A stability control method for vehicle transfer robot

Abstract

The present invention discloses a stability control method for a vehicle transfer robot, comprising: obtaining an ideal yaw rate based on longitudinal vehicle speed and rear wheel angle; determining an additional yaw torque and an additional rear wheel angle based on the difference between the ideal yaw rate and the actual yaw rate; allocating coordinated control weights between an ARS control area and a DYC control area based on the real-time stability of the transfer robot; determining a coordinated control weight coefficient so as to calculate the required additional rear wheel angle and additional yaw torque output, and distribute the additional yaw torque to each wheel; and distributing the additional rear wheel angle and additional yaw torque, after allocation by the coordinated control weight coefficient, to a steering motor and wheel hub motors for output. The present invention uses a coordinated controller to achieve active steering and direct yaw torque coordinated control, as well as vehicle body posture adjustment under hazardous conditions, thereby improving the stability of the vehicle transfer robot under complex operating conditions at ports and terminals.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle stability control, and in particular relates to a stability control method for a vehicle transfer robot. Background Art

[0002] Vehicle transfer robots are a key achievement in the development of intelligent modern urban transportation, and stability control is crucial for their safe operation. Vehicle transfer robots must precisely maneuver within confined spaces, often handling heavy vehicles. Without effective stability control, the robots could tilt, wobble, or even overturn during operation, potentially damaging the vehicles and posing a threat to the surrounding environment and personnel. In-depth research on stability control can ensure that vehicle transfer robots maintain stable operation under various complex operating conditions, effectively mitigating safety risks and providing reliable protection for vehicles and personnel. Stable operation ensures that the robots accurately execute parking tasks according to pre-set paths and speeds, reducing repeated adjustments and downtime caused by instability. This not only shortens vehicle access times and improves parking lot turnover, but also enhances the efficiency of the entire parking system, alleviating urban parking congestion. Furthermore, stability control helps extend the service life of vehicle transfer robots. Under stable operating conditions, the mechanical structure and drive system of vehicle transfer robots are less susceptible to shock and wear, thereby reducing component wear, maintenance costs, and equipment replacement frequency. This is of great significance for reducing the operating costs and maintenance expenses of parking lots.

[0003] Traditional vehicle transfer equipment has limitations in stability control: Traditional multi-axle transfer platforms often rely on mechanical linkage for steering control, which limits their turning radius and lacks independent wheel height adjustment capabilities, making it prone to center of gravity shift on bumpy roads. The power system is concentrated on the front axle, leaving the rear axle without active control capabilities. Intelligent AGV transfer devices utilize single- or dual-axle drives, which limit their load capacity. Steering relies on the front-wheel steering mechanism, resulting in tracking errors on complex paths. The suspension system lacks active compensation mechanisms, making cargo prone to tilting when driving on slopes. Hydraulic lift transport equipment also suffers from slow lift mechanism response speeds (≥500ms), making it incapable of adapting to dynamic road conditions in real time. Existing vehicle transfer equipment is primarily designed for specific or favorable road conditions and lacks the structures and corresponding control methods for complex road conditions. Summary of the Invention

[0004] In order to solve the above-mentioned problems existing in the prior art, the present invention provides a stability control method for a vehicle transfer robot, which performs stability analysis of the vehicle transfer robot under various complex working conditions in port terminals, and realizes active steering and direct yaw moment coordinated control and vehicle body posture adjustment under dangerous working conditions through a coordinated controller, so as to improve the stability of the vehicle transfer robot under complex operating conditions in port terminals, and is particularly suitable for application scenarios of vehicle transfer in roll-on / roll-off ships in port terminals.

[0005] The purpose of the present invention is achieved through the following technical solutions:

[0006] A vehicle transfer robot stability control method, characterized by comprising:

[0007] S1. Using a two-degree-of-freedom reference model, calculate the ideal yaw rate based on the longitudinal vehicle speed and rear wheel angle.

[0008] S2. Based on the difference between the ideal yaw rate and the actual yaw rate, the sliding mode variable structure control algorithm is used to determine the additional yaw torque. and additional rear wheel angle ; Step S2 comprises:

[0009] S21. The actual yaw rate and the ideal yaw rate The deviation is input to the direct yaw moment controller, and the sliding film variable structure control algorithm is used to determine the additional yaw moment ;

[0010] S22. The actual yaw rate and the ideal yaw rate The deviation is input to the direct yaw moment controller, and the sliding mode control is used to determine the additional rear wheel steering angle , and then transmit the determined turning angle signal to the steering motor;

[0011] S3. The coordination controller determines the boundaries of the transfer robot's stable region based on the transfer robot's real-time stability state and uses this to allocate coordinated control weights between the ARS control region and the DYC control region. The controller also determines the suspension height adjustment state by detecting whether the transfer robot's roll angle is greater than a safety threshold.

[0012] S4. The coordination controller determines a coordination control weight coefficient and assigns it to the active rear steering controller and the direct yaw moment controller, respectively calculating the required additional rear wheel steering angle and additional yaw moment output. The additional yaw moment is then distributed to each wheel using a dynamic allocation method based on quadratic programming. The suspension height controller then allocates the suspension height adjustment amount.

[0013] S5. Distribute the additional rear wheel steering angle and additional yaw moment after coordinated control weight coefficient allocation to the steering motor and each wheel hub motor and output them; distribute the suspension height adjustment amount allocated to each wheel to each wheel suspension height adjustment motor and output them.

[0014] Furthermore, the step S1 includes:

[0015] From the vehicle's two-degree-of-freedom motion model, the state equation is obtained:

[0016]

[0017] Ideal yaw rate during steady-state steering for:

[0018]

[0019] in, , +

[0020] Adhesion coefficient of road surface The maximum yaw rate satisfies the following restrictions:

[0021]

[0022] In summary, the ideal yaw rate of the vehicle is expressed as:

[0023]

[0024] Where, is a symbolic function; , are the front and rear axle cornering stiffnesses, respectively; 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle respectively; is the sideslip angle of the center of mass; is the yaw angular velocity; u and v are the longitudinal and lateral vehicle speeds respectively; is the rear wheel turning angle; is the moment of inertia around the Z axis; is the vehicle mass; is the rear wheel turning angle; L is the wheelbase.

[0025] Furthermore, the step S21 includes:

[0026] Considering the effect of the additional yaw moment on the two-degree-of-freedom reference model, the state space equation is obtained:

[0027]

[0028] Where, , are the front and rear axle cornering stiffnesses, 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle, respectively. is the sideslip angle of the center of mass, is the yaw rate, u and v are the longitudinal and lateral speeds respectively, is the rear wheel turning angle, is the moment of inertia around the Z axis, is the additional yaw moment;

[0029] According to the above formula, we can get:

[0030] + +

[0031] The sliding surface expression of the sliding mode controller is:

[0032]

[0033] Where, is the yaw rate deviation, is a positive weighting coefficient;

[0034] The derivative is:

[0035]

[0036] Further we get:

[0037] + +

[0038] Select the exponential approach rate:

[0039]

[0040] Where k>0, is the isokinetic approach term, The speed at which the system approaches stability;

[0041] Substituting the above control rate into the vehicle yaw motion model after adding the yaw moment, the expression of the additional yaw moment is obtained as follows:

[0042]

[0043] To reduce chattering, replace the sign function with a saturation function:

[0044]

[0045] Where, >0 is the boundary layer thickness;

[0046] Final additional yaw moment The control rate is:

[0047]

[0048] Where, .

[0049] Furthermore, the step S22 includes:

[0050] The sliding surface used for the additional rear wheel steering angle is defined as:

[0051]

[0052] Where, is the yaw rate deviation, is a positive weighting coefficient;

[0053] The derivative is:

[0054]

[0055] From the state equation of the two-degree-of-freedom model, we know:

[0056] +

[0057] Where, , are the front and rear axle cornering stiffnesses, 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle, respectively. is the sideslip angle of the center of mass, is the yaw rate, u and v are the longitudinal and lateral speeds respectively, is the rear wheel turning angle, is the moment of inertia around the Z axis;

[0058] Use constant velocity approach rate:

[0059]

[0060] The larger the k value, the faster the approach speed and the greater the jitter generated;

[0061] Combining the above formulas, we get:

[0062]

[0063] Use a saturation function instead of a sign function:

[0064]

[0065] is the boundary thickness; the final rear wheel steering angle output by the sliding mode control is:

[0066]

[0067] At this time, the additional rear wheel angle is the deviation between the rear wheel steering angle after the sliding film control output and the initial steering angle.

[0068] Furthermore, step S3 includes:

[0069] S31. Coordinate the controller to determine the stability area and divide the control area of ​​the transfer robot:

[0070] use Phase plane method is used to determine the vehicle stability of the coordinated controller. The phase plane divides the vehicle stability region by two straight lines symmetrical about the origin as boundary lines;

[0071] The boundary of the stable region is expressed as:

[0072]

[0073] Where, , is the boundary coefficient of the stable region;

[0074] When the vehicle's center of mass sideslip angle and center of mass sideslip angle angular velocity satisfy the above formula, the vehicle is considered to be in a stable state;

[0075] exist The control areas of each controller in the phase plane are divided into: ARS control area, ARS and DYC coordinated control area, and DYC control area;

[0076] The boundary equation of the stable region divided according to each control region is:

[0077]

[0078] Where, , is the control boundary weight coefficient, 0< <1, ; The smaller it is, the smaller the area controlled by ARS alone; The larger it is, the larger the coordinated control area between ARS and DYC is;

[0079] S32. Detect whether the roll angle is greater than a threshold and determine the suspension height adjustment state:

[0080] The IMU sensor is used to detect whether the roll angle and pitch angle of the transfer robot are greater than the set safety threshold, so as to determine whether the height of each suspension needs to be adjusted.

[0081] Furthermore, the step S4 includes:

[0082] S41. The coordinated controller determines the coordinated control weight coefficient and calculates the required additional rear wheel steering angle and additional yaw moment output;

[0083] S42. A dynamic allocation method based on quadratic programming is used to distribute the additional yaw moment, and the torque difference between each wheel is controlled by the wheel hub motor to form an additional yaw moment around the center of mass;

[0084] S43. The height adjustment amount of each suspension is based on the tilt direction, and the suspension height controller allocates the corresponding suspension height lifting motor to raise or lower the suspension height.

[0085] Furthermore, the step S41 includes:

[0086] The ARS control weight coefficient is defined as , the DYC control weight coefficient is ;

[0087] When ARS control is performed alone, ;

[0088] When DYC control is performed alone, ;

[0089] When ARS and DYC are coordinated, the sigmoid function is used to coordinate the control weight coefficients:

[0090]

[0091] The total expression of ARS control weight coefficient can be obtained:

[0092]

[0093] Where, , is the boundary coefficient of the stable region; , is the control area boundary weight coefficient, 0< <1, ;

[0094] The additional rear wheel steering angle after coordinated control distribution is obtained With additional yaw moment , as follows:

[0095]

[0096] The weighted additional yaw moment is obtained and the weighted additional rear wheel steering angle , through the coordinated control coefficient Realize coordinated control of direct yaw moment control and active rear wheel steering control.

[0097] Furthermore, the step S42 includes:

[0098] Dynamic allocation takes the lowest comprehensive utilization rate of the six wheels or the maximum tire stability margin as the optimization objective function, and uses the quadratic programming algorithm to find the optimal solution;

[0099] The tire utilization expression is as follows:

[0100]

[0101] Where i=1,2,3,4,5,6, respectively represent the left and right wheels of the front axle, the left and right wheels of the intermediate axle, and the left and right wheels of the rear axle;

[0102] Without considering the influence of the tire lateral force, only the longitudinal force of the tire is considered, and the objective function is simplified to:

[0103]

[0104] The yaw moment output by the upper controller and the total longitudinal force of the vehicle and the motor torque should satisfy the following equality constraints:

[0105]

[0106] Where, is the tire rolling radius; 、 ...is the torque of each wheel motor, 、 ...is the longitudinal force of each wheel, , fr, ml, mr, rl, rr are the left and right wheels of the front axle, the left and right wheels of the intermediate axle, and the left and right wheels of the rear axle respectively; d is the wheelbase;

[0107] The output torque of the drive motor is limited by the peak torque of the motor itself Influenced by the road adhesion coefficient, the drive motor torque satisfies the following inequality constraints:

[0108]

[0109] Adding yaw moment The formula for stability judgment is transformed into a quadratic programming problem for solution. The standard form of quadratic programming is:

[0110]

[0111]

[0112] Where, , ,

[0113] ,

[0114] The above quadratic programming problem is solved by the interior point algorithm to obtain the torque distribution results of each wheel.

[0115] Furthermore, the step S43 includes:

[0116] The suspension height adjustment motor adjusts the suspension height of each wheel in real time to keep the vehicle body roll angle within a safe range;

[0117]

[0118] Where, is the difference between the vehicle body roll angle and the safety threshold, is the roll angle of the vehicle body, is the safety threshold of the roll angle;

[0119] The roll angle is defined as positive in the counterclockwise direction and negative in the clockwise direction. >0, the left suspension height is increased and the right suspension height is decreased; when When <0, the right suspension height is increased and the left suspension height is decreased;

[0120] Adjustment of suspension height:

[0121]

[0122] Where d is the wheelbase, is the suspension height adjustment amount;

[0123] The suspension height distribution controller receives the required suspension height adjustment amount from the suspension height controller After that, the suspension height distribution of each wheel is as follows:

[0124]

[0125] In the formula , They are the high-speed adjustment values ​​of the suspension for the front axle, intermediate axle and rear axle respectively; 1 and 2 represent the left and right wheels respectively.

[0126] The present invention has the following advantages:

[0127] The present invention provides a stability control method for a vehicle transfer robot, which takes into account the robustness of the control algorithm and adopts a sliding film algorithm to calculate the additional yaw moment and the additional rear wheel angle, thereby ensuring the effective operation of the stability control system during actual vehicle operation.

[0128] This invention employs a hierarchical control architecture with upper and lower layers. The upper-layer controller is a coordination controller. Based on the vehicle's real-time stability state, it determines the boundaries of the vehicle's stable region. This determines the coordinated control weights for the ARS and DYC, allowing each controller to switch to its operating region promptly. The lower-layer controller is the control system's execution layer. Based on the control weights output by the upper-layer coordination controller, it assigns coordinated control weight coefficients to the active rear steering controller and the direct yaw moment controller. These controllers calculate the required additional rear wheel steering angle and additional yaw moment output, respectively, to restore the vehicle to a stable driving state. This reduces controller computing power and improves control efficiency and effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0129] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0130] Figure 1 This is a flowchart of a vehicle transfer robot stability control method according to an embodiment of the present invention;

[0131] Figure 2 Schematic diagram of the kinetic model used in the embodiments of the present invention;

[0132] Figure 3 Schematic diagram of a two-degree-of-freedom reference model used in an embodiment of the present invention;

[0133] Figure 4 A schematic diagram of a tire mechanical properties model used in an embodiment of the present invention;

[0134] Figure 5 Schematic diagram of the phase plane stable region in an embodiment of the present invention;

[0135] Figure 6 This is a schematic diagram of dividing the working areas of each controller into the phase plane stability area according to an embodiment of the present invention;

[0136] Figure 7 Schematic diagram of the vehicle body angle of the vehicle transfer robot when it rolls dangerously in an embodiment of the present invention. DETAILED DESCRIPTION

[0137] The present invention is further described below with reference to the accompanying drawings and embodiments.

[0138] The vehicle transfer robot disclosed herein uses a rear axle power motor (with a steering motor) to propel the four front axles and the vehicle they carry. Because the front and rear plates are connected by die-casting, stability analysis can be simplified: the original five-axis structure is reduced to a three-axis structure, and the rear axle is steerable, reducing workload while maintaining effective control. The vehicle transfer robot disclosed herein will be referred to as a "vehicle" in the following description. The present invention will be described below with reference to the accompanying drawings.

[0139] like Figure 1 As shown, this embodiment is a vehicle transfer robot stability control method, including:

[0140] S1. Using a two-degree-of-freedom reference model, obtain the ideal yaw rate based on the longitudinal vehicle speed and rear wheel angle.

[0141] like Figure 2 As shown in Figure 3, the vehicle transfer robot model is simplified into a three-degree-of-freedom model, representing longitudinal motion along the x-axis, lateral motion along the y-axis, and yaw motion around the z-axis. This simplified three-degree-of-freedom vehicle model can well reflect the vehicle's longitudinal and lateral motion characteristics. The x-axis represents the vehicle's longitudinal motion direction, the y-axis represents the vehicle's lateral motion direction, and γ represents the vehicle's yaw motion.

[0142] The longitudinal motion equation of the vehicle is:

[0143]

[0144] The vehicle's lateral motion equation is:

[0145]

[0146] The equation of motion of the vehicle around the z-axis is:

[0147] - ) - ) - ) +( - ) ] +( + ) -( ) ) -( )

[0148] Among them, m is the mass of the vehicle, is the rear wheel turning angle, 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle, d is the wheelbase, u and v are the longitudinal and lateral speeds, respectively. is the yaw angular velocity, is the moment of inertia around the Z axis, , , Respectively represent the longitudinal forces of the front axle, intermediate axle, and rear axle tires (i=1, 2 represent the left and right wheels, respectively), , , Represent the lateral forces of the tires on the front axle, intermediate axle, and rear axle respectively.

[0149] The rubber viscoelastic structure of the tire itself leads to complex nonlinear mechanical properties when it moves under complex working conditions. Therefore, in vehicle dynamics control simulation, it is crucial to establish a suitable tire model to analyze the tire mechanical properties. Figure 4 As shown, based on the Magic Formula tire model, the relationship between tire force and sideslip angle, slip rate and load can be known:

[0150] Considering the tire sideways slipping condition during cornering, ignoring the effect of the tire camber angle, and assuming the tire only slips in the lateral direction, the Magic Formula tire lateral force mechanical characteristic curve expression can be obtained when the tire is only subjected to lateral force:

[0151]

[0152] The various factors satisfy the following relationship:

[0153]

[0154] Where, is the lateral force of the tire, are the curve shape factor and curvature factor, is the peak factor, is the stiffness factor, is the vertical force on the tire.

[0155] Considering that the tire is only subjected to longitudinal forces during driving and the tire only slips in the longitudinal direction, the expression of the Magic Formula tire longitudinal force mechanical characteristic curve under the condition that the tire is only subjected to longitudinal forces can be obtained:

[0156]

[0157] The various factors satisfy the following relationship:

[0158]

[0159] Where, is the longitudinal force of the tire, are the curve shape factor and curvature factor, is the peak factor, is the stiffness factor, is the vertical force of the tire, 、 、 … are the tire fitting parameters, which are obtained from tire test data. The tire fitting parameter values ​​in this embodiment are shown in the following table:

[0160]

[0161] During actual driving, the tires are subjected to both longitudinal and lateral forces. The relationship between the tire force and the sideslip angle, slip rate, and load can be expressed as follows:

[0162]

[0163] Where: , , , is the longitudinal force, is the lateral force, is the sideslip angle, is the slip rate.

[0164] The tire slip rate s can be calculated by the following formula:

[0165]

[0166] Where, is the tire rolling radius, is the tire angular velocity, is the longitudinal speed.

[0167] Vertical load on tire It can be calculated by the following formula:

[0168]

[0169] Where, is the mass, g is the acceleration due to gravity; is the distance between the vehicle's center of mass and the ground, 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle, respectively. , , They represent the longitudinal forces of the tires on the front axle, intermediate axle, and rear axle respectively (i=1, 2 represent the left and right wheels respectively), d is the wheelbase, and L is the wheelbase.

[0170] Since the vehicle transfer robot of the present invention has only the rear axle with an inputtable rotation angle Here we can assume that the tire side slip angles of the front axle and the intermediate axle are the same, then we can make appropriate simplifications, such as Figure 3 As shown, the two-degree-of-freedom motion model obtains the following equation:

[0171]

[0172] Written in the form of state equation:

[0173]

[0174] Where, , are the front and rear axle cornering stiffnesses, 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle, respectively. is the sideslip angle of the center of mass, is the yaw rate, u and v are the longitudinal and lateral speeds respectively, is the rear wheel turning angle, is the moment of inertia around the Z axis.

[0175] The ideal yaw rate during steady-state steering is derived from the above formula: for:

[0176]

[0177] in, , +

[0178] Adhesion coefficient of road surface The maximum yaw rate is limited to:

[0179]

[0180] In summary, the ideal yaw rate of the vehicle is:

[0181]

[0182] Where, is a symbolic function.

[0183] S2. Input the difference between the ideal yaw rate and the actual yaw rate into the direct yaw moment controller and the active rear wheel steering controller, and use the sliding mode variable structure control algorithm to determine the additional yaw moment. and additional rear wheel angle .

[0184] S21. The actual yaw rate and the ideal yaw rate The deviation is input to the direct yaw moment controller, and the sliding film variable structure control algorithm is used to determine the additional yaw moment .

[0185] Direct yaw moment control is a method of controlling the vehicle's yaw by adjusting the longitudinal forces on different wheels to generate an additional yaw moment rotating around the center of mass. Therefore, the effect of the additional yaw moment on the two-degree-of-freedom reference model should be considered, and the state space equation should be modified to:

[0186]

[0187] Where, , are the front and rear axle cornering stiffnesses, 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle, respectively. is the sideslip angle of the center of mass, is the yaw rate, u and v are the longitudinal and lateral speeds respectively, is the rear wheel turning angle, is the moment of inertia around the Z axis, is the additional yaw moment.

[0188] According to the above formula, we can get:

[0189] + +

[0190] The sliding surface expression of the sliding mode controller is:

[0191]

[0192] Where, is the yaw rate deviation, is a positive weighting coefficient;

[0193] The derivative is:

[0194]

[0195] Bring in:

[0196] + +

[0197] Select the exponential approach rate:

[0198]

[0199] Where k>0, is the isokinetic approach term, The speed at which the system approaches stability;

[0200] Substituting the above control rate into the vehicle yaw motion model after adding the yaw moment, the expression of the additional yaw moment is obtained as follows:

[0201]

[0202] To reduce chattering, replace the sign function with a saturation function:

[0203]

[0204] Where, >0 is the boundary layer thickness;

[0205] Final additional yaw moment The control rate is:

[0206]

[0207] Where, .

[0208] Stability is determined based on the Lyapunov function.

[0209] S22. The actual yaw rate and the ideal yaw rate The deviation is input to the direct yaw moment controller, and the sliding mode control is used to determine the additional rear wheel steering angle , and then transmits the determined turning angle signal to the steering motor to maintain vehicle stability.

[0210] Similar to the sliding film control used for the additional yaw moment, the sliding surface used for the additional rear wheel steering angle is defined as:

[0211]

[0212] Where, is the yaw rate deviation, is a positive weighting coefficient.

[0213] The derivative is:

[0214]

[0215] From the state equation of the two-degree-of-freedom model, we can know that:

[0216] +

[0217] Where, , are the front and rear axle cornering stiffnesses, 、 are the distances from the center of mass to the front axle, intermediate axle, and rear axle, respectively. is the sideslip angle of the center of mass, is the yaw rate, u and v are the longitudinal and lateral speeds respectively, is the rear wheel turning angle, is the moment of inertia around the Z axis.

[0218] Use constant velocity approach rate:

[0219]

[0220] The larger the k value, the faster the approach speed and the greater the jitter generated.

[0221] Combining the above formulas, we can get:

[0222]

[0223] Similarly, the saturation function is used instead of the sign function:

[0224]

[0225] The boundary thickness is generally 0.05, and the final rear wheel steering angle output by the sliding mode control is:

[0226]

[0227] At this time, the additional rear wheel angle is the deviation between the rear wheel steering angle after the sliding film control output and the initial steering angle.

[0228] S3. The coordination controller determines the stable area boundary of the transfer robot based on the real-time stable state of the transfer robot, and allocates the coordinated control weights of the ARS control area and the DYC control area. It determines the suspension height adjustment state by detecting whether the roll angle of the transfer robot is greater than the safety threshold.

[0229] S31. Coordinate the controller to determine the stability area and divide the control area of ​​the transfer robot:

[0230] In order to give full play to the advantages of the active rear-wheel steering control system and the direct yaw moment control system, a coordinated controller is designed to transform the two control systems from separate control to integrated control. The working tasks and working timing between the two control systems are coordinated according to the vehicle's stability state to ensure that the vehicle can achieve optimal yaw stability control under different driving conditions.

[0231] 1) Stability determination

[0232] like Figure 5 As shown, this embodiment adopts Phase plane method is used to determine the vehicle stability of the coordinated controller. Phase plane, the vehicle stability region is divided by two straight lines symmetrical about the origin. These two straight lines are the boundary lines between the stable region and the unstable region, such as Figure 5 shown.

[0233] The boundary of the stable region can be expressed as:

[0234]

[0235] Where, , is the stable region boundary coefficient; specifically, is the slope of the stable region boundary, is the intercept of the stability region boundary with the axis.

[0236] When the vehicle's sideslip angle and angular velocity satisfy the above equation, that is, the vehicle is in the stable region A between the two red lines in Figure 5, the vehicle is considered to be in a stable state. Otherwise, the vehicle is in the unstable region C outside the two lines and loses stability.

[0237] 2) Control area division

[0238] Active rear wheel steering control only works well in the linear working area of ​​the tire. DYC control intervention is required for nonlinear areas. The division of the phase plane stable area should also be consistent with the working area of ​​the tire. Figure 6 As shown, in The control areas of each controller in the phase plane are divided into: ARS control area, ARS and DYC coordinated control area, and DYC control area.

[0239] The road adhesion coefficient has the greatest impact on the change of the phase plane stable area. The boundary coefficient of the stable area can be obtained according to different road adhesion coefficients. , , the boundary equation of the stable region divided according to each control region is expressed as:

[0240]

[0241] Where, , is the control boundary weight coefficient, 0< <1, . The smaller it is, the smaller the area controlled by ARS alone; The larger the value, the larger the coordinated control area between ARS and DYC. , The solution can be taken as the longitudinal speed and front wheel angle as input, the boundary weight coefficient , Specifically solve the output fuzzy controller.

[0242] S32. Detect whether the roll angle is greater than a threshold and determine the suspension height adjustment state.

[0243] GB 7258-2017 stipulates that the roll stability angle of a passenger vehicle body should not exceed 35°. Based on the specific analysis of the vehicle transfer robot in this embodiment, a safety threshold of 20° is set. The IMU sensor detects whether the transfer robot's roll and pitch angles are in a dangerous state (greater than the set safety threshold) to determine whether the suspension heights need to be adjusted. Transient excessive roll angles typically occur when the transfer robot passes over potholes or bumps in the road. Active suspension height adjustment can maintain a stable body posture and maintain vehicle stability.

[0244] S4. The coordination controller determines the coordination control weight coefficient and allocates the coordination control weight coefficient to the active rear-wheel steering controller and the direct yaw moment controller, so that they can respectively calculate the required additional rear wheel angle and additional yaw moment output, and use the dynamic allocation method based on quadratic programming to distribute the additional yaw moment to each wheel, so that the vehicle can return to a stable driving state; reasonably allocate the height adjustment of each suspension to restore the transfer robot to a stable state.

[0245] S41. The coordinated controller determines the coordinated control weight coefficient and calculates the required additional rear wheel steering angle and additional yaw moment output:

[0246] like Figure 1 As shown, in this embodiment, the ARS control weight coefficient is defined as , the DYC control weight coefficient is ; When ARS control is performed alone, ; When DYC control is performed alone, When ARS and DYC are coordinated, the sigmoid function is used to coordinate the control weight coefficients:

[0247]

[0248] Therefore, the overall expression of the ARS control weight coefficient can be obtained as follows:

[0249]

[0250] Where, , is the stable region boundary coefficient; specifically, is the slope of the stable region boundary, is the intercept between the boundary of the stable region and the axis, , is the control area boundary weight coefficient, 0< <1, .

[0251] According to the above analysis, the additional rear wheel turning angle after coordinated control distribution can be obtained With additional yaw moment , as follows:

[0252]

[0253] The weighted additional yaw moment is obtained and the weighted additional rear wheel steering angle , through the coordinated control coefficient Realize coordinated control of direct yaw moment control and active rear wheel steering control.

[0254] S42. A dynamic allocation method based on quadratic programming is used to distribute the additional yaw moment. The in-wheel motors are used to control the torque difference between the wheels to form an additional yaw moment about the center of mass.

[0255] Dynamic allocation, also known as optimal allocation, takes into account tire mechanical properties and actuator constraints, dynamically adjusting the torque of each wheel to fully utilize the longitudinal force of each wheel and improve tire adhesion. Dynamic allocation considers the lowest overall tire utilization rate or the maximum tire stability margin for all six wheels as the optimization objective function, and uses a quadratic programming algorithm to find the optimal solution. The tire utilization expression is as follows:

[0256]

[0257] Where i=1, 2, 3, 4, 5, and 6 represent the left and right wheels of the front axle, the left and right wheels of the intermediate axle, and the left and right wheels of the rear axle, respectively.

[0258] In practice, the lateral force of the tire cannot be directly controlled due to conditional constraints. Therefore, the influence of the lateral force of the tire is not considered. Only the longitudinal force of the tire is considered to improve the efficiency of the torque distribution controller. The objective function is simplified to:

[0259]

[0260] The yaw moment output by the upper controller and the total longitudinal force of the vehicle and the motor torque should satisfy the following equality constraints:

[0261]

[0262] Where, is the tire rolling radius; 、 ...is the torque of each wheel motor, 、 ...is the longitudinal force of each wheel, , fr, ml, mr, rl, rr represent the left and right wheels on the front axle, the left and right wheels on the middle axle, and the left and right wheels on the rear axle respectively; d is the wheelbase.

[0263] The output torque of the drive motor is limited by the peak torque of the motor itself and road adhesion coefficient, select is 320 N.m, that is, the drive motor torque should satisfy the following inequality constraints:

[0264]

[0265] Adding yaw moment The formula for stability judgment is transformed into a quadratic programming problem for solution. The standard form of quadratic programming is:

[0266]

[0267]

[0268] Where, , ,

[0269] , .

[0270] The above quadratic programming problem can be solved by the interior point algorithm to obtain the torque distribution results of each wheel.

[0271] S43. The height adjustment amount of each suspension is based on the tilt direction. The suspension height controller assigns the corresponding suspension height lifting motor to raise or lower the suspension height:

[0272] For suspension height adjustment, the coordinated controller achieves vehicle stability control by dividing the control areas of each controller within the stability zone and coordinating control weights. Under extreme conditions, such as when traversing a large uneven surface, the vehicle's roll angle can increase instantaneously and exceed the safety threshold (20° in this embodiment), potentially posing a rollover risk. The suspension height adjustment motor, with its superior speed to hydraulic systems, adjusts the suspension height of each wheel in real time, keeping the roll angle within a safe range.

[0273]

[0274] Where, is the difference between the vehicle body roll angle and the safety threshold, is the roll angle of the vehicle body, is the safety threshold of the roll angle°

[0275] The definition of roll angle is that the counterclockwise direction is positive and the clockwise direction is negative. >0, the left suspension height is increased and the right suspension height is decreased; when When <0, the right suspension height is increased and the left suspension height is decreased.

[0276] like Figure 7 As shown, at this time <0, adjustment of suspension height:

[0277]

[0278] Where d is the wheelbase, is the suspension height adjustment amount.

[0279] The suspension height distribution controller receives the required suspension height adjustment amount from the suspension height controller After that, the suspension height distribution of each wheel is as follows:

[0280]

[0281] In the formula , The high-speed adjustment values ​​of the front, intermediate, and rear axles (i=1, 2 represent the left and right wheels, respectively)

[0282] S5. Distribute the additional rear wheel steering angle and additional yaw moment after coordinated control weight coefficient allocation to the steering motor and each wheel hub motor and output them; distribute the suspension height adjustment amount allocated to each wheel to each wheel suspension height adjustment motor and output them.

[0283] This step is to match the additional rear wheel angle and the distributed additional yaw torque signal with the characteristics of the steering motor, hub motor and suspension height adjustment motor, and convert them into corresponding electrical signals to control the output of the motor and achieve stability control.

Claims

1. A vehicle transfer robot stability control method, characterized in that: include: S1. Using a two-degree-of-freedom reference model, determine the ideal yaw rate based on the longitudinal vehicle speed and rear wheel angle. S2. Based on the difference between the ideal yaw rate and the actual yaw rate, the sliding mode variable structure control algorithm is used to determine the additional yaw moment ΔM. Z and additional rear wheel turning angle Δδ r ; Step S2 comprises: S21. The actual yaw rate γ and the ideal yaw rate γ d The deviation is input to the direct yaw moment controller, and the sliding mode variable structure control algorithm is used to determine the additional yaw moment ΔM Z ; S22. The actual yaw rate γ and the ideal yaw rate γ d The deviation is input to the direct yaw moment controller, and the sliding mode control is used to determine the additional rear wheel steering angle Δδ r , and then transmit the determined turning angle signal to the steering motor; S3. The coordination controller determines the stable region boundary of the transfer robot according to the real-time stable state of the transfer robot, thereby allocating the coordinated control weights of the ARS control region and the DYC control region; by detecting whether the roll angle of the transfer robot is greater than the safety threshold, determining the suspension height adjustment state; Step S3 includes: S31. Coordinate the controller to determine the stability area and divide the control area of ​​the transfer robot: use Phase plane method is used to determine the vehicle stability of the coordinated controller. The phase plane divides the vehicle stability region by two straight lines symmetrical about the origin as boundary lines; The boundary of the stable region is expressed as: Where B1 and B2 are the boundary coefficients of the stable region; When the vehicle's center of mass sideslip angle and center of mass sideslip angle angular velocity satisfy the above formula, the vehicle is considered to be in a stable state; exist The control areas of each controller in the phase plane are divided into: ARS control area, ARS and DYC coordinated control area, and DYC control area; The boundary equation of the stable region divided according to each control region is: Where ρ1 and ρ2 are the control boundary weight coefficients, 0<ρ1<1, ρ2≥1; the smaller ρ1 is, the smaller the ARS independent control area is; the larger ρ2 is, the larger the ARS and DYC coordinated control area is; S32. Detect whether the roll angle is greater than a threshold and determine the suspension height adjustment state: The IMU sensor is used to detect whether the roll angle and pitch angle of the transfer robot are greater than the set safety threshold, so as to determine whether the height of each suspension needs to be adjusted; S4. The coordination controller determines a coordination control weight coefficient and assigns it to the active rear steering controller and the direct yaw moment controller, respectively calculating the required additional rear wheel steering angle and additional yaw moment output. The additional yaw moment is then distributed to each wheel using a dynamic allocation method based on quadratic programming. The suspension height controller then allocates the suspension height adjustment amount. S5. Distribute the additional rear wheel steering angle and additional yaw moment after coordinated control weight coefficient allocation to the steering motor and each wheel hub motor and output them; distribute the suspension height adjustment amount allocated to each wheel to each wheel suspension height adjustment motor and output them.

2. A vehicle transfer robot stability control method according to claim 1, characterized in that: The step S1 comprises: From the vehicle's two-degree-of-freedom motion model, the state equation is obtained: Ideal yaw rate γ during steady-state steering d for: in, Limited by the road adhesion coefficient μ, the maximum yaw rate satisfies: In summary, the ideal yaw rate of the vehicle is expressed as: Where, sign is the sign function; k1 and k2 are the lateral stiffness of the front and rear axles respectively; l f 、l m 、l r are the distances from the center of mass to the front axle, intermediate axle, and rear axle respectively; β is the sideslip angle of the center of mass; γ is the yaw rate; u and v are the longitudinal and lateral speeds respectively; δ is the rear wheel turning angle; I Z is the moment of inertia around the Z axis; m is the vehicle mass; L is the wheelbase.

3. A vehicle transfer robot stability control method according to claim 1, characterized in that: The step S21 includes: Considering the effect of the additional yaw moment on the two-degree-of-freedom reference model, the state space equation is obtained: Where k1 and k2 are the lateral stiffness of the front and rear axles respectively, l f 、l m 、l r are the distances from the center of mass to the front axle, intermediate axle, and rear axle, β is the sideslip angle of the center of mass, γ is the yaw rate, u and v are the longitudinal and lateral speeds, δ is the rear wheel turning angle, and I Z is the moment of inertia around the Z axis, ΔM Z is the additional yaw moment; According to the above formula, we can get: The sliding surface expression of the sliding mode controller is: Where, e = γ - γ d is the yaw rate deviation, λ is a positive weighting coefficient; The derivative is: Further we get: Select the exponential approach rate: Where k>0, -ksgn(s) is the constant speed approaching term, and ε is the speed at which the system approaches stability; Substituting the above expression of exponential approach rate into the vehicle yaw motion model after adding yaw moment, the expression of additional yaw moment is obtained as follows: To reduce chattering, replace the sign function with a saturation function: Where, τ>0 is the boundary layer thickness; Final additional yaw moment ΔM Z The control rate is: Where, k>0,ε>0.

4. A vehicle transfer robot stability control method according to claim 1, characterized in that: The step S22 includes: The sliding surface used for the additional rear wheel steering angle is defined as: Where, e = γ - γ d is the yaw rate deviation, λ is a positive weighting coefficient; The derivative is: From the state equation of the two-degree-of-freedom model, we know: Where k1 and k2 are the lateral stiffness of the front and rear axles respectively, l f 、l m 、l r are the distances from the center of mass to the front axle, intermediate axle, and rear axle, β is the sideslip angle of the center of mass, γ is the yaw rate, u and v are the longitudinal and lateral speeds, δ is the rear wheel turning angle, and I Z is the moment of inertia around the Z axis; Use constant velocity approach rate: The larger the k value, the faster the approach speed and the greater the jitter generated; Combining the above formulas, we get: Use a saturation function instead of a sign function: Δ is the boundary thickness; the final rear wheel steering angle output by the sliding mode control is: At this time, the additional rear wheel turning angle Δδ r is the deviation between the rear wheel steering angle after sliding mode control output and the initial steering angle.

5. The vehicle transfer robot stability control method according to claim 1, characterized in that: The step S4 comprises: S41. The coordinated controller determines the coordinated control weight coefficient and calculates the required additional rear wheel steering angle and additional yaw moment output; S42. A dynamic allocation method based on quadratic programming is used to distribute the additional yaw moment, and the torque difference between each wheel is controlled by the wheel hub motor to form an additional yaw moment around the center of mass; S43. The height adjustment amount of each suspension is based on the tilt direction, and the suspension height controller allocates the corresponding suspension height lifting motor to raise or lower the suspension height.

6. A vehicle transfer robot stability control method according to claim 5, characterized in that: The step S41 includes: The ARS control weight coefficient is defined as λ, and the DYC control weight coefficient is 1-λ; When ARS control is performed alone, λ = 1; When DYC control is performed alone, λ = 0; When ARS and DYC are coordinated, the sigmoid function is used to coordinate the control weight coefficients: The total expression of the ARS control weight coefficient can be obtained: Where B1, B2 are the boundary coefficients of the stable region; ρ1, ρ2 are the weight coefficients of the control region boundary, 0<ρ1<1, ρ2≥1; The additional rear wheel steering angle Δδ after coordinated control allocation is obtained ′ and the additional yaw moment ΔM Z ′ , as follows: The weighted additional yaw moment ΔM is obtained from this z ′ and the weighted additional rear wheel steering angle Δδ ′ , coordinated control of direct yaw moment control and active rear wheel steering control is achieved through the coordinated control coefficient λ.

7. A vehicle transfer robot stability control method according to claim 5, characterized in that: The step S42 includes: Dynamic allocation takes the lowest comprehensive utilization rate of the six wheels or the maximum tire stability margin as the optimization objective function, and uses the quadratic programming algorithm to find the optimal solution; The tire utilization expression is as follows: Where i=1, 2, 3, 4, 5, 6, representing the left and right wheels of the front axle, the left and right wheels of the intermediate axle, and the left and right wheels of the rear axle respectively; Without considering the influence of the tire lateral force, only the longitudinal force of the tire is considered, and the objective function is simplified to: The yaw moment output by the upper controller and the total longitudinal force F of the vehicle X and the motor torque should satisfy the following equality constraints: Where R e is the tire rolling radius; T fl 、T fr ...is the torque of each wheel motor, F xfl 、F xfr ...is the longitudinal force of each wheel, fl, fr, ml, mr, rl, rr are the left and right wheels of the front axle, the left and right wheels of the intermediate axle, and the left and right wheels of the rear axle respectively; d is the wheelbase; The output torque of the drive motor is limited by the peak torque of the motor itself. max Influenced by the road adhesion coefficient, the drive motor torque satisfies the following inequality constraints: The additional yaw moment ΔM Z The formula for stability judgment is transformed into a quadratic programming problem for solution. The standard form of quadratic programming is: min J=x T Wx; where ω = [F X ΔM Z T , u = [T fl T fr T ml T mr T rl T rr T ,​​ The above quadratic programming problem is solved by the interior point algorithm to obtain the torque distribution results of each wheel.

8. The vehicle transfer robot stability control method according to claim 5, characterized in that: The step S43 includes: The suspension height adjustment motor adjusts the suspension height of each wheel in real time to keep the vehicle body roll angle within a safe range; Δφ=φ r -φ0; Where Δφ is the difference between the vehicle body roll angle and the safety threshold, φ r is the roll angle of the vehicle body, φ0 is the safety threshold of the roll angle; The roll angle is defined as positive in the counterclockwise direction and negative in the clockwise direction along the vehicle head. When Δφ>0, the left suspension height is increased and the right suspension height is decreased. When Δφ<0, the right suspension height is increased and the left suspension height is decreased. Adjustment of suspension height: Δh=dtanΔφ≈dΔφ; Where d is the wheelbase, Δh is the suspension height adjustment; After the suspension height distribution controller receives the required suspension height adjustment amount Δh from the suspension height controller, the suspension height distribution amount of each wheel is as follows: Where, Δ, They are the high-speed adjustment values ​​of the suspension for the front axle, intermediate axle and rear axle respectively; 1 and 2 represent the left and right wheels respectively.

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