Vehicle state estimation method of drive-by-wire electro-hydraulic steering system fusing steering resistance torque and dynamic model

Abstract

The invention provides a vehicle state estimation method for a drive-by-wire electro-hydraulic steering system by fusing a steering resistance torque and a dynamic model, which comprises the following steps of: firstly, calculating to obtain an equivalent steering resistance torque based on steering dynamics according to an electric power-assisted torque of an electric power-assisted subsystem and a hydraulic force of a hydraulic power-assisted subsystem in the drive-by-wire electro-hydraulic steering system; secondly, obtaining a state equation of a vehicle state estimation system based on a transverse and yawing two-degree-of-freedom vehicle dynamics model, and obtaining an observation equation based on an equivalent steering resistance moment of steering dynamics; and finally, discretizing the state equation and the observation equation of the vehicle state estimation system to obtain the state equation and the measurement equation of the Kalman filtering algorithm, and estimating the transverse speed, the yaw velocity and the side slip angle of the vehicle in combination with the prediction and updating steps of the Kalman filtering algorithm.

Description

[0001] This invention belongs to the field of intelligent vehicle state estimation, and particularly relates to a vehicle state estimation method for a steer-by-wire electro-hydraulic steering system that integrates steering resistance torque and dynamic model. Background Technology

[0002] Accurate acquisition of vehicle state signals is a core prerequisite for vehicle motion planning and dynamic control, and its measurement accuracy directly determines the response performance and safety boundaries of the control system. However, vehicle state signals characterizing lateral stability, such as sideslip angle and yaw rate, are difficult to obtain directly through onboard sensors, while high-precision sensors cannot meet mass production requirements due to their high cost and poor environmental adaptability. Therefore, it is necessary to design low-cost, highly reliable vehicle state estimation algorithms to replace direct measurement schemes and provide real-time, accurate state input to the motion control layer.

[0003] Existing vehicle state estimation algorithms mostly construct state-space equations based on vehicle dynamics models, achieving state estimation by fusing kinematic measurements (such as acceleration) with model predictions. However, these methods only reflect the overall motion trend of the vehicle and cannot perceive changes in the tire-road contact state. This leads to significant deviations between the algorithm's estimation results and the actual state under extreme conditions such as low-adhesion surfaces (e.g., icy or flooded surfaces) and split surfaces (e.g., ice on the left and asphalt on the right), resulting in erroneous control command triggering or response lag. Therefore, developing a vehicle state estimation method that combines high accuracy and strong robustness has become a critical issue. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a vehicle state estimation method for steerable electro-hydraulic steering systems that integrates steering resistance torque and dynamics models.

[0005] A method for estimating vehicle state in a steerable electro-hydraulic steering system by integrating steering resistance torque and a dynamic model, characterized by comprising the following steps:

[0006] Step S1: Obtain the current of the steering motor from the current sensor, and then calculate the electric assist torque of the electric power assist subsystem.

[0007] Step S2: Calculate the hydraulic pressure of the hydraulic power assist subsystem based on the pressure difference of the assist oil formed in the left and right chambers of the hydraulic power assist cylinder and the effective area of ​​the hydraulic cylinder piston.

[0008] Step S3: Combine the electric assist torque of the electric power steering subsystem obtained in step S1 with the hydraulic pressure of the hydraulic power steering subsystem obtained in step S2 to obtain the equivalent steering resistance torque.

[0009] Step S4: Based on the state equation and observation equation of the vehicle state estimation system, the lateral speed, yaw rate and centroid sideslip angle of the vehicle are estimated using the Kalman filter algorithm.

[0010] In a preferred embodiment, in step S4, the state equation of the vehicle state estimation system is:

[0011]

[0012] Wherein, the state variable of the vehicle state estimation system is x = [v y ω r ] Τ The input quantity is u = δ f ,

[0013]

[0014] In the formula, k1 and k2 represent the equivalent sideslip stiffness of the front and rear wheels, respectively, β is the sideslip angle of the vehicle's center of gravity, and v x For longitudinal vehicle speed, ω r Let m be the yaw rate of the vehicle, and I be the mass of the vehicle. z Let be the moment of inertia of the vehicle about the z-axis, and a and b represent the distances from the vehicle's center of mass to the front and rear axles, respectively.

[0015] The observation equations for the vehicle state estimation system are:

[0016]

[0017] in,

[0018] ε1=Rtan(γ)

[0019]

[0020] In the formula, R is the static radius of the wheel, γ is the caster angle, ξ is the tire contact patch length, ε1 is the mechanical drag torque, ε2 is the tire drag torque, D is the inward displacement of the kingpin, θ is the inward inclination angle of the kingpin, g is the acceleration due to gravity, and h is the height of the vehicle's center of gravity.

[0021] In a preferred embodiment, step S4, which estimates the vehicle's lateral speed, yaw rate, and sideslip angle based on the Kalman filter algorithm, includes the following steps:

[0022] Step S4.1: Discretize the state equation and observation equation of the vehicle state estimation system to obtain the state equation and measurement equation of the Kalman filter algorithm, as shown below:

[0023]

[0024] In the formula, x kLet A be the current state of the target (vehicle speed, angle, etc.), and let A be the state transition matrix.

[0025] B is the control input matrix. u k-1 To control the input, w k-1 For process noise, z k To estimate the steering resistance torque based on steering dynamics, z k =T p H is the observation matrix. v k For measuring noise;

[0026] Step S4.2: Initialize the parameters in the Kalman filter, as shown below:

[0027]

[0028] In the formula, x0 is the initial value of the state variable. Let P0 be the mean of the state variables, and let P0 be the initial covariance matrix of the state variables.

[0029] Step S4.3: Based on the state variables predicted at time k-1, obtain the prior estimate. The calculation formula is as follows:

[0030]

[0031] In the formula, The prior estimate of the state variables at time k is given. The estimated results of the state variables at time k-1;

[0032] Step S4.4: Based on the covariance P at time k-1 k-1 The covariance matrix of the prior error is obtained, and the calculation formula is shown below:

[0033]

[0034] In the formula, Let P be the covariance matrix of the prior error at time k. k-1 Let Q be the covariance matrix and w be the process noise. k-1 The covariance matrix;

[0035] Step S4.5: Based on the covariance matrix of the prior error at time k in step S4.4... Observation matrix H and observation noise v k-1 The Kalman gain can be calculated from the covariance matrix R, as shown in the following formula:

[0036]

[0037] In the formula, Kk Kalman gain;

[0038] Step S4.6: Using the Kalman gain calculated in step S4.5, calculate the optimal estimates of the lateral speed and yaw rate at the current moment. The calculation formula is as follows:

[0039]

[0040] Step S4.7: Based on the Kalman gain calculated in step S4.5 and the covariance matrix of the prior error calculated in step S4.4, update the covariance matrix. The formula for calculating the updated covariance matrix is ​​as follows:

[0041]

[0042] In the formula, P k To update the covariance matrix, I is the identity matrix;

[0043] Step S4.8: Based on the lateral velocity estimated by Kalman filtering in step S4.6, the centroid sideslip angle is obtained, and the calculation formula is as follows:

[0044]

[0045] In the formula, The centroid sideslip angle is estimated using Kalman filtering.

[0046] In a preferred embodiment, step S1, the method for calculating the electric assist torque of the electric power assist subsystem, includes the following steps:

[0047] Step S1.1: Obtain the current I of the steering motor from the motor current sensor. m The output torque of the steering motor is calculated using the following formula:

[0048] T m =K m I m

[0049] In the formula, T m K is the output torque of the steering motor. m I is the electromagnetic torque coefficient of the steering motor. m This refers to the current of the steering motor;

[0050] Step S1.2: Calculate the electric assist torque of the electric power steering subsystem. The formula for calculating the electric assist torque is as follows:

[0051] In the formula, J m B is the moment of inertia of the steering motor. m θ is the damping coefficient of the steering motor.m T is the steering motor's rotation angle. a For the electric assist torque of the electric power assist subsystem, i w This is the worm gear transmission ratio.

[0052] In a preferred embodiment, step S2, the method for calculating the hydraulic force of the hydraulic assist subsystem includes the following steps:

[0053] Step S2.1: Calculate the hydraulic oil pump output flow rate based on the hydraulic oil pump flow coefficient and the pump motor speed. The calculation formula is as follows:

[0054] Q s =η p V p w p

[0055] In the formula, Q s η is the output flow rate of the hydraulic oil pump. p V is the mechanical efficiency value. p For hydraulic pump displacement, w p This refers to the oil pump motor speed;

[0056] Step S2.2: Based on the conservation of flow on the left and right sides of the hydraulic cylinder, determine the flow rate of the rotary valve into the left and right chambers of the hydraulic cylinder. The calculation formula is as follows:

[0057]

[0058] In the formula, Q L1 Q is the flow rate that flows into the left chamber of the hydraulic cylinder via the rotary valve. L2 A is the flow rate into the right chamber of the hydraulic cylinder via the rotary valve. p x is the effective working area of ​​the piston. p For piston displacement, C i The internal leakage coefficient of the hydraulic cylinder is given by p1 and p2, which are the pressures in the left and right chambers of the hydraulic cylinder, respectively.

[0059] Step S2.3: The electric torque of the electric power assist subsystem is transmitted to the torsion bar in the rotary valve. Based on the torque transmitted by the torsion bar, the rotary valve angle is calculated using the following formula:

[0060]

[0061] In the formula, k s Let θ be the stiffness of the torsion bar in the rotary valve, and Δθ be the rotation angle of the rotary valve.

[0062] Step S2.4: Calculate the opening area of ​​each valve port of the rotary valve based on the rotation angle of the rotary valve. The calculation formula is shown below:

[0063] when The formula for calculating the valve opening area is as follows:

[0064]

[0065] when The formula for calculating the valve opening area is as follows:

[0066]

[0067] In the formula, L1 is the pre-opening gap length of the valve port, r is the valve core radius, and A j (j=1,2,3,4) represents the opening area of ​​each valve port of the rotary valve, W1 represents the axial length of the valve port pre-opening gap, W2 represents the axial length of the short cut, and L2 represents the length of the short cut.

[0068] Step S2.5: Based on the hydraulic pump output flow rate, the flow rate into the left and right chambers of the hydraulic cylinder from the rotary valve, and the opening area of ​​each valve port of the rotary valve, calculate the pressure difference of the booster oil formed in the left and right chambers of the hydraulic booster cylinder. The calculation formula is as follows: Δp=p1-p2

[0069] in,

[0070]

[0071] In the formula, Δp is the pressure difference of the power steering oil formed in the left and right chambers of the hydraulic power steering cylinder, and C d Here, A0 is the orifice flow coefficient, and A0 is the valve opening area when the rotary valve is in the neutral position.

[0072] Step S2.6: Based on the pressure difference of the power assist oil formed in the left and right chambers of the hydraulic power assist cylinder and the effective area of ​​the hydraulic cylinder piston, the hydraulic pressure of the hydraulic power assist subsystem is calculated. The calculation formula is as follows:

[0073] F z =Δp·A p

[0074] The formula for calculating the effective area of ​​the hydraulic cylinder piston is as follows:

[0075]

[0076] In the formula, F z D1 is the hydraulic pressure of the hydraulic power assist subsystem, D2 is the piston diameter, and D3 is the piston push rod diameter.

[0077] In a preferred embodiment, step S3, the method for calculating the equivalent steering resistance torque includes the following steps:

[0078] Step S3.1: Calculate the axial force on the nut in the steering screw-steering nut transmission pair based on the steering screw model. The calculation formula is shown below:

[0079]

[0080] in, In the formula, T L In the steering screw-steering nut drive pair, the screw transmits torque, J s2 B is the equivalent moment of inertia of the steering input shaft. s2 θ is the viscous damping coefficient of the steering input shaft. s2 For the steering screw rotation angle, F L L represents the axial force on the nut in the steering screw-steering nut transmission pair, and L represents the lead in the steering screw-steering nut transmission pair.

[0081] Step S3.2: Calculate the force acting on the rocker arm shaft gear sector. The calculation formula is as follows:

[0082]

[0083] In the formula, M p For the mass of the steering nut, B p The damping coefficient of the steering nut. F cs This refers to the force acting on the rocker arm shaft gear sector;

[0084] Step S3.3: Calculate the equivalent steering resistance torque. The calculation formula is shown below:

[0085]

[0086] In the formula, J cs B is the equivalent rotational inertia of the gear sector. cs Let θ be the equivalent damping coefficient of the gear sector. cs For the gear sector corner, T p For the equivalent steering resistance torque, r cs Let be the pitch circle radius of the gear sector.

[0087] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0088] The vehicle state estimation method proposed in this invention significantly improves the accuracy and robustness of vehicle yaw rate and center of gravity sideslip angle estimation by using the steering resistance torque estimated based on the vehicle steering dynamics model as an observation and fusing the vehicle dynamics model with the estimated steering resistance torque. This effectively solves the problem that the center of gravity sideslip angle is difficult to measure directly, provides key state parameters for autonomous driving decision-making and vehicle stability control, and significantly reduces the dependence on expensive sensors. Attached Figure Description

[0089] Figure 1 This is a schematic diagram of the steer-by-wire electro-hydraulic steering system of the present invention.

[0090] Figure 2 This is a flowchart of vehicle state estimation that integrates steering resistance torque and dynamics model.

[0091] Figure 3 This is a schematic diagram illustrating the principle of steering resistance torque estimation.

[0092] Figure 4 This is a schematic diagram of a vehicle state estimator based on the Kalman filter algorithm. Detailed Implementation

[0093] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0094] like Figure 1 As shown, the steer-by-wire electro-hydraulic steering system includes an electric power assist subsystem S1, a hydraulic power assist subsystem S2, and a road feel simulation assembly S3.

[0095] The road feel simulation assembly S3 includes a steering wheel S31, a road feel motor S33, and a reduction mechanism S32. The electric power steering subsystem S1 includes a steering motor S11, a reduction mechanism S12, and a steering angle sensor S13. The hydraulic power steering subsystem S2 includes a recirculating ball steering gear assembly S21, a hydraulic pump S22, an oil pump motor S23, and a rotary valve S24.

[0096] This invention proposes a vehicle state estimation method for a steerable electro-hydraulic steering system that integrates steering resistance torque and a dynamic model, such as... Figure 2 As shown, the specific steps are as follows:

[0097] Step S1: Obtain the current of the steering motor from the current sensor, and then calculate the electric assist torque of the electric power assist subsystem.

[0098] Step S2 calculates the hydraulic pressure of the hydraulic power assist subsystem based on the pressure difference of the assist oil formed in the left and right chambers of the hydraulic power assist cylinder and the effective area of ​​the hydraulic cylinder piston.

[0099] Step S3 combines the electric power steering torque obtained in step S1 with the hydraulic pressure obtained in step S2 to estimate the equivalent steering resistance torque. The principle diagram for steering resistance torque estimation is shown below. Figure 3 As shown;

[0100] Step S4 uses the Kalman filter algorithm to estimate the vehicle's lateral speed, yaw rate, and sideslip angle based on the state equation and observation equation of the vehicle state estimation system. The principle of the vehicle state estimator is as follows: Figure 4 As shown.

[0101] It should be noted that step S1 includes the following sub-steps:

[0102] Step S1.1: Obtain the current I of the steering motor from the motor current sensor. m The output torque of the steering motor is calculated using the following formula:

[0103] T m =K m I m

[0104] In the formula, T m K is the output torque of the steering motor. m I is the electromagnetic torque coefficient of the steering motor. m This is the current of the steering motor.

[0105] Step S1.2: Calculate the electric assist torque of the electric power steering subsystem. The formula for calculating the electric assist torque is as follows:

[0106]

[0107] In the formula, J m B is the moment of inertia of the steering motor. m θ is the damping coefficient of the steering motor. m T is the steering motor's rotation angle. a For the electric assist torque of the electric power assist subsystem, i w This is the worm gear transmission ratio.

[0108] It should be noted that step S2 includes the following sub-steps:

[0109] Step S2.1: Calculate the hydraulic oil pump output flow rate based on the hydraulic oil pump flow coefficient and the pump motor speed. The calculation formula is as follows:

[0110] Q s =η p V p w p

[0111] In the formula, Q s η is the output flow rate of the hydraulic oil pump. p V is the mechanical efficiency value. p For hydraulic pump displacement, w p This refers to the speed of the oil pump motor.

[0112] Step S2.2: Based on the conservation of flow on the left and right sides of the hydraulic cylinder, determine the flow rate of the rotary valve into the left and right chambers of the hydraulic cylinder. The calculation formula is as follows:

[0113]

[0114] In the formula, QL1 Q is the flow rate into the left chamber of the hydraulic cylinder via the rotary valve. L2 A is the flow rate into the right chamber of the hydraulic cylinder via the rotary valve. p x is the effective working area of ​​the piston. p For piston displacement, C i Let p1 be the leakage coefficient inside the hydraulic cylinder, and p2 be the pressures in the left and right chambers of the hydraulic cylinder, respectively.

[0115] Step S2.3: The electric torque of the electric power assist subsystem is transmitted to the torsion bar in the rotary valve. Based on the torque transmitted by the torsion bar, the rotary valve angle is calculated using the following formula:

[0116]

[0117] In the formula, k s Let θ be the stiffness of the torsion bar in the rotary valve, and Δθ be the rotary valve angle.

[0118] Step S2.4: Calculate the opening area of ​​each valve port of the rotary valve based on the rotation angle of the rotary valve. The calculation formula is shown below:

[0119] when The formula for calculating the valve opening area is as follows:

[0120]

[0121] when The formula for calculating the valve opening area is as follows:

[0122]

[0123] In the formula, L1 is the pre-opening gap length of the valve port, r is the valve core radius, and A j (j=1,2,3,4) represents the opening area of ​​each valve port of the rotary valve, W1 represents the axial length of the valve port pre-opening gap, W2 represents the axial length of the short cut, and L2 represents the length of the short cut.

[0124] Step S2.5: Based on the hydraulic pump output flow rate, the flow rate into the left and right chambers of the hydraulic cylinder from the rotary valve, and the opening area of ​​each valve port of the rotary valve, calculate the pressure difference of the booster oil formed in the left and right chambers of the hydraulic booster cylinder. The calculation formula is as follows:

[0125] Δp=p1-p2

[0126] in,

[0127]

[0128] In the formula, Δp is the pressure difference of the power steering oil formed in the left and right chambers of the hydraulic power steering cylinder, and C d is the flow coefficient of the short orifice, and A0 is the opening area of ​​the valve orifice when the rotary valve is in the neutral position.

[0129] Step S2.6: Based on the pressure difference of the power assist oil formed in the left and right chambers of the hydraulic power assist cylinder and the effective area of ​​the hydraulic cylinder piston, the hydraulic pressure of the hydraulic power assist subsystem is calculated. The calculation formula is as follows:

[0130] F z =Δp·A p

[0131] The formula for calculating the effective area of ​​the hydraulic cylinder piston is as follows:

[0132]

[0133] In the formula, F z D1 is the hydraulic pressure of the hydraulic power assist subsystem, D2 is the piston diameter, and D3 is the piston push rod diameter.

[0134] It should be noted that step S3 includes the following sub-steps:

[0135] Step S3.1: Calculate the axial force on the nut in the steering screw-steering nut transmission pair based on the steering screw model. The calculation formula is shown below:

[0136]

[0137] in,

[0138] In the formula, T L In the steering screw-steering nut drive pair, the screw transmits torque, J s2 B is the equivalent moment of inertia of the steering input shaft. s2 θ is the viscous damping coefficient of the steering input shaft. s2 For the steering screw rotation angle, F L L represents the axial force on the nut in the steering screw-steering nut transmission pair, and L represents the lead in the steering screw-steering nut transmission pair.

[0139] Step S3.2: Calculate the force acting on the rocker arm shaft gear sector. The calculation formula is as follows:

[0140]

[0141] In the formula, M p For the mass of the steering nut, B p The damping coefficient of the steering nut. F cs This is the force acting on the rocker arm shaft gear sector.

[0142] Step S3.3: Calculate the equivalent steering resistance torque. The calculation formula is shown below:

[0143]

[0144] In the formula, J cs B is the equivalent rotational inertia of the gear sector. cs Let θ be the equivalent damping coefficient of the gear sector. cs For the gear sector corner, T p For the equivalent steering resistance torque, r cs Let be the pitch circle radius of the gear sector.

[0145] Furthermore, the state equation of the vehicle state estimation system in step S4 is:

[0146]

[0147] Wherein, the state variable of the vehicle state estimation system is x = [v y ω r ] Τ The input quantity is u = δ f ,

[0148]

[0149] In the formula, k1 and k2 represent the equivalent sideslip stiffness of the front and rear wheels, respectively, β is the sideslip angle of the vehicle's center of gravity, and v x For longitudinal vehicle speed, ω r Let m be the yaw rate of the vehicle, and I be the mass of the vehicle. z Let be the moment of inertia of the vehicle about the z-axis, and a and b represent the distances from the vehicle's center of mass to the front and rear axles, respectively.

[0150] Furthermore, the observation equations of the vehicle state estimation system in step S4 are as follows:

[0151]

[0152] in,

[0153] ε1=Rtan(γ)

[0154]

[0155] In the formula, R is the static radius of the wheel, γ is the caster angle, ξ is the tire contact patch length, ε1 is the mechanical drag torque, ε2 is the tire drag torque, D is the inward displacement of the kingpin, θ is the inward inclination angle of the kingpin, g is the acceleration due to gravity, and h is the height of the vehicle's center of gravity.

[0156] It should be noted that the specific process of vehicle state estimation based on the Kalman filter algorithm in step S4 is as follows:

[0157] Step S4.1: Discretize the state equation and observation equation of the vehicle state estimation system to obtain the state equation and measurement equation of the Kalman filter algorithm, as shown below:

[0158]

[0159] In the formula, x k Let A be the current state of the target (vehicle speed, angle, etc.), and let A be the state transition matrix. B is the control input matrix. u k-1 To control the input, w k-1 For process noise, z k To estimate the steering resistance torque based on steering dynamics, z k =T p H is the observation matrix. v k For measuring noise.

[0160] Step S4.2: Initialize the parameters in the Kalman filter, as shown below:

[0161]

[0162] In the formula, x0 is the initial value of the state variable. Let P0 be the mean of the state variables and P0 be the initial covariance matrix of the state variables.

[0163] Step S4.3: Based on the state variables predicted at time k-1, obtain the prior estimate. The calculation formula is as follows:

[0164]

[0165] In the formula, The prior estimate of the state variables at time k is given. This is the estimation result of the state variables at time k-1.

[0166] Step S4.4: Based on the covariance P at time k-1 k-1 The covariance matrix of the prior error is obtained, and the calculation formula is shown below:

[0167]

[0168] In the formula, Let P be the covariance matrix of the prior error at time k. k-1 Let Q be the covariance matrix and w be the process noise. k-1 The covariance matrix.

[0169] Step S4.5: Based on the covariance matrix of the prior error at time k in step S4.4... Observation matrix H and observation noise v k-1 The Kalman gain can be calculated from the covariance matrix R, as shown in the following formula:

[0170]

[0171] In the formula, K k This is the Kalman gain.

[0172] Step S4.6: Using the Kalman gain calculated in step S4.5, calculate the optimal estimates of the lateral speed and yaw rate at the current moment. The calculation formula is as follows:

[0173]

[0174] Step S4.7 Updates the covariance matrix based on the Kalman gain calculated in step S4.5 and the covariance matrix of the prior error calculated in step S4.4. The formula for calculating the updated covariance matrix is ​​as follows:

[0175]

[0176] In the formula, P k To update the covariance matrix, I is the identity matrix.

[0177] Step S4.8: Based on the lateral velocity estimated by the Kalman filter algorithm in step S4.6, the centroid sideslip angle is obtained, and the calculation formula is shown below:

[0178]

[0179] In the formula, The centroid sideslip angle is estimated using Kalman filtering.

[0180] The vehicle state estimation method proposed in this invention significantly improves the accuracy and robustness of vehicle yaw rate and center of gravity sideslip angle estimation by using the steering resistance torque estimated based on the vehicle steering dynamics model as an observation and fusing the vehicle dynamics model with the estimated steering resistance torque. This effectively solves the problem that the center of gravity sideslip angle is difficult to measure directly, provides key state parameters for autonomous driving decision-making and vehicle stability control, and significantly reduces the dependence on expensive sensors.

[0181] The above embodiments are only used to illustrate the design concept and features of the present invention, and their purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications made based on the principles and design ideas disclosed in the present invention are within the protection scope of the present invention.

Claims

1. A method for estimating vehicle state in a steerable electro-hydraulic steering system by integrating steering resistance torque and a dynamic model, characterized in that, Includes the following steps: Step S1: Obtain the current of the steering motor from the current sensor, and then calculate the electric assist torque of the electric power assist subsystem. Step S2: Calculate the hydraulic pressure of the hydraulic power assist subsystem based on the pressure difference of the assist oil formed in the left and right chambers of the hydraulic power assist cylinder and the effective area of ​​the hydraulic cylinder piston. Step S3: Combine the electric assist torque of the electric power steering subsystem obtained in step S1 with the hydraulic pressure of the hydraulic power steering subsystem obtained in step S2 to obtain the equivalent steering resistance torque. Step S4: Based on the state equation and observation equation of the vehicle state estimation system, the lateral speed, yaw rate and centroid sideslip angle of the vehicle are estimated using the Kalman filter algorithm.

2. The vehicle state estimation method for a steerable electro-hydraulic steering system based on the fusion of steering resistance torque and dynamic model according to claim 1, characterized in that, In step S4, the state equation of the vehicle state estimation system is: Wherein, the state variable of the vehicle state estimation system is x = [v y ω r ] Τ The input quantity is u = δ f , In the formula, k1 and k2 represent the equivalent sideslip stiffness of the front and rear wheels, respectively, β is the sideslip angle of the vehicle's center of gravity, and v x For longitudinal vehicle speed, ω r Let m be the yaw rate of the vehicle, and I be the mass of the vehicle. z Let be the moment of inertia of the vehicle about the z-axis, and a and b represent the distances from the vehicle's center of mass to the front and rear axles, respectively. The observation equations for the vehicle state estimation system are: in, ε1=Rtan(γ) In the formula, R is the static radius of the wheel, γ is the caster angle, ξ is the tire contact patch length, ε1 is the mechanical drag torque, ε2 is the tire drag torque, D is the inward displacement of the kingpin, θ is the inward inclination angle of the kingpin, g is the acceleration due to gravity, and h is the height of the vehicle's center of gravity.

3. The vehicle state estimation method for a steerable electro-hydraulic steering system integrating steering resistance torque and dynamic model according to claim 1, characterized in that, Step S4, the process of estimating the vehicle's lateral speed, yaw rate, and sideslip angle based on the Kalman filter algorithm, includes the following steps: Step S4.1: Discretize the state equation and observation equation of the vehicle state estimation system to obtain the state equation and measurement equation of the Kalman filter algorithm, as shown below: In the formula, x k Let A be the current state of the target (vehicle speed, angle, etc.), and let A be the state transition matrix. B is the control input matrix. u k-1 To control the input, w k-1 For process noise, z k To estimate the steering resistance torque based on steering dynamics, z k =T p H is the observation matrix. v k For measuring noise; Step S4.2: Initialize the parameters in the Kalman filter, as shown below: In the formula, x0 is the initial value of the state variable. Let P0 be the mean of the state variables, and let P0 be the initial covariance matrix of the state variables. Step S4.3: Based on the state variables predicted at time k-1, obtain the prior estimate. The calculation formula is as follows: In the formula, The prior estimate of the state variables at time k is given. The estimated results of the state variables at time k-1; Step S4.4: Based on the covariance P at time k-1 k-1 The covariance matrix of the prior error is obtained, and the calculation formula is shown below: P k - =AP k-1 From T +Q In the formula, Let P be the covariance matrix of the prior error at time k. k-1 Let Q be the covariance matrix and w be the process noise. k-1 The covariance matrix; Step S4.5: Based on the covariance matrix of the prior error at time k in step S4.4... Observation matrix H and observation noise v k-1 The Kalman gain can be calculated from the covariance matrix R, as shown in the following formula: In the formula, K k Kalman gain; Step S4.6: Using the Kalman gain calculated in step S4.5, calculate the optimal estimates of the lateral speed and yaw rate at the current moment. The calculation formula is as follows: Step S4.7: Based on the Kalman gain calculated in step S4.5 and the covariance matrix of the prior error calculated in step S4.4, update the covariance matrix. The formula for calculating the updated covariance matrix is ​​as follows: In the formula, P k To update the covariance matrix, I is the identity matrix; Step S4.8: Based on the lateral velocity estimated by Kalman filtering in step S4.6, the centroid sideslip angle is obtained, and the calculation formula is as follows: In the formula, The centroid sideslip angle is estimated using Kalman filtering.

4. The vehicle state estimation method for a steerable electro-hydraulic steering system integrating steering resistance torque and dynamics model according to claim 1, characterized in that, In step S1, the method for calculating the electric assist torque of the electric power assist subsystem includes the following steps: Step S1.1: Obtain the current I of the steering motor from the motor current sensor. m The output torque of the steering motor is calculated using the following formula: T m =K m I m In the formula, T m K is the output torque of the steering motor. m I is the electromagnetic torque coefficient of the steering motor. m This refers to the current of the steering motor; Step S1.2: Calculate the electric assist torque of the electric power steering subsystem. The formula for calculating the electric assist torque is as follows: In the formula, J m B is the moment of inertia of the steering motor. m θ is the damping coefficient of the steering motor. m T is the steering motor's rotation angle. a For the electric assist torque of the electric power assist subsystem, i w This is the worm gear transmission ratio.

5. The vehicle state estimation method for a steerable electro-hydraulic steering system based on the fusion of steering resistance torque and dynamic model according to claim 1, characterized in that, In step S2, the method for calculating the hydraulic force of the hydraulic power assist subsystem includes the following steps: Step S2.1: Calculate the hydraulic oil pump output flow rate based on the hydraulic oil pump flow coefficient and the pump motor speed. The calculation formula is as follows: Q s =η p V p w p In the formula, Q s η is the output flow rate of the hydraulic oil pump. p V is the mechanical efficiency value. p For hydraulic pump displacement, w p This refers to the oil pump motor speed; Step S2.2: Based on the conservation of flow on the left and right sides of the hydraulic cylinder, determine the flow rate of the rotary valve into the left and right chambers of the hydraulic cylinder. The calculation formula is as follows: In the formula, Q L1 Q is the flow rate that flows into the left chamber of the hydraulic cylinder via the rotary valve. L2 A is the flow rate into the right chamber of the hydraulic cylinder via the rotary valve. p x is the effective working area of ​​the piston. p For piston displacement, C i The internal leakage coefficient of the hydraulic cylinder is given by p1 and p2, which are the pressures in the left and right chambers of the hydraulic cylinder, respectively. Step S2.3: The electric torque of the electric power assist subsystem is transmitted to the torsion bar in the rotary valve. Based on the torque transmitted by the torsion bar, the rotary valve angle is calculated using the following formula: In the formula, k s Let θ be the stiffness of the torsion bar in the rotary valve, and Δθ be the rotation angle of the rotary valve. Step S2.4: Calculate the opening area of ​​each valve port of the rotary valve based on the rotation angle of the rotary valve. The calculation formula is shown below: when The formula for calculating the valve opening area is as follows: when The formula for calculating the valve opening area is as follows: In the formula, L1 is the pre-opening gap length of the valve port, r is the valve core radius, and A j (j=1,2,3,4) represents the opening area of ​​each valve port of the rotary valve, W1 represents the axial length of the valve port pre-opening gap, W2 represents the axial length of the short cut, and L2 represents the length of the short cut. Step S2.5: Based on the hydraulic pump output flow rate, the flow rate into the left and right chambers of the hydraulic cylinder from the rotary valve, and the opening area of ​​each valve port of the rotary valve, calculate the pressure difference of the booster oil formed in the left and right chambers of the hydraulic booster cylinder. The calculation formula is as follows: Δp=p1-p2 in, In the formula, Δp is the pressure difference of the power steering oil formed in the left and right chambers of the hydraulic power steering cylinder, and C d Here, A0 is the orifice flow coefficient, and A0 is the valve opening area when the rotary valve is in the neutral position. Step S2.6: Based on the pressure difference of the power assist oil formed in the left and right chambers of the hydraulic power assist cylinder and the effective area of ​​the hydraulic cylinder piston, the hydraulic pressure of the hydraulic power assist subsystem is calculated. The calculation formula is as follows: F z =Δp·A p The formula for calculating the effective area of ​​the hydraulic cylinder piston is as follows: In the formula, F z D1 is the hydraulic pressure of the hydraulic power assist subsystem, D2 is the piston diameter, and D3 is the piston push rod diameter.

6. The vehicle state estimation method for a steerable electro-hydraulic steering system integrating steering resistance torque and dynamic model according to claim 1, characterized in that, In step S3, the method for calculating the equivalent steering resistance torque includes the following steps: Step S3.1: Calculate the axial force on the nut in the steering screw-steering nut transmission pair based on the steering screw model. The calculation formula is shown below: in, In the formula, T L In the steering screw-steering nut drive pair, the screw transmits torque, J s2 B is the equivalent moment of inertia of the steering input shaft. s2 θ is the viscous damping coefficient of the steering input shaft. s2 For the steering screw rotation angle, F L L represents the axial force on the nut in the steering screw-steering nut transmission pair, and L represents the lead in the steering screw-steering nut transmission pair. Step S3.2: Calculate the force acting on the rocker arm shaft gear sector. The calculation formula is as follows: In the formula, M p For the mass of the steering nut, B p The damping coefficient of the steering nut. F cs This refers to the force acting on the rocker arm shaft gear sector; Step S3.3: Calculate the equivalent steering resistance torque. The calculation formula is shown below: In the formula, J cs B is the equivalent rotational inertia of the gear sector. cs Let θ be the equivalent damping coefficient of the gear sector. cs For the gear sector corner, T p For the equivalent steering resistance torque, r cs Let be the pitch circle radius of the gear sector.

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