Steering control device

Abstract

Disclosed is a steering control device. A software processing device of a steering control device (60) is configured to execute a sampling process, a steering angle calculation process, and a control constant learning process. And the sampling processing is to synchronously sample the steering angle and the yaw velocity. The steering angle calculation process is a process for calculating the steering angle of the steered wheel (40) using the yaw velocity and the vehicle velocity as inputs. The control constant learning process is a process for learning a control constant on the basis of a plurality of combinations, each of which is composed of a steering angle sampled by the sampling process and a steering angle corresponding to the steering angle. The control constant is a constant indicating rotational displacement of the steered wheel (40) with respect to the steering shaft (14).

Description

Technical Field

[0001] The invention relates to a steering control device. Background Art

[0002] For example, Japanese Unexamined Patent Application Publication No. 2022-68056 describes a device for learning the amount of play, which is the maximum value of the amount by which the steering angle of the steering wheel does not change even when the steering steering angle changes. When the key switch is turned on, the device rotates the electric power steering motor left and right. Then, the device detects the steering steering angle at which the steering wheel starts to turn based on the increase in the current flowing through the motor. Then, the device assigns the difference between a pair of detected steering steering angles to the amount of play. Summary of the invention

[0003] The above amount of play varies according to the vehicle speed. However, the above device cannot calculate the amount of play when the vehicle speed is above zero.

[0004] Configuration 1. A steering control device according to one aspect of the present disclosure includes a software processing device. The software processing device controls the steering device. The steering device includes a steering shaft and a steering wheel of a vehicle, and the steering wheel steers as the steering shaft rotates. The software processing device is configured to perform sampling processing, steering angle calculation processing, and control constant learning processing. The sampling processing is a process of synchronously sampling the steering angle and yaw rate. The steering angle is the rotation angle of the steering shaft. The steering angle calculation processing is a process of calculating the steering angle of the steering wheel using the yaw rate and the vehicle speed as inputs. The control constant learning processing is a process of learning control constants based on multiple combinations, each of the multiple combinations consisting of a steering angle sampled by the sampling processing and a steering angle corresponding to the steering angle. The control constant is a constant indicating the rotational displacement of the steering wheel relative to the rotational displacement of the steering shaft.

[0005] In the above configuration 1, the steering angle is calculated from the yaw rate and the vehicle speed. Therefore, the relationship between the steering angle and the steering angle can be acquired when the vehicle speed is higher than zero, and thus the value of the control constant can be learned.

[0006] Configuration 2. In the steering control device according to the above configuration 1, the control constant may include a stiffness coefficient as a ratio of the steering angle to the steering angle. The control constant learning process may include a process of learning a slope of a straight line as the stiffness coefficient, the slope of the straight line being determined by a plurality of combinations, each of the plurality of combinations being composed of a steering angle and a steering angle corresponding to the steering angle.

[0007] There is a proportional relationship between the steering control angle and the steering angle. In the above configuration 2, the rigidity coefficient indicating the proportional relationship can be learned.

[0008] Configuration 3. In the steering control device according to configuration 1 or configuration 2 above, the control constant may include a dead zone width. The dead zone width may be the amount of rotation of the steering shaft after the rotation direction of the steering shaft is switched from one of the right steering direction and the left steering direction to the other of the right steering direction and the left steering direction and before the steering wheel is turned. The control constant learning process may include a right steering straight line calculation process, a left steering straight line calculation process, and a dead zone width calculation process. The right steering straight line calculation process may be a process for calculating the right steering straight line according to the following first plurality of combinations: the first plurality of combinations are included in a plurality of combinations each consisting of a sampled steering angle and a steering angle corresponding to the steering angle and are combinations when the rotation direction is the right steering direction. The left steering straight line calculation process may be a process for calculating the left steering straight line according to the following second plurality of combinations: the second plurality of combinations are included in a plurality of combinations each consisting of a sampled steering angle and a steering angle corresponding to the steering angle and are combinations when the rotation direction is the left steering direction. The dead zone width calculation process may be a process for calculating the difference in intercepts between the right steering straight line and the left steering straight line as the dead zone width.

[0009] In the above configuration 3, the dead zone width can be calculated by calculating the right turning straight line and the left turning straight line.

[0010] Configuration 4. In a steering control device according to any one of the above configurations 1 to 3, the control constant learning process may be a process of calculating the control constant for each of vehicle speeds that are different from each other based on a plurality of combinations as follows: each of the plurality of combinations is composed of a steering angle sampled by a sampling process for each of vehicle speeds that are different from each other and a steering angle corresponding to the steering angle.

[0011] The control constant tends to vary depending on the vehicle speed. Therefore, in the above configuration 4, the control constant is learned for each vehicle speed. Therefore, an appropriate control constant can be obtained according to the vehicle speed.

[0012] Configuration 5. In the steering control device according to any one of Configuration 1 to Configuration 4 above, the sampling process may be performed in a case where the magnitude of the steering angle is equal to or greater than the learning minimum value.

[0013] In the case where the magnitude of the steering angle is too small, the yaw rate becomes too small, and thus the accuracy of estimating the steering angle using the yaw rate decreases. In response, in the above configuration 5, the control constant is learned using the yaw rate sampled in the case where the magnitude of the steering angle is equal to or greater than the learning minimum value. Therefore, the learning accuracy of the control constant can be improved compared to the case where the yaw rate sampled in the case where the magnitude of the steering angle is less than the learning minimum value is used.

[0014] Configuration 6. In the steering control device according to any one of the above configurations 1 to 5, sampling processing may be performed in a case where the magnitude of the steering angle is equal to or less than the learning maximum value. In a case where the magnitude of the steering angle is too large, the behavior of the vehicle tends to become unstable, and thus the accuracy of estimating the steering angle using the yaw rate decreases. In response, in the above configuration 6, the control constant is learned using the yaw rate sampled in a case where the magnitude of the steering angle is equal to or less than the learning maximum value. Therefore, the learning accuracy of the control constant can be improved compared to the case where the yaw rate sampled in a case where the magnitude of the steering angle is greater than the learning maximum value is used.

[0015] Configuration 7. In the steering control device according to any one of the above configurations 1 to 6, sampling processing can be performed when the magnitude of the speed of change of the steering angle is equal to or less than a prescribed speed. When the steering angle changes, the yaw rate changes in response to the change of the steering angle. Therefore, in the case where the yaw rate is sampled when the change of the steering angle is large, the yaw rate is unstable, and thus the accuracy of estimating the steering angle using the yaw rate is reduced. In response, in the above configuration 7, the control constant is learned using the yaw rate sampled when the magnitude of the speed of change of the steering angle is equal to or less than a prescribed speed. Therefore, compared with the case of using the yaw rate sampled when the magnitude of the speed of change of the steering angle is greater than the prescribed speed, the learning accuracy of the control constant can be improved.

[0016] Configuration 8. In the steering control device according to any one of the above configurations 1 to 7, the sampling process may be performed when the combination of the steering angle and the steering angle is not in a dead zone. The dead zone may be a zone where the steering angle does not change in response to a change in the steering angle.

[0017] In the case where the yaw rate is sampled when the combination of the steering angle and the steering angle is within the dead zone, the relationship between the steering angle and the steering angle learned from the yaw rate is affected by the dead zone. Meanwhile, the dead zone is not an area that is clearly determined based on the steering angle and the steering angle, but an area that changes based on the history of the steering angle. Therefore, the relationship between the steering angle and the steering angle affected by the dead zone is a relationship specific to the situation when the sampling is performed. In response, in the above configuration 8, the yaw rate sampled when the combination of the steering angle and the steering angle is not within the dead zone is used, and thus the control constant representing a universal relationship that is independent of the history of each driving can be learned.

[0018] Configuration 9. In the steering control device according to any one of Configuration 1 to Configuration 8 above, the sampling process may be performed in a case where the magnitude of the change speed of the steering angle during the latest predetermined period is equal to or smaller than a threshold value.

[0019] In the case where the change in the steering angle during the predetermined period immediately before sampling is large, there is a concern that the behavior of the vehicle at the time of sampling is unstable. That is, there is a concern that the behavior of the vehicle at the time of sampling will be affected by the change in the steering angle during the predetermined period. In this case, the accuracy of the steering angle calculated based on the sampled yaw rate decreases. In response, in the above configuration 9, sampling is performed in the case where the magnitude of the change speed of the steering angle during the most recent predetermined period is equal to or less than a threshold value, and thus the accuracy of the estimation of the steering angle can be improved.

[0020] Configuration 10. In a steering control device according to any one of configurations 1 to 9 above, sampling processing may be performed in each of a first state, a second state, a third state, and a fourth state. The first state may be a state in which the steering steering angle is in a right steering region when the steering steering angle changes in a right steering direction. The second state may be a state in which the steering steering angle is in a left steering region when the steering steering angle changes in a right steering direction. The third state may be a state in which the steering steering angle is in a right steering region when the steering steering angle changes in a left steering direction. The fourth state may be a state in which the steering steering angle is in a left steering region when the steering steering angle changes in a left steering direction.

[0021] In the above configuration 10, the yaw rate is sampled in each of the first state, the second state, the third state, and the fourth state, and thus the yaw rate can be sampled according to various steering manipulation situations. Therefore, it is easy to learn the control constant according to various steering manipulation situations.

[0022] Configuration 11. In the steering control device according to any one of the above configurations 2 to 10 (except for items not depending on the above configuration 2), the software processing device may be configured to perform a steering angle estimation process. The steering angle estimation process is a process of calculating an estimated value of the steering angle using a detected value of the steering angle and a stiffness coefficient learned by a control constant learning process.

[0023] In the above configuration 11, the estimated value is calculated using the stiffness coefficient learned by the control constant learning process, and therefore a more appropriate stiffness coefficient can be used for the steering device compared to the case where the default stiffness coefficient is used. Therefore, the accuracy of the estimated value can be improved.

[0024] Configuration 12. In the steering control device according to the above configuration 11, the steering device may include a motor that rotates the steering shaft. The software processing device may be configured to perform a steering process. The steering process may be a process of manipulating the torque of the motor according to a manipulated variable for feedback control in which an estimated value of the steering angle is a controlled variable and a target value of the steering angle is a target value of the controlled variable.

[0025] In the above configuration 12, by using the estimated value, feedback control in which the control variable is the steering angle can be performed without a sensor that detects the steering angle.

[0026] Configuration 13. In the steering control device according to any one of the above configurations 3 to 12 (except for the items not depending on the above configuration 3), the steering device may include a motor that rotates the steering shaft. The software processing device may be configured to perform a steering process. The steering process may be a process of manipulating the torque of the motor using a dead zone amount as an input, the dead zone amount being calculated based on a dead zone width learned by a control constant learning process. The dead zone amount is a maximum amount by which the steering angle does not change in response to a change in the steering angle in the steering direction.

[0027] In the above configuration 13, the input of the process of manipulating the torque of the motor is the dead zone amount calculated according to the dead zone width learned by the control constant learning process. Therefore, compared with the case of using the default dead zone width, an accurate dead zone width can be used. Therefore, in the above configuration 13, the torque of the motor can be manipulated according to the accurate dead zone amount. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will be described below with reference to the accompanying drawings, in which like reference numerals denote like elements, and in which:

[0029] Figure 1is a diagram showing a configuration of a steering system according to an embodiment;

[0030] Figure 2 It is shown Figure 1 A diagram showing the relationship between the steering control angle and the steering angle in the steering control system shown in FIG.

[0031] Figure 3 It is shown by Figure 1 A block diagram of a process performed by a steering control device shown in;

[0032] Figure 4 It is shown by Figure 1 A flowchart of the process performed by the steering control device shown in;

[0033] Figure 5 It is shown by Figure 1 A flowchart of the process performed by the steering control device shown in;

[0034] Figure 6 is an example Figure 5 A diagram of a portion of the process shown in ;

[0035] Figure 7 It is shown by Figure 1 A flowchart of the process performed by the steering control device shown in;

[0036] Figure 8 It is shown by Figure 1 A flowchart of the process performed by the steering control device shown in;

[0037] Fig. 9 It is shown by Figure 1 A flowchart of the process performed by the steering control device shown in ; and

[0038] Fig.10 is exemplified by Figure 1 0 is a timing chart of the processing executed by the steering control device shown in . DETAILED DESCRIPTION

[0039] Embodiments of the present disclosure will be described below with reference to the accompanying drawings.

[0040] Prerequisite Configuration

[0041] Figure 1The steering device 10 shown in FIG. 1 includes a steering wheel 12. A steering shaft 14 is coupled to the steering wheel 12. The end of the steering shaft 14 on the opposite side of the steering wheel 12 is coupled to a steering gear box 20. The sector shaft of the steering gear box 20 is coupled to one end of a link arm 22. The other end of the link arm 22 is coupled to one end of a trailing link 24. The other end of the trailing link 24 is coupled to one end of a knuckle arm 26. The other end of the knuckle arm 26 is coupled to a kingpin shaft 28 of a right steering wheel 40 (R). The kingpin shaft 28 of the right steering wheel 40 (R) and the kingpin shaft 28 of the left steering wheel 40 (L) are coupled through a tie rod arm 30 and a tie rod 32.

[0042] The rotational power of the motor 50 is transmitted to the steering shaft 14. The motor 50 is a synchronous motor as an example. The output voltage of the inverter 52 is applied to the terminals of the motor 50.

[0043] The steering control device 60 includes a PU (processing unit) 62 and a storage device 64. The PU 62 is a software processing device such as a CPU (central processing unit), a GPU (graphics processing unit), and a TPU (tensor processing unit). The storage device 64 may be a non-volatile memory that is not electrically rewritable. In addition, the storage device 64 may be a non-volatile memory that is electrically rewritable, or a storage medium such as a disk medium. The PU 62 executes the program stored in the storage device 64, so that the steering control device 60 performs processing for controlling the control object.

[0044] The control object of the steering control device 60 is the steering device 10. In order to control the control object, the steering control device 60 refers to the rotation angle θm of the motor 50 detected by the rotation angle sensor 70. In addition, the steering control device 60 refers to the yaw rate γ detected by the yaw rate sensor 71. In addition, the steering control device 60 refers to the currents iu, iv, iw flowing through the terminals of the motor 50. For example, the currents iu, iv, iw can be detected as the voltage drop amount at the shunt resistor set on the arm of the inverter 52. The steering control device 60 refers to the vehicle speed V detected by the vehicle speed sensor 84 through the network 72.

[0045] The steering control device 60 can communicate with a high-level ECU (Electronic Control Unit) 80 through the network 72. The high-level ECU 80 performs a process of generating a command for intervening in the steering of the vehicle, independently of a steering instruction due to the operation of the steering wheel 12. In other words, the high-level ECU 80 performs an autonomous steering process. In order to perform the autonomous steering process, the high-level ECU 80 acquires image data about the surroundings of the vehicle captured by the camera device 82. In addition, for example, the high-level ECU 80 learns an intention indication related to the execution of the autonomous steering process and input by the driver through the interface 86.

[0046] Characteristics of the steering device 10

[0047] The above-described steering device 10 includes a complicated link mechanism, and therefore a so-called play in which the steering wheel 40 does not rotate in response to the rotation of the steering shaft 14 is large.

[0048] Figure 2 The relationship between the steering angle θh and the steering angle θt is shown. The steering angle θh is the rotation angle of the steering shaft 14. On the other hand, the steering angle θt is the movement angle of the tire associated with the steering wheel 40. In addition, Figure 2 The neutral position O described in is a point where both the steering angle θh and the steering angle θt are zero. This means that both the steering angle θh and the steering angle θt indicate the direction of linear motion. In the following, it is assumed that the rotation angle in the right steering direction is positive, and the rotation angle in the left steering direction is negative.

[0049] like Figure 2 As shown in , even when the steering angle θh changes in the right steering direction from the neutral position O, the steering angle θt does not change until the steering angle θh reaches point A. Then, when the steering angle θh becomes a value larger than point A, the steering angle θt increases.

[0050] Furthermore, even if the steering angle θh is reduced at point B, the steering angle θt does not change. In other words, even if the steering direction is switched to the left at point B, the steering angle θt does not change. The steering direction is the rotation direction of the steering shaft 14. Then, when the steering angle θh becomes a smaller value than that at point C, the steering angle θt decreases.

[0051] Then, at point D, the steering angle θt becomes zero. Point E is a value obtained by further shifting the steering angle θh in the left steering direction after the steering angle θt becomes zero. Even if the steering angle θh is increased at point E, the steering angle θt does not change until the steering angle θh reaches point F. When the steering angle θh becomes larger than point F, the steering angle θt increases.

[0052] In this way, in the case where the combination of the steering angle θh and the steering angle θt is at point B, the steering angle θt does not change even if the steering angle θh changes between point B and point C. In addition, for example, in the case where the combination of the steering angle θh and the steering angle θt is at point E, the steering angle θt does not change even if the steering angle θh changes between point E and point F. In this way, a dead zone region exists due to the play of the steering device 10, and the dead zone region is a region where the steering angle θt does not change in response to the change of the steering angle θh. The dead zone region is not a region including a fixed value of the steering angle θh, but a region that can change according to the history of the change of the steering angle θh.

[0053] The displacement of the steering angle θh from point B to point C occurs when switching back from right steering. In addition, the displacement of the steering angle θh from point E to point F occurs when switching back from left steering. Figure 2 The dead band width α shown in is the length of the dead band region in which the steering angle θt does not change in response to a change in the steering angle θh when switching back from right steering or left steering.

[0054] Control overview of steering control

[0055] Figure 3 Some of the processes performed by the steering control device 60 are shown. The PU 62 is implemented when, for example, the program stored in the storage device 64 is repeatedly executed at a predetermined period of time. Figure 3 The process shown in .

[0056] The feedback process M10 is a process that takes the target steering angle θt* and the steering angle θt as inputs and takes the feedback manipulated variable Tfb as output. The feedback manipulated variable Tfb is a manipulated variable for feedback control for which the steering angle θt is a controlled variable and the target steering angle θt* is a target value of the controlled variable. The target steering angle θt* is calculated by the high-level ECU 80. When the automatic driving mode is selected through the operation of the interface 86, the high-level ECU 80 calculates the target trajectory along which the vehicle should travel based on the image data about the vehicle's surroundings from the camera device 82. Then, the high-level ECU 80 calculates the target steering angle θt* so that the actual travel path of the vehicle is close to the target trajectory.

[0057] The steering angle estimation process M12 is a process that takes the steering angle θh as an input and takes the steering angle θt as an output. The steering angle θt is an estimated value. The steering angle θh is calculated by the PU 62 through an integration process of the rotation angle θm.

[0058] The dead zone compensation torque calculation process M14 is a process that uses the dead zone compensation torque Tdz as an output, and the dead zone compensation torque Tdz is a manipulated variable used for feedforward control in the dead zone area. The addition process M16 is a process that assigns the sum of the feedback manipulated variable Tfb and the dead zone compensation torque Tdz to the torque command value Trq*. The torque command value Trq* is a command value of the torque of the motor 50. The manipulation signal generation process M18 is a process that generates a manipulation signal MS for such control that the torque of the motor 50 is close to the torque command value Trq* and outputs the manipulation signal MS to the inverter 52. The manipulation signal generation process M18 can be a process that makes the currents iu, iv, iw close to the current command value according to the torque command value Trq*.

[0059] The dead zone position calculation process M20 is a process for calculating the dead zone position Δα, where Δα indicates Figure 2 The variables of position within the dead zone area are shown. Figure 2 The dead zone position Δα when the combination of the steering angle θh and the steering angle θt is at the point P is illustrated.

[0060] The control constant learning process M22 is a process of learning a control constant, which is a constant indicating the rotational displacement of the steered wheel 40 relative to the steering shaft 14 .

[0061] Control constant learning process M22

[0062] Figure 4 FIG. 2 shows a procedure for preprocessing of the control constant learning process M22. The control constant learning process M22 is implemented when the PU 62 repeatedly executes the program stored in the storage device 64 at a predetermined period of time. Figure 4 Hereinafter, the step numbers of the processes are indicated as reference numerals prefixed with "S".

[0063] exist Figure 4 In the processing sequence shown in , PU 62 first acquires the steering angle θh and the vehicle speed V (S10). Next, PU 62 determines whether the absolute value of the steering angle θh is equal to or greater than the learning minimum value θL and equal to or less than the learning maximum value θH (S12). The learning minimum value θL is set based on the lower limit of the steering angle θh that enables the learning process described later to be accurately performed. In addition, the learning maximum value θH is set based on the upper limit of the steering angle θh that enables the learning process described later to be accurately performed. When setting the learning maximum value θH, it is considered that the driving of the vehicle is unstable in the case where the steering angle θh is too large.

[0064] In the case where the PU 62 determines that the above absolute value is equal to or greater than the learning minimum value θL and equal to or less than the learning maximum value θH (S12: Yes), the PU 62 determines whether the condition that the absolute value of the steering angle velocity ωh is equal to or less than the threshold value ωth1 is satisfied (S14). The steering angle velocity ωh is the speed of change of the steering angle θh. The PU 62 calculates the steering angle velocity ωh using the time series data on the steering angle θh. The condition that the absolute value of the steering angle velocity ωh is equal to or less than the threshold value ωth1 is one of the execution conditions for the learning process described later. This condition is a condition indicating that the steering angle θh is stable.

[0065] In the case where the PU 62 determines that the absolute value of the steering angle velocity ωh is equal to or less than the threshold value ωth1 (S14: YES), the PU 62 determines whether the combination of the steering angle θh and the steering angle θt is outside the dead zone area (S16). The input in this process is the dead zone in-position Δα output by the dead zone in-position calculation process M20. In the case where the absolute value of the dead zone in-position Δα is less than "1 / 2" of the dead zone width αi described later, the PU 62 determines that the combination of the steering angle θh and the steering angle θt is in the dead zone area.

[0066] In the case where the PU 62 determines that the combination of the steering angle θh and the steering angle θt is not in the dead zone region ( S16 : YES), the PU 62 determines whether the following condition (A) is satisfied ( S18 ).

[0067] Condition (A): Figure 4 The condition that the absolute value of the steering angular velocity ωh is equal to or smaller than the threshold value ωth2 after the timing of a predetermined period before the current execution timing of the processing sequence in and before the current timing.

[0068] In the case where the PU 62 determines that the condition (A) is satisfied (S18: Yes), the PU 62 acquires the yaw rate γ (S20). Next, the PU 62 assigns the value obtained by multiplying the yaw rate γ by "(1+A·V·V) / V / I" to the steering angle θt (S22). This process is a process in which the PU 62 estimates the steering angle θt based on the yaw rate γ. The stability factor A and the wheelbase I are used here.

[0069] Next, the PU 62 stores the steering angle θt estimated by the process of S22 in the storage device 64 in association with the steering direction, the vehicle speed V, and the steering control angle θh (S24). In the case where the PU 62 completes the process of S24 or in the case where the PU 62 makes a negative determination in the process of S12, S14, S16, or S18, the PU 62 ends the process. Figure 4 The processing sequence shown in .

[0070] Figure 5 The process of the control constant learning process M22 is shown. The PU 62 is implemented when, for example, the program stored in the storage device 64 is repeatedly executed at a predetermined period of time. Figure 5 The processing sequence shown in .

[0071] exist Figure 5 In the illustrated processing sequence, the PU 62 determines whether the data stored in the storage device 64 by the process of S24 has reached such an amount that the learning condition is satisfied (S30). As an example, the learning condition is a condition that the number of values ​​stored by the process of S24 in each of the following states 1 to 4 is a predetermined number. A plurality of predetermined numbers may be adopted.

[0072] State 1: When the steering direction is the right steering direction, the steering angle θh is equal to or larger than the learned minimum value θL and equal to or smaller than the learned maximum value θH.

[0073] State 2: In a case where the steering direction is the right steering direction, the state in which the steering angle θh is equal to or larger than “−θH” and equal to or smaller than “−θL”.

[0074] State 3: When the steering direction is the left steering direction, the steering angle θh is equal to or larger than the learned minimum value θL and equal to or smaller than the learned maximum value θH.

[0075] State 4: In a case where the steering direction is the left steering direction, the state in which the steering angle θh is equal to or larger than "-θH" and equal to or smaller than "-θL".

[0076] In the case where PU 62 determines that it has been ensured that the data has reached such an amount that satisfies the learning condition (S30: Yes), PU 62 assigns "1" to the variable i that identifies the above data (S32). Next, PU 62 reads the following data, which is the data stored in the storage device 64 through the processing of S24 and the data in the sampling data of the vehicle speed V in the area Ai (S34). Area Ai shows one of the areas A1, A2,... according to the variable i. Areas A1, A2,... are areas of vehicle speeds V that are different from each other. For example, area A3 is an area of ​​30km / h to 40km / h, and area A4 is an area of ​​40km / h to 50km / h. Then, PU 62 calculates the rigidity coefficient ki (S36). The rigidity coefficient is a coefficient that determines the ratio of the change in the steering angle θt to the change in the steering angle θh when the combination of the steering angle θh and the steering angle θt is not in the dead zone.

[0077] Figure 6Each of the black circles shown in indicates a combination of the steering angle θh and the steering angle θt stored by the process of S24. For example, the PU 62 uses the least square method to evaluate a straight line that minimizes the deviation from the sampling point indicating the combination of the steering angle θh and the steering angle θt. Then, the PU 62 assigns the slope of the straight line to the rigidity coefficient ki. The rigidity coefficient ki is a learning value in the case where the vehicle speed V is a value in the region Ai.

[0078] Back to Figure 5 PU 62 extracts data indicating that the steering direction is the right steering direction from the data read out by the process of S34 (S38). Then, PU 62 calculates based on the data extracted by the process of S38. Figure 6 The right steering straight line L1 shown in (S40). The right steering straight line L1 is a straight line having a slope of the rigidity coefficient ki calculated by the process of S36 and having an intercept b1. The process of S40 is a process of evaluating the intercept b1 that minimizes the difference between the extracted data and the right steering straight line L1. The right steering straight line L1 is an approximate expression for approximating the relationship between the steering steering angle θh and the steering angle θt when the steering steering direction is the right steering direction.

[0079] Next, PU 62 extracts data from the data that the steering manipulation direction is the left steering direction read by the process of S34 (S42). Then, PU 62 calculates the left steering straight line L2 based on the data extracted by the process of S42 (S44). The left steering straight line L2 is a straight line having a slope of the rigidity coefficient ki calculated by the process of S36 and an intercept b2. The process of S44 is a process of evaluating the intercept b2 that minimizes the difference between the extracted data and the left steering straight line L2. The left steering straight line L2 is an approximate expression for approximating the relationship between the steering manipulation angle θh and the steering angle θt when the steering manipulation direction is the left steering direction.

[0080] Next, the PU 62 assigns the absolute value of the difference between the intercept b1 and the intercept b2 to the dead zone width αi (S46). The dead zone width αi is a learned value in the case where the vehicle V is a value in the region Ai. Then, the PU 62 determines whether the learning of the rigidity coefficients k1, k2, ... and the dead zone widths α1, α2, ... has been completed for all the regions A1, A2, ... related to the vehicle speed V (S48). In the case where the PU 62 determines that there is an area for which the learning has not been completed (S48: No), the PU 62 increments the variable i (S50) and returns to the process of S34.

[0081] On the other hand, in the case where the PU 62 determines that the learning has been completed for all areas (S48: YES), the PU 62 stores the learned data in a predetermined area of ​​the storage device 64 (S52). In the case where the PU 62 completes the processing of S52 or in the case where the PU 62 makes a negative determination in the processing of S30, the PU 62 ends. Figure 5 The processing sequence shown in .

[0082] Incidentally, before completing the above learning, the PU 62 uses preset default values ​​as the rigidity coefficient ki and the dead zone width αi. The default values ​​are previously stored in the storage device 64. In addition, it is possible to provide a vehicle speed V of zero and not Figure 6 In this case, the learning of the dead zone width α0 in the area A0 can be performed separately using a well-known technique.

[0083] Steering angle estimation processing

[0084] Figure 7 The process of the steering angle estimation process M12 is shown. The PU 62 is implemented when, for example, the program stored in the storage device 64 is repeatedly executed at a predetermined period of time. Figure 7 The process shown in .

[0085] exist Figure 7 In the processing sequence shown in , first, the PU 62 acquires the steering angle θh and the vehicle speed V (S60). Next, the PU 62 selects the stiffness coefficient k1 based on the vehicle speed V acquired by the process of S60 (S62). For example, in the case where the vehicle speed V is a value in the area A2, the PU 62 selects the stiffness coefficient k2.

[0086] Next, PU 62 assigns the value obtained by dividing the steering angle θh by the stiffness coefficient ki to the steering angle θt0 (S64). Next, PU 62 calculates the steering angle θt by correcting the steering angle θt0 at an appropriate time (S66). That is, in the case where the steering angle θt0 is in the dead zone area, PU 62 assigns the previous value of the steering angle θt to the steering angle θt. On the other hand, in the case where the steering angle θt0 is not in the dead zone area, PU 62 assigns the value obtained by adding the difference between the current value of the steering angle θt0 and the previous value of the steering angle θt to the previous value of the steering angle θt to the current value of the steering angle θt. Whether the steering angle θt0 is in the dead zone area is determined based on whether the size of the dead zone position Δα calculated by the dead zone position calculation processing M20 is less than "1 / 2" of the dead zone width αi. That is, in the processing of S66, the dead zone position Δα is used as input.

[0087] When PU 62 completes the processing of S66, PU 62 ends Figure 7 The processing sequence shown in .

[0088] Dead zone position calculation processing M20

[0089] Figure 8 FIG. 2 shows the process of the dead zone position calculation process M20. The process is realized when the PU 62 repeatedly executes the program stored in the storage device 64 at a predetermined period of time, for example. Figure 8 The process shown in .

[0090] exist Figure 8 In the processing sequence shown in , first, the PU 62 acquires the vehicle speed V (S70). Next, the PU 62 selects the dead zone width αi corresponding to the vehicle speed V acquired by the process of S70 (S72). For example, in the case where the vehicle speed V is a value in the area A2, the PU 62 selects the dead zone width α2.

[0091] Next, the PU 62 assigns to the temporary position X a value obtained by adding a value obtained by subtracting a previous value "θh(n-1)" of the steering angle θh from a current value "θh(n)" of the steering angle θh to a previous value "Δα(n-1)" of the position Δα in the dead zone (S74). Next, the PU 62 determines whether the temporary position X is equal to or greater than "(-1)·αi / 2" and equal to or less than "αi / 2" (S76). This process is a process of determining whether the combination of the steering angle θh and the steering angle θt is in the dead zone area. In the case where the PU 62 determines that the temporary position X is equal to or greater than "(-1)·αi / 2" and equal to or less than "αi / 2" (S76: Yes), the PU 62 assigns the temporary position X to the dead zone position Δα (S77).

[0092] On the other hand, in the case where the PU 62 makes a negative determination in the process of S76, the PU 62 determines whether the temporary position X is greater than "αi / 2" (S78). In the case where the PU 62 determines that the temporary position X is greater than "αi / 2" (S78: Yes), the PU 62 assigns "αi / 2" to the position Δα within the dead zone (S80). On the other hand, in the case where the PU 62 determines that the temporary position X is less than "αi / 2" (S78: No), the PU 62 assigns "(-1)·αi / 2" to the position Δα within the dead zone (S82).

[0093] When PU 62 completes the processing of S77, S80 or S82, PU 62 ends the process. Figure 8 The processing sequence shown in .

[0094] Dead zone compensation torque calculation processing M14

[0095] Fig. 9 The process of the dead zone compensation torque calculation processing M14 is shown. The PU 62 is implemented when, for example, the program stored in the storage device 64 is repeatedly executed at a predetermined period of time. Fig. 9 The process shown in .

[0096] exist Fig. 9 In the processing sequence shown in , first, the PU 62 acquires the vehicle speed V ( S90 ). Next, the PU 62 selects the dead zone width αi corresponding to the vehicle speed V acquired by the process of S90 ( S92 ).

[0097] PU 62 determines whether the value obtained by subtracting the previous value "θt*(n-1)" of the target steering angle θt* from the current value "θt*(n)" of the target steering angle θt* is positive (S94). This process is a process for determining whether the steering manipulation direction is the right steering direction. In the case where PU 62 determines that the value obtained by the above subtraction is positive (S94: Yes), PU 62 assigns to the dead zone amount Dα a value obtained by subtracting the position Δα in the dead zone from "1 / 2" of the dead zone width αi selected by the process of S92 (S96). The dead zone amount Dα obtained by the process of S96 is the maximum amount by which the steering angle θt does not change when the steering manipulation angle θh changes in the right steering direction.

[0098] Next, the PU 62 determines whether the dead zone amount Dα is greater than zero (S98). In the case where the PU 62 determines that the dead zone amount Dα is greater than zero (S98: Yes), the PU 62 assigns the sum of the following two to the dead zone compensation torque Tdz: the value obtained by multiplying the prescribed torque TdzA by the value obtained by dividing the dead zone amount Dα by the dead zone width αi; and the offset amount TdzB (S100).

[0099] On the other hand, in the case where PU 62 makes a negative determination in the process of S94, PU 62 determines whether the value obtained by subtracting the previous value "θt*(n-1)" of the target steering angle θt* from the current value "θt*(n)" of the target steering angle θt* is negative (S102). This process is a process for determining whether the steering manipulation direction is the left steering direction. In the case where PU 62 determines that the value obtained by the above subtraction is negative (S102: Yes), PU 62 assigns to the dead zone amount Dα a value obtained by subtracting the position Δα within the dead zone from "-1 / 2" of the dead zone width αi selected by the process of S92 (S104). The absolute value of the dead zone amount Dα obtained by the process of S104 is the maximum amount by which the steering angle θt does not change when the steering manipulation angle θh changes in the left steering direction, and the maximum amount means the maximum value of the absolute value. Here, the dead zone amount Dα is equal to or less than zero.

[0100] When the PU 62 determines that the dead zone amount Dα is less than zero ( S106 : YES), the PU 62 assigns to the dead zone compensation torque Tdz a value obtained by subtracting the offset amount TdzB from the value obtained by multiplying the prescribed torque TdzA by the value obtained by dividing the dead zone amount Dα by the dead zone width αi ( S108 ).

[0101] On the other hand, in the case where the PU 62 makes a negative determination in the process of S98 or S106, the PU 62 assigns "0" to the dead zone compensation torque Tdz (S110). In the case where the PU 62 completes the process of S100, S108, or S110, or in the case where the PU 62 makes a negative determination in the process of S102, the PU 62 ends. Fig. 9 The processing sequence shown in .

[0102] Fig.10 FIG. 2 shows an example of the transition of the dead zone compensation torque Tdz according to the embodiment. Fig.10 As shown in , at time t1 when PU 62 determines that the steering direction has changed from the right steering direction to the left steering direction based on the target steering angle θt*, PU 62 sets the dead zone compensation torque Tdz to the torque for left steering. Fig.10 , it is assumed that the steering angle θt is not in the dead zone region immediately before time t1. Therefore, the dead zone amount Dα at time t1 is "-αi". Therefore, at time t1, PU 62 changes the dead zone compensation torque Tdz from "0" to "-TdzA-TdzB" in a step-by-step manner. Then, PU 62 gradually reduces the magnitude of the dead zone compensation torque Tdz until the dead zone amount Dα becomes zero. At time t2 when the dead zone amount Dα becomes zero, PU 62 changes the dead zone compensation torque Tdz from "-TdzB" to "0" in a step-by-step manner.

[0103] Thereafter, at time t3 when PU 62 determines that the steering manipulation direction has changed from the left steering direction to the right steering direction based on the target steering angle θt*, PU 62 sets the dead zone compensation torque Tdz to the torque for right steering. The dead zone amount Dα at time t3 is "αi". Therefore, at time t3, PU 62 changes the dead zone compensation torque Tdz from "0" to "TdzA+TdzB" in a step-by-step manner. Then, PU 62 gradually reduces the size of the dead zone compensation torque Tdz until the dead zone amount Dα becomes zero. At time t4 when the dead zone amount Dα becomes zero, PU 62 changes the dead zone compensation torque Tdz from "TdzB" to "0" in a step-by-step manner.

[0104] In this way, when the steering angle θt is in the dead zone region, the PU 62 uses the dead zone compensation torque Tdz as a manipulated variable for feedforward control to control the torque of the motor 50. Therefore, the responsiveness of the steering angle θt can be improved compared to the case where the torque of the motor 50 is controlled using only the feedback manipulated variable Tfb.

[0105] Operation and Effects of Implementation Methods

[0106] PU 62 synchronously acquires the yaw rate γ and the steering angle θh. Then, PU 62 stores the steering angle θt calculated based on the yaw rate γ and the vehicle speed V in association with the corresponding steering angle θh in the storage device 64. When a sufficient number of sampled values ​​(each of which is a combination of the steering angle θh and the steering angle θt) are stored in the storage device 64, PU 62 calculates the approximate expression shown by the sampled values. PU 62 calculates the slope of the approximate expression as the rigidity coefficient ki. In addition, PU 62 assigns the difference between the corresponding intercepts of the approximate expression determined based on the sampled values ​​of the right steering direction and the approximate expression determined based on the sampled values ​​of the left steering direction to the dead zone width αi. Therefore, the rigidity coefficient ki and the dead zone width αi specific to the steering device 10 can be learned.

[0107] In the above-described embodiment, the following operations and effects are also obtained.

[0108] (1-1) The PU 62 learns the dead band width αi according to the vehicle speed V. Therefore, compared with the case where the dead band width αi is a value that does not depend on the vehicle speed V, the in-dead band position Δα can be calculated with higher accuracy.

[0109] (1-2) The PU 62 learns the rigidity coefficient ki according to the vehicle speed V. Therefore, compared with the case where the rigidity coefficient ki is a value that does not depend on the vehicle speed V, the steering angle θt can be estimated with higher accuracy.

[0110] (1-3) PU 62 estimates the steering angle θt using the yaw rate γ when the magnitude of the steering angle θh is equal to or greater than the learning minimum value θL. When the magnitude of the steering angle θh is too small, the yaw rate γ becomes too small, and thus the accuracy of estimating the steering angle using the yaw rate γ decreases. In response, in the embodiment, the steering angle θt is estimated using the yaw rate γ sampled when the magnitude of the steering angle θh is equal to or greater than the learning minimum value θL. Therefore, compared with the case of using the yaw rate γ sampled when the magnitude of the steering angle θh is less than the learning minimum value θL, the learning accuracy based on the steering angle θt can be improved.

[0111] (1-4) PU 62 estimates the steering angle θt using the yaw rate γ when the magnitude of the steering angle θh is equal to or less than the learning maximum value θH. In the case where the magnitude of the steering angle θh is too large, the behavior of the vehicle tends to become unstable, and thus the accuracy of estimating the steering angle θt using the yaw rate γ decreases. In response, in the embodiment, the steering angle θt is estimated using the yaw rate γ sampled when the magnitude of the steering angle θh is equal to or less than the learning maximum value θH. Therefore, compared with the case where the yaw rate γ sampled when the magnitude of the steering angle θh is greater than the learning maximum value θH is used, the learning accuracy based on the steering angle θt can be improved.

[0112] (1-5) PU 62 estimates the steering angle θt using the yaw rate γ in a case where the magnitude of the steering angle velocity ωh is equal to or less than the threshold value ωth1. In a case where the steering angle θh changes, the yaw rate γ is unstable, and thus the accuracy of estimating the steering angle θt using the yaw rate γ decreases. In response, in the embodiment, the steering angle θt is estimated using the yaw rate γ sampled in a case where the magnitude of the steering angle velocity ωh is equal to or less than the threshold value ωth1. Therefore, compared with the case where the yaw rate γ sampled in a case where the magnitude of the steering angle velocity ωh is greater than the threshold value ωth1 is used, the learning accuracy based on the steering angle θt can be improved.

[0113] (1-6) PU 62 estimates the steering angle θt using the yaw rate γ when the combination of the steering angle θh and the steering angle θt is not in the dead zone. In the case where the yaw rate γ is sampled when the combination of the steering angle θh and the steering angle θt is in the dead zone, the relationship between the steering angle θt and the steering angle θh learned from the yaw rate γ is affected by the dead zone. Meanwhile, the dead zone is not a region that is clearly determined based on the steering angle θh and the steering angle θt, but is a region that changes based on the history of the steering angle θh. Therefore, the relationship between the steering angle θt and the steering angle θh affected by the dead zone is a relationship specific to the situation when the sampling is performed. In response, in the embodiment, the steering angle θt is estimated using the yaw rate γ sampled when the combination of the steering angle θh and the steering angle θt is not in the dead zone. Therefore, PU 62 can learn a universal relationship that is independent of the history of each driving as the relationship between the steering angle θh and the steering angle θt.

[0114] (1-7) PU 62 estimates the steering angle θt using the yaw angular velocity γ when the magnitude of the steering steering angle velocity ωh during the most recent predetermined period is equal to or less than the threshold value ωth2. In the case where the change in the steering steering angle during the most recent predetermined period is large, there is a concern that the behavior of the vehicle at the time of sampling is unstable. That is, there is a concern that the behavior of the vehicle at the time of sampling will be affected by the change in the steering steering angle during the predetermined period. In this case, the accuracy of the steering angle θt calculated based on the sampled yaw angular velocity γ is reduced. In response, in an embodiment, sampling is performed when the magnitude of the steering steering angle velocity ωh during the most recent predetermined period is equal to or less than the threshold value ωth2, and thus the accuracy of the estimation of the steering angle θt can be improved.

[0115] (1-8) PU 62 learns the dead zone width αi and the stiffness coefficient ki using the steering angle θt estimated from the yaw rate γ sampled in each of the first state, the second state, the third state, and the fourth state. This means, for example, that it is different from the case where only the steering angle θt estimated from the yaw rate γ sampled in each of the first state and the third state is used. That is, the right steering straight line L1 and the left steering straight line L2 are determined using sampling points of the steering operation angle θh and the steering angle θt in a wider range. Therefore, the accuracy with which the relationship between the steering operation angle θh and the steering angle θt at the time of right steering or left steering in the actual steering operation is approximated by the right steering straight line L1 or the left steering straight line L2 can be improved.

[0116] (1-9) The PU 62 samples the same number of yaw angular velocity γ for learning in the respective states of the first state, the second state, the third state, and the fourth state. Therefore, the accuracy with which the relationship between the steering angle θh and the steering angle θt at the time of right or left steering in actual steering manipulation is approximated by the right steering straight line L1 or the left steering straight line L2 can be improved.

[0117] (1-10) The rigidity coefficient ki is calculated using all the sampling points used to calculate the right turning straight line L1 and the left turning straight line L2. Therefore, the number of sampling points used to calculate the rigidity coefficient ki can be maximized. Therefore, the rigidity coefficient ki can be calculated with higher accuracy than when only some of the sampling points are used.

[0118] (1-11) PU 62 adopts the stiffness coefficient ki as the slopes of the right turning straight line L1 and the left turning straight line L2. Therefore, the difference between the slopes of the right turning straight line L1 and the left turning straight line L2 can be easily suppressed compared with the case where the slopes are calculated separately.

[0119] Correspondence

[0120] The correspondence relationship between the matters in the above embodiment and the matters described in “Summary of the Invention” is as follows. The correspondence relationship of each of the configuration numbers described in “Summary of the Invention” will be shown below.

[0121] In configurations 1, 2, 5, 6, and 11, the sampling process corresponds to the processes of S20 and S24. The steering angle calculation process corresponds to the process of S22. The control constant learning process corresponds to Figure 5 The processing corresponds to .

[0122] In configuration 3, the right turning straight line calculation process corresponds to the processes of S38 and S40. The left turning straight line calculation process corresponds to the processes of S42 and S44. The dead zone width calculation process corresponds to the process of S46.

[0123] Arrangement 4 corresponds to data in area Ai determined for each vehicle speed extracted by the process of S34.

[0124] In configuration 7, the prescribed speed corresponds to the threshold value ωth1.

[0125] Configuration 8 corresponds to the process of S16.

[0126] Configuration 9 corresponds to the process of S18.

[0127] Configuration 10 and Figure 6 The sampling points shown in FIG.

[0128] In the configuration 12, the steering process corresponds to the feedback process M10, the dead zone compensation torque calculation process M14, the addition process M16, and the manipulation signal generation process M18.

[0129] Configuration 13 corresponds to calculation of the dead zone compensation torque Tdz based on the dead zone amount Dα in the processes of S96 and S104 in the dead zone compensation torque calculation process M14.

[0130] Other Implementations

[0131] The embodiment can be performed with the following modifications. As long as there is no technical inconsistency, the embodiment and the following modifications can be performed while being combined with each other.

[0132] Sampling Processing

[0133] The sampling method in the sampling process is not limited to Figure 6The method illustrated in . That is, the following method is not necessary: ​​in the area where the steering angle θh is equal to or greater than the learning minimum value θL and equal to or less than the learning maximum value θH and the area where the steering angle θh is equal to or greater than "-θH" and equal to or less than "-θL", sampling when the steering direction is the right steering direction and sampling when the steering direction is the left steering direction are respectively performed. For example, sampling may be performed for each of the right steering direction and the left steering direction only in the area where the steering angle θh is equal to or greater than the learning minimum value θL and equal to or less than the learning maximum value θH. In addition, for example, sampling may be performed for each of the right steering direction and the left steering direction only in the area where the steering angle θh is equal to or greater than "-θH" and equal to or less than "-θL".

[0134] The execution condition of the sampling process does not need to be a condition that an affirmative determination is made in all of the processes of S12 to S18 .

[0135] Steering angle calculation and processing

[0136] In the process of S22, the PU 62 calculates the steering angle θt using the stability factor A and the wheelbase I, but the present disclosure is not limited thereto. For example, the PU 62 may perform mapping calculation of the steering angle θt in a state where mapping data is stored in the storage device 64. The mapping data is data that takes the yaw rate γ and the vehicle speed V as input variables and takes the steering angle θt as an output variable.

[0137] Control constant learning process

[0138] exist Figure 6 , the number of sampling points used in the control constant learning process in each of the first state, the second state, the third state, and the fourth state is three, but the present disclosure is not limited thereto. For example, the number of sampling points used in the control constant learning process in each state may be two. Furthermore, for example, the number of sampling points used in the control constant learning process in each state may be four. Furthermore, the number of sampling points used in the control constant learning process in each state does not need to be the same as each other.

[0139] The sampling points for learning the rigidity coefficient ki are not limited to Figure 6The points illustrated in . That is, the sampling points for the control constant learning process are not limited to the points sampled in the corresponding states among the first state to the fourth state above. For example, the sampling points for learning the rigidity coefficient ki may include only the points sampled in three arbitrary states among the four states from the first state to the fourth state above. In addition, for example, the sampling points for learning the rigidity coefficient ki may include only the points sampled in two arbitrary states among the four states from the first state to the fourth state above. In addition, for example, the sampling points for learning the rigidity coefficient ki may include only the points sampled in one arbitrary state among the four states from the first state to the fourth state above. In this case, the number of sampling points only needs to be two or more.

[0140] The sampling points used for learning the dead zone width αi are not limited to the points sampled in the corresponding states among the first state to the fourth state above. For example, the sampling points used for learning the dead zone width αi may include only the points sampled in the first state and the third state. In this case, the number of sampling points in each state only needs to be two or more. In addition, for example, the sampling points used for learning the dead zone width αi may include only the points sampled in the second state and the fourth state. In this case, the number of sampling points in each state only needs to be two or more.

[0141] The sampling points for learning the rigidity coefficient ki and the sampling points for learning the dead zone width αi do not need to be the same. The learning process for the dead zone width αi does not need to be performed after the learning process for the rigidity coefficient ki. For example, the right turning straight line L1 and the left turning straight line L2 may be calculated before learning the rigidity coefficient ki. Even in this case, the dead zone width αi may be learned by the process of S46. In this case, for example, the rigidity coefficient ki may be the average of the slopes of the right turning straight line L1 and the slopes of the left turning straight line L2.

[0142] The control constant learning process does not need to be a process of learning the dead band width αi at each of mutually different vehicle speeds V. For example, a process of learning the dead band width αi at a single vehicle speed V higher than zero may be employed.

[0143] The control constant learning process does not need to be a process of learning the rigidity coefficient ki at each of mutually different vehicle speeds V. For example, a process of learning the rigidity coefficient ki at a single vehicle speed V may be employed.

[0144] Steering handling

[0145] The process of manipulating the torque of the motor 50 using the dead zone amount Dα calculated from the dead zone width αi as input is not limited to the process of using the dead zone compensation torque Tdz. For example, a process of correcting the target steering angle θt* according to the dead zone amount Dα may be adopted.

[0146] Torque control of electric motors

[0147] It is not necessary to operate the drive circuit of the motor 50 according to the manipulated variable for control in which the steering angle is the controlled variable and the target value of the steering angle is the target value of the controlled variable. For example, the drive circuit of the motor 50 may be operated according to the manipulated variable for feedforward control depending on the target value. In this case, in the dead zone, the PU 62 may superimpose the dead zone compensation torque Tdz on the manipulated variable for feedforward control calculated even outside the dead zone area.

[0148] Autopilot mode

[0149] In the automatic driving mode, the sensing means for acquiring information about the outside of the vehicle (including the lane) is not limited to the camera 82. For example, LIDAR (Laser Radar) may be used.

[0150] Driving Mode

[0151] The driving mode in which the dead zone compensation torque Tdz is superimposed on the torque of the motor 50 is not limited to the automatic driving mode. For example, a manual driving mode may be adopted, which is a mode in which a steering operation by a driver is performed. In this case, for example, in the processing of S94 and S102, only the steering operation angle θh needs to be adopted instead of the target steering angle θt*.

[0152] Steering Controls

[0153] The high-level ECU 80 and the steering control device 60 may be configured integrally. The steering control device is not limited to a device that performs software processing. For example, a dedicated hardware circuit that performs at least some of the processing performed in the above embodiment may be included, as exemplified by an ASIC. That is, the steering control circuit only needs to include a processing circuit having one of the following (a) to (c) configurations.

[0154] (a) A processing circuit including: a processing device for executing all of the above processes according to a program, and a program storage device exemplified by a storage device for storing the program.

[0155] (b) A processing circuit including: a processing device that executes some of the above processes according to a program, a program storage device, and a dedicated hardware circuit that executes other processes.

[0156] (c) Processing circuit including the following: a dedicated hardware circuit that performs all of the above processing.

[0157] A plurality of software execution means may be provided, each of the plurality of software execution means comprising a processing means and a program storage means. In addition, a plurality of dedicated hardware circuits may be provided.

Claims

1. A steering control device (60), characterized in that: The invention comprises a software processing device, wherein: The software processing device controls the steering control device (10); The steering control device (10) comprises: a steering shaft (14), and A steering wheel (40) of a vehicle, wherein the steering wheel (40) turns as the steering shaft (14) rotates; The software processing device is configured to perform sampling processing, steering angle calculation processing, and control constant learning processing; The sampling process is a process of synchronously sampling the steering angle and the yaw angular velocity; The steering control angle is the rotation angle of the steering control shaft (14); The steering angle calculation process is a process of calculating the steering angle of the steering wheel (40) using the yaw rate and the vehicle speed as input; The control constant learning process is a process of learning a control constant based on a plurality of combinations, each of the plurality of combinations being composed of the steering angle sampled by the sampling process and the steering angle corresponding to the steering angle; and The control constant is a constant indicating a rotational displacement of the steering wheel (40) relative to the steering shaft (14).

2. The steering control device (60) according to claim 1, characterized in that: The control constant includes a stiffness coefficient which is a ratio of the steering angle to the steering angle; and The control constant learning process is a process of learning the slope of a straight line as the stiffness coefficient, the slope of the straight line being determined by the plurality of combinations, each of the plurality of combinations being composed of the steering angle and the steering angle corresponding to the steering angle.

3. The steering control device (60) according to claim 1, characterized in that: The control constants include dead zone width; The dead zone width is a rotation amount of the steering shaft (14) after the rotation direction of the steering shaft (14) is switched from one of the right steering direction and the left steering direction to the other of the right steering direction and the left steering direction and before the steering wheel (40) is turned; The control constant learning process includes a right-turn straight line calculation process, a left-turn straight line calculation process, and a dead zone width calculation process; The right turning straight line calculation process is a process of calculating a right turning straight line based on the following first plurality of combinations: the first plurality of combinations are included in the plurality of combinations each consisting of the sampled steering angle and the steering angle corresponding to the steering angle and are combinations when the rotation direction is the right turning direction; The left turning straight line calculation process is a process of calculating a left turning straight line based on a second plurality of combinations included in the plurality of combinations each consisting of the sampled steering angle and the steering angle corresponding to the steering angle and being a combination when the rotation direction is the left turning direction; and The dead zone width calculation process is a process of calculating a difference in intercepts between the right turning straight line and the left turning straight line as the dead zone width.

4. The steering control device (60) according to claim 1, characterized in that: The control constant learning process is a process of calculating the control constant for each of vehicle speeds that are different from each other based on a plurality of combinations, each of which is composed of the steering angle sampled by the sampling process for each of the vehicle speeds that are different from each other and the steering angle corresponding to the steering angle.

5. The steering control device (60) according to claim 1, characterized in that: The sampling process is performed when the magnitude of the steering angle is equal to or greater than a learned minimum value.

6. The steering control device (60) according to claim 1, characterized in that: The sampling process is performed when the magnitude of the steering angle is equal to or smaller than a learned maximum value.

7. The steering control device (60) according to claim 1, characterized in that: The sampling process is performed when the magnitude of the change speed of the steering angle is equal to or smaller than a prescribed speed.

8. The steering control device (60) according to claim 1, characterized in that: performing the sampling process in a case where the combination of the steering steering angle and the steering angle is not within a dead band region; and The dead zone region is a region in which the steering angle does not change in response to a change in the steering angle.

9. The steering control device (60) according to claim 1, characterized in that: The sampling process is performed in the case where the magnitude of the change speed of the steering angle during the latest predetermined period is equal to or smaller than a threshold value.

10. The steering control device (60) according to claim 1, characterized in that: performing the sampling process in each of a first state, a second state, a third state, and a fourth state; The first state is a state in which the steering angle is in a right turning area when the steering angle changes in a right turning direction; The second state is a state in which the steering angle is in a left turning area when the steering angle changes in a right turning direction; The third state is a state in which the steering angle is in a right turning region when the steering angle changes in a left turning direction; and The fourth state is a state in which the steering angle is in a left turning region when the steering angle changes in the left turning direction.

11. The steering control device (60) according to claim 2, characterized in that: The software processing means is configured to perform a steering angle estimation process; and The steering angle estimation process is a process of calculating an estimated value of the steering angle using the detection value of the steering steering angle and the stiffness coefficient learned by the control constant learning process.

12. The steering control device (60) according to claim 11, characterized in that: The steering device (10) comprises a motor (50) for rotating the steering shaft (14); The software processing means is configured to perform a diversion process; and The steering process is a process of manipulating the torque of the motor (50) according to a manipulated variable for feedback control in which the estimated value of the steering angle is a controlled variable and the target value of the steering angle is the target value of the controlled variable.

13. The steering control device (60) according to claim 3, characterized in that: The steering device (10) comprises a motor (50) for rotating the steering shaft (14); The software processing device is configured to perform a steering process; The steering process is a process of manipulating the torque of the motor (50) using a dead zone amount as an input, the dead zone amount being calculated based on the dead zone width learned by the control constant learning process; and The deadband amount is a maximum amount in which the steering angle does not change in response to a change in the steering angle in the steering direction.

Images