WO2023231833A1

WO2023231833A1 - Creep control method and apparatus, electronic device and storage medium

Info

Publication number: WO2023231833A1
Application number: PCT/CN2023/095758
Authority: WO
Inventors: 郭丁伊; 刘建康; 刘元治; 郁大嵬; 尹建坤; 徐家良; 程健; 宋浩源
Original assignee: 中国第一汽车股份有限公司
Priority date: 2022-05-30
Filing date: 2023-05-23
Publication date: 2023-12-07
Also published as: CN114771283A

Abstract

A creep control method and apparatus, an electronic device and a storage medium. The method comprises: acquiring measured values of driving parameters of an electric vehicle during a driving process; according to the measured values of the driving parameters and a dynamical model of a gradient road surface, obtaining estimated values of the driving parameters; according to the estimated values of the driving parameters and a state observation model, obtaining observed values of the driving parameters; and, according to the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and a creeping condition of the electric vehicle during the driving process, calculating an approach control value of the electric vehicle on the gradient road surface.

Description

Crawling control method, device, electronic device and storage medium

This application claims priority to the Chinese patent application with application number 202210598801.7, which was submitted to the China Patent Office on May 30, 2022. The entire content of the above application is incorporated into this application by reference.

Technical field

This application relates to the technical field of crawling control, for example, to a crawling control method, device, electronic equipment and storage medium.

Background technique

The share of electric vehicles in the automobile market is increasing, and their advantages such as fast response and low noise are gradually accepted by users. When the working state of electric vehicles is crawling during operation, it is necessary to accurately identify the road gradient and vehicle speed. Maintain the stability of vehicle control and cope with various working conditions during crawling.

Contents of the invention

This application provides a crawling control method, device, electronic equipment and storage medium.

In the first aspect, embodiments of the present application provide a crawling control method. The method includes: obtaining measured values of driving parameters of an electric vehicle during driving; obtaining the driving parameters based on the measured values of the driving parameters and the dynamic model of the sloped road surface. The estimated values of the parameters; based on the estimated values of the driving parameters and the state observation model, the observed values of the driving parameters are obtained; based on the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the driving process of the electric vehicle In the crawling condition, the approach control value of the electric vehicle on the slope road is calculated.

In a second aspect, embodiments of the present application also provide a crawling control device. The device includes: a parameter acquisition module configured to acquire measured values of the driving parameters of the electric vehicle during driving; a first calculation module configured to obtain the measured values of the driving parameters according to the driving process. The measured values of the parameters and the dynamic model of the sloped road surface are used to obtain the estimated values of the driving parameters; the second calculation module is set to obtain the observed values of the driving parameters based on the estimated values of the driving parameters and the state observation model; the third calculation module , is set to calculate the approach control value of the electric vehicle on the sloped road based on the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the crawling conditions of the electric vehicle during driving.

In a third aspect, embodiments of the present application further provide an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores information that can be executed by the at least one processor. a computer program executed by at least one processor, So that at least one processor can execute the crawling control method of any embodiment of the present application.

In the fourth aspect, embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium stores computer instructions. The computer instructions are used to enable the processor to implement the crawling control method of any embodiment of the application when executed.

It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of the application, nor is it intended to limit the scope of the application. Other features of the present application will become readily understood from the following description.

Description of the drawings

The drawings needed to be used in the description of the embodiments will be briefly introduced below. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting creative efforts.

Figure 1 is a flow chart of a crawling control method provided in the embodiment of the present application;

Figure 2 is another flow chart of a crawling control method provided in the embodiment of the present application;

Figure 3 is a schematic structural diagram of a crawling control device provided in an embodiment of the present application;

Figure 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.

Detailed ways

For vehicle crawling control, the method of obtaining torque based on the difference between the actual vehicle speed and the target vehicle speed is used to obtain the target torque through proportional adjustment and slope adjustment. The process is too rough, has poor stability, and cannot control the car better.

Considering the above situation, embodiments of the present application disclose a crawling control method, device, electronic device and storage medium.

The embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall within the scope of protection of this application.

It should be noted that the terms "first", "second", etc. in the description and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances so that the embodiments of the application described herein can be practiced in sequences other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, e.g., a process, method, system, product, or apparatus that encompasses a series of steps or units and need not be limited to those explicitly listed. That These steps or elements may include other steps or elements not expressly listed or inherent to such processes, methods, products or apparatuses.

Figure 1 is a flow chart of a crawling control method provided in an embodiment of the present application. This embodiment can cope with various working conditions during the crawling process. The method can be executed by a crawling control device. The crawling control device can adopt Implemented in the form of hardware and/or software, the crawling control device can be configured in electronic equipment. As shown in Figure 1, the method in the embodiment of the present application includes the following steps:

S110. Obtain the measured values of the driving parameters of the electric vehicle during driving.

Among them, the driving parameters include driving speed and driving acceleration. The driving speed can be used to indicate the speed of the electric vehicle during driving. The driving acceleration refers to the rate of change of the electric vehicle's driving speed per unit time, which can reflect the speed of the electric vehicle in a certain period. A state of motion at a moment.

For example, while the electric vehicle is driving, the measured value of the driving speed and the measured value of the driving acceleration of the electric vehicle are obtained based on the sensors of the electric vehicle.

S120. Obtain the estimated values of the driving parameters based on the measured values of the driving parameters and the dynamic model of the sloped road surface.

For example, based on the measured value of the driving speed, the measured value of the driving acceleration and the vehicle speed dynamics model, the estimated value of the driving speed is obtained. Among them, the vehicle speed dynamics model is m is the mass of the electric vehicle, g represents the acceleration of gravity, is _the estimated value _of the driving speed, _V area, C _D is the air resistance coefficient, θ is the measured value of the road slope, and x is the time.

In an example, the tire force of an electric vehicle on a flat road And the relationship between the driving acceleration a _x of the electric vehicle and the tire force F _x is _max = F _x , then through the vehicle speed dynamics model tire force and the relationship between the driving acceleration a _x and the tire force F _x ma _x = F _x to obtain the estimated value of the driving speed At the same time, the driving acceleration is obtained through the sensor of the electric vehicle After the measured value a _x , the estimated value of the driving acceleration is determined by the difference between the next moment of the driving acceleration and the previous moment.

S130. Obtain the observed values of the driving parameters based on the estimated values of the driving parameters and the state observation model.

For example, when obtaining an estimate of the driving speed of an electric vehicle and estimated driving acceleration Then, based on the state observation model, the correction term is calculated. The correction term includes the correction term for the driving speed and the correction term for the driving acceleration, which is used to estimate the driving speed of the electric vehicle. and estimated driving acceleration Make corrections, and then obtain the observed values of driving speed respectively. and the observed values of driving acceleration

S140. Calculate the approach control value of the electric vehicle on the sloped road according to the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the crawling conditions of the electric vehicle during driving.

For example, after obtaining and calculating the measured value V _x of the driving speed and the estimated value of the driving speed Observed values of driving speed Measured value a _x of driving acceleration, estimated value of driving acceleration and the observed values of driving acceleration Afterwards, based on the crawling conditions of the electric vehicle during driving, the approach control value of the electric vehicle on the sloped road is calculated.

On the basis of the above embodiments, in one embodiment, the sliding mode surface function is obtained based on the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the sliding mode surface parameters; when the electric vehicle crawls When the working condition is in a stable state, the sliding mode surface function is derived, and the estimated value of the sliding mode surface function and the driving speed is equal to 0, and the approach control value of the electric vehicle on the slope road is calculated; when the electric vehicle is in the crawling condition When in an unstable state, the power approach law calculation is performed on the sliding mode surface function to obtain the approach control value of the electric vehicle on the sloped road surface.

Among them, the sliding mode surface parameter is C, which represents the slope of the crawling condition during the driving of the electric vehicle. The sliding mode surface function Where, e= _Vx - _Vd , e represents the difference between the measured value _of _the actual vehicle speed _V is the estimated value of the driving speed The acceleration relative to the crawling target vehicle speed V _d difference.

For example, after determining the sliding mode surface function s, derive the sliding mode surface function s to obtain the sliding mode surface function When the electric vehicle enters the sliding mode surface, let the derivative of the sliding mode surface function At the same time, the target vehicle speed is required to be a preset stable value, so the reciprocal of the crawling target vehicle speed of the electric vehicle is the crawling target vehicle speed v _d acceleration is 0, then it passes Deduced combine The approach control value of electric vehicles on sloped roads is derived, that is, the motor torque of electric vehicles.

On the basis of the above embodiments, in one embodiment, when the crawling condition of the electric vehicle is in a stable state, the approach control value of the electric vehicle on the sloped road for the crawling condition _{is MT,D} 1; when the electric vehicle is in a stable state, When the car's crawling condition is in an unstable state, the approach control value of the electric vehicle on the sloped road is M _T,D 2.

In one embodiment, when the crawling condition of the electric vehicle is in a stable state, for the crawling condition, the motor torque of the electric vehicle is That is, when the crawling condition of the electric vehicle is in an unstable state, for the crawling condition, the sliding mode surface function Among them, ε>0, 0<α<1, sgn represents the sign function, k is a constant term, when s>0, the sign function takes 1, when s<0, the sign function takes -1, and finally through and Deriving motor torque for electric vehicles

Through this setting, the electric torque of the electric vehicle during crawling conditions can be calculated to maintain the stability of vehicle control.

In the embodiment of the present application, the measured values of the driving parameters of the electric vehicle are obtained during driving; the estimated values of the driving parameters are obtained based on the measured values of the driving parameters and the dynamic model of the sloped road surface; and the estimated values of the driving parameters are obtained based on the estimated values of the driving parameters and The state observation model is used to obtain the observed values of the driving parameters; based on the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the crawling conditions of the electric vehicle during driving, the trend of the electric vehicle on the slope road is calculated. near control value. On the basis of the above embodiments, by obtaining the driving parameters of the electric vehicle and predicting the driving parameters, the approach control value of the electric vehicle on the slope road is finally obtained, maintaining the stability of the vehicle control and coping with various working conditions during the crawling process. .

Figure 2 is another flowchart of a crawling control method provided in the embodiment of the present application. Based on the above embodiment, it describes how to calculate the observed values of the driving parameters and the driving parameters of the electric vehicle based on the estimated values of the driving parameters. The approach control value of the sloped road surface is shown in Figure 2. The method includes the following steps:

S210. Obtain the measured values of the driving parameters of the electric vehicle during driving.

S220. Obtain the estimated values of the driving parameters based on the measured values of the driving parameters and the dynamic model of the sloped road surface.

For example, based on the measured value of the driving speed, the measured value of the driving acceleration and the vehicle speed dynamics model, the estimated value of the driving speed is obtained. Among them, the vehicle speed dynamics model is m is the mass of the electric vehicle, is _the estimated value _of the driving speed, _V area, C _D is the air resistance coefficient, θ is the measured value of the road slope, and x is the time.

In an example, the tire force of an electric vehicle on a flat road And the relationship between the driving acceleration a _x of the electric vehicle and the tire force F _x is _max = F _x , then through the vehicle speed dynamics model tire force and the relationship between the driving acceleration a _x and the tire force F _x ma _x = F _x to obtain the estimated value of the driving speed At the same time, after the measured value _a

S230. Calculate the correction term based on the estimated values of the driving parameters and the state observation model.

Among them, the correction terms include the correction term of driving speed and the correction term of driving acceleration.

For example, based on the measured value V _x of the driving speed and the estimated value of the driving speed The correction term to determine the driving speed is Based on the measured value a _x of the driving acceleration and the estimated value of the driving acceleration The correction term to determine the driving acceleration is

S240: Obtain the observed value of the traveling vehicle speed based on the estimated value of the traveling vehicle speed and the correction term of the traveling vehicle speed, and obtain the observed value of the traveling acceleration based on the estimated value of the traveling vehicle speed and the correction term of the traveling vehicle speed.

For example, the state observation model based on the driving speed and the correction term of the driving acceleration are Calculate the observed value of driving speed The correction term based on the state observation model of driving acceleration and the driving speed is Calculate the observed value of driving acceleration

S250: Calculate the approach control value of the electric vehicle on the sloped road according to the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the crawling conditions of the electric vehicle during driving.

In the embodiment of the present application, by obtaining the measured values of the driving parameters of the electric vehicle during driving, the estimated values of the driving parameters are obtained based on the measured values of the driving parameters and the dynamic model of the sloped road surface, and the correction terms are calculated based on the state observation model. , according to the estimated value of the driving speed and the correction term of the driving acceleration, the observed value of the driving speed is obtained, and according to the estimated value of the driving acceleration and the correction term of the driving speed, the observed value of the driving acceleration is obtained, according to the driving parameter Measured values, estimated values of driving parameters, observed values of driving parameters and the crawling conditions of electric vehicles during driving are used to calculate the approach control value of electric vehicles on sloped roads. On the basis of the above embodiment, by obtaining the driving parameters of the electric vehicle, then correcting the driving parameters through the correction term, and predicting the corrected driving parameters, the approach control value of the electric vehicle on the slope road is finally obtained, that is, the electric vehicle The motor torque of the car during the crawling process enables the electric vehicle to maintain the stability of vehicle control and cope with various working conditions during the crawling process.

Figure 3 is a schematic structural diagram of a crawling control device provided in an embodiment of the present application. As shown in Figure 3, the device includes: a parameter acquisition module 310, a first calculation module 320, a second calculation module 330 and a third calculation module. 340. in,

The parameter acquisition module 310 is configured to acquire the measured values of the driving parameters of the electric vehicle during driving.

The first calculation module 320 is configured to obtain an estimate of the driving parameters based on the measured values of the driving parameters and the dynamic model of the sloped road surface.

The second calculation module 330 is configured to obtain the observed value of the driving parameter based on the estimated value of the driving parameter and the state observation model.

The third calculation module 340 is configured to calculate the approach control value of the electric vehicle on the sloped road based on the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the crawling conditions of the electric vehicle during driving. .

In one embodiment, the driving parameters include driving speed and driving acceleration.

In one embodiment, the first calculation module 320 is configured to: obtain an estimated value of the driving speed based on the measured value of the driving speed, the measured value of the driving acceleration, and the vehicle speed dynamics model; and obtain the driving acceleration based on the measured value of the driving acceleration. estimated value.

In one embodiment, the vehicle speed dynamics model is Among them, m is the mass of the electric vehicle, is the estimated value of the driving speed, v is the measured value of the driving speed, M _{T, D} is the motor torque, r is the wheel rolling radius, f _r is the road rolling resistance coefficient, ρ is the air density, A is the windward area of the electric vehicle, C _D is the air resistance coefficient, and θ is the measured value of the road slope.

In one embodiment, the second calculation module 330 is configured to: calculate a correction term according to the state observation model, the correction term includes a correction term for the driving speed and a correction term for the driving acceleration; according to the estimated value of the driving speed and the driving acceleration The correction term is used to obtain the observed value of the driving speed, and the correction term is based on the estimated value of the driving acceleration and the driving speed to obtain the observed value of the driving acceleration.

In one embodiment, the third calculation module 340 is configured to: obtain the sliding mode surface function based on the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the sliding mode surface parameters; when the electric vehicle When the crawling condition is in a stable state, the sliding mode surface function is derived, and the estimated value of the sliding mode surface function and the driving speed is equal to 0, and the approach control value of the electric vehicle on the slope road is calculated; when the crawling condition of the electric vehicle is When the situation is in an unstable state, the power approach law calculation is performed on the sliding mode surface function to obtain the approach control value of the electric vehicle on the sloped road surface.

In one embodiment, the third calculation module 340 is set as follows: when the crawling condition of the electric vehicle is in a stable state, the approach control value of the electric vehicle on the sloped road _{is MT,D} 1; when the crawling condition of the electric vehicle is When the situation is in an unstable state, the approach control value of the electric vehicle on the slope road is M _T,D 2.

The crawling control device provided by the embodiments of this application can execute the crawling control method provided by any embodiment of this application, and has functional modules and beneficial effects corresponding to the execution method.

FIG. 4 shows a schematic structural diagram of an electronic device 10 that can be used to implement embodiments of the present application. Electronic devices are intended to refer to various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (eg, helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are examples only and are not intended to limit the implementation of the present application as described and/or claimed herein.

As shown in Figure 4, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (Read-Only Memory, ROM) 12, a random access memory (Random Access Memory, RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can be loaded into the random access memory (RAM) according to the computer program stored in the read-only memory (ROM) 12 or from the storage unit 18. A computer program in RAM) 13 to perform various appropriate actions and processes. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via the bus 14. An input/output (I/O) interface 15 is also connected to the bus 14 .

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

Processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU), various dedicated artificial intelligence (Artificial Intelligence, AI) computing chips, various running Machine learning model algorithm processor, digital signal processor (Digital Signal Processor, DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes various methods and processes described above, such as the crawling control method.

In some embodiments, the crawling control method may be implemented as a computer program, which is tangibly included in a computer-readable storage medium, such as the storage unit 18 . In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19 . When the computer program is loaded into RAM 13 and executed by processor 11, the above described One or more steps of the crawling control method. Alternatively, in other embodiments, the processor 11 may be configured to perform the crawling control method in any other suitable manner (eg, by means of firmware).

Various implementations of the systems and techniques described above may be implemented in digital electronic circuit systems, integrated circuit systems, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Product (ASSP), System on Chip (SOC), Complex Programmable Logic Device (CPLD), computer hardware, firmware, software, and/or they realized in a combination. These various embodiments may include implementation in one or more computer programs executable and/or interpreted on a programmable system including at least one programmable processor, the programmable processor The processor, which may be a special purpose or general purpose programmable processor, may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device. An output device.

Computer programs for implementing the methods of the present application 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 the computer program, when executed by the processor, causes the functions/operations specified in the flowcharts and/or block diagrams to be implemented. A computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

The storage medium may be a non-transitory storage medium.

In the context of this application, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium may be a machine-readable signal medium. Examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer disks, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (Erasable Programmable Read-Only Memory (EPROM) or flash memory, optical fiber, portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above .

To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having a display device (eg, a cathode ray tube) for displaying information to a user. Ray Tube (CRT) or Liquid Crystal Display (LCD) monitor); and a keyboard and pointing device (eg, a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and may be provided in any form, including Acoustic input, voice input or tactile input) to receive input from the user.

The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., A user's computer having a graphical user interface or web browser through which the user can interact with implementations of the systems and technologies described herein), or including such backend components, middleware components, or any combination of front-end components in a computing system. The components of the system may be interconnected by any form or medium of digital data communication (eg, a communications network). Examples of communication networks include: Local Area Network (LAN), Wide Area Network (WAN), blockchain network, and the Internet.

Computing systems may include clients and servers. Clients and servers are generally remote from each other and typically interact over a communications network. The relationship of client and server is created by computer programs running on corresponding computers and having a client-server relationship with each other. The server can be a cloud server, also known as cloud computing server or cloud host. It is a host product in the cloud computing service system to solve the problems that exist in traditional physical host and virtual private server (VPS) services. It has the disadvantages of difficult management and weak business scalability.

Embodiments of the present application provide a crawling control method, device, electronic equipment and storage medium to cope with various working conditions of the crawling process, so that the electric vehicle has a certain degree of robustness during the crawling control process.

It should be understood that various forms of the process shown above may be used, with steps reordered, added or deleted. For example, each step described in this application can be executed in parallel, sequentially, or in a different order, which is not limited herein.

The above-mentioned specific embodiments do not constitute a limitation on the scope of protection of the present application. It will be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions are possible depending on design requirements and other factors.

Claims

A crawling control method includes:

Obtain the measured values of the driving parameters of the electric vehicle during driving;

According to the measured values of the driving parameters and the dynamic model of the sloped road surface, the estimated values of the driving parameters are obtained;

According to the estimated value of the driving parameter and the state observation model, the observed value of the driving parameter is obtained;

Calculate the approach of the electric vehicle on a sloped road according to the measured values of the driving parameters, the estimated values of the driving parameters, the observed values of the driving parameters and the crawling conditions of the electric vehicle during driving. control value.
The method of claim 1, wherein the driving parameters include driving speed and driving acceleration.
The method according to claim 2, wherein obtaining the estimated value of the driving parameter based on the measured value of the driving parameter and the dynamic model of the sloped road surface includes:

Obtain the estimated value of the driving speed according to the measured value of the driving speed, the measured value of the driving acceleration and the vehicle speed dynamics model;

The estimated value of the traveling acceleration is obtained based on the measured value of the traveling acceleration.
The method of claim 3, wherein,

The vehicle speed dynamics model is

Among them, m is the mass of the electric vehicle, is the estimated value of the driving speed, v is the measured value of the driving speed, M T, D is the motor torque, r is the wheel rolling radius, f r is the road rolling resistance coefficient, ρ is the air density, and A is the Describe the windward area of the electric vehicle, C D is the air resistance coefficient, and θ is the measured value of the road slope.
The method according to claim 2, wherein obtaining the observed value of the driving parameter based on the estimated value of the driving parameter and the state observation model includes:

According to the state observation model, a correction term is calculated, and the correction term includes a correction term for the driving speed and a correction term for the driving acceleration;

According to the estimated value of the traveling vehicle speed and the correction term of the traveling acceleration, an observed value of the traveling vehicle speed is obtained, and according to the estimated value of the traveling acceleration and the correction term of the traveling vehicle speed, an observed value of the traveling acceleration is obtained.
The method according to claim 2, wherein the method is based on the measured value of the driving parameter, the estimated value of the driving parameter, the observed value of the driving parameter and the crawling work of the electric vehicle during driving. Under this condition, calculate the approach control value of the electric vehicle on a sloped road, including:

According to the measured value of the driving parameter, the estimated value of the driving parameter, the observed value of the driving parameter and the sliding mode surface parameter, a sliding mode surface function is obtained;

In response to the crawling condition of the electric vehicle being in a stable state, the sliding mode surface function is derived, and the estimated value of the sliding mode surface function and the driving speed is equal to 0, and the electric vehicle is calculated. Approach control value for sloped pavement;

In response to the fact that the crawling condition of the electric vehicle is in an unstable state, a power approach law calculation is performed on the sliding mode surface function to obtain the approach control value of the electric vehicle on a sloped road surface.
The method of claim 6, wherein

When the crawling condition of the electric vehicle is in a stable state, the approach control value of the electric vehicle on a sloped road is MT,D 1;

When the crawling condition of the electric vehicle is in an unstable state, the approach control value of the electric vehicle on a sloped road is MT,D 2 .
A crawling control device including:

The parameter acquisition module is configured to obtain the measured values of the driving parameters of the electric vehicle during driving;

The first calculation module is configured to obtain the estimated value of the driving parameter based on the measured value of the driving parameter and the dynamic model of the sloped road surface;

The second calculation module is configured to obtain the observed value of the driving parameter based on the estimated value of the driving parameter and the state observation model;

The third calculation module is configured to calculate the electric vehicle based on the measured value of the driving parameter, the estimated value of the driving parameter, the observed value of the driving parameter and the crawling condition of the electric vehicle during driving. The approach control value of a car on a sloped road.
An electronic device including:

at least one processor; and

a memory communicatively connected to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor, so that the at least one processor can execute any one of claims 1-7 The crawling control method.
A computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the crawling control method described in any one of claims 1-7 when executed by a processor.