Steering control method of a wire-controlled hydraulic steering system for a rear axle of a multi-axle steering vehicle

Abstract

The present invention discloses a steering control method for a wire-controlled hydraulic steering system of a rear axle of a multi-axle steering vehicle, wherein the wire-controlled steering system mainly comprises a hydraulic module and an electronic control module, wherein a control module ECU in the electronic control module collects sensor signals in the wire-controlled hydraulic steering system; and by collecting sensor information and a set control algorithm, the control module ECU outputs a voltage signal to indirectly drive a centering self-locking oil cylinder to push or pull back a steering tie rod, or to keep the steering tie rod in a certain state, so as to change the turning angle of the wheel, thereby realizing the steering control of the tire, improving and enhancing the steering wear resistance of the third axle and the handling stability of the whole vehicle; when the wire-controlled steering system fails, the steering wheel of the third axle is controlled to be in a centering locked state and no longer changes with the change of the turning angle of the first axle, so as to ensure the safety of the vehicle.

Description

Technical Field

[0001] The invention belongs to the technical field of automobile steering, and in particular relates to a method for controlling steering wear resistance and handling stability of a rear axle-controlled hydraulic steering system of a multi-axle steering vehicle. Background Art

[0002] Multi-axle steering vehicles offer advantages such as flexible movement, multiple degrees of freedom, and good maneuverability. Current research on multi-axle vehicle steering focuses on the following areas: vehicle steering mode research; steering system structural optimization design; and hydraulic steering system research. Hydraulic steering systems for multi-axle vehicles primarily consist of full hydraulic steering and hydraulic power steering. With the advancement of modern electronic technology, some researchers have proposed combining steer-by-wire and full hydraulic steering technologies to develop hydraulic steer-by-wire systems. Hydraulic steer-by-wire systems eliminate the need for a mechanical steering shaft and instead utilize an electronic control unit (ECU), sensors, and valve-controlled steering thrust cylinders to achieve steer-by-wire control. These systems also offer advantages such as flexible control of steering force based on vehicle speed and steering wheel angle. To reduce R&D and manufacturing costs, domestic commercial vehicle manufacturers typically utilize mechanical hydraulic steering for general multi-axle heavy-duty vehicles. This system transmits the hydraulic steering force from the front steering shaft of the cab to the rear steering shaft of the cargo compartment via a steering transmission system, controlling the steering wheel angle of the rear steering shaft to achieve responsive steering with the front steering shaft. However, the rear steering axle in the cargo compartment at the rear of the vehicle is far away from the front steering axle of the cab, and the steering transmission rod system has low stiffness, which makes it prone to deformation and vibration, resulting in increased wear of the rear axle tires and worse vehicle handling stability. Summary of the Invention

[0003] The present invention aims to address the deficiencies of the above-mentioned prior art and proposes a steering control method for a wire-controlled hydraulic steering system of the rear axle of a multi-axle steering vehicle, in order to improve and enhance the steering wear resistance of the third axle and the handling stability of the entire vehicle, thereby ensuring vehicle safety.

[0004] In order to achieve the above-mentioned object, the present invention adopts the following technical solutions:

[0005] The present invention provides a steering control method for a wire-controlled hydraulic steering system of a rear axle of a multi-axle steering vehicle, wherein the wire-controlled hydraulic steering system of the rear axle of the multi-axle steering vehicle comprises: a mechanical transmission module, a hydraulic module, and an electronic control module;

[0006] The mechanical transmission module includes: axles and steering tie rods; the hydraulic module includes: a hydraulic oil pump, a centering self-locking cylinder, a fuel tank, a fine filter, a coarse filter, a relief valve, a one-way valve, two three-position four-way proportional reversing valves, and three two-position four-way solenoid valves;

[0007] The high-pressure end of the hydraulic oil pump is connected to one end of the one-way valve and the overflow valve respectively; the low-pressure end of the hydraulic oil pump is connected to the oil outlet of the coarse filter, and the oil inlet of the coarse filter is connected to the fuel tank; the other end of the one-way valve is connected to the oil inlet of the fine filter; the oil outlet of the fine filter flows directly to two proportional reversing valves and indirectly to the other two solenoid valves through one solenoid valve; one end of the centering self-locking cylinder is connected to the axle, and the other end is connected to the steering tie rod through a connecting rod;

[0008] The electronic control module includes: a control module ECU, an acceleration sensor, a vehicle speed sensor, a third-axis rotation angle sensor, a first-axis rotation angle sensor, and a yaw rate sensor; wherein the acceleration sensor is used to measure the lateral acceleration of the vehicle; the vehicle speed sensor is used to measure the vehicle speed; the first and third-axis rotation angle sensors are used to measure the rotation angles of the front and rear axles of the multi-axis steering vehicle, respectively; and the yaw rate sensor is used to measure the yaw rate of the vehicle. The control method is characterized in that the control method includes the following steps:

[0009] Step 1. The control module ECU collects the front axle angle signal, vehicle speed signal, and lateral acceleration signal a y , yaw rate signal, and judge whether the wire-controlled hydraulic steering system is working normally. If it is working normally, go to step 3; if a fault or abnormality is detected, go to step 2;

[0010] Step 2. Control the two proportional reversing valves to be in the cut-off state, so that the oil flows into the centering self-locking cylinder through the three solenoid valves, thereby centering and locking the steering wheels of the rear axle of the multi-axle steering vehicle, and ending the process;

[0011] Step 3. When the lateral acceleration signal a y ≤p1×g, then go to step 4;

[0012] When the lateral acceleration a y >p1×g, then go to step 5; where g is the acceleration due to gravity; p1 represents the lateral angular velocity threshold parameter, and p1∈[0.1,0.4];

[0013] Step 4. Taking the steering wear resistance of the rear axle of the multi-axle steering vehicle as the control target, calculate the target turning angle δ of the rear axle of the multi-axle steering vehicle 3d , and proceed to step 6;

[0014] Step 5. Taking the steering stability of the multi-axle steering vehicle as the control target, the linear time-varying model predictive controller LTV-MPC is used to calculate the target steering angle δ of the rear axle of the multi-axle steering vehicle 3d , and proceed to step 6;

[0015] Step 6: The angle sensor feeds back the actual angle δ3 of the rear axle wheel of the multi-axis steering vehicle to the control module ECU, so that the control module ECU can adjust the angle according to the target angle δ3. 3d The fuzzy PID control method is used to calculate the control electrical signals of the two proportional control valves based on the actual steering angle δ3, thereby realizing closed-loop feedback control of the rear axle steering angle of the multi-axis steering vehicle.

[0016] The steering control method of the wire-controlled hydraulic steering system for the rear axle of a multi-axle steering vehicle of the present invention is characterized in that: in step 4, the target turning angle δ of the rear axle of the multi-axle steering vehicle is calculated using formula (1) 3d :

[0017]

[0018] In formula (1), L3 is the wheelbase between the third and fourth axles; L is the wheelbase of the vehicle; δ1 is the turning angle of the front axle of the multi-axle steering vehicle.

[0019] The step 5 comprises:

[0020] Step 5.1. Use equation (2) to construct the linearized tire force equation:

[0021]

[0022] In formula (2): F Yi is the lateral force of the tire on the i-th axle, α i is the sideslip angle of the tire on the i-th axle, is the current slip angle of the tire on the i-th axle The nominal cornering stiffness at is obtained by equation (4); is the residual lateral force of the tire on the i-th axle and is obtained from formula (3); i=1,2,3,4;

[0023]

[0024] In formula (3): Indicates the current slip angle of the tire on the i-th axle lateral force at ;

[0025] Step 5.2. Calculate the ideal tracking parameters for multi-axle vehicle handling stability control using equation (4):

[0026]

[0027] In formula (4), ω rd is the ideal yaw rate; β d is the ideal center of mass sideslip angle; represents the reference yaw rate; β * represents the reference center of mass sideslip angle; ω rmaxrepresents the maximum yaw angular velocity; β max represents the maximum center of mass sideslip angle; sgn() represents the sign function, and has:

[0028]

[0029]

[0030]

[0031]

[0032] In formulas (5) to (8), p2 is the maximum yaw rate parameter; p3 is the maximum center of mass sideslip angle parameter; a 11 、a 12 、a 21 、a 22 are four matrix elements respectively; b 11 、b 12 、b 13 、b 21 、b 22 、b 23 are six matrix elements respectively; m is the vehicle mass; ω r is the vehicle's yaw rate; u and v represent the components of the vehicle's center of mass velocity on the x and y axes, respectively; l1, l2, l3, and l4 are the distances from the first, second, third, and fourth axes to the vehicle's center of mass, respectively; δ2 and δ3 represent the second and third axis rotation angles, respectively; I z is the moment of inertia of the car around the z-axis; β is the sideslip angle of the car's center of mass; μ is the road adhesion coefficient; the fourth axis is the rearmost axis of the vehicle;

[0033] Step 5.3. Use Equation (9) to construct the rolling optimization model of the linear time-varying model predictive controller LTV-MPC for multi-axis vehicle handling stability control, and use the quadratic programming method to solve the rolling optimization model to obtain the target turning angle δ 3d ;

[0034]

[0035] In formula (9), j represents any prediction time domain, and j = 1, 2, 3…, N p , N p is the prediction time domain; k is the discrete sampling time point; u represents the control input, that is, the third axis angle; y is the system output, that is, the center of mass sideslip angle and yaw rate; y(k) represents the system output at time k, that is, the center of mass sideslip angle and yaw rate of the system output at time k; u(k) represents the control input at time k, that is, the third axis angle at time k; Δu(k) represents the increment of the control input at time k, that is, the increment of the third axis angle at time k; u minis the minimum limit of the third axis angle; u max is the maximum limit of the third axis angle; Δu max The maximum limit of the third axis rotation angle increment; y max is the maximum limit of the system's center of mass sideslip angle and yaw rate; ε is the relaxation factor; J LTV-MPC represents the objective function of the rolling optimization model, and has:

[0036]

[0037] In formula (10), Q and R are two weight matrices; ρ is the weight coefficient of the relaxation factor ε; x ref (k) represents the ideal tracking parameter at time k.

[0038] An electronic device of the present invention includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute any of the steering control methods, and the processor is configured to execute the program stored in the memory.

[0039] The present invention provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and the computer program executes any step of the steering control method when executed by a processor.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. The present invention improves the third-axle tire wear resistance and vehicle handling stability during high-speed steering by controlling the third-axle steering wheel angle. A vehicle's steering performance is directly related to vehicle handling stability and tire steering wear. Hydraulic steering by wire combines the advantages of steer-by-wire systems for flexible steering with the advantages of mechanical hydraulic steering systems for greater steering force. It is highly suitable for multi-axle heavy-duty vehicles. Furthermore, on multi-axle steering vehicles with rear axles that are farther from the front axle, the use of hydraulic steering by wire eliminates the need for a road feel feedback module.

[0042] 2. The control method proposed by this invention uses lateral acceleration as a threshold to calculate the target steering wheel angle of the third axle in the upper-level control layer. The lower-level controller is used to track and implement the third axle steering angle control. When the actual vehicle lateral acceleration exceeds the set threshold, vehicle handling stability is the control target; otherwise, steering wear resistance is the control target. This improves vehicle steering stability while minimizing tire wear during steering.

[0043] 3. The present invention is designed with a safety redundancy system. The hydraulic system of the embodiment has a normal working oil circuit and a redundant oil circuit. Under normal circumstances, the hydraulic system operates in the normal working oil circuit. Once the electronic control system detects a fault or abnormality, it controls the redundant system and the oil cylinder to make the third-axle steering wheel enter the centering self-locking state. The hydraulic system operates in the redundant oil circuit. At this time, the third-axle tire does not follow the front axle steering, ensuring the safety of the vehicle.

[0044] 4. The present invention can not only realize the rapid and accurate steering of the third-axle steering wheel under low-speed safe driving conditions and reduce tire wear, but also realize the high-speed driving handling stability control without the need for additional hardware, thereby realizing the active safety of the vehicle and having a high cost-effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a schematic diagram of the structure of the wire-controlled hydraulic steering system involved in the present invention;

[0046] Figure 2 It is a schematic diagram of the steering control method of the present invention;

[0047] Figure 3 This is the LTV-MPC control principle diagram of the present invention;

[0048] Numbers in the figure: 1. Acceleration sensor; 2. First shaft angle sensor; 3. Third shaft left steering wheel; 4. Steering tie rod; 5. Axle; 6. Centering self-locking cylinder A1 oil port; 7. Centering self-locking cylinder B1 oil port 2; 8. Centering self-locking cylinder A2 oil port 1; 9. Centering self-locking cylinder B2 oil port 2; 10. Centering self-locking cylinder; 11. Proportional valve A; 12. Proportional valve B; 13. Solenoid valve A; 14. Solenoid valve B; 15. Solenoid valve C; 16. Fine filter; 17. One-way valve; 18. Hydraulic oil pump; 19. Coarse filter; 20. Fuel tank; 21. Overflow valve; 22. First shaft left steering wheel; 23. Third shaft angle sensor; 24. Vehicle speed sensor; 25. Electronic control unit ECU; 26. Yaw angular velocity sensor. DETAILED DESCRIPTION

[0049] In this embodiment, the wire-controlled hydraulic steering system of the rear axle of the multi-axle steering vehicle is as follows: Figure 1 Shown include: mechanical transmission module, hydraulic module, electronic control module;

[0050] The mechanical transmission module includes: axles and steering tie rods; the hydraulic module includes: hydraulic oil pump, centering self-locking cylinder, oil tank, fine filter, coarse filter, relief valve, one-way valve, two three-position four-way proportional reversing valves, and three two-position four-way solenoid valves;

[0051] The high-pressure end of the hydraulic oil pump is connected to one end of the one-way valve and the relief valve respectively; the low-pressure end of the hydraulic oil pump is connected to the oil outlet of the coarse filter, and the oil inlet of the coarse filter is connected to the fuel tank; the other end of the one-way valve is connected to the oil inlet of the fine filter; the oil outlet of the fine filter flows directly to two proportional reversing valves and indirectly to two other solenoid valves through one solenoid valve; one end of the centering self-locking cylinder is connected to the axle, and the other end is connected to the steering tie rod through a connecting rod;

[0052] The electronic control module includes: a control module ECU, an acceleration sensor, a vehicle speed sensor, a third-axis rotation angle sensor, a first-axis rotation angle sensor, and a yaw rate sensor; wherein the acceleration sensor is used to measure the lateral acceleration of the vehicle; the vehicle speed sensor is used to measure the vehicle speed; the first-axis and third-axis rotation angle sensors are used to measure the rotation angles of the front and rear axles of the multi-axis steering vehicle, respectively; and the yaw rate sensor is used to measure the yaw rate of the vehicle;

[0053] A steering control method for a wire-controlled hydraulic steering system of a rear axle of a multi-axle steering vehicle, such as Figure 2 The following steps are shown:

[0054] Step 1. The control module ECU collects the front axle angle signal, vehicle speed signal, and lateral acceleration signal a y , yaw rate signal, and judge whether the wire-controlled hydraulic steering system is working normally. If it is working normally, go to step 3; if a fault or abnormality is detected, go to step 2;

[0055] Step 2. Control the two proportional reversing valves to the cut-off state, allowing the oil to flow through the three solenoid valves into the centering self-locking cylinder, thereby centering and locking the steering wheels of the rear axle of the multi-axis steering vehicle, ending the process;

[0056] Step 3. When the lateral acceleration signal a y ≤p1×g, then go to step 4;

[0057] When the lateral acceleration a y >p1×g, then go to step 5; where g is the acceleration due to gravity; p1 represents the lateral angular velocity threshold parameter, and p1∈[0.1,0.4];

[0058] Step 4. Taking the steering wear resistance of the rear axle of the multi-axle steering vehicle as the control target, use formula (1) to calculate the target steering angle δ of the rear axle of the multi-axle steering vehicle 3d , and proceed to step 6;

[0059]

[0060] In formula (1), L3 is the wheelbase between the third and fourth axles; L is the wheelbase of the vehicle; δ1 is the turning angle of the front axle of the multi-axle steering vehicle.

[0061] Step 5. Taking the steering stability of the multi-axle steering vehicle as the control target, construct LTV-MPC and calculate the target steering angle δ of the rear axle of the multi-axle steering vehicle 3d ;

[0062] Step 5.1. Calculate the ideal tracking parameters for multi-axle vehicle handling stability control using equation (2):

[0063]

[0064] In formula (2), ω rd is the ideal yaw rate; β d is the ideal center of mass sideslip angle; represents the reference yaw rate; β * represents the reference center of mass sideslip angle; ω rmax represents the maximum yaw angular velocity; β max Indicates the maximum center of mass sideslip angle; sgn() represents the sign function; β * 、ω rmax , β max From equations (3) to (6), we can obtain:

[0065]

[0066]

[0067]

[0068]

[0069] In formula (3) to formula (6), p2 is the maximum yaw rate parameter, which is 0.85 in this embodiment; p3 is the maximum center of mass sideslip angle parameter, which is 0.02 in this embodiment; I z is the moment of inertia of the car around the z-axis; μ is the road adhesion coefficient; k1, k2, k3, k4 represent the lateral stiffness of the tires on the 1st, 2nd, 3rd, and 4th axles respectively; a 11 、a 12 、a 21 、a 22 are intermediate variables 1, 2, 3, and 4 respectively; b 11 、b 12 、b 13 、b 21 、b 22 、b 23 are intermediate variables 5, 6, 7, 8, 9, and 10 respectively; m is the mass of the vehicle; u represents the forward speed of the vehicle; l1, l2, l3, and l4 are the distances from the first, second, third, and fourth axes to the center of mass of the vehicle respectively; the fourth axis is the rearmost axis of the vehicle; I zis the moment of inertia of the car around the z-axis;

[0070] Step 5.2. Use equation (7) to construct the linearized tire force equation:

[0071]

[0072] In formula (7): F Yi is the lateral force of the tire on the i-th axle, α i is the sideslip angle of the tire on the i-th axle, is the current slip angle of the tire on the i-th axle The nominal cornering stiffness at is obtained by equation (4); is the residual lateral force of the tire on the i-th axle and is obtained from formula (3); i=1,2,3,4;

[0073]

[0074] In formula (8): Indicates the current slip angle of the tire on the i-th axle lateral force at ;

[0075] Step 5.3. Figure 3 The LTV-MPC (Linear Time-Varying Model Predictive Controller) control principle shown in the figure calculates the incremental discrete prediction model of LTV-MPC;

[0076] Combined with step 5.2, the continuous prediction model of LTV-MPC for multi-axis vehicle handling stability control at time t can be expressed in the form of state space equation as Equation (9):

[0077]

[0078] In formula (9): x = [β, ω r ] is the state variable, β is the vehicle's center of mass side slip angle; ω r is the vehicle yaw rate; u is the control input, i.e. u = [δ3]; the interference input matrix y is the system output. Output matrix C x and the state matrix A x , input matrix B u And the interference input matrix B d As shown in formulas (10) to (13):

[0079]

[0080]

[0081]

[0082]

[0083] In formulas (10) to (13): They are intermediate variables 11, 12, 13, and 14 respectively; They are intermediate variables 15, 16, 17, 18, 19, and 20;

[0084] Intermediate variables 11 to 20 are calculated using equations (14) and (15):

[0085]

[0086]

[0087] Discretize Equation (9) with a discrete step length of T s , k is a discrete sampling point. Let the increment of the state variable at the k sampling point be Δx(k), x(k) is the state variable at the k sampling point, and x(k-1) is the state variable at the k-1 sampling point, then Δx(k)=x(k)-x(k-1); let the increment of the control input at the k sampling point be Δu(k), u(k) is the control input at the k sampling point, and u(k-1) is the control input at the k-1 sampling point, then Δu(k)=u(k)-u(k-1); let the increment of the interference input at the k sampling point be Δd(k), d(k) is the interference input at the k sampling point, and d(k-1) is the interference input at the k-1 sampling point, then Δd(k)=d(k)-d(k-1), d(k) is the interference input at the k sampling point, and d(k-1) is the interference input at the k-1 sampling point. Thus, the incremental discrete prediction model of the system shown in Equation (16) can be obtained:

[0088]

[0089] In formula (16), y(k) is the system output at sampling point k, i.e., the sideslip angle and yaw rate of the center of mass; y(k-1) is the system output at sampling point k-1; is the discretized state matrix, is the discretized input matrix; is the discretized interference input matrix.

[0090] Step 5.4. Figure 3 The LTV-MPC control principle shown in the figure calculates the predicted output of LTV-MPC;

[0091] According to the working principle of LTV-MPC, the incremental discrete prediction model based on equation (16) in step 5.3 is used to predict the future state of the system. Assuming that the control time domain N c In addition, the control input remains unchanged, and the prediction time domain N can be obtained from formula (16) pThe system predicts the output of It can be expressed in matrix form as formula (17):

[0092]

[0093] In formula (17): is vector 1, as in formula (18); ΔU is vector 2, as in formula (19); S x is the coefficient matrix 1, as shown in formula (20); S u is the coefficient matrix 2, as shown in formula (21); S d is the coefficient matrix 3, as shown in formula (22); S y is the coefficient matrix 4, as shown in formula (23).

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100] Step 5.5. Figure 3 The LTV-MPC control principle shown in Figure 2 is used to construct the rolling optimization model of the multi-axis vehicle handling stability controller LTV-MPC using Equation (24). The rolling optimization model of the multi-axis vehicle handling stability control is solved using the quadratic programming method to obtain the target turning angle δ 3d ;

[0101]

[0102] In formula (24), j represents any prediction time domain, and j = 1, 2, 3…, N p , N p is the prediction time domain; u min is the minimum limit of the third axis angle; u max is the maximum limit of the third axis angle; Δu max The maximum limit of the third axis rotation angle increment; y max is the maximum limit of the system's center of mass sideslip angle and yaw rate; ε is the relaxation factor; J LTV-MPC The LTV-MPC optimization objective function of multi-axle vehicle handling control is expressed as follows:

[0103]

[0104] In formula (24), Q = dig{q1,q2} and R = dig{r} are weight matrices; dig{} is a diagonal matrix function; ρ is the weight coefficient of the relaxation factor ε; q1, q2, and r represent the three weight values ​​of the weight matrix; x(k) is the state variable of the system at time k, that is, the sideslip angle and yaw rate of the vehicle at time k; x ref (k) represents the ideal tracking parameter at time k.

[0105] Step 6. The angle sensor feeds back the actual angle δ3 of the rear axle wheel of the multi-axis steering vehicle to the control module ECU, so that the control module ECU can adjust the angle according to the target angle δ3. 3d The fuzzy PID control method is used to calculate the control electrical signals of the two proportional control valves based on the actual steering angle δ3, thereby realizing closed-loop feedback control of the rear axle steering angle of the multi-axis steering vehicle.

[0106] Let e ​​= δ 3d -δ3 is the target turning angle δ 3d The angle error from the actual angle δ3, ec is the rate of change of the angle error, ΔK p , ΔK i , ΔK d is the PID incremental adjustment parameter, the fuzzy control input is e and ec, and the output is ΔK p , ΔK i , ΔK d First, fuzzify e and ec and input the processed data into the fuzzy controller; after fuzzification, fuzzy reasoning and clarification, ΔK is obtained. p , ΔK i , ΔK d , and then get the new PID control parameter value.

[0107] Step 6.1. Determine the fuzzy domain: domain of e, ec: [-3, 3]; ΔK p The domain of discourse is [-2,2]; ΔK i The domain of discourse is [-1,1]; ΔK d The domain of is [-0.05,0.05].

[0108] Step 6.2. Determine the fuzzy set: The fuzzy control input and output fuzzy set is {NB, NM, NS, ZE, PS, PM, PB}, which represent {negative large, negative medium, negative small, zero, positive small, positive medium, positive large} respectively.

[0109] Step 6.3. Determine the membership function: triangular membership function.

[0110] Step 6.4. Establish fuzzy rules;

[0111] ΔK p , ΔK i, ΔK d The fuzzy rules are shown in Table 1-Table 3.

[0112] Table 1ΔK p Fuzzy rules

[0113]

[0114] Table 2ΔK i Fuzzy rules

[0115]

[0116] Table 3ΔK d Fuzzy rules

[0117]

[0118]

[0119] In this embodiment, an electronic device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0120] In this embodiment, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are executed.

[0121] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A steering control method for a wire-controlled hydraulic steering system for a rear axle of a multi-axle steering vehicle, the wire-controlled hydraulic steering system for the rear axle of the multi-axle steering vehicle comprising: Mechanical transmission module, hydraulic module, electronic control module; The mechanical transmission module includes: axles and steering tie rods; the hydraulic module includes: a hydraulic oil pump, a centering self-locking cylinder, a fuel tank, a fine filter, a coarse filter, a relief valve, a one-way valve, two three-position four-way proportional reversing valves, and three two-position four-way solenoid valves; The high-pressure end of the hydraulic oil pump is connected to one end of the one-way valve and the overflow valve respectively; the low-pressure end of the hydraulic oil pump is connected to the oil outlet of the coarse filter, and the oil inlet of the coarse filter is connected to the fuel tank; the other end of the one-way valve is connected to the oil inlet of the fine filter; the oil outlet of the fine filter flows directly to two proportional reversing valves and indirectly to the other two solenoid valves through one solenoid valve; one end of the centering self-locking cylinder is connected to the axle, and the other end is connected to the steering tie rod through a connecting rod; The electronic control module includes: a control module ECU, an acceleration sensor, a vehicle speed sensor, a third-axis rotation angle sensor, a first-axis rotation angle sensor, and a yaw rate sensor; wherein the acceleration sensor is used to measure the lateral acceleration of the vehicle; the vehicle speed sensor is used to measure the vehicle speed; the first and third-axis rotation angle sensors are used to measure the rotation angles of the front and rear axles of the multi-axis steering vehicle, respectively; and the yaw rate sensor is used to measure the yaw rate of the vehicle; and the control method includes the following steps: Step 1. The control module ECU collects the front axle angle signal, vehicle speed signal, and lateral acceleration signal a y , yaw rate signal, and judge whether the wire-controlled hydraulic steering system is working normally. If it is working normally, go to step 3; if a fault or abnormality is detected, go to step 2; Step 2. Control the two proportional reversing valves to be in the cut-off state, so that the oil flows into the centering self-locking cylinder through the three solenoid valves, thereby centering and locking the steering wheels of the rear axle of the multi-axle steering vehicle, and ending the process; Step 3. When the lateral acceleration signal a y ≤p1×g, then go to step 4; When the lateral acceleration a y >p1×g, then go to step 5; where g is the acceleration due to gravity; p1 represents the lateral angular velocity threshold parameter, and p1∈[0.1,0.4]; Step 4. Taking the steering wear resistance of the rear axle of the multi-axle steering vehicle as the control target, calculate the target turning angle δ of the rear axle of the multi-axle steering vehicle 3d , and proceed to step 6; Step 5. Taking the steering stability of the multi-axle steering vehicle as the control target, the linear time-varying model predictive controller LTV-MPC is used to calculate the target steering angle δ of the rear axle of the multi-axle steering vehicle 3d , and proceed to step 6; Step 6: The angle sensor feeds back the actual angle δ3 of the rear axle wheel of the multi-axis steering vehicle to the control module ECU, so that the control module ECU can adjust the angle according to the target angle δ3. 3d The fuzzy PID control method is used to calculate the control electrical signals of the two proportional control valves based on the actual steering angle δ3, thereby realizing closed-loop feedback control of the rear axle steering angle of the multi-axis steering vehicle.

2. The steering control method of the wire-controlled hydraulic steer system for the rear axle of a multi-axle steering vehicle according to claim 1, characterized in that: In step 4, the target turning angle δ of the rear axle of the multi-axle steering vehicle is calculated using formula (1): 3d : In formula (1), L3 is the wheelbase between the third and fourth axles; L is the wheelbase of the vehicle; δ1 is the turning angle of the front axle of the multi-axle steering vehicle.

3. The steering control method of a wire-controlled hydraulic steer-by-wire system for a rear axle of a multi-axle steering vehicle according to claim 1, namely, a linear time-varying model predictive controller (LTV-MPC), is characterized by: The step 5 comprises: Step 5.

1. Use equation (2) to construct the linearized tire force equation: In formula (2): F Yi is the lateral force of the tire on the i-th axle, α i is the sideslip angle of the tire on the i-th axle, is the current slip angle of the tire on the i-th axle The nominal cornering stiffness at is obtained by equation (4); is the residual lateral force of the tire on the i-th axle and is obtained from formula (3); i=1,2,3,4; In formula (3): Indicates the current slip angle of the tire on the i-th axle lateral force at ; Step 5.

2. Calculate the ideal tracking parameters for multi-axle vehicle handling stability control using equation (4): In formula (4), ω rd is the ideal yaw rate; β d is the ideal center of mass sideslip angle; represents the reference yaw rate; β * represents the reference center of mass sideslip angle; ω rmax represents the maximum yaw angular velocity; β max represents the maximum center of mass sideslip angle; sgn() represents the sign function, and has: In formulas (5) to (8), p2 is the maximum yaw rate parameter; p3 is the maximum center of mass sideslip angle parameter; a 11 、a 12 、a 21 、a 22 are four matrix elements respectively; b 11 、b 12 、b 13 、b 21 、b 22 、b 23 are six matrix elements respectively; m is the vehicle mass; ω r is the vehicle's yaw rate; u and v represent the components of the vehicle's center of mass velocity on the x and y axes, respectively; l1, l2, l3, and l4 are the distances from the first, second, third, and fourth axes to the vehicle's center of mass, respectively; δ2 and δ3 represent the second and third axis rotation angles, respectively; I z is the moment of inertia of the car around the z-axis; β is the sideslip angle of the car's center of mass; μ is the road adhesion coefficient; the fourth axis is the rearmost axis of the vehicle; Step 5.

3. Use Equation (9) to construct the rolling optimization model of the linear time-varying model predictive controller LTV-MPC for multi-axis vehicle handling stability control, and use the quadratic programming method to solve the rolling optimization model to obtain the target turning angle δ 3d ; In formula (9), j represents any prediction time domain, and j = 1, 2, 3…, N p , N p is the prediction time domain; k is the discrete sampling time point; u represents the control input, that is, the third axis angle; y is the system output, that is, the center of mass sideslip angle and yaw rate; y(k) represents the system output at time k, that is, the center of mass sideslip angle and yaw rate of the system output at time k; u(k) represents the control input at time k, that is, the third axis angle at time k; Δu(k) represents the increment of the control input at time k, that is, the increment of the third axis angle at time k; u min is the minimum limit of the third axis angle; u max is the maximum limit of the third axis angle; Δu max The maximum limit of the third axis rotation angle increment; y max is the maximum limit of the system's center of mass sideslip angle and yaw rate; ε is the relaxation factor; J LTV-MPC represents the objective function of the rolling optimization model, and has: In formula (10), Q and R are two weight matrices; ρ is the weight coefficient of the relaxation factor ε; x ref (k) represents the ideal tracking parameter at time k.

4. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the steering control method according to any one of claims 1 to 3, and the processor is configured to execute the program stored in the memory.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the steering control method according to any one of claims 1 to 3 are executed.

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