Two-wheeled vehicle stable travel control system and two-wheeled vehicle stable travel controller

Abstract

To provide a modeling method of a two-wheeled vehicle stable travel control system, a two-wheeled vehicle stable travel simulator, a program, a two-wheeled vehicle stable travel control system, and a two-wheeled vehicle stable travel controller.SOLUTION: A two-wheeled vehicle stable travel control system (190) includes an actual-machine two-wheeled vehicle (300), a power steering unit (312) having as a constituent component a steering torque actuator (310) that is attached to the actual-machine two-wheeled vehicle and generates a steering torque in the actual-machine two-wheeled vehicle, a measurement unit (350) that implements measurement processing based on outputs of plural sensors (301, 303, 305, 307, 308, 311, and 313) attached to the actual-machine two-wheeled vehicle, and a power steering control unit (403) including a steering torque actuator control signal generator (408) that is attached to the two-wheeled vehicle and generates a control signal of the steering torque actuator on the basis of the output of the measurement unit.SELECTED DRAWING: Figure 12

Description

[Technical field]

[0001] The present invention relates to a modeling method for a motorcycle stable running control system, a motorcycle stable running simulator, a program, a motorcycle stable running control system, and a motorcycle stable running control device, etc. [Background technology]

[0002] In the past, power steering has been used to control stable driving of two-wheeled vehicles, just as it has been done for four-wheeled vehicles. In the following explanation, the term "two-wheeled vehicles" includes not only motorcycles but also electrically assisted bicycles and the like.

[0003] In the following description, the term power steering will be used for two-wheeled vehicles as well as for four-wheeled vehicles.

[0004] The stable running control of a motorcycle also includes so-called automatic driving, which enables stable running by autonomously suppressing running disturbances caused by various disturbances. Note that in this specification, the stable running control of a motorcycle that autonomously suppresses running disturbances may be referred to as autonomous stable running control or simply automatic driving control.

[0005] When analyzing the movement of a motorcycle, there are more degrees of freedom that must be considered compared to a four-wheeled vehicle, and the influence of the rider's posture and steering operation is greater than in a four-wheeled vehicle. For this reason, discussion of autonomous driving for motorcycles is said to be lagging behind that for four-wheeled vehicles.

[0006] However, with the recent advances in autonomous driving technology for four-wheeled vehicles, there has been an increased discussion of autonomous driving for motorcycles as well. In addition, future needs can be envisioned, such as using autonomous motorcycles for everyday shopping, or touring tourist spots.

[0007] Conventional techniques for stable driving assist control or autonomous stable driving control of a motorcycle include, for example, the following.

[0008] Patent Document 1 discloses that in order to provide a motorcycle that can automatically travel stably along a road without wobbling, the amount of steering of the wheels by the steering means and the amount of swinging of the wheels by the swinging means are controlled based on target values ​​of the yaw momentum and roll momentum of the motorcycle.

[0009] Patent Document 2 shows a control object model in which a gyro actuator is integrally arranged with an object in order to control the posture of a two-wheeled vehicle, and a control system is provided in which a torque is applied to the object whose posture is tilted by the operation of the gyro actuator, thereby controlling the posture of the object to a stable state.

[0010] Patent Document 3 shows a fall prevention device in which a bicycle robot is mounted on an actual two-wheeled vehicle and the movement of the bicycle robot prevents the two-wheeled vehicle from falling over.

[0011] Patent Document 4 discloses a motorcycle steering assist system that provides an actuator capable of applying a steering torque to a motorcycle and assists the running of the motorcycle with a power steering operation similar to that of a four-wheeled vehicle.

[0012] Patent Document 5 shows a configuration in which a moving body is provided with a steering actuator that generates a driving force to steer the front wheels, and a trail length changing actuator that generates a driving force to change the trail length of the front wheels, in order to increase the stability of the vehicle body posture when stopped and to make it easier for the driver to control the vehicle body posture when traveling at high speeds.

[0013] Patent Document 6 discloses the construction of a system for improving the driving performance of a leanable vehicle, i.e., a two-wheeled vehicle that can lean, which has a state estimator that estimates the motion state of the vehicle and a dynamic vehicle model module that receives external data indicating the motion state, for the purpose of driving assistance of the vehicle.

[0014] Patent Document 7 discloses a motion control method for a four-wheeled vehicle using a state equation. Claim 5 and Figure 5 of Patent Document 7 show that a feedback gain, which is a function of vehicle speed, is calculated using the state equation.

[0015] Furthermore, a system and method for simulating the motion of a multibody system using the principle of virtual power and Hamilton's equation of motion is described in Patent Document 8.

[0016] Furthermore, a device for deriving an equation of motion for a multi-rigid body system and a method for deriving an equation of motion for a multi-rigid body system using the principle of virtual power and Kane's equation of motion are described in, for example, Patent Document 9. [Prior art documents] [Patent documents]

[0017] [Patent Document 1] JP 2004-338507 A [Patent Document 2] JP 2015-158390 A [Patent Document 3] Patent No. 4605227 [Patent Document 4] JP 2013-60187 A [Patent Document 5] Patent No. 6081238 [Patent Document 6] Patent Publication No. 2019-119447 [Patent Document 7] Japanese Patent Application Publication No. 63-312271 [Patent Document 8] International Publication No. 2006 / 012709 [Patent Document 9] JP 2014-078090 A Summary of the Invention [Problem to be solved by the invention]

[0018] The present invention has been developed based on various considerations regarding autonomous stable driving control of a two-wheeled vehicle using power steering. In the following description, the power steering technique is assumed to be, for example, a technique of applying steering torque to at least one of the handle and the rotating shaft that rotates the handle, in other words the steering shaft, by a torsion bar actuator or the like. Here, although the names of handle angle and steering angle are different, they are common in that they are steering angles related to steering of a motorcycle in a broad sense.

[0019] For example, when a motorcycle with a rider is traveling in a straight line, the handlebars actually shake slightly. If the entire vehicle body is balanced and the entire vehicle body and the front wheel system have the same roll angle, and if the fluctuations in steering torque due to disturbances can be countered by controlling the steering torque with the power steering, the moment of inertia and the steering force applied by the rider to the handlebars will be balanced with respect to the steering axis, and the rider will be able to feel as if he or she is driving automatically.

[0020] Therefore, by establishing appropriate power steering technology, it is believed possible to enable a motorcycle to travel stably and autonomously without tipping over.

[0021] Here, it is preferable that the autonomous stable driving control technology for a two-wheeled vehicle is one that can be widely applied to various types of general two-wheeled vehicles available on the market, that is, it is a versatile control technology.

[0022] Furthermore, in order to realize the autonomous stable driving control, a steering torque control with higher accuracy than that of the conventional stable driving assist control is required.

[0023] As a result of various investigations, the present inventor has come to the knowledge that in order to realize a power steering technology that is versatile and enables autonomous stable driving, it is necessary to fully consider not only the behavior of the vehicle as a moving body, but also the behavior of the vehicle as a vibrating body.

[0024] That is, it is important to analyze the vibration of the vehicle taking into consideration the characteristics of the front suspension, called a front fork, and the rear suspension, which are attached to the motorcycle, in other words, the vibration suppression effect of each suspension.

[0025] In addition, a development methodology known as Model Based Development (MBD), which incorporates simulation technology into software development, is effective in developing an autonomous stable driving control system for motorcycles.

[0026] In model-based development, the model becomes a "moving specification" and analysis and processing are carried out on a simulator implemented using a computer. Therefore, developers can actually see the visualized movement and perform various verifications and considerations.

[0027] However, it is very difficult to treat a motorcycle not simply as a moving body, but as a moving body that vibrates as it moves, and to analyze in detail its complex dynamic behavior using a vehicle model.

[0028] For example, due to the nonlinearity of the springs in the suspension, in other words the suspension springs, the equation of motion that describes the behavior of a two-wheeled vehicle becomes a function that includes a quadratic term with respect to time, making analysis of the equation difficult.

[0029] For example, in modern control theory, when analyzing the dynamic behavior of a system, a method is adopted in which state variables are introduced as internal variables that relate the system's input and output, and the state variables are described by first-order matrix differential equations called state equations.

[0030] Since this state equation is a linear simultaneous equation, the equation of motion, which is expressed by a function including a quadratic term with respect to time, cannot be converted into the state equation for analysis.

[0031] In addition, the behavior of motorcycles has been analyzed based on a simplified model with one center of gravity in the past, but in reality motorcycles are designed with a front section and a rear section, so it is preferable to analyze the motorcycle divided into, for example, the front body, rear body, front suspension, and rear suspension.

[0032] In this case, a method known as multi-body dynamics (MD), which uses simulation to analyze the dynamic behavior and performance of objects performing complex movements, is effective.

[0033] However, in the prior art, a method for accurately analyzing the behavior of a two-wheeled vehicle, including its suspension, using multi-body dynamics has not been established.

[0034] The above-mentioned Patent Document 1 is based on the premise that a two-wheeled vehicle with a special shape will be moved at an extremely slow speed, and this autonomous driving technology lacks versatility.

[0035] In Patent Document 2, a special device called a gyro actuator is integrally attached to a motorcycle to perform attitude control, and this attitude control technology in Patent Document 2 also lacks versatility.

[0036] Patent Document 3 uses a motorcycle robot to actually measure the tilt angle and other factors that are suitable for stable running of a motorcycle, but this technology alone does not enable a motorcycle to run stably autonomously.

[0037] Patent Document 4 shows a steering assist system for a motorcycle using power steering, but in this patent document 4, an analysis of the complex behavior of the motorcycle taking into account the characteristics of the suspension is not carried out.

[0038] In Patent Document 5, the steering of a motorcycle is controlled by using a steering actuator. However, as shown in FIG. 1, for example, the model of the motorcycle is a simple model having one center of gravity, and no analysis of the complex behavior of the motorcycle taking into account the characteristics of the suspension is performed.

[0039] Patent Document 6 describes a system for improving the driving performance of a leanable motorcycle, but does not perform an analysis of the complex behavior of the motorcycle taking into account the characteristics of the suspension. Furthermore, although Patent Document 6 describes the use of various sensors such as speed sensors and inertial sensors, it does not describe at all how to use these numerous sensors to construct a negative feedback control system that enables autonomous and stable driving.

[0040] For example, in Figure 5 of Patent Document 7, analysis of the behavior of a four-wheeled vehicle using a state equation is shown, but the model of the four-wheeled vehicle is a simplified model having one center of gravity, and there is no mention of an analysis of the complex behavior of a two-wheeled vehicle taking into account the characteristics of the suspension. Therefore, Patent Document 7 is not useful as a reference for making the present invention.

[0041] Patent Document 8 discloses a system and method for simulating the motion of a multibody system, and in this Patent Document 8, an analysis is performed using Hamilton's equation of motion that describes the motion of a classical dynamics system. Because this is an analysis method for a classical dynamics system, it is not possible to analyze a control target that exhibits complex behavior, such as a multi-input / multi-output control target, as in the case of analysis using modern control theory.

[0042] Patent Document 9 describes an apparatus for deriving an equation of motion for a multi-rigid body system and a method for deriving an equation of motion for a multi-rigid body system that utilizes the principle of virtual power and Kane's equation of motion, but this Patent Document 9 is based on the premise that all components to be controlled are rigid bodies. Therefore, it cannot be applied to the analysis of a motion system that includes non-rigid elements, for example elements that are considered to be elastic or flexible with respect to a given motion. In addition, an example of a controlled object that includes an element that can be regarded as an elastic body or a flexible body with respect to a specified movement may be a two-wheeled vehicle system that includes a rigid vehicle body and a tire system that supports this rigid vehicle body and can be regarded as an elastic body or a flexible body with respect to vibrations in the vertical direction, for example.

[0043] The present invention aims to provide a versatile motorcycle stable running control technology etc. that can multifacetedly and scientifically verify the running stability of motorcycles involving complex nonlinear behavior, in other words, a method for modeling a motorcycle stable running control system, a motorcycle stable running simulator, a program, a motorcycle stable running control system, and a motorcycle stable running control device etc. [Means for solving the problem]

[0044] As a result of extensive research, the inventors have discovered that it is possible to develop a stable driving control system for a two-wheeled vehicle that is both practical and versatile, by modeling a two-wheeled vehicle as a model that includes multiple centers of gravity and also includes a suspension, integrating the equations of motion for each center of gravity to obtain a linearized equation of motion for the two-wheeled vehicle, converting the linear equation of motion into a state equation to perform a stability analysis, and determining the feedback gain required for appropriate steering torque control for each speed within a desired speed range. The present invention was completed based on these findings.

[0045] The present disclosure will be described below.

[0046] According to one aspect of the present disclosure, a first step (S1) of acquiring a vehicle model in which a two-wheeled vehicle is modeled into a model having a center of gravity (2f) of a front body, a center of gravity (2r) of a rear body, a center of gravity (1f) of a front tire (FT) including a front tire body (104f) and a front suspension (106f), and a center of gravity (1r) of a rear tire (RT) including a rear tire body (104r) and a rear suspension (106r), and a vehicle model (MDL) is acquired under the condition that an action term indicating the sum of the action forces acting on each of the centers of gravity and an inertia term indicating the sum of the inertial forces acting on each of the centers of gravity are balanced. The present invention provides a method for modeling a motorcycle stable driving control system, the method including: a second step (S2, S3) of creating a linear equation of motion for the vehicle; a third step (S4) of converting the linear equation of motion into a state equation; a fourth step (S5, S6) of acquiring a feedback gain capable of stabilizing the driving of the vehicle model at speeds within a predetermined speed range by a root locus analysis of the state equation; and a fifth step (S7) of creating a model (180) of the motorcycle stable driving control system that performs negative feedback control using the feedback gain acquired in the fourth step.

[0047] According to another aspect of the present disclosure, there is provided a motorcycle stable driving simulator (40) having a signal processing device (44) that performs signal processing for obtaining a feedback gain in the fourth step of the modeling method for a motorcycle stable driving control system of the one aspect described above, an input interface (42) that inputs design parameters of a vehicle model and driving condition parameters of the vehicle model to the signal processing device, and an output interface (46) that outputs information on the behavior of the vehicle model with respect to the parameters input from the input interface.

[0048] According to another aspect of the present disclosure, there is provided a program (32) for causing a computer to operate as the two-wheeled vehicle stable driving simulator of the other aspect described above.

[0049] According to yet another aspect of the present disclosure, there is provided a motorcycle stability control system (190) including: a real motorcycle (300); a power steering unit (312) attached to the real motorcycle and including as a component a steering torque actuator (310) that generates a steering torque in the motorcycle; a measurement unit (350) that performs measurement processing based on outputs of a plurality of sensor units (301, 303, 305, 307, 308, 311, 313) attached to the real motorcycle; and a power steering control unit (403) attached to the motorcycle and having a steering torque actuator control signal generation unit (408) that generates a control signal for the steering torque actuator based on the output of the measurement unit.

[0050] According to still another aspect of the present disclosure, there is provided a motorcycle stability control device (402) functioning as a power steering control unit (403) in the above motorcycle stability control system. Effect of the Invention

[0051] According to the present invention, it is possible to provide a versatile motorcycle stable running control technology that can multifacetedly and scientifically verify the running stability of a motorcycle that has complex nonlinear behavior, in other words, a method for modeling a motorcycle stable running control system, a motorcycle stable running simulator, a program, a motorcycle stable running control system, and a motorcycle stable running control device, etc. [Brief description of the drawings]

[0052] [Figure 1] FIG. 2 is a diagram showing an example of the configuration of a computer system and a motorcycle stable driving simulator. [Diagram 2] FIG. 2 is a diagram showing an example of a basic configuration of a vehicle model of a two-wheeled vehicle. [Diagram 3] 1A to 1C are diagrams illustrating an example of a procedure for a modeling method of a motorcycle stable driving control system and an example of a procedure for constructing the motorcycle stable driving control system. [Figure 4]1A and 1B are diagrams showing a specific example of a configuration of a vehicle model of a two-wheeled vehicle, and an example in which the velocity and angular velocity at each of a plurality of centers of gravity are displayed by vectors. [Diagram 5] 11 is a diagram showing the velocity, angular velocity, acceleration, angular acceleration, acting force, and acting torque of each center of gravity in a vehicle model of a two-wheeled vehicle. FIG. [Figure 6] 11 is a diagram showing an example of a definition of a generalized speed in a vehicle model of a two-wheeled vehicle, and a method of linearizing a function using a Jacobian at the generalized speed. FIG. [Figure 7] FIG. 13 is a diagram showing linearized action terms in a vehicle model of a two-wheeled vehicle. [Figure 8] FIG. 13 is a diagram showing linearized inertia terms in a vehicle model of a two-wheeled vehicle. [Figure 9] FIG. 13 is a diagram showing an overview of a method for creating a Kane equation of motion for a motorcycle vehicle model using the principle of virtual power, converting the equation of motion into a state equation, determining appropriate feedback gains by root locus analysis, and obtaining a model of a motorcycle stable driving control system. [Figure 10] 11A and 11B are diagrams showing an example of a simulation result regarding the running stability of a two-wheeled vehicle when the present invention is applied to the two-wheeled vehicle running straight ahead. [Figure 11] 1A and 1B are diagrams illustrating examples of a handlebar angle and a roll angle when a two-wheeled vehicle is turning. [Figure 12] FIG. 1 is a diagram showing an example of the configuration of a motorcycle stability control system using an actual motorcycle. [Figure 13] FIG. 11 is a diagram showing another example of the configuration of a motorcycle stable driving control system using an actual motorcycle. [Figure 14] FIG. 13 is a diagram showing an example of a configuration for synchronizing updating of the damping force value in the damper with measurement of the extension speed of the suspension. [Figure 15] FIG. 13 is a diagram illustrating an example of a process for synchronizing updating of the damping force value in the damper with measurement of the extension speed of the suspension. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0053] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below with reference to the accompanying drawings. The embodiments shown in the accompanying drawings are merely examples of the present invention, and the present invention is not limited to these embodiments.

[0054] <Example 1> Please refer to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of a computer system and a motorcycle stable driving simulator. Note that the motorcycle stable driving simulator may be simply referred to as a simulator.

[0055] In A-1 of FIG. 1, a computer system 10 includes a computer main unit 12, a monitor 14, a keyboard 16 and a mouse 18 as input devices, and four folders 21, 23, 26, and 28.

[0056] The folders 21 and 23 constitute a first folder 20 that is used when acquiring a state equation corresponding to a vehicle model of a two-wheeled vehicle and when modifying the state equation.

[0057] The folders 26 and 28 constitute a second folder 25 that is used when creating a model as a specification of the motorcycle stability control system by simulation using the simulator 40, and when editing the model.

[0058] The memory device 30 of the computer main body 12 stores a program 32 for operating the computer, in other words the computer system 10, as a motorcycle stable driving simulator 40 shown in A-2 of FIG. 1, in other words, a simulation program 32 for analyzing a motorcycle stable driving control system.

[0059] A state equation 22 corresponding to the motorcycle stability control system is stored in a folder 21. A folder 23 stores data 24 for the state equation.

[0060] A model 27 as a specification of the motorcycle stability control system, i.e., a program describing the specifications of the motorcycle stability control system, is stored in folder 26. When the final specifications of the motorcycle stability control system are determined as a result of analysis by simulator 40, the program describing the final specifications becomes a so-called "moving specification" in model-based development or model-based design of a motorcycle.

[0061] In the folder 28, editing software 29 for the model 27 is stored.

[0062] In A-2 of FIG. 1, a two-wheeler stable driving simulator 40 includes a signal processing device 44 for feedback gain analysis based on a state equation, an input interface 42 for inputting design parameters of a vehicle model and driving condition parameters of the vehicle model to the signal processing device 44, and an output interface 46 for outputting information on the behavior of the vehicle model with respect to the parameters input from the input interface 42.

[0063] Next, reference is made to Fig. 2. Fig. 2 is a diagram showing an example of the basic configuration of a vehicle model of a two-wheeled vehicle. In Fig. 2, the X direction indicates the forward direction or the traveling direction, the Y direction indicates the lateral direction, and the Z direction indicates the up-down direction or the height direction.

[0064] A-1 in Fig. 2 shows a schematic example of a conventional vehicle model having one center of gravity. In A-1 in Fig. 2, the vehicle model of a two-wheeled vehicle has a front wheel 17, a body 15, and a rear wheel 19, and one center of gravity CG is set for the entire vehicle. The vehicle model in A-1 in Fig. 2 runs on a flat road surface 3 without any bumps or irregularities.

[0065] A-2 in Fig. 2 shows a vehicle model MDL with multiple centers of gravity 1f, 2f, 1r, and 2r, which is suitable for an analysis method using multibody dynamics. Note that the rotation of the vehicle model MDL around the X-axis is called roll, the rotation around the Y-axis is called pitch, and the rotation around the Z-axis is called yaw.

[0066] The motorcycle vehicle model MDL of A-2 in Fig. 2 is roughly divided into a front portion and a rear portion. The front portion includes a handlebar 121, a steering shaft 120 as a rotation shaft of the handlebar 121, a front body 100, and a front tire FT. The rear portion includes a rear body 102 and a rear tire RT.

[0067] The front tire FT can be referred to as the front wheel or the front wheel portion, and the rear tire RT can be referred to as the rear wheel or the rear wheel portion.

[0068] The front tire FT has a pair of front suspensions FR1 and FR2, called front forks, which function as dampers, and a tire body 104f. Generally, a suspension has a damper and a spring, but the example of A-2 in Fig. 2 shows the external appearance of the front forks, and the springs are provided inside the front suspensions FR1 and FR2.

[0069] In addition, in the following description, for ease of analysis, the cushioning characteristics realized by the pair of front suspensions FR1, FR2 are treated as being realized by a single virtual front suspension 106f.

[0070] The same is true for the rear tire RT. That is, the rear tire RT has a pair of rear suspensions RSU1 and RSU2. Each of the rear suspensions RSU1 and RSU2 has a damper Dp and a suspension spring Sp. In addition, the cushioning characteristics realized by the pair of rear suspensions RSU1 and RSU2 are treated as being realized by a single virtual rear suspension 106r.

[0071] The center of gravity of the front tire FT including the front suspension 106f is denoted as 1f, and the mass of that center of gravity is denoted as m1f. The center of gravity of the front body 100 is denoted as 2f, and the mass of the center of gravity is denoted as m2f. The center of gravity of the rear tire RT including the rear suspension 106r is denoted as 1r, and the mass of that center of gravity is denoted as m1r. The center of gravity of the rear body 102 is denoted as 2r, and the mass of the center of gravity is denoted as m2r.

[0072] Moreover, the vehicle model MDL is assumed to travel on an uneven road surface 4.

[0073] 2, the handlebar 121 is shown in the Z-axis direction, i.e., as viewed from above. With the handlebar position when the two-wheeled vehicle is moving straight in the X direction as a reference, it is assumed that the handlebar 121 has rotated a predetermined angle, for example, clockwise, around the steering axis 120. In this case, the predetermined angle is defined as the handlebar angle θhd.

[0074] Next, a method for model-based development of a motorcycle stable driving control system will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of a procedure for a modeling method of a motorcycle stable driving control system and an example of a procedure for constructing the motorcycle stable driving control system.

[0075] In step 1, the motorcycle is modeled as a multibody model including a front suspension and a rear suspension. In other words, this motorcycle model can be said to be a model that has multiple centers of gravity and includes rigid bodies and elastic or flexible bodies. An example of the outline of the model is shown in A-2 of FIG. 2. A specific example of the model will be described later with reference to FIG. 4.

[0076] In step S2, the vehicle's equation of motion is created. In the preferred embodiment of the present invention, the Kane's equation of motion is used.

[0077] Kane's equations of motion are equations of motion that assume a virtual displacement in the generalized velocity direction and are derived based on the principle of virtual power by focusing on the point where the action force and action torque acting on an object are balanced with the inertial force and inertial torque. In the Kane equations of motion, inertial terms and nonlinear terms can be expressed using a type of unit vector called a partial velocity, making it easier to create the equations of motion.

[0078] The generalized velocity can be explained as, for example, the velocity or angular velocity in a generalized coordinate system, in which the velocity or angular velocity of any position of an object can be expressed in only one way as a sum of linear functions.

[0079] However, at the stage of step S2, the equation of motion includes a second-order nonlinear term.

[0080] In step S3, the equation of motion of the vehicle is linearized. Specifically, for example, linearization can be achieved by multiplying a function expressed by a vector by a Jacobian matrix that functions as a differential operator, in other words, a Jacobian. As the Jacobian, it is preferable to use a Jacobian at a generalized speed. This will be described later. Note that Taylor expansion or the like may also be used.

[0081] In step S4, the equation of motion is converted into a state equation to enable analysis using modern control theory.

[0082] In step S5, a root locus analysis of the vehicle stability is performed. Here, the root locus is a locus that the roots of the state equation trace on the complex plane when the feedback gain is changed.

[0083] For example, when the root locus is within the region of the left half of the complex plane, the feedback control system can be evaluated as stable at the feedback gain value, and when the root locus is outside the region of the left half of the complex plane, the feedback control system can be evaluated as unstable at that feedback gain value.

[0084] In step S6, a feedback gain value capable of stabilizing the vehicle at each speed when the vehicle speed is changed within a desired speed range is obtained.

[0085] In step S6, the simulator 40 shown in A-2 of FIG. 1 is used to quickly find optimal feedback gains under various conditions.

[0086] In the simulation using the simulator 40, it is preferable to perform the simulation assuming that when the rotation speed of the engine or electric motor is changed, constant torque control is performed to keep the torque of the engine or electric motor constant regardless of the rotation speed. This ensures the conditions for linearizing the equation of motion and can suppress a decrease in simulation accuracy. This will be described later.

[0087] In a preferred embodiment, the desired speed range can be set to, for example, a vehicle speed of 1 m / s to 60 m / s, taking into consideration the actual traveling speed of an actual two-wheeled vehicle.

[0088] In step S7, a model is obtained as a specification for the motorcycle stability control system. When a feedback gain capable of ensuring vehicle stability at all speeds within the desired speed range is obtained by the analysis using the simulator in step S6, the state of the motorcycle stability control system in which the feedback gain is obtained is uniquely determined. This becomes a program called a "moving specification," in other words, a model as a specification for the motorcycle stability control system.

[0089] In step S8, for example, a sensor unit, a power steering unit, and a control signal generation unit for a steering torque actuator are implemented in the actual motorcycle to be controlled, i.e., the actual vehicle, and a motorcycle stable driving control system is constructed as a negative feedback control system that realizes the feedback gain acquired in step S6. An example of the constructed motorcycle stable driving control system will be described later with reference to Figs. 12 and 13.

[0090] Next, reference is made to Fig. 4. This is a diagram showing a specific example of the configuration of a vehicle model of a two-wheeled vehicle, and an example in which the speed and angular velocity at each of a number of centers of gravity are displayed by vectors. In A-1 of Fig. 4, parts common to A-2 of Fig. 2 are given the same reference numerals. This also applies to Figs. 5 and 6. Also, in A-1 of Fig. 4, for the sake of convenience, the illustration of the handle is omitted. This also applies to Figs. 5 and 6.

[0091] As explained earlier, the center of gravity of the front tire FT is 1f, the mass of the center of gravity 1f is m1f, the center of gravity of the front body 100 is 2f, the mass of the center of gravity 2f is m2f, the center of gravity of the rear tire RT is 1r, the mass of the center of gravity 1r is m1r, the center of gravity of the rear body 102 is 2r, and the mass of the center of gravity 2r is m2r.

[0092] In A-1 of Fig. 4, the front body 100 and the rear body 102 are treated as rigid bodies. In addition, in a typical actual motorcycle, the tire body is composed of a rim located on the inside, which is considered to be a rigid body, and an elastically deformable pneumatic tube and the like located on the outside. When modeling the tire body, taking into account the three-dimensional elastic deformation characteristic of the tire body, it can be treated as an elastic body or a flexible body for convenience.

[0093] Therefore, the front tire body 104f included in the front tire FT and the rear tire body 104r included in the rear tire RT are modeled as having at least a portion thereof being elastic or flexible, assuming that they are capable of elastic deformation.

[0094] In a preferred embodiment, the front tire body 104f and the rear tire body 104r can be modeled using the Magic Formula equation.

[0095] The magic formula is an equation obtained by identifying the values ​​of parameters that indicate the characteristics of a tire based on experimental data obtained by a tire testing machine, and is an equation that expresses the force and torque reaction force of the tire from the road surface using trigonometric functions, etc.

[0096] Reference numeral 105f denotes a spring that represents the elasticity characteristic of the front tire body 104f.

[0097] The front suspension 106f includes a spring 110f, in other words, a suspension spring 110f, and a front damper 108f. The symbol FU indicates an upper point of the front suspension 106f. The front damper may be simply called a damper.

[0098] Reference numeral 105r denotes a spring that represents the elastic characteristic of the rear tire body 104r.

[0099] The rear suspension 106r includes a spring 110r, in other words, a suspension spring 110r, and a rear damper 108r. The suspension spring 110r corresponds to the spring Sp shown in A-2 of FIG. 2. The rear damper may simply be called a damper. The symbol RU indicates an upper point of the rear suspension 106r.

[0100] Further, the caster angle θcas of the steering shaft 120 is determined so that the steering shaft 120 and the rear vehicle body axis 122 are perpendicular to each other.

[0101] As a result, the vector VSf of the vibration component that reflects the damping characteristics of the front suspension 106f, which occurs in the extension direction of the steering shaft 120, and the vector VSr of the vibration component that reflects the damping characteristics of the rear suspension 106r, which occurs in the extension direction of the rear body axle 122, are perpendicular to each other, and the inner product of each vector becomes zero, so that the vectors do not interfere with each other and can be treated as independent. Therefore, the vibration component caused by the front suspension 106f and the vibration component caused by the rear suspension 106r can be treated independently, making analysis easier.

[0102] In A-1 of Figure 4, symbol A indicates the contact point between the rear tire RT and the ground, symbol B indicates the contact point between the front tire FT and the ground, symbol B' indicates the intersection point between the steering axis 120 and the ground, and symbol C indicates the intersection point between the rear body axis 122 and the steering axis 120.

[0103] Moreover, the front vehicle body 100 rotates around the axis CB' when viewed from the rear vehicle body 102, and the front tire body 104f and the rear tire body 104r are each considered to rotate. Moreover, the front tire body 104f and the rear tire body 104r are each considered to be in contact with the ground at one point, the above-mentioned point A and point B.

[0104] See A-2 in Figure 4. In the figure, v indicates velocity and w indicates angular velocity. Since these velocities and angular velocities act on each of the centers of gravity 1f, 2f, 1r, and 2f, in order to distinguish which center of gravity the velocity and the like act on, for example, the velocity and angular velocity for center of gravity 1f are written as v1f and w1f. Similar notations are used for the other centers of gravity.

[0105] Furthermore, u, v, and w are coordinate axes of generalized velocity in the generalized coordinate system, which correspond to the Cartesian coordinate axes X, Y, and Z in the three-dimensional space, respectively.

[0106] Furthermore, p, q, and r are coordinate axes of a generalized angular velocity in a generalized coordinate system corresponding to the orthogonal coordinate axes X, Y, and Z in three-dimensional space, respectively. In A-2 of FIG. 4, the velocity v2r about the center of gravity m2r is expressed as a function of u, v, and w, and the angular velocity w2r is expressed as a function of p, q, and r. The same is true for the other centers of gravity m2f, m1r, and m1f, but in order to distinguish which center of gravity the velocity and angular velocity refer to, the signs of each center of gravity are added to u, v, w, and p, q, and r. The same is true for the velocity and angular velocity of the model MDL as a whole, but in order to distinguish them from the velocities and angular velocities of the four centers of gravity, the velocities and angular velocities of the model MDL are indicated by adding the symbol mdl to each of u, v, w and p, q, and r.

[0107] In addition, each of the centers of gravity 1f, 2f, 1r, and 2f is bound by predetermined constraint conditions and behaves as a single moving body. Therefore, a state in which the velocity and angular velocity shown in A-2 of FIG. 4 are acting on each center of gravity means that the velocity vmdl and angular velocity wmdl are acting on the vehicle model MDL, and the two are equivalent.

[0108] For example, when using the expression "the velocity of the vehicle model MDL," this "velocity of the vehicle model MDL" is uniquely determined by calculation of each vector of the velocities v1f, v2f, v1r, and v2r acting on each center of gravity 1f, 2f, 1r, and 2r included in the vehicle model MDL.

[0109] Therefore, observing or measuring the "velocity of the vehicle model MDL" is synonymous with observing or measuring the "velocity of each center of gravity." This also applies to the angular velocity. In addition, the term "observation" is used for the analysis of a model of a motorcycle stability control system constructed on a computer, and the term "measurement" is used for the analysis of a motorcycle stability control system applied to an actual motorcycle.

[0110] For example, in Figs. 12 and 13 described later, when measuring the "vehicle speed of an actual two-wheeled vehicle," the "vehicle speed at points corresponding to each center of gravity of the actual two-wheeled vehicle" is measured.

[0111] Next, reference is made to Fig. 5. Fig. 5 is a diagram showing the velocity, angular velocity, acceleration, angular acceleration, acting force, and acting torque of each center of gravity in a vehicle model of a two-wheeled vehicle. In Fig. 5, parts common to Fig. 4 are given the same reference numerals.

[0112] A-1 in FIG. 5 shows a simplified configuration of A-1 in FIG.

[0113] In A-2 of FIG. 5, the velocities and angular velocities of the masses m1r, m2r, m1f, and m2f at the centers of gravity are shown in tabular form.

[0114] As described above, each of the velocities v1r, v2r, v2f, and v1f in A-2 of Fig. 5 corresponds to the velocity of the vehicle or the vehicle model. Similarly, each of the angular velocities w1r, w2r, w2f, and w1f corresponds to the angular velocity of the vehicle or the vehicle model.

[0115] Additionally, the speed v1r reflects the extension speed of the rear suspension, v1f reflects the extension speed of the front suspension, and w2f reflects the steering wheel angular velocity.

[0116] In A-3 of FIG. 5, the acceleration and angular acceleration at the masses m1r, m2r, m1f, and m2f of the centers of gravity are shown in tabular form.

[0117] In A-4 of Figure 5, the acting forces and torques at the masses m1r, m2r, m1f, and m2f of the centers of gravity are shown in table form. T2r and T2f are acting torques that reflect the input of the handle torque.

[0118] Next, reference is made to Fig. 6. Fig. 6 is a diagram showing an example of the definition of a generalized speed in a vehicle model of a two-wheeled vehicle, and a linearization method of a function using a Jacobian at the generalized speed.

[0119] A-1 in FIG. 6 is the same as A-1 in FIG.

[0120] A-2 in FIG. 6 is a diagram showing an example of a definition of a generalized speed for the vehicle model MDL of the two-wheeled vehicle shown in A-1 in FIG.

[0121] As shown in A-2 of FIG. 6, the generalized speed of the vehicle model MDL is defined to include a plurality of speed components related to the speed in the direction of movement of the vehicle.

[0122] For example, assuming that a real vehicle is moving forward on a road surface, the speed is usually measured by a speedometer provided on the vehicle solely based on, for example, the number of tire revolutions.

[0123] However, when observing the vehicle speed microscopically in more detail, various force components acting on the vehicle must be taken into consideration.

[0124] For example, the moment generated by turning the steering wheel also contributes to moving the vehicle forward, and the vibration component generated by the extension of the suspension also contributes to moving the vehicle forward.

[0125] From this perspective, in A-2 of Figure 6, a function is created by incorporating as many variables as possible of the various speed components related to the speed in the vehicle's direction of movement, and a generalized speed is defined using this function, making it possible to analyze the behavior of a motorcycle in the direction of vehicle movement in more detail.

[0126] In A-2 of Fig. 6, a function Gen is defined that includes as parameters the velocity v2r about the u, v, and w axes, the angular velocity w2r about the p, q, and r axes, the steering wheel angular velocity, the rear suspension extension velocity, the front suspension extension velocity, the angular velocity w1r of the rear tires, and the angular velocity w1f of the front tires, all of which act on the mass m2r of the center of gravity 2r of the rear body. Here, this function Gen is defined as the vehicle model MDL, or the generalized velocity of the actual vehicle.

[0127] As described above, the equation of motion is linearized in step S3 in Fig. 3. In this case, linearization is performed by multiplying a function including a nonlinear term expressed by a vector by the Jacobian, which is a differential operator.

[0128] At this time, under the condition that the generalized speed of the above vehicle model is constant and does not fluctuate over a very short period of time, an operation is performed to multiply the function by the Jacobian, thereby making it possible to perform a first-order approximation, in other words, a linear approximation of the nonlinear terms.

[0129] Therefore, when linearizing the equation of motion, it is necessary to ensure that the generalized speed of the vehicle model, which is a prerequisite for linear approximation, is constant and does not fluctuate over a very short period of time.

[0130] This point is also applicable when the present invention is applied to an actual motorcycle. For this purpose, it is effective to implement constant torque control that controls the torque of the engine or electric motor of the actual vehicle to a constant value regardless of the rotation speed, and to minimize the fluctuation of each component related to the speed in the direction of vehicle movement. This makes it possible to suppress a decrease in the accuracy of stable running control of the motorcycle.

[0131] A-3 in Fig. 6 shows an example of an expression of multiplying a function by a Jacobian. That is, the operation of multiplying a function f by a Jacobian at the above generalized speed is expressed as Y(f,Gen).

[0132] Next, reference is made to Fig. 7. Fig. 7 is a diagram showing linearized action terms in a vehicle model of a two-wheeled vehicle.

[0133] A-1 in FIG. 7 is the same as A-1 in FIG.

[0134] In A-2 of FIG. 7, the forces and torques acting on the masses m1r, m2r, m2f, and m1f of the centers of gravity 1r, 2r, 2f, and 1f are shown in a table.

[0135] A-3 in Figure 7 is a reprint of the table in A-2 in Figure 5.

[0136] 7A-4 shows, as an example, that the action term for mass m1f can be expressed by adding up the action force F1r and the action torque T1r. The same is true for the other masses.

[0137] In A-5 of Figure 7, as an example, an equation showing the action term at generalized velocity for mass m1f is shown. In this equation, the expression showing the operation of multiplying a function by a Jacobian, shown in A-3 of Figure 6, is adopted. The same applies to other masses.

[0138] As shown in A-6 of FIG. 7, the linearized action term of the vehicle model, in other words, the linearized action term of the vehicle, can be calculated by adding up the action terms for each mass, in other words, taking the dot product of each vector.

[0139] Reference is now made to Figure 8, which shows the linearized inertia terms in a vehicle model of a two-wheeled vehicle.

[0140] A-1 in Figure 8 is a reprint of the table A-3 in Figure 5.

[0141] A-2 in Fig. 8 shows the inertial force for acceleration at each center of gravity 1r, 2r, 1f, and 2f, in other words, the inertial force of linear motion. The inertial force of linear motion can be expressed using the inner product of vectors according to the well-known Newton's equation of motion.

[0142] A-3 in Figure 8 is a reprint of the table in A-2 in Figure 5.

[0143] A-4 in Fig. 8 shows the inertial force for angular acceleration at each center of gravity 1r, 2r, 1f, and 2f, in other words, the inertial force of rotational motion. The inertial force of rotational motion can be expressed using the moment of inertia tensor of each center of gravity and the cross product of a vector according to the well-known Euler's equation of motion.

[0144] A-5 in Fig. 8 shows a method for calculating the inertia term of the vehicle model, in other words, the inertia term of the vehicle model. At the generalized speed previously shown in A-2 in Fig. 6, the function indicating the inertia force for the angular acceleration of each center of gravity obtained in A-4 in Fig. 8 is multiplied by a Jacobian to calculate the linearized inertia force of each center of gravity, and the linearized inertia forces of each center of gravity thus obtained are added, that is, an inner product of vectors is taken, thereby making it possible to calculate the linearized inertia term of the vehicle model, in other words, the linearized inertia term of the vehicle.

[0145] Next, reference will be made to Fig. 9. Fig. 9 is a diagram showing an overview of a method for creating a Kane's equation of motion for a motorcycle vehicle model using the principle of virtual power, converting the equation of motion into a state equation, determining appropriate feedback gains by root locus analysis, and acquiring a model of a motorcycle stable driving control system.

[0146] A-1 in Figure 9 shows the Kane equation of motion using the principle of virtual power. According to the principle of virtual power, the action term and the inertia term acting on an object are balanced, so the Kane equation of motion can be created using this relationship.

[0147] By solving the Kane equation of motion, the coefficient for the virtual displacement in the generalized velocity direction can be determined unambiguously. Since the Kane equation of motion is a linear equation of motion, it can be converted into a state equation, which is a first-order simultaneous differential equation.

[0148] A-2 in Fig. 9 shows the form of the state equation used in the present invention. In the state equation in A-2 in Fig. 9, x is a state variable, u is an input, y is an output, A and B are determinants related to the input characteristics of the system, and C is a determinant related to the output characteristics of the system.

[0149] A-3 in Fig. 9 is a block diagram showing the state equation shown in A-2 in Fig. 9. As can be seen from this block diagram, the state equation shown in A-2 in Fig. 9 shows a feedback control system having a feedback path with a feedback gain A. Here, if the feedback gain can be appropriately adjusted, it is possible to construct a negative feedback control system capable of converging input fluctuations within a predetermined time, in other words, a negative feedback control system having stable controllability.

[0150] If the feedback gain is not appropriate, the input will diverge and it will be impossible to construct a negative feedback control system.

[0151] A-4 in Fig. 9 shows that the root locus method is effective for obtaining an appropriate feedback gain, in other words, for analyzing control stability. The root locus is the locus of the roots of the state equation on the complex plane when the feedback gain is changed. For example, when the root locus is within the region of the left half of the complex plane, the feedback control system can be evaluated as stable at the feedback gain value, and when the root locus is outside the region of the left half of the complex plane, the feedback control system can be evaluated as unstable at that feedback gain value.

[0152] A-4 in Fig. 9 shows that linear optimal control LQR (Linear Quadratic Regulation) can be used as a specific method for finding an appropriate feedback gain. Specifically, a solution to the Riccatti equation is found to obtain a control input that can quickly converge the fluctuation of the state variable.

[0153] In this embodiment, the vehicle speed is changed from 1 m / s to 60 m / s, for example, in increments of 1 m / s, and the optimal feedback gain is obtained for each speed. Once the optimal feedback gain is obtained, it can be used to obtain a model of a stable motorcycle driving system that allows a motorcycle to travel stably.

[0154] A-5 in FIG. 9 shows an example of the configuration of the obtained model of the two-wheeled vehicle stable driving system.

[0155] Model 180 of the two-wheeled vehicle stable driving system has model MOD1 of the two-wheeled vehicle system which is the controlled object, model MOD2 of an input system which inputs input variables to model MOD1 of the two-wheeled vehicle system, model MOD3 of an output system which outputs output variables from model MOD1 of the two-wheeled vehicle system, and model MOD4 of a feedback system which changes the values ​​of the input variables in model MOD2 of the input system by feedback using the feedback gains acquired in step S6 of Figure 3 based on the output variables.

[0156] In the example of A-5 in FIG. 9, the input variable is the steering torque of a motorcycle.

[0157] Moreover, the two-wheeler system model MOD1 is a model with rear suspension / front suspension and power steering.

[0158] In other words, the model MOD1 of the motorcycle system is a two-rigid-body / two-elastic-body multibody model that includes two rigid bodies, the rear body and the front body, and two elastic bodies, at least parts of which can be considered as elastic bodies, the rear tire including the rear suspension, and the front tire including the front suspension.

[0159] Specifically, the output system model MOD3 can output, in other words, can observe, at least the vehicle speed, vehicle angular velocity, steering wheel angular velocity, and suspension extension speed. More preferably, the output system model MOD3 can output, in other words, can observe, the vehicle acceleration, vehicle angular acceleration, and steering wheel angle.

[0160] The model MOD4 of the feedback system has a function of realizing an optimal feedback gain for each speed within a predetermined speed range, in other words, a loop gain of a negative feedback loop, of a negative feedback control system that preferably allows the model MOD1 of the two-wheeled vehicle system to travel in an autonomous and stable manner.

[0161] In this way, it is possible to create model 180 of a motorcycle stable driving control system as a negative feedback control system in which the motorcycle system model MOD1 is the control target, the inputs of the motorcycle system model MOD1 include at least the steering torque u of the motorcycle, and the output y of the motorcycle system model MOD1 includes at least the speed of the vehicle model, the angular velocity of the vehicle model, the handlebar angular velocity of the handlebar included in the vehicle model, and the suspension extension speeds of each of the front suspension and rear suspension, and negative feedback control is performed using the feedback gain obtained in process A-5 of Figure 9 based on the output of the vehicle model to control the steering torque as input u of the motorcycle system model MOD1.

[0162] Next, reference is made to Fig. 10. Fig. 10 is a diagram showing an example of a simulation result regarding the running stability of a two-wheeled vehicle when the present invention is applied to the two-wheeled vehicle running straight ahead.

[0163] As explained above, the control stability of a motorcycle system can be analyzed by the root locus of the state equation. The root locus is the locus that the roots of the state equation trace on a complex plane when the feedback gain is changed, and the feedback control system can be evaluated as stable at a feedback gain value when the root locus is within a stable region on the left half of the complex plane, and the feedback control system can be evaluated as unstable at that feedback gain value when the root locus is outside the region on the left half of the complex plane, i.e., when it enters an unstable region.

[0164] In FIG. 10, the unpatterned region Z1 is a stable region on the complex plane, and the shaded region Z2 is an unstable region on the complex plane.

[0165] In Fig. 10, the vehicle speed of a motorcycle model is changed from 1 m / s to 60 m / s, the root locus corresponding to each vehicle speed is obtained, and the results are plotted on a complex plane. In Fig. 10, the root locus is represented by discrete points or a line consisting of continuous points.

[0166] Furthermore, prior analysis by the inventors based on the root locus has revealed that if negative feedback control is not implemented at all, the root locus will be in the unstable region Z2 within vehicle speed ranges of 1 m / s to 7.2 m / s and 14.2 m / s to 60 m / s, resulting in reduced driving stability.

[0167] As can be seen from Fig. 10, the root locus when the present invention is applied is within the stable region Z1 and does not enter the unstable region Z2 within the entire range of vehicle speeds from 1 m / s to 60 m / s. In other words, the running stability of a straight-traveling motorcycle can be ensured within the entire range of vehicle speeds.

[0168] Next, reference is made to Fig. 11. Fig. 11 is a diagram showing an example of the handlebar angle and roll angle when a two-wheeled vehicle is turning.

[0169] Even when a two-wheeled vehicle is turning, the feedback gain required for stable running can be found using the same method as that explained using Figures 2 to 9. However, the state equation applied when a two-wheeled vehicle is turning is not the same as the state equation applied when a two-wheeled vehicle is running in a straight line.

[0170] In other words, the state equation that applies when a motorcycle is traveling in a straight line needs to be transformed to take into account the changes in state when the motorcycle is turning, or new terms need to be added to create a form suitable for analyzing the state of a motorcycle when turning.

[0171] In Fig. 11, we consider how to modify the state equation. A-1 in Fig. 11 shows a state in which the motorcycle model shown in A-2 in Fig. 2 is turning right, as viewed from the Z-axis direction. For ease of explanation, the motorcycle model is shown in a simplified form in A-1 in Fig. 11. The handlebars are not shown in A-1 in Fig. 11.

[0172] Also, A-2 in FIG. 11 shows a front view of the two-wheeled vehicle model in the state of A-1 in FIG. 11, as viewed from the X-axis direction.

[0173] In A-1 and A-2 of Fig. 11, the same reference numerals are used for the parts common to A-2 of Fig. 2. As shown in A-2 of Fig. 11, when a motorcycle turns, the body of the motorcycle tilts as it turns. The roll angle at this time is defined as θrol.

[0174] Let's take motorcycles as an example. Normally, motorcycles are equipped with a self-steering mechanism that allows the handlebars, or steering, to turn in the direction the body is tilted without the rider being aware of it.

[0175] When a motorcycle turns, the steering wheel turns inward due to self-steering, and the inward lateral force generated by the camber angle of the tire, i.e. the camber thrust force, allows the motorcycle to turn smoothly. However, depending on the turning condition, a turning force due to the slip angle may also come into play.

[0176] In A-1 of Figure 11, the motorcycle is turning to the right at a handlebar angle θhd. At this time, a lateral force Lf as indicated by the thick arrow is generated in the front tire FT in the direction opposite to the centrifugal force, and a lateral force Lr as indicated by the thick arrow is generated in the rear tire FT in the direction opposite to the centrifugal force.

[0177] Therefore, when analyzing the driving stability of a motorcycle when it is turning, it is necessary to determine the speed, angular velocity, acceleration, angular acceleration, acting force, and acting torque of the four centers of gravity 1f, 1r, 2f, 2r, taking into consideration, for example, the influence of the lateral force Lf generated on the rear tire FT and the lateral force Lr acting on the front tire RT, as well as the centrifugal force and wind force generated when turning.

[0178] In addition, when the motorcycle is turning, for example, the roll angle θrol and the like must be observed or measured, and the number of variables to be considered increases. As a result, it is necessary to add terms to the state equation or update the coefficient values ​​to values ​​different from those when traveling in a straight line.

[0179] If a state equation suitable for analyzing the stability of a motorcycle when cornering is obtained, the feedback gain required for stable driving can be found for all speeds within a predetermined speed range using the same method as previously explained with reference to Figures 2 to 9. Thus, a model of a stable driving control system for a motorcycle that also handles cornering can be obtained.

[0180] Next, reference will be made to Fig. 12. Fig. 12 is a diagram showing an example of the configuration of a stable running control system for a motorcycle using an actual motorcycle.

[0181] The two-wheeler stable driving control system 190 using an actual two-wheeler has a two-wheeler body 300, and, which are provided on the two-wheeler body 300, a rear tire sensor unit 301, a rear suspension sensor unit 303, a rear body sensor unit 305, a front body sensor unit 307, a handlebar sensor unit 308, a power steering unit 312, a front suspension sensor unit 311, a front tire sensor unit 313, an engine control unit 315, a measurement unit 350, and an ECU (Electronic Control Unit) 400 as an electronic control device.

[0182] The power steering unit 312 includes a steering torque sensor 309 and a steering torque actuator 310 .

[0183] The engine control section 315 has a constant torque control section 317 that controls the output of the engine or electric motor 319, that is, the torque of the engine or electric motor 319, to be constant.

[0184] The torque of the engine or electric motor 319 affects the moment acting on each of the four centers of gravity described above. If the torque of the engine or electric motor, i.e., the moment, varies with a change in the rotation speed of the engine or electric motor 319, i.e., a change in the vehicle speed of the two-wheeled vehicle, it also affects the generalized speed shown in A-2 of Fig. 6, and the error associated with the linearization of the equation of motion increases, which is one of the causes of a decrease in the control accuracy of the negative feedback control. Therefore, constant torque control is implemented to stabilize the output of the engine or electric motor 319 and suppress a decrease in the control accuracy of the negative feedback control.

[0185] The rear tire sensor unit 301 detects the rear tire speed and the rear tire angular velocity, and supplies the detection signals to the measurement unit 350. However, a 6-axis MEMS (Micro Electro Mechanical Systems) sensor or the like may also be used to detect the rear tire acceleration and the rear tire angular acceleration.

[0186] The rear suspension sensor unit 303 detects the extension speed of the rear suspension and supplies the detection signal to the measurement unit 350 .

[0187] The rear body sensor unit 305 detects the rear body speed and the rear body angular velocity, and supplies the detection signals to the measurement unit 350. However, for example, a 6-axis MEMS sensor or the like may be used to detect the rear body acceleration and the rear body angular acceleration as well.

[0188] The front body sensor unit 307 detects the front body speed and the front body angular velocity, and supplies the detection signals to the measurement unit 350. However, for example, a 6-axis MEMS sensor or the like may be used to detect the front body acceleration and the front body angular acceleration as well.

[0189] The steering wheel sensor unit 308 detects the steering wheel angle and steering wheel angular velocity, and supplies the detection signals to the measurement unit 350. However, for example, a six-axis MEMS sensor or the like may be used to detect the steering wheel acceleration and steering wheel angular acceleration as well.

[0190] The power steering unit 312 detects the steering torque applied to the periphery of the steering shaft, for example, the handle torque or the steering torque related to the steering shaft, using a steering torque sensor 309, and supplies the detection signal to the measurement unit 350. As the steering torque sensor 309, for example, a torsion bar sensor can be used.

[0191] Moreover, the steering torque actuator 310 included in the power steering unit 312 can be configured, for example, by a torsion bar actuator, a magnetostrictive actuator, or the like.

[0192] The steering torque actuator 310 is operated by a steering torque actuator control signal DCT that is generated and output by a steering torque actuator control signal generating unit 408 (described later) provided in the ECU 400, and applies the torque required to prevent the two-wheeled vehicle from tipping over, i.e., an anti-tip-over moment, to the handlebars, steering shaft, etc.

[0193] The front suspension sensor unit 311 detects the extension speed of the front suspension, and supplies the detection signal to the measurement unit 350 .

[0194] Front tire sensor unit 313 detects the front tire speed and the front tire angular velocity, and supplies detection signals to measurement unit 350. However, a six-axis MEMS sensor or the like may also be used to detect the front tire acceleration and the front tire angular acceleration.

[0195] The measuring unit 350 amplifies various detection signals input thereto, and then performs A / D conversion and sampling.

[0196] In addition, in FIG. 12, in the measurement unit 350, the output corresponding to the input of various detection signals other than the steering torque detection signal is represented as y(t), and the output corresponding to the input of the steering torque detection signal is represented as s(t).

[0197] y(t) is the "various sensor signal values" that vary with time, and s(t) is the "steering torque value" around the steering axis of the motorcycle that varies with time.

[0198] The ECU 400 has a microcomputer 402 and a power steering control unit 403 provided in the microcomputer 402. The microcomputer 402 functions as a two-wheeled vehicle stable running control device.

[0199] The power steering control section 403 includes an error detection section 406 including a comparison section 407 , and a steering torque actuator control signal generation section 408 .

[0200] Here, a comparison unit 407 included in the error detection unit 406 compares the steering torque value S(t) sent from the measurement unit 350 with a target value sd of the negative feedback control, and outputs the difference as an error e(t). The error e(t) can be expressed as sd-s(t).

[0201] The steering torque actuator control signal generation unit 408 includes a generalized velocity calculation unit 410 and a steering torque actuator control signal calculation unit 412 .

[0202] 6, the generalized speed GEN is defined by a function including multiple speed components related to the moving direction of the two-wheeled vehicle. The generalized speed calculation unit 410 calculates the current generalized speed of the vehicle based on the various sensor signal values ​​y(t) sent from the measurement unit 350.

[0203] When the current generalized speed is calculated, the coefficient k corresponding to the optimal feedback gain corresponding to the calculated generalized speed is uniquely determined. That is, as described above, under the condition that the generalized speed is constant and does not fluctuate in an extremely short time, the nonlinear equation of motion that indicates the behavior of the vehicle is linearized. That is, the feedback gain at the generalized speed is determined by linearly approximating a quadratic function to a linear equation, converting the equation into a state equation, and solving the state equation to obtain an eigenvalue. The coefficient corresponding to this feedback gain is the coefficient k shown in FIG. 12.

[0204] Once the coefficient k is determined, the steering torque actuator control signal calculation unit 412 obtains a control input u(t) as a steering torque actuator control signal by multiplying the error e(t) (=(sd-s(t)) by the coefficient k. This control input u(t) causes the motorcycle stable driving control system 190 to function as a negative feedback control system, and is a control input that can quickly converge, within a predetermined time, any fluctuations that occur in the steering torque, which is an input to the system 190.

[0205] This control input u(t) is given to a steering torque actuator 310 included in a power steering unit 312, which performs negative feedback control and achieves stable running of the two-wheeled vehicle.

[0206] <Example 2> Next, reference is made to Fig. 13. Fig. 13 is a diagram showing another example of the configuration of a motorcycle stable driving control system using an actual motorcycle. In Fig. 13, the same reference numerals are used to designate the same parts as in Fig. 12.

[0207] In the example of FIG. 13, it is assumed that the damping force is variably controlled in at least one of a front suspension 106f included in a front tire FT of a motorcycle and a rear suspension 106r included in a rear tire RT.

[0208] In other words, for example, electronic variable damping force control is implemented in at least one of the dampers of the front suspension 106f and the dampers of the rear suspension 106r.

[0209] At this time, in a damper in which the damping force is variably controlled, the damping force value is updated when the spring included in the suspension is fully compressed, and as for measurement of the extension speed of the suspension, the suspension extension speed is measured in synchronization with the update of the damping force value, thereby synchronizing the update of the damping force value with the measurement of the extension speed of the suspension.

[0210] Possible modes of variably controlling the damping force of a damper in a suspension include a mode in which the damping force value is set lower than normal, or conversely, a mode in which the damping force value is set higher than normal, or a mode in which variable damping force control by process is implemented, in which the damping force value generated is switched between the compression process and the extension process of the spring.

[0211] In either case, the damping characteristics of the suspension change as the damping force value is updated, and this change in damping characteristics is highly likely to affect the overall behavior of the two-wheeled vehicle.

[0212] Therefore, it is preferable to accurately measure the suspension extension speed in synchronization with the update of the damping characteristics of the suspension, and to accurately reflect the change in the suspension extension speed accompanying the update of the damping characteristics in the stable driving control of the motorcycle, thereby further improving the accuracy of the stable driving control of the motorcycle.

[0213] 13, a notification signal TM of the timing to update the damping force value is supplied to the measurement unit 350 from each of the rear suspension sensor unit 303 and the front suspension sensor unit 311. The other configurations are the same as those in the example of FIG.

[0214] 13, the measurement unit 350 synchronizes the sampling period by A / D conversion of at least one of the rear suspension extension speed and the front suspension extension speed, in other words, the start timing of the period during which the suspension extension speed can be measured, with the damping direct value update timing. This makes it possible to accurately measure and observe the suspension extension speed, which corresponds to the change in the damping force characteristics due to the update of the damper's damping force value.

[0215] The above-mentioned synchronization control will be specifically described below. Please refer to Fig. 14. Fig. 14 is a diagram showing an example of a configuration for synchronizing the updating of the damping force value in the damper with the measurement of the extension speed of the suspension. In Fig. 14, the same reference numerals are used for the parts common to the previous figures.

[0216] 14 shows an example of a configuration for implementing synchronous control in a rear suspension. Note that the following description can also be applied to a front suspension.

[0217] As shown in A-2 of Figure 2, the rear suspension has a pair of rear suspensions RSU1, RSU2, each of which has the same damping force characteristics and is both electronically variable damping force control.

[0218] Each of the pair of rear suspensions RSU1, RSU2 has a spring, in other words a suspension spring Sp, and a damper Dp.

[0219] In the motorcycle model of A-1 in Fig. 4 shown above, the damper is given the symbol 108r and the spring is given the symbol 110r, but these are expedient symbols given to explain the characteristics of the modeled rear tire. In A-2 in Fig. 2 described above, the rear suspension is explained in a form closer to the actual machine, so here, the symbols in A-2 in Fig. 2 are used, the spring is given the symbol Sp, and the damper is given the symbol Dp. This is also the case in Fig. 15.

[0220] The damper Dp has a cylinder 450 in which hydraulic oil is sealed as a hydraulic fluid, a movable piston 451 provided in the cylinder 450, a piston rod 453, and a stroke sensor 360.

[0221] Cylinder 450 is divided into a first oil chamber 454 and a second oil chamber 455 by piston 451. In addition, piston 451 is provided with an orifice 452.

[0222] A suspension extension speed sensor 456 capable of detecting the piston movement speed, in other words, the suspension extension speed, is attached to the piston 451. This sensor 456 is a component of the rear suspension sensor unit 303 described above.

[0223] In addition, the direction and amount of movement of piston 451 can be measured by stroke sensor 360. When piston 451 moves toward second oil chamber 455, the direction of movement is referred to as the extension direction of the suspension, and the opposite direction is referred to as the compression direction of the suspension.

[0224] A flow passage 470 for flowing hydraulic oil as a hydraulic fluid is provided between the cylinder 450 and the spring Sp, and an electronically controlled flow control valve 460 is provided in this flow passage 470.

[0225] A variable damping force control section 500 is provided to variably control the damping force by controlling the flow rate of the hydraulic oil in this flow control valve 460 .

[0226] The variable damping force control unit 500 includes a damping force value update timing determination unit 502 and a flow control valve drive unit 504 .

[0227] The damping force value update timing determination unit 502 detects the timing when the spring Sp is fully compressed, based on the detection signal of the stroke sensor 360. In other words, it detects the timing when the spring Sp changes from a compressed state to an expanded state.

[0228] At the detection timing, the damping force value update timing determination unit 502 notifies the flow control valve driving unit 504 of information SS1 on the damping force update value, and the flow control valve driving unit 504 outputs a control signal SS2 at the timing of receiving the notification, and controls the flow control valve 460 to change the damping force value.

[0229] The reason why the damping force value is updated when the spring Sp is fully compressed is that if the damping force value is updated while the spring Sp is being compressed and moving, or while the spring Sp is being extended, accurate switching of the damping force value cannot be realized. Therefore, the damping force value is updated in synchronization with the time when the spring Sp is fully compressed.

[0230] On the other hand, the measurement section 350 is supplied with a detection signal from a suspension extension speed sensor 456, and is also supplied with a signal SS3 indicating the update timing of the damping force value from a damping force value update timing determination section 502.

[0231] As explained above, the measuring unit 350 has an internal A / D converter and measures the suspension extension speed by sampling the suspension extension speed detection signal supplied from the suspension extension speed sensor 456. However, this measurement method is just one example and is not limited to this, and for example, a measurement method in which the suspension extension speed sensor 456 is directly controlled to enable detection by the suspension extension speed sensor 456 at the measurement timing may also be used.

[0232] The measurement is performed within a period during which the suspension extension speed can be measured. This will be described later with reference to Fig. 15. In this embodiment, the start timing of the period during which the measurement can be performed is synchronized with the update timing of the damping force value.

[0233] The reason is that if the damping force value is updated while the suspension extension speed is being measured, an accurate suspension extension speed measurement that reflects the updated damping force cannot be obtained.

[0234] By synchronizing the update of the damping force value with the measurement of the suspension extension speed, it is possible to accurately measure the suspension extension speed that reflects the update of the damping force.

[0235] The measuring unit 350 supplies a detection signal of the suspension extension speed to a microcomputer 402 in the ECU 400 .

[0236] As explained above, the microcomputer 402 serving as the two-wheeled vehicle stable driving control device is provided with the power steering control section 403, and this power steering control section 403 is provided with the steering torque actuator control signal generation section 408.

[0237] The steering torque actuator control signal generation unit 408 performs processing required for power steering control, such as calculation of a generalized speed, based on the accurate detection signal of the suspension extension speed, to generate a steering torque actuator control signal DTC, and supplies the steering torque actuator control signal DTC to the steering torque actuator 310 of the power steering unit 312. This realizes highly accurate power steering control that takes into account the update of the damping force value of the suspension.

[0238] Next, reference is made to Fig. 15. Fig. 15 is a diagram showing an example of a process for synchronizing the update of the damping force value in the damper with the measurement of the extension speed of the suspension. In Fig. 15, the same reference numerals are used for the parts common to Fig. 14. The operation of each part is explained in Fig. 14, so the explanation of the operation of each part will be omitted.

[0239] In Fig. 15, the spring Sp is in a fully extended state at time t0, and compression of the spring Sp begins from this time t0. At time t1, the spring Sp is in a fully contracted state, and at this timing, the period during which the suspension extension speed can be measured begins. At time t2, the spring Sp returns to a fully extended state.

[0240] The period T from time t1 to t2 is the suspension extension speed measurement period. The measurement unit 350 can measure the suspension extension speed during at least a part of this suspension extension speed measurement period T, or at a predetermined point in time within that period T. In this way, it is possible to synchronize the update of the damping force value in the damper and the measurement of the suspension extension speed.

[0241] At time t3, the measurement section 350 outputs a measurement value of the extension speed of the suspension, in other words, a detection signal of the extension speed of the suspension.

[0242] As described above, in one aspect of the present invention, a method for modeling a motorcycle stable driving control system includes a first step (S1) of acquiring a vehicle model in which a motorcycle is modeled into a model having a center of gravity (2f) of a front body, a center of gravity (2r) of a rear body, a center of gravity (1f) of a front tire (FT) including a front tire body (104f) and a front suspension (106f), and a center of gravity (1r) of a rear tire (RT) including a rear tire body (104r) and a rear suspension (106r), and an action term indicating the sum of the acting forces acting on each of the centers of gravity and an action term indicating the sum of the inertial forces acting on each of the centers of gravity. The method includes a second step (S2, S3) of creating a linear equation of motion for the vehicle model (MDL) on the condition that the inertia terms are balanced; a third step (S4) of converting the linear equation of motion into a state equation; a fourth step (S5, S6) of acquiring a feedback gain capable of stabilizing the traveling of the vehicle model at speeds within a predetermined speed range by root locus analysis of the state equation; and a fifth step (S7) of creating a model (180) of a motorcycle stable traveling control system that implements negative feedback control using the feedback gain acquired in the fourth step.

[0243] This makes it possible to model the motorcycle as a multibody model and use root locus analysis based on modern control theory to determine an appropriate gain for the negative feedback control system for any speed within the desired speed range. Therefore, for example, it becomes possible to perform scientific and objective analysis and evaluation of stable driving control of a two-wheeled vehicle. Furthermore, for example, it will be possible to efficiently design a two-wheeled vehicle that can run stably and autonomously using model-based development techniques.

[0244] In a second aspect dependent on the first aspect, the model (180) of the motorcycle stable driving control system created in the fifth step may include a motorcycle system model (MOD1) corresponding to the motorcycle to be controlled, an input system model (MOD2) that inputs input variables to the motorcycle system model, an output system model (MOD3) that outputs output variables from the motorcycle system model, and a feedback system model (MOD4) that changes values ​​of input variables in the input system model by feedback using the feedback gains acquired in the fourth step based on the output variables.

[0245] According to the second aspect, since the motorcycle stability control system is divided into a plurality of models, in model-based development, the motorcycle stability control system can be easily designed by replacing each model with an actual part.

[0246] In a third aspect dependent on the first or second aspect, when creating the model (180) of the two-wheeled vehicle stability control system, a vehicle model (MDL) is set as a control object, the input of the vehicle model includes at least a steering torque in the vehicle model, and the output of the vehicle model includes at least a speed of the vehicle model, an angular velocity of the vehicle model, a handlebar angular velocity for the handlebar included in the vehicle model, and a suspension extension speed of each of the front suspension and the rear suspension. Based on the output of the vehicle model, negative feedback control is performed by the feedback gain acquired in the fourth step to control the steering torque as an input of the vehicle model.

[0247] According to the third aspect, by taking into full consideration the characteristics of the suspension and the like, a steering torque acting on the handles and steering shaft of the two-wheeled vehicle can be appropriately generated, and the traveling of the two-wheeled vehicle can be stabilized using power steering technology.

[0248] In a fourth aspect dependent on any one of the first to third aspects, in the second step, when creating a linear equation of motion for the vehicle model, a condition may be applied in which an engine or motor (319) included in an actual two-wheeled vehicle corresponding to the vehicle model is subjected to constant torque control so that the torque is constant even if the rotation speed fluctuates.

[0249] According to the fourth aspect, the constant torque control can reduce the moment and the like generated in the vehicle body in response to changes in the rotation speed of the engine or motor of the two-wheeled vehicle, thereby improving the accuracy of analysis of stable driving controllability of the two-wheeled vehicle.

[0250] In a fifth aspect dependent on any one of the first to fourth aspects, in the second step, when creating a linear equation of motion for the vehicle model, a generalized velocity of the vehicle model may be defined by a function including, as variables, a first velocity component generated in the movement direction of the vehicle model due to translational motion without rotation of the vehicle model, and a second velocity component generated in the movement direction of the vehicle model due to rotational motion of the vehicle model, and a linearized action term and a linearized inertia term may be calculated by multiplying each of the nonlinear action terms and inertia terms included in the nonlinear equation of motion by a Jacobian matrix at the generalized velocity, and a linear equation of motion may be created under the condition that the linearized action term and the linearized inertia term are balanced.

[0251] In the fifth aspect, the average speed is defined by comprehensively taking into account the speed components resulting from translational motion and rotational motion occurring in the moving direction of the vehicle model, so that the complex behavior of a two-wheeled vehicle can be analyzed with high accuracy by considering vibrations and the like that accompany rotation. When linearizing the equation of motion, the linearization process is performed under the condition that the average speed is constant, so that the information lost due to this linearization, i.e., first-order approximation, can be minimized, and degradation of analysis accuracy can be suppressed.

[0252] In a sixth aspect which is dependent on any one of the first to fifth aspects, a damper (Dp) included in at least one of the front suspension and the rear suspension has a damping force that is variably controlled, and a suspension (RSU1, RSU2, FR1, FR2) which includes a damper whose damping force is variably controlled as a component is a variable damping force suspension. In this case, when observing the suspension extension speed of the variable damping force suspension, the damping force value is updated when a spring (Sp), which is a component of the variable damping force suspension, is fully compressed, and the suspension extension speed may be observed in synchronization with the update of the damping force value.

[0253] According to the sixth aspect, when observing the suspension extension speed, if the suspension is a variable damping suspension, the damping force value is updated when the spring included in the variable damping suspension is fully compressed, and the suspension extension speed is observed in synchronization with this update, making it possible to accurately observe the suspension extension speed corresponding to the updated damping force value. By using the technology of this aspect, even in the case of a two-wheeled vehicle equipped with an electronically controlled suspension that implements variable damping force control, the changes in the damping force value can be accurately reflected, making it possible to more accurately observe, analyze, evaluate, etc. the complex behavior of the two-wheeled vehicle. In addition, it is possible to accurately generate the steering torque for power steering, which is necessary for autonomous stable driving control of a two-wheeled vehicle. This makes it possible to evaluate and analyze the autonomous stable driving controllability of a wide variety of motorcycles. It also greatly improves the versatility of model-based development. It also improves the accuracy of power steering technology for motorcycles.

[0254] In a seventh aspect, a motorcycle stable driving simulator (40) has a signal processing device (44) that performs signal processing for acquiring a feedback gain in the fourth step of the modeling method for a motorcycle stable driving control system of the first aspect, an input interface (42) that inputs design parameters of a vehicle model and driving condition parameters of the vehicle model to the signal processing device, and an output interface (46) that outputs information on the behavior of the vehicle model with respect to the parameters input from the input interface.

[0255] According to the seventh aspect, it is possible to perform detailed analysis and evaluation of appropriate feedback gains for motorcycles that exhibit complex behavior, which could not be scientifically verified in the past. This makes it possible to expedite the design of motorcycles with autonomous driving functions.

[0256] In an eighth aspect, the program causes a computer to operate as the two-wheeled vehicle stable driving simulator of the seventh aspect.

[0257] According to the eighth aspect, the simulator can be constructed by the program, and realization is facilitated.

[0258] In a ninth aspect, the motorcycle stable driving control system (190) includes: an actual motorcycle (300); a power steering unit (312) that is attached to the actual motorcycle and includes as a component a steering torque actuator (310) that generates a steering torque in the motorcycle; a measurement unit (350) that performs measurement processing based on outputs of a plurality of sensor units (301, 303, 305, 307, 308, 311, 313) that are attached to the actual motorcycle; and a power steering control unit (403) that is attached to the motorcycle and has a steering torque actuator control signal generation unit (408) that generates a control signal for the steering torque actuator based on the output of the measurement unit.

[0259] According to the ninth aspect, a high-performance motorcycle stable driving control system for an actual motorcycle can be realized by using a model-based development method.

[0260] In a tenth aspect dependent on the ninth aspect, the measurement unit (350) may measure the rear tire speed, rear tire angular velocity, rear body speed, rear body angular velocity, front tire speed, front tire angular velocity, front body speed, front body angular velocity, handlebar angular velocity of the handlebars of the real motorcycle, extension speed of the front suspension of the real motorcycle, and suspension extension speed of the rear suspension of the real motorcycle.

[0261] According to the ninth aspect, by taking into full consideration the characteristics of the suspension and the like, a steering torque acting on the handles and steering shaft of the two-wheeled vehicle can be appropriately generated, and the traveling of the two-wheeled vehicle can be stabilized using power steering technology.

[0262] In an eleventh aspect dependent on the ninth or tenth aspect, each of the front suspensions (FR1, FR2) and rear suspensions (RSU1, RSU2) provided on an actual two-wheeled vehicle, i.e., the two-wheeled vehicle body (300), has a spring (Sp) and a damper (Dp), and at least one of the front suspension and the rear suspension further has a variable damping force control unit (500) that variably controls the damping force of the damper, and when a suspension including a damper whose damping force is variably controlled as a component is defined as a variable damping force suspension, the variable damping force control unit (500) updates the damping force value when the spring (Sp), which is a component of the variable damping force suspension, is fully compressed, and the measurement unit (350), when measuring the suspension extension speed of the variable damping force suspension, may measure the suspension extension speed in synchronization with the update of the damping force value in the variable damping force control unit (500).

[0263] According to the eleventh aspect, when measuring the suspension extension speed, if the suspension is a variable damping suspension, the damping force value is updated when the spring included in the variable damping suspension is fully compressed, and the suspension extension speed is measured in synchronization with this update, making it possible to accurately measure the suspension extension speed corresponding to the updated damping force value. By using the technology of this aspect, even in the case of a two-wheeled vehicle equipped with an electronically controlled suspension that implements variable damping force control, the changes in the damping force value can be accurately reflected, making it possible to more accurately observe, analyze, evaluate, etc. the complex behavior of the two-wheeled vehicle. In addition, it is possible to accurately generate the steering torque for power steering, which is necessary for autonomous stable driving control of a two-wheeled vehicle. This makes it possible to evaluate and analyze the autonomous stable driving controllability of a wide variety of motorcycles. It also greatly improves the versatility of model-based development. It also improves the accuracy of power steering technology for motorcycles.

[0264] In a twelfth aspect which is dependent on any one of the ninth to eleventh aspects, the actual two-wheeled vehicle has a constant torque control unit (317) which performs constant torque control on an engine or motor (319) included in the moving actual two-wheeled vehicle so that the torque is constant relative to the rotation speed, and when the two-wheeled vehicle stability control system is operating, the constant torque control may be performed by the constant torque control unit (317).

[0265] According to the twelfth aspect, the constant torque control can reduce the moment and the like generated in the vehicle body in response to changes in the rotation speed of the engine or motor of the two-wheeled vehicle, thereby improving the accuracy of analysis of the stable driving controllability of the two-wheeled vehicle.

[0266] In the thirteenth aspect, the motorcycle stable running control device (402) functions as the power steering control section (403) in the motorcycle stable running control system in any one of the ninth to twelfth aspects.

[0267] According to the thirteenth aspect, it is possible to realize a motorcycle stable running control device, which is a device required for implementing high-precision stable running control of a motorcycle, that is, a microcomputer, a signal processing circuit, and the like.

[0268] In a fourteenth aspect dependent on the thirteenth aspect, the steering torque control device may include an error detection unit (406) that detects an error between the steering torque and a target value based on an output of the measurement unit (350), and a steering torque actuator control signal generation unit (408) that generates a steering torque actuator control signal (DTC) so as to suppress the error in the detected steering torque.

[0269] According to the fourteenth aspect, it is possible to realize a motorcycle stable driving control device, i.e., a microcomputer, a signal processing circuit, etc., that is required to construct a negative feedback control system that can quickly converge errors that occur in the steering torque of a motorcycle within a desired time period.

[0270] In the above explanation, a motorcycle has been used as an example, however, the present invention can also be applied to three-wheeled or four-wheeled vehicles, etc., and can also be applied to electric two-wheeled vehicles, etc., which are currently under development, regardless of the type of vehicle.

[0271] As described above, according to the present invention, it is possible to provide a versatile motorcycle stable running control technology etc. that can multifacetedly and scientifically verify the running stability of a motorcycle involving complex nonlinear behavior, in other words, a method for modeling a motorcycle stable running control system, a motorcycle stable running simulator, a program, a motorcycle stable running control system, and a motorcycle stable running control device etc.

[0272] As long as the functions and effects of the invention are achieved, the present invention is not limited to the examples. [Industrial Applicability]

[0273] INDUSTRIAL APPLICABILITY The present invention is useful as a modeling method for a motorcycle stable running control system, a motorcycle stable running simulator, a program, a motorcycle stable running control system, a motorcycle stable running control device, etc. [Explanation of symbols]

[0274] 1f, 2f, 1r, 2r...center of gravity, 4...road surface, 10...computer system, 12...computer main body, 14...monitor, 15...vehicle body, 16...keyboard, 17...front wheel, 18...mouse, 19...rear wheel, 20...first folder, 21, 23, 26, 28...folders, 22...state equation corresponding to motorcycle stability control system, 24...data for state equation, 25...second folder, 27...model as specification of motorcycle stability control system, 28...folder, 30...storage device, 32...simulation program (program) for analyzing motorcycle stability control system, 40...simulator data (two-wheeled vehicle stable driving simulator), 44 ... signal processing device for feedback gain analysis based on state equation, 42 ... input interface, 46 ... output interface, 100 ... front body, 102 ... rear body, 104f, 104r ... tire body, 105f ... spring representing the elastic characteristics of the front tire body, 105r ... spring representing the elastic characteristics of the rear tire body, 106f ... one virtual front suspension (front suspension), 106r ... one virtual rear suspension (rear suspension), 108f ... front damper, 108r ... rear damper, 110f,110r...spring (suspension spring), 120...steering shaft, 121...handle, 122...rear body axle, 180...model of motorcycle stable driving system, 190...motorcycle stable driving control system, 300...motorcycle body, 301...rear tire sensor section, 303...rear suspension sensor section, 305...rear body sensor section, 307...front body sensor section, 308...handle sensor section, 309...steering torque sensor, 310...steering torque actuator, 311...front suspension sensor 312...power steering unit, 313...front tire sensor unit, 315...engine control unit, 317...constant torque control unit, 319...engine or electric motor, 350...measurement unit, 360...stroke sensor, 400...ECU, 402...microcomputer (two-wheeled vehicle stable driving control), 403...power steering control unit, 406...error detection unit, 407...comparison unit, 408...steering torque actuator control signal generation unit, 410...generalized speed calculation unit, 412...steering torque Actuator control signal calculation unit, 450...cylinder, 451...piston, 452...orifice, 454...first oil chamber, 455...second oil chamber, 456...suspension extension speed sensor, 460...flow control valve, 500...variable damping force control unit, 502...damping force value update timing determination unit, 504...flow control valve drive unit, Dp...damper, FR1, FR2...front suspension functioning as a damper, FT...front tire, FU...upper point of front suspension, Lf, Lr...lateral force, m1f, m2f, m1r, m2r...mass of center of gravity, MDL...vehicle model, MOD1...model of motorcycle system, MOD2...model of input system, MOD3...model of output system, MOD4...model of feedback system, RSU1, RSU2...rear suspension, RT...rear tire, RU...upper point of rear suspension, Sp...spring, T...period during which suspension extension speed can be measured, TM...notification signal for timing of damping force value update, θcas...caster angle, θhd...handle angle.

Claims

1. With the actual motorcycle, a power steering unit that is attached to the actual motorcycle and includes, as a component, a steering torque actuator that generates a steering torque in the actual motorcycle; a measurement unit that performs measurement processing based on outputs from a plurality of sensors that are attached to the actual motorcycle; a power steering control unit attached to the two-wheeled vehicle and having a steering torque actuator control signal generation unit that generates a control signal for the steering torque actuator based on an output of the measurement unit; A motorcycle stability control system having the above-mentioned configuration.

2. The measurement unit includes: measuring the rear tire speed, rear tire angular velocity, rear body speed, rear body angular velocity, front tire speed, front tire angular velocity, front body speed, front body angular velocity, handlebar angular velocity of the actual motorcycle, extension speed of the front suspension of the actual motorcycle, and suspension extension speed of the rear suspension of the actual motorcycle; The motorcycle stability control system according to claim 1 .

3. The front suspension and the rear suspension of the actual motorcycle each have a spring and a damper. a damping force variable control unit that variably controls the damping force of the damper in at least one of the front suspension and the rear suspension, When a suspension including a damper whose damping force is variably controlled as a component is considered as a variable damping force suspension, The damping force variable control unit is When a spring, which is a component of the variable damping force suspension, is fully compressed, the damping force value is updated, The measurement unit includes: When measuring the suspension extension speed of the variable damping force suspension, measuring the extension speed of the suspension in synchronization with updating of the damping force value in the damping force variable control unit; The motorcycle stability control system according to claim 1 .

4. The actual two-wheeled vehicle has a constant torque control unit that performs constant torque control on an engine or a motor included in the moving actual two-wheeled vehicle so that the torque is constant with respect to the rotation speed, When the motorcycle stable driving control system is operating, the constant torque control is performed by the constant torque control unit. The motorcycle stability control system according to claim 1 .

5. 5. A motorcycle stable running control device functioning as the power steering control unit in the motorcycle stable running control system according to claim 1.

6. an error detection unit that detects an error between the steering torque and a target value based on an output of the measurement unit; a steering torque control signal generation unit that generates the steering torque actuator control signal so as to suppress an error in the detected steering torque; having The motorcycle stable running control device according to claim 5.

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