yaw rate θγ* and the actual yaw rate γ, increases, and the target yaw moment M* and target deceleration αx* are set to converge the skidding state (understeer US) of the four wheels.

[0065] In contrast, if the timing of vehicle behavior control intervention is determined based on lateral acceleration deviation, control intervention will not be performed even if four-wheel skid occurs, because the lateral acceleration will not decrease. Instead, understeer US will cause the driver to turn the steering wheel more, and this turning will increase the lateral acceleration deviation, which will result in control intervention. In other words, by determining the timing of intervention in vehicle behavior control based on the steering angle yaw rate deviation θγ_err, the microcomputer 500A can initiate control intervention earlier than when the timing of intervention in vehicle behavior control is determined based on the lateral acceleration deviation, thereby improving the convergence response of the four-wheel skid state (understeer US).

[0066] Next, the calculation of the target deceleration αx* according to the lane departure risk COR and the driving state (autonomous driving mode, manual driving mode, driving assistance mode) will be explained in detail. FIG. 12 shows the correlation between the future distance from the vehicle 10 to the road edge and the lane departure risk COR, which indicates the risk of the vehicle 10 departing from the road edge on the outside of a turn.

[0067] If the future position of vehicle 10 (in other words, the forward gaze point) is on the inside of the turning lane near the center of the lane in which vehicle 10 is traveling and the distance to the road edge on the outside of the turning lane is secured, the possibility of vehicle 10 deviating from the road edge on the outside of the turning lane is sufficiently low, so the lane departure risk COR is set to the minimum value of zero. On the other hand, the closer the future position of vehicle 10 (in other words, the forward gaze point) is from near the center of the lane in which vehicle 10 is traveling to the outside edge of the road, the higher the possibility that vehicle 10 will deviate from the outside edge of the road, and therefore the lane departure risk COR gradually increases as the vehicle approaches the outside edge of the road, reaching a maximum value of 1.0 near the outside edge of the road.

[0068] FIG. 13 shows the future vehicle position when the vehicle 10 exhibits a tendency to oversteer OS on a left-hand turning road. If the vehicle 10 is oversteering OS and the future vehicle position will be near the road edge on the inside of the turn, the lane departure risk COR, which is the risk that the vehicle 10 will deviate from the outside of the turn, is set to zero, which indicates the lowest departure risk, as shown in Figure 12.

[0069] However, the oversteer OS situation shown in FIG. 13 is a situation in which the yaw rate toward the inside of the turn is too large. For this reason, the microcomputer 500A generates a yaw moment toward the outside of the turn by, for example, yaw moment control that applies braking forces to the front and rear wheels on the outside of the turn, thereby suppressing oversteer OS.

[0070] FIG. 14 also shows the future vehicle position when the vehicle 10 exhibits a tendency toward neutral steering NS on a left-hand turning road. When the vehicle 10 is in neutral steering NS and the future vehicle position is near the center of the lane, the lane departure risk COR, which is the risk that the vehicle 10 will deviate from the outside of the turn, is set to zero as shown in Figure 12. In the neutral steering NS situation shown in FIG. 14, an appropriate yaw rate is generated that causes the vehicle 10 to travel along the center of the lane, so the microcomputer 500A does not perform vehicle behavior control (yaw moment control and deceleration control).

[0071] FIG. 15 also shows the future vehicle position when the vehicle 10 exhibits a tendency to slight understeer US on a left-hand turning road. When the vehicle 10 is in a slight understeer US state and the future vehicle position is midway between the center of the lane and the road edge on the outside of the turn, the lane departure risk COR, which is the risk that the vehicle 10 will deviate from the outside of the turn, is set to near zero, as shown in Figure 12.

[0072] However, the weak understeer US situation in FIG. 15 is a situation in which the yaw rate toward the inside of the turn is smaller than the optimum value. For this reason, the microcomputer 500A generates a yaw moment toward the inside of the turn by, for example, yaw moment control that applies braking forces to the front and rear wheels on the inside of the turn, thereby suppressing understeer US.

[0073] FIG. 16 also shows the future vehicle position when the vehicle 10 exhibits a strong tendency to understeer US on a left-hand turning road. When the vehicle 10 is experiencing strong understeer US and the future vehicle position is near the road edge on the outside of the turn, the lane departure risk COR, which is the risk that the vehicle 10 will deviate from the outside of the turn, is set to a value greater than zero, as shown in Figure 12, indicating that the departure risk is high.

[0074] In the case of strong understeer US in FIG. 16, the yaw rate toward the inside of the turn is smaller than the optimum value, and there is a possibility that the vehicle 10 will deviate from the road edge on the outside of the turn. For this reason, the microcomputer 500A performs, for example, yaw moment control to apply braking force to the front and rear wheels on the inside of the turn, thereby generating a yaw moment toward the inside of the turn, and also performs deceleration control to decelerate the vehicle 10 by applying braking force to all four wheels. This vehicle behavior control suppresses understeer US of the vehicle 10, and prevents the vehicle 10 from running off the road edge on the outside of a turn.

[0075] Here, when the vehicle 10 exhibits a tendency toward understeer US while driving in the driving assistance mode, the microcomputer 500A sets the target deceleration αx* by weighting the first target deceleration θαx* and the second target deceleration Rαx* according to the lane departure risk COR, so that the deceleration requirement in the deceleration control changes according to the lane departure risk COR. According to such weighting processing in accordance with the lane departure risk COR, it is possible to more effectively prevent the vehicle 10 from departing from the outside of a turn when traveling in the driving assistance mode.

[0076] 17 to 19 are time charts illustrating the characteristics of the yaw moment control amount and the deceleration control amount in each of the driving modes, namely, the manual driving mode, the automatic driving mode, and the driving assistance mode. FIG. 17 illustrates the control characteristics in the manual driving mode.

[0077] In the manual driving mode, the target yaw moment M*, which is the yaw moment control amount, is calculated based on the steering angle yaw rate deviation θγ_err, which is the absolute value of the deviation between the steering angle yaw rate θγ* corresponding to the steering angle due to the operation of the steering wheel by the driver and the actual yaw rate γ. In the manual driving mode, the steering angle yaw rate deviation θγ_err, which is the difference between the actual yaw rate γ and the steering angle yaw rate θγ*, and the limit yaw rate γ limit The first target deceleration θαx* obtained from the above is set as the final deceleration control amount (target deceleration αx*).

[0078] FIG. 18 illustrates the control characteristics in the automatic driving mode. In the autonomous driving mode, the target yaw moment M*, which is the yaw moment control amount, is calculated based on the steering angle yaw rate deviation θγ_err, which is the absolute value of the deviation between the steering angle yaw rate θγ* corresponding to the steering angle controlled by autonomous driving and the actual yaw rate γ. In the autonomous driving mode, the trajectory yaw rate deviation Rγ_err, which is the difference between the trajectory yaw rate Rγ* and the actual yaw rate γ, and the limit yaw rate γ limit The second target deceleration Rαx* obtained from the above is set as the final deceleration control amount (target deceleration αx*).

[0079] FIG. 19 illustrates the control characteristics in the driving assistance mode. In the driving assistance mode, the target yaw moment M*, which is the yaw moment control amount, is calculated based on the steering angle yaw rate deviation θγ_err, which is the absolute value of the deviation between the steering angle yaw rate θγ* corresponding to the steering wheel operation by the driver or the steering angle controlled by driving assistance, and the actual yaw rate γ. In addition, in the driving assistance mode, the first target deceleration θαx* and the second target deceleration Rαx* are weighted according to the lane departure risk COR to set the final deceleration control amount (target deceleration αx*), and the higher the risk of departure from the road edge on the outside of the turn, the closer the deceleration control amount (target deceleration αx*) is set to a value that is closer to the second target deceleration Rαx* based on the trajectory yaw rate deviation Rγ_err.

[0080] The technical ideas explained in the above embodiments can be used in appropriate combinations as long as no contradiction occurs. Furthermore, although the contents of the present invention have been specifically described with reference to preferred embodiments, it is obvious that a person skilled in the art can adopt various modified embodiments based on the basic technical idea and teachings of the present invention.

[0081] The vehicle 10 is not limited to a vehicle that has all of the driving modes, namely, a manual driving mode, an automatic driving mode, and a driving assistance mode, and is driven in accordance with a driving mode selected from these driving modes. In other words, the vehicle may have only one of the driving modes: manual driving mode, automatic driving mode, or driving assistance mode, or it may have two of the driving modes: manual driving mode, automatic driving mode, and driving assistance mode.

[0082] For example, in the case of a vehicle operated in either a manual driving mode or an automatic driving mode, the process in the target deceleration calculation unit 521 of weighting the first target deceleration θαx* and the second target deceleration Rαx* according to the lane departure risk COR to determine the target deceleration αx* is omitted. In addition, in a vehicle that is driven only in manual driving mode, the functional units of the driving state detection unit 511, driving state calculation unit 512, trajectory yaw rate deviation calculation unit 513, and second target deceleration calculation unit 514 are omitted.

[0083] Furthermore, the lane departure risk COR may indicate, for example, whether there is a possibility that the vehicle 10 will depart from the road edge on the outside of the turn, by either "yes" or "no." In this case, when in driving assistance mode, the microcomputer 500A can set the second target deceleration Rαx* as the target deceleration αx* if there is a possibility of lane departure, and can set the first target deceleration θαx* as the target deceleration αx* if there is no possibility of lane departure.

[0084] In addition, the microcomputer 500A can execute a combination of control that intervenes in vehicle behavior control based on the deviation between the target lateral acceleration and the actual lateral acceleration, and control that intervenes in vehicle behavior control based on the steering angle yaw rate deviation θγ_err or the trajectory yaw rate deviation Rγ_err. Furthermore, if the vehicle 10 is equipped with, for example, an in-wheel motor and is capable of individually controlling the driving force applied to each wheel, the microcomputer 500A can impart a yaw moment to the vehicle 10 by controlling the braking force as well as the driving force of each wheel in the yaw moment control. [Explanation of symbols]

[0085] 10...vehicle, 500...vehicle control device, 500A...microcomputer (control unit), 504...steering angle yaw rate deviation calculation unit, 505...target yaw moment calculation unit, 506...first target deceleration calculation unit, 513...trajectory yaw rate deviation calculation unit, 514...second target deceleration calculation unit, 521...target deceleration calculation unit, 522...target braking force calculation unit, 523...target value calculation unit, 600...actuator unit

Claims

1. a target yaw moment calculation unit that calculates a target yaw moment based on a steering angle yaw rate deviation, which is the difference between an actual yaw rate generated in the host vehicle and a steering angle yaw rate that is a yaw rate calculated based on an actual steering angle and a vehicle speed of the host vehicle, and an estimated road surface friction coefficient of a road on which the host vehicle is traveling; a target deceleration calculation unit that calculates a target deceleration based on a yaw rate deviation, which is a difference between the actual yaw rate and an estimated yaw rate calculated based on a physical quantity indicating the running state of the host vehicle, and the estimated road surface friction coefficient; a yaw moment control unit that applies a yaw moment to the host vehicle by a braking / driving force difference between the wheels of the host vehicle based on the target yaw moment, thereby controlling the turning movement of the host vehicle; a deceleration control unit that controls the speed of the host vehicle based on the target deceleration; A vehicle control device comprising:

2. The vehicle control device according to claim 1, The deceleration control unit is executed when the control by the yaw moment control unit is being executed. Vehicle control device.

3. The vehicle control device according to claim 1, the estimated yaw rate includes the steering angle yaw rate and a trajectory yaw rate that is a yaw rate calculated based on a target trajectory and a target vehicle speed of the host vehicle, the yaw rate deviation includes a steering angle yaw rate deviation that is a difference between the actual yaw rate and the steering angle yaw rate, and a trajectory yaw rate deviation that is a difference between the actual yaw rate and the trajectory yaw rate, The target deceleration calculation unit calculating the target deceleration based on a first target deceleration calculated based on the steering angle yaw rate deviation and the estimated road surface friction coefficient, and a second target deceleration calculated based on the trajectory yaw rate deviation and the estimated road surface friction coefficient; Vehicle control device.

4. The vehicle control device according to claim 3, The target deceleration calculation unit When the host vehicle is being manually driven by a driver, the first target deceleration is calculated as the target deceleration; During automatic driving of the host vehicle, the second target deceleration is calculated as the target deceleration; During driving assistance of the host vehicle, the target deceleration is calculated by weighting the first target deceleration and the second target deceleration. Vehicle control device.

5. The vehicle control device according to claim 1, the estimated yaw rate includes the steering angle yaw rate, the yaw rate deviation includes a steering angle yaw rate deviation that is a difference between the actual yaw rate and the steering angle yaw rate, The target deceleration calculation unit calculating the target deceleration based on the steering angle yaw rate deviation and the estimated road surface friction coefficient; Vehicle control device.

6. The vehicle control device according to claim 1, the estimated yaw rate includes a trajectory yaw rate, which is a yaw rate calculated based on a target trajectory and a target vehicle speed of the host vehicle; the yaw rate error includes a trajectory yaw rate error that is a difference between the actual yaw rate and the trajectory yaw rate, The target deceleration calculation unit calculating the target deceleration based on the trajectory yaw rate deviation and the estimated road surface friction coefficient; Vehicle control device.

7. A vehicle control method executed by a control unit mounted on a vehicle, comprising: calculating a target yaw moment based on a steering angle yaw rate deviation, which is the difference between an actual yaw rate generated in the host vehicle and a steering angle yaw rate, which is a yaw rate calculated based on an actual steering angle and a vehicle speed of the host vehicle, and an estimated road surface friction coefficient of a road on which the host vehicle is traveling; calculating a target deceleration based on a yaw rate deviation, which is a difference between the actual yaw rate and an estimated yaw rate calculated based on a physical quantity indicating a running state of the host vehicle, and the estimated road surface friction coefficient; applying a yaw moment to the host vehicle by a braking / driving force difference between the wheels of the host vehicle based on the target yaw moment, thereby controlling the turning movement of the host vehicle; controlling the speed of the host vehicle based on the target deceleration; Vehicle control method.

Images