EPS-based steering wheel angle control method, device, apparatus and medium

Abstract

This invention discloses a steering wheel angle control method, device, equipment, and medium based on EPS (Electric Power Steering). The method involves determining a system model of the EPS steering system based on the steering wheel structure; this system model includes system inputs, system outputs, and steering wheel parameters; determining the parameter values ​​of the steering wheel parameters based on the historical input / output information of the EPS steering system and the system model; constructing a state model of the EPS steering system based on the parameter values; determining the target torque based on the state model; and determining the target steering wheel angle based on the target torque. Compared to traditional theoretical value calculations and PID control, this invention effectively reduces the impact of parameter inaccuracies and abnormal poles in the EPS steering system caused by changes in operating conditions, improving angle control accuracy while also achieving adaptive control of the EPS steering system.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving, and more particularly to a steering wheel angle control method, device, equipment, and medium based on EPS. Background Technology

[0002] During autonomous driving, the HAD controller (Highly Autonomous Driving Controller) calculates a steering wheel angle based on information such as road lines and its own state, and sends it to the EPS controller to achieve lateral control of the vehicle. However, for some models, the EPS controller can only control by torque. Therefore, an efficient control strategy is needed to convert torque into steering wheel angle and complete the entire lateral control link.

[0003] However, most current control methods use PID controllers (Proportional-Integral-Derivative Controllers). This control method is fast to calculate and has a simple algorithm, but it requires high parameter accuracy. Moreover, under normal circumstances, the control parameters of vehicles vary significantly under different conditions, requiring the configuration of corresponding poles according to the corresponding operating conditions, which makes the pole configuration process cumbersome. Summary of the Invention

[0004] This invention provides a steering wheel angle control method, device, equipment, and medium based on EPS to solve the problem that vehicle control parameters vary under different conditions, requiring the configuration of corresponding poles according to the corresponding operating conditions, which leads to cumbersome pole configuration steps.

[0005] According to one aspect of the present invention, a steering wheel angle control method based on EPS is provided, comprising:

[0006] The system model of the EPS steering system is determined based on the steering wheel steering structure; the system model includes system input, system output, and steering wheel steering parameters.

[0007] The parameter values ​​of the steering wheel parameters are determined based on the historical input and output information of the EPS steering system and the system model;

[0008] Construct a state model of the EPS steering system based on the parameter values ​​of the steering wheel steering parameters;

[0009] The target torque is determined based on the state model, and the target steering wheel angle is determined based on the target torque.

[0010] According to another aspect of the present invention, a steering wheel angle control device based on EPS is provided, comprising:

[0011] The system model determination module is used to determine the system model of the EPS steering system based on the steering wheel steering structure; the system model includes system inputs, system outputs, and steering wheel steering parameters.

[0012] The parameter value determination module is used to determine the parameter values ​​of the steering wheel parameters based on the historical input and output information of the EPS steering system and the system model.

[0013] The state model determination module is used to construct the state model of the EPS steering system based on the parameter values ​​of the steering wheel steering parameters;

[0014] The target angle determination module is used to determine the target torque based on the state model, and then determine the target angle of the steering wheel based on the target torque.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the EPS-based steering wheel angle control method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the EPS-based steering wheel angle control method according to any embodiment of the present invention.

[0020] The technical solution of this invention establishes a system model of the EPS steering system based on the steering wheel steering structure, determines the parameter values ​​of the steering wheel steering parameters according to the historical input and output information of the EPS steering system, constructs a state model of the EPS steering system based on the parameter values, calculates the target torque, and obtains the target angle of the steering wheel to match the target torque. Compared with traditional theoretical value calculation and PID control, this method effectively reduces the impact of parameter inaccuracies and abnormal poles in the EPS steering system caused by changes in operating conditions, improves control accuracy, and also achieves adaptive control of the EPS steering system.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart of a steering wheel angle control method based on EPS provided in Embodiment 1 of the present invention;

[0024] Figure 2 This is a structural block diagram of a steering wheel angle control based on EPS provided in Embodiment 1 of the present invention;

[0025] Figure 3 This is a schematic diagram of a steering wheel angle control device based on EPS provided in Embodiment 2 of the present invention;

[0026] Figure 4 A schematic diagram of the structure of an electronic device for implementing the EPS-based steering wheel angle control method of this invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "candidate," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] Example 1

[0030] Figure 1This is a flowchart of a steering wheel angle control method based on EPS (Electric Power Surgery) according to Embodiment 1 of the present invention. This embodiment is applicable to situations where vehicle control parameters vary under different conditions, requiring the configuration of corresponding poles based on the specific operating conditions, thus leading to cumbersome pole configuration steps. This method can be executed by an EPS-based steering wheel angle control device, which can be implemented in hardware and / or software. This EPS-based steering wheel angle control device can be configured in an electronic device with network connectivity. Figure 1 As shown, the method includes:

[0031] S110. Determine the system model of the EPS steering system based on the steering wheel steering structure; wherein, the system model includes system input, system output and steering wheel steering parameters.

[0032] EPS (Electrical Power Steering) system generally consists of a mechanical steering system plus a torque sensor, vehicle speed sensor, electronic control unit, reducer, electric motor, etc. Based on the traditional mechanical steering system, it uses an electronic control device to make the electric motor generate auxiliary power of corresponding magnitude and direction according to the torque signal on the steering wheel and the vehicle speed signal, so as to assist the driver in steering operation.

[0033] The system input is the torque of the steering wheel; the system output is the steering angle of the steering wheel; the steering parameters of the steering wheel are the moment of inertia of the steering wheel, the damping of the steering wheel, and the stiffness of the steering wheel.

[0034] The EPS steering system model is established based on the steering wheel structure using either mechanistic modeling or Lagrange modeling methods. Mechanistic modeling, based on system mechanisms such as physical and chemical changes, employs mathematical methods to analyze and determine the relationship between the EPS steering system's inputs and outputs and the steering wheel parameters, as well as the model's structure. Lagrange modeling, on the other hand, builds its model based on the changes in the EPS steering system's kinetic and potential energy, without needing to consider the forces between rigid bodies within the EPS steering system.

[0035] Optionally, a system model for determining the EPS steering system based on the steering wheel steering structure includes:

[0036] The system model is expressed as follows:

[0037] T d =J sw θ″ sw +C sw θ′ sw +K sw θ sw ;

[0038] Among them, Td For system input, θ represents the torque in the EPS steering system. sw This is the system output, representing the steering wheel angle in the EPS steering system, J. sw C represents the moment of inertia of the steering wheel. sw K represents the damping parameter of the steering wheel. sw J represents the stiffness parameter of the steering wheel. sw C sw and K sw These are the steering wheel parameters.

[0039] The relationship between torque and steering angle is determined based on the influence of the steering wheel's moment of inertia, damping, and stiffness on the steering wheel angle, and a system model of the EPS steering system is constructed based on this relationship.

[0040] S120. Determine the parameter values ​​of the steering wheel parameters based on the historical input / output information and system model of the EPS steering system.

[0041] Historical input / output information refers to the EPS steering system input / output information from previous cycles. The current cycle is the time period in which the steering wheel angle needs to be determined.

[0042] By inputting the steering wheel torque and steering wheel rotation angle from the previous cycle of the EPS steering system into the system model, the parameter values ​​of the steering wheel are calculated, namely the steering wheel moment of inertia parameter, the steering wheel damping parameter, and the steering wheel stiffness parameter.

[0043] Optionally, the parameter values ​​of the steering wheel parameters are determined based on the historical input / output information and system model of the EPS steering system, including steps A1-A3:

[0044] Step A1: Convert the system model into a transfer function using the Laplace transform, and then discretize the transfer function to obtain a discretized system model.

[0045] The system model is converted into a transfer function using the Laplace transform, and the resulting transfer function is shown in the following equation:

[0046]

[0047] Among them, J sw C represents the moment of inertia of the steering wheel. sw K represents the damping parameter of the steering wheel. sw J represents the stiffness parameter of the steering wheel. sw C sw and K sw These are the steering wheel parameters.

[0048] Since all data in the EPS steering system is discrete, the transfer function needs to be discretized before calculation.

[0049] Specifically, the transfer function is discretized using the difference of the latter term, as shown in the following equation:

[0050]

[0051] Where s is a continuous domain, z is a discrete domain, and T represents the sampling period of the EPS steering system.

[0052] Substituting s into the transfer function and rearranging, we obtain the discretized model of the EPS steering system, as shown in the following equation:

[0053]

[0054] Among them, T d (z) represents the torque of the EPS steering system in the current cycle, θ sw (z) represents the steering wheel angle of the EPS steering system in the current cycle, θ sw (z-1) represents the steering wheel angle of the EPS steering system in the previous cycle, θ sw (z-2) represents the steering wheel angle of the EPS steering system in the first two cycles; T represents the sampling period of the EPS steering system.

[0055] Step A2: Convert the discretized system model into a stochastic linear model, and construct a residual sum of squares cost function based on the stochastic linear model.

[0056] The steering wheel parameters can be calculated based on the historical input / output information of the EPS steering system and the discretized system model. However, to further improve the calculation efficiency of the parameters, the discretized system model is converted into a stochastic linear model.

[0057] Optionally, the discretized system model can be converted into a stochastic linear model, and the resulting stochastic linear model is shown in the following equation:

[0058]

[0059] Where T represents the sampling period of the EPS steering system; T d (z) represents the torque of the EPS steering system in the current cycle, θ sw (z) represents the steering wheel angle of the EPS steering system in the current cycle, θ sw (z-1) represents the steering wheel angle of the EPS steering system in the previous cycle, θ sw (z-2) represents the steering wheel angle of the EPS steering system in the first two cycles.

[0060] Optionally, a residual sum of squares cost function can be constructed based on the stochastic linear model, resulting in the residual sum of squares cost function as shown in the following equation:

[0061]

[0062]

[0063]

[0064] in, This represents the residual sum of squares cost function, where i represents the calculation period of the EPS steering system. The data collected by the sensor consists of inputs and outputs. The parameter matrix is ​​estimated by the parameters of the EPS steering system.

[0065] The purpose of using a cost function is to make the output calculated from the estimated parameters close to the actual output, thereby minimizing the sum of squared residuals.

[0066] Step A3: Determine the parameter values ​​of the steering wheel parameters based on the residual sum of squares cost function and the historical input / output information of the EPS steering system.

[0067] Differentiating the residual sum of squares type cost function yields:

[0068]

[0069]

[0070]

[0071] By substituting the historical input-output information of the EPS steering system into the differentiated residual sum-of-squares cost function, the parameter matrix of the steering wheel parameters can be obtained. Solving the parameter matrix yields the values ​​of the steering wheel parameters.

[0072] S130. Construct a state model of the EPS steering system based on the parameter values ​​of the steering wheel steering parameters.

[0073] Based on the steering wheel parameters and the calculated transfer function, a state model of the EPS steering system is constructed. This state model represents the steering angle error control results of the EPS steering system.

[0074] Construct a state model of the EPS steering system based on the parameter values ​​of the steering wheel parameters, including steps B1-B2:

[0075] Step B1: Construct the error equation of the EPS steering system based on the parameter values ​​of the steering wheel steering parameters.

[0076] The transfer function of the EPS steering system calculated above is linearly transformed to obtain the state-space expression of the EPS steering system. Substituting the values ​​of the steering wheel parameters into the state-space expression, the error equation of the EPS steering system is obtained, as shown in the following equation:

[0077]

[0078]

[0079]

[0080]

[0081] in, Let A represent the error value, B represent the input matrix of the EPS steering system, and x represent the state vector of the EPS steering system, which consists of the error between the set and actual steering wheel angle and the steering wheel rotation speed. sw C represents the moment of inertia of the steering wheel. sw K represents the damping parameter of the steering wheel. sw J represents the stiffness parameter of the steering wheel. sw C sw and K sw For steering wheel parameters, θ sw θ represents the actual steering wheel angle of the EPS steering system in the previous cycle. sw_set The set angle for the EPS steering system in the current cycle. The derivative of the steering wheel angle is the speed at which the steering wheel rotates.

[0082] By using the above steps to establish the error equation of the EPS steering system, and by configuring the poles of the EPS steering system, the x vector can be made to become a zero vector, that is, the final state of the steering wheel speed is 0, and the difference between the actual value and the set value is also 0. This enables the control of the entire steering wheel angle.

[0083] Step B2: Determine the cost function based on the error equation, and construct the state model from the error equation and the cost function.

[0084] A linear quadratic regulator (LQR) is used to control the EPS steering system, and its cost function is shown in the following equation:

[0085]

[0086] Among them, T dThe torque in the EPS steering system is represented by Q and R, which are the weights of the state vector and the input torque, respectively. When Q is large, the cost function makes the change in state smaller, while when R is large, the cost function makes the change in input smaller.

[0087] Optionally, the target torque is determined based on the state model, including steps C1-C2:

[0088] Step C1: Determine the parameters of the covariance matrix based on the error equation and cost function.

[0089] The cost function is solved using the Raccati equation (Algebraic Riccati Equation), and the results are as follows:

[0090] A T P+PA+Q-RBR -1 BP=0

[0091] Where P is the covariance matrix parameter, A represents the state transition matrix of the EPS steering system, B is the output matrix, and Q and R are the weights of the state vector and the input torque, respectively.

[0092] Solving the above equation yields the covariance matrix parameter P.

[0093] Step C2: Determine the control coefficients based on the covariance matrix parameters and the EPS steering system.

[0094] Based on the structural information of the EPS steering system, the control coefficients are determined according to the covariance matrix parameters and the EPS steering system, and can be expressed by the following formula:

[0095] K = R -1 B T P

[0096] Where K is the LQR control coefficient, P represents the covariance matrix parameter, B is the output matrix, and R is the weight of the input torque.

[0097] Step C3: Determine the target torque based on the control coefficients and the state vector of the EPS steering system.

[0098] The target torque is determined based on the control coefficients and the state vector of the EPS steering system, and can be expressed by the following formula:

[0099] T d =-K T *x

[0100] Where K is the LQR control coefficient and x is the state vector.

[0101] S140. Determine the target torque based on the state model, and determine the target angle of the steering wheel based on the target torque.

[0102] The target torque is obtained by solving the state model. Based on the mapping relationship between the target torque and the target steering wheel angle, the target steering wheel angle is determined.

[0103] like Figure 2 The diagram shown is a structural block diagram of a steering wheel angle control based on EPS provided in Embodiment 1 of the present invention; the set angle θ of the EPS steering system corresponding to the current cycle is obtained by the upper-level control algorithm. sw_set The set angle value is input into the adjustable parameter controller, which determines the steering wheel parameter value based on the historical input and output information of the EPS steering system. Then, based on the calculated steering wheel parameter value, the state model of the EPS steering system is constructed, and the corresponding target torque is calculated based on the set angle. Finally, the EPS actuator obtains the corresponding target angle based on the target torque to reduce the error between the target angle and the set angle.

[0104] This invention utilizes a parameter estimation algorithm to dynamically estimate the steering parameters of the EPS steering system. The estimated parameters are used to establish a dynamic system equation for control. The control strategy derives the corresponding error equation based on the parameters and employs a linear quadratic regulator to achieve precise control of the steering wheel angle. Since the parameter estimation is based on historical input / output information corresponding to the current cycle, different system parameters can be applied under different operating conditions, enabling adaptive adjustment of the controller. This eliminates the cumbersome pole configuration required by traditional PID methods for different operating conditions.

[0105] Optionally, after determining the target angle of the steering wheel, the EPS steering system controls the steering wheel according to the target angle to achieve vehicle steering.

[0106] This embodiment establishes a system model of the EPS steering system based on the steering wheel steering structure, determines the parameter values ​​of the steering wheel steering parameters according to the historical input and output information of the EPS steering system, constructs a state model of the EPS steering system based on the parameter values, calculates the target torque, and obtains the target steering wheel angle to match the target torque. Compared with traditional theoretical value calculation and PID control, this method effectively reduces the impact of parameter inaccuracies and abnormal control system poles caused by changes in operating conditions, improves control accuracy, and also achieves adaptive control of the EPS steering system.

[0107] Example 2

[0108] Figure 3This is a schematic diagram of a steering wheel angle control device based on EPS provided in Embodiment 2 of the present invention. Figure 3 As shown, the device includes:

[0109] System model determination module 210: used to determine the system model of the EPS steering system based on the steering wheel steering structure; wherein, the system model includes system input, system output and steering wheel steering parameters;

[0110] Parameter value determination module 220: used to determine the parameter values ​​of steering wheel parameters based on the historical input and output information of the EPS steering system and the system model;

[0111] State model determination module 230: used to construct the state model of the EPS steering system based on the parameter values ​​of the steering wheel steering parameters;

[0112] Target angle determination module 240: used to determine the target torque based on the state model, and to determine the target angle of the steering wheel based on the target torque.

[0113] Optionally, the system model determination module 210 is specifically used for:

[0114] The system model is expressed as follows:

[0115] T d =J sw θ″ sw +C sw θ′ sw +K sw θ sw ;

[0116] Among them, T d For system input, θ represents the torque in the EPS steering system. sw This is the system output, representing the steering wheel angle in the EPS steering system, J. sw C represents the moment of inertia of the steering wheel. sw K represents the damping parameter of the steering wheel. sw J represents the stiffness parameter of the steering wheel. sw C sw and K sw These are the steering wheel parameters.

[0117] Optionally, the parameter value determination module 220 includes:

[0118] Discretized system model determination unit: used to convert the system model into a transfer function through Laplace transform, and to discretize the transfer function to obtain a discretized system model;

[0119] Residual sum of squares type cost function building unit: used to convert discretized system models into stochastic linear models and construct residual sum of squares type cost functions based on stochastic linear models;

[0120] Parameter value determination unit: used to determine the parameter values ​​of steering wheel parameters based on the residual sum of squares cost function and the historical input and output information of the EPS steering system.

[0121] Optional, discretized system model defining elements, specifically used for:

[0122] The expression for the discretized system model is:

[0123]

[0124] Among them, T d (z) represents the torque of the EPS steering system in the current cycle, θ sw (z) represents the steering wheel angle of the EPS steering system in the current cycle, θ sw (z-1) represents the steering wheel angle of the EPS steering system in the previous cycle, θ sw (z-2) represents the steering wheel angle of the EPS steering system in the first two cycles; T represents the sampling period of the EPS steering system.

[0125] Optional, residual sum of squares type cost function building unit, specifically used for:

[0126] The expression for the stochastic linear model is:

[0127]

[0128]

[0129] Constructing a residual sum-of-squares cost function based on a stochastic linear model, including:

[0130] The expression for the residual sum of squares type cost function is as follows:

[0131]

[0132]

[0133]

[0134] in, Let i represent the residual sum of squares cost function, and let i represent the calculation period of the EPS steering system.

[0135] Optionally, the state model determination module 230 includes:

[0136] Error equation determination unit: used to construct the error equation of the EPS steering system based on the parameter values ​​of the steering wheel steering parameters;

[0137] State model determination unit: used to determine the cost function based on the error equation, and the state model is composed of the error equation and the cost function;

[0138] The expression for the error equation is as follows:

[0139]

[0140]

[0141]

[0142]

[0143] in, Let A represent the error value, B represent the state transition matrix of the EPS steering system, and x represent the state vector of the EPS steering system. sw C represents the moment of inertia of the steering wheel. sw K represents the damping parameter of the steering wheel. sw J represents the stiffness parameter of the steering wheel. sw C sw and K sw For steering wheel parameters, θ sw θ represents the actual steering wheel angle of the EPS steering system in the previous cycle. sw_set The set angle for the EPS steering system in the current cycle. The derivative of the steering wheel angle;

[0144] The expression for the cost function is:

[0145]

[0146] Among them, T d This represents the torque in the EPS steering system, where Q and R are the weights of the state vector and the input torque, respectively.

[0147] Optionally, the target angle determination module 240 includes:

[0148] Covariance matrix parameter determination unit: used to determine the covariance matrix parameters based on the error equation and cost function;

[0149] Control coefficient determination unit: used to determine control coefficients based on covariance matrix parameters and EPS steering system;

[0150] The expression for the control coefficient K is as follows:

[0151] K = R-1 B T P;

[0152] Where P represents the parameters of the covariance matrix;

[0153] Target torque determination unit: used to determine the target torque based on the control coefficients and the state vector of the EPS steering system;

[0154] Target torque T d The calculation formula is:

[0155] T d =-K T *x.

[0156] The EPS-based steering wheel angle control device provided in this embodiment of the invention can execute the EPS-based steering wheel angle control method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0157] The acquisition, storage, use, and processing of data in this application comply with relevant national laws and regulations and do not violate public order and good morals.

[0158] Example 3

[0159] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0160] Figure 4 This is a schematic diagram of the structure of an electronic device for implementing the EPS-based steering wheel angle control method according to an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0161] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0162] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0163] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the EPS-based steering wheel angle control method.

[0164] In some embodiments, the EPS-based steering wheel angle control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the EPS-based steering wheel angle control method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the EPS-based steering wheel angle control method by any other suitable means (e.g., by means of firmware).

[0165] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific reference products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0166] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0167] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0168] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0169] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data servers), or computing systems that include switching components (e.g., application servers), or computing systems that include front-end components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such back-end, switching, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0170] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0171] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0172] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A steering wheel angle control method based on EPS, characterized by, The method includes: The system model of the EPS steering system is determined based on the steering wheel steering structure; wherein, the system model includes system input, system output and steering wheel steering parameters; The parameter values ​​of the steering wheel parameters are determined based on the historical input and output information of the EPS steering system and the system model; Construct a state model of the EPS steering system based on the parameter values ​​of the steering wheel parameters; The target torque is determined based on the state model, and the target angle of the steering wheel is determined based on the target torque. The process of constructing a state model of the EPS steering system based on the parameter values ​​of the steering wheel parameters includes: The error equation of the EPS steering system is constructed based on the parameter values ​​of the steering wheel parameters; The cost function is determined based on the error equation, and the state model is formed by the error equation and the cost function. The expression for the error equation is as follows: ； ； ； ； in, Indicates the error value. This represents the state transition matrix of the EPS steering system. Represents the input matrix, Let be the state vector of the EPS steering system. The parameter representing the moment of inertia of the steering wheel. This indicates the damping parameters of the steering wheel. This indicates the stiffness parameters of the steering wheel. , and For steering wheel parameters, This refers to the actual steering wheel angle of the EPS steering system described in the previous cycle. The set angle for the EPS steering system in the current cycle. The derivative of the steering wheel angle; The expression for the cost function is: ； in, This indicates the torque in the EPS steering system. and These are the weights of the state vector and the input torque, respectively. Determining the target torque based on the state model includes: The parameters of the covariance matrix are determined based on the error equation and the cost function; The control coefficients are determined based on the covariance matrix parameters and the EPS steering system. The target torque is determined based on the control coefficients and the state vector of the EPS steering system; Wherein, the control coefficient The expression is: ； in, Let P represent the parameters of the covariance matrix. The formula for calculating P is: ； The target torque The calculation formula is: 。 2. The method according to claim 1, characterized in that, The system model of the EPS steering system is determined based on the steering wheel steering structure, including: The expression for the system model is as follows: ； in, The system input represents the torque in the EPS steering system. This is the system output, representing the angle of the steering wheel in the EPS steering system. The parameter representing the moment of inertia of the steering wheel. This indicates the damping parameters of the steering wheel. This indicates the stiffness parameters of the steering wheel. , and These are the steering wheel parameters.

3. The method according to claim 2, characterized in that, The parameter values ​​of the steering wheel parameters are determined based on the historical input / output information of the EPS steering system and the system model, including: The system model is converted into a transfer function by Laplace transform, and the transfer function is then discretized to obtain a discretized system model. The discretized system model is converted into a stochastic linear model, and a residual sum of squares cost function is constructed based on the stochastic linear model. The parameter values ​​of the steering wheel parameters are determined based on the residual sum of squares cost function and the historical input-output information of the EPS steering system.

4. The method according to claim 3, characterized in that, The expression for the discretized system model is: ； in, This indicates the torque of the EPS steering system in the current cycle. This indicates the angle of the steering wheel in the EPS steering system during the current cycle. This indicates the angle of the steering wheel in the EPS steering system described in the previous cycle. This indicates the angle of the steering wheel in the EPS steering system described in the first two cycles; This indicates the sampling period of the EPS steering system; The expression for the stochastic linear model is: 。 5. The method according to claim 4, characterized in that, Constructing a residual sum-of-squares cost function based on the stochastic linear model includes: The expression for the residual sum of squares type cost function is as follows: ； ； ； in, This represents the residual sum of squares type cost function. This indicates the calculation cycle of the EPS steering system; The data collected by the sensor consists of inputs and outputs; The parameter matrix is ​​estimated by the parameters of the EPS steering system.

6. A steering wheel angle control device based on EPS, characterized in that, include: The system model determination module is used to determine the system model of the EPS steering system based on the steering wheel steering structure; wherein, the system model includes system input, system output and steering wheel steering parameters; The parameter value determination module is used to determine the parameter values ​​of the steering wheel parameters based on the historical input and output information of the EPS steering system and the system model. The state model determination module is used to construct a state model of the EPS steering system based on the parameter values ​​of the steering wheel parameters. The target angle determination module is used to determine the target torque based on the state model, and to determine the target angle of the steering wheel based on the target torque; The state model determination module includes: An error equation determination unit is used to construct the error equation of the EPS steering system based on the parameter values ​​of the steering wheel parameters. A state model determination unit is used to determine a cost function based on the error equation, and the state model is composed of the error equation and the cost function. The expression for the error equation is as follows: ； ； ； ； in, Indicates the error value. This represents the state transition matrix of the EPS steering system. Represents the input matrix, Let be the state vector of the EPS steering system. The parameter representing the moment of inertia of the steering wheel. This indicates the damping parameters of the steering wheel. This indicates the stiffness parameters of the steering wheel. , and For steering wheel parameters, This refers to the actual steering wheel angle of the EPS steering system described in the previous cycle. The set angle for the EPS steering system in the current cycle. The derivative of the steering wheel angle; The expression for the cost function is: ； in, This indicates the torque in the EPS steering system. and These are the weights of the state vector and the input torque, respectively. The target angle determination module includes: The covariance matrix parameter determination unit is used to determine the covariance matrix parameters based on the error equation and the cost function. A control coefficient determination unit is used to determine control coefficients based on the covariance matrix parameters and the EPS steering system. A target torque determination unit is used to determine the target torque based on the control coefficient and the state vector of the EPS steering system. Wherein, the control coefficient The expression is: ； in, Let P represent the parameters of the covariance matrix. The formula for calculating P is: ； The target torque The calculation formula is: 。 7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the EPS-based steering wheel angle control method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the EPS-based steering wheel angle control method according to any one of claims 1-5.

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