CN116238479A - Vehicle drift control method, device, equipment and storage medium - Google Patents
Vehicle drift control method, device, equipment and storage medium Download PDFInfo
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- CN116238479A CN116238479A CN202310190851.6A CN202310190851A CN116238479A CN 116238479 A CN116238479 A CN 116238479A CN 202310190851 A CN202310190851 A CN 202310190851A CN 116238479 A CN116238479 A CN 116238479A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/02—Control of vehicle driving stability
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/02—Control of vehicle driving stability
- B60W30/045—Improving turning performance
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/18—Propelling the vehicle
- B60W30/18009—Propelling the vehicle related to particular drive situations
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/72—Electric energy management in electromobility
Abstract
The invention discloses a vehicle drift control method, device and equipment and a storage medium, and belongs to the technical field of vehicle control. The invention obtains the current state parameters of the vehicle; determining a parameter difference value between the current state parameter and a preset state parameter; calculating a target control parameter according to the parameter difference value and a vehicle state error model; and carrying out drift control on the vehicle according to the target control parameters, calculating the target control parameters according to the current state parameters of the vehicle and the preset state parameters to be achieved, and then directly carrying out drift control on the vehicle through the target control parameters without calibrating the physical parameters of the vehicle, and directly calibrating the control parameters without depending on an empirical dynamic model, thereby improving the accuracy of vehicle drift control.
Description
Technical Field
The present invention relates to the field of vehicle control technologies, and in particular, to a vehicle drift control method, device, apparatus, and storage medium.
Background
The limit control such as drifting and tail flicking can break through the constraint of steady-state control, give the vehicle a larger degree of freedom, and improve the active safety of the vehicle under the working conditions such as sideslip, side tipping, low road surface adhesion and the like.
The automatic driving control technology is mainly oriented to the steady-state control of the vehicle, all wheels have good ground grabbing force, and the state of the vehicle is on a stable balance surface similar to an ideal Ackerman model. When the state of the vehicle is disturbed, the vehicle tends to automatically recover to the balance state, and the control difficulty is low. When the vehicle is in limit working conditions such as sideslip, drifting, tail flicking and the like, the rear wheels are generally in a slipping state. To maintain balance, the front wheels need to be counter-steered, with the vehicle condition on an unstable balance surface. When the state of the vehicle is disturbed, the vehicle tends to deviate from the balance state continuously, and the control difficulty is high.
The existing automatic driving drift control technology generally needs to calibrate physical parameters such as the gravity center position, the moment of inertia, the tire friction curve and the like of a vehicle in advance and substitutes the physical parameters into a vehicle dynamics equation to calculate the relation between the control quantity and the vehicle dynamic response, but the existing problems are that 1, part of vehicle parameters are complex and changeable and are difficult to calibrate accurately; 2. the friction force changes along with the ground state, so that the friction force is difficult to calibrate in advance; 3. the empirical dynamic model and the actual vehicle state have deviation, the vehicle is out of control due to small calculation errors, and the accuracy of the vehicle drift control cannot be ensured by the existing mode due to the defects.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a vehicle drift control method, device, equipment and storage medium, and aims to solve the technical problem that the drift of a vehicle cannot be accurately controlled in the prior art.
In order to achieve the above object, the present invention provides a vehicle drift control method including the steps of:
acquiring current state parameters of a vehicle;
determining a parameter difference value between the current state parameter and a preset state parameter;
calculating a target control parameter according to the parameter difference value and a vehicle state error model;
and carrying out drift control on the vehicle according to the target control parameter.
Optionally, before calculating the target control parameter according to the parameter difference value and the vehicle state error model, the method further includes:
acquiring historical parameter information of the vehicle;
and constructing a vehicle state error model corresponding to the vehicle according to the historical parameter information.
Optionally, the constructing a vehicle state error model corresponding to the vehicle according to the historical parameter information includes:
extracting a historical steady state parameter and a historical steady state control parameter from the historical parameter information;
determining model parameters according to the historical steady state parameters and the historical steady state control parameters;
and constructing a vehicle state error model corresponding to the vehicle according to the model parameters.
Optionally, the historical steady state parameters at least include a historical centroid speed slip angle, a historical yaw rate and a historical vertical axis direction speed, the historical steady state control parameters at least include a historical steering wheel angle and a historical rear wheel driving force, and the extracting the historical steady state parameters and the historical steady state control parameters from the historical parameter information includes:
acquiring a historical centroid speed slip angle and a historical yaw rate of the vehicle from the historical parameter information;
constructing a state parameter two-dimensional curved surface according to a plurality of reference state parameters of the vehicle in different steady-state drift states;
constructing a control parameter two-dimensional curved surface according to a plurality of reference control parameters of the vehicle in different steady-state drift states;
and acquiring the historical longitudinal axis direction speed, the historical steering wheel corner and the historical rear wheel driving force of the vehicle according to the historical centroid speed slip angle, the historical yaw rate, the state parameter two-dimensional curved surface and the control parameter two-dimensional curved surface.
Optionally, the obtaining the historical longitudinal axis direction speed, the historical steering wheel angle and the historical rear wheel driving force of the vehicle according to the historical centroid speed slip angle, the historical yaw rate, the state parameter two-dimensional curved surface and the control parameter two-dimensional curved surface includes:
searching a historical longitudinal axis direction speed from the state parameter two-dimensional curved surface based on the historical centroid speed slip angle and the historical yaw rate;
and searching a historical steering wheel corner and a historical rear wheel driving force from the control parameter two-dimensional curved surface based on the historical centroid speed slip angle and the historical yaw rate.
Optionally, before the constructing the two-dimensional curved surface of the state parameter according to the plurality of reference state parameters of the vehicle in different steady-state drift states, the method further includes:
controlling the vehicle from a stationary state to a steady state drift state through an open loop drift model;
and when the vehicle is in a steady-state drift state, adjusting open-loop control parameters of the open-loop drift model to change the vehicle from the current steady-state drift state to other steady-state drift states.
Optionally, the calculating a target control parameter according to the parameter difference value and a vehicle state error model comprises;
inputting the parameter difference value into a vehicle state error model to obtain a correction quantity of a control parameter;
and determining a target control parameter according to the correction quantity of the control parameter and the current control parameter.
In addition, in order to achieve the above object, the present invention also proposes a vehicle drift control device including:
the acquisition module is used for acquiring current state parameters of the vehicle;
the calculation module is used for determining a parameter difference value between the current state parameter and a preset state parameter;
the calculation module is also used for calculating a target control parameter according to the parameter difference value and a vehicle state error model;
and the control module is used for carrying out drift control on the vehicle according to the target control parameter.
In addition, in order to achieve the above object, the present invention also proposes a vehicle drift control apparatus including: a memory, a processor, and a vehicle drift control program stored on the memory and running on the processor, the vehicle drift control program configured to implement the vehicle drift control method as described above.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon a vehicle drift control program which, when executed by a processor, implements the vehicle drift control method as described above.
The invention obtains the current state parameters of the vehicle; determining a parameter difference value between the current state parameter and a preset state parameter; calculating a target control parameter according to the parameter difference value and a vehicle state error model; and carrying out drift control on the vehicle according to the target control parameters, calculating the target control parameters according to the current state parameters of the vehicle and the preset state parameters to be achieved, and then directly carrying out drift control on the vehicle through the target control parameters without calibrating the physical parameters of the vehicle, and directly calibrating the control parameters without depending on an empirical dynamic model, thereby improving the accuracy of vehicle drift control.
Drawings
Fig. 1 is a schematic structural diagram of a vehicle drift control device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of a vehicle drift control method according to the present invention;
FIG. 3 is a schematic diagram of a vehicle model according to an embodiment of the present invention;
FIG. 4 is a flow chart of a second embodiment of the vehicle drift control method of the present invention;
FIG. 5 is a flow chart of an open loop float model in an embodiment of a vehicle drift control method according to the present invention;
FIG. 6 is a schematic view of a two-dimensional curved surface of a state parameter according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a two-dimensional curved surface of a control parameter according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a two-dimensional curved surface of another control parameter according to an embodiment of the present invention;
FIG. 9 is a flow chart of a third embodiment of a vehicle drift control method according to the present invention;
fig. 10 is a block diagram showing the construction of a first embodiment of the vehicle drift control device according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic diagram of a vehicle drift control device in a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the vehicle drift control device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the vehicle drift control device, and may include more or fewer components than shown, or may combine certain components, or may be a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a vehicle drift control program may be included in the memory 1005 as one type of storage medium.
In the vehicle drift control device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the vehicle drift control device of the present invention may be provided in the vehicle drift control device, and the vehicle drift control device invokes the vehicle drift control program stored in the memory 1005 through the processor 1001 and executes the vehicle drift control method provided by the embodiment of the present invention.
An embodiment of the present invention provides a vehicle drift control method, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a vehicle drift control method according to the present invention.
In this embodiment, the vehicle drift control method includes the steps of:
step S10: the current state parameters of the vehicle are obtained.
In this embodiment, the execution body of the embodiment is the vehicle drift control device, and the vehicle drift control device has functions of data collection, data communication, program running, and the like. Of course, other devices having similar functions may be used, and this embodiment is not limited thereto, and the vehicle drift control device is described as an example in this embodiment.
It should be noted that the automatic driving control technology is mainly oriented to steady-state control of the vehicle, all wheels have good ground grabbing force, and the vehicle state is on a stable balance plane similar to an ideal ackerman model. When the state of the vehicle is disturbed, the vehicle tends to automatically recover to the balance state, and the control difficulty is low. When the vehicle is in limit working conditions such as sideslip, drifting, tail flicking and the like, the rear wheels are generally in a slipping state. To maintain balance, the front wheels need to be counter-steered, with the vehicle condition on an unstable balance surface. When the state of the vehicle is disturbed, the vehicle tends to deviate from the balance state continuously, and the control difficulty is high. However, the existing automatic driving drift control technology generally needs to calibrate physical parameters such as the gravity center position, the moment of inertia, the tire friction curve and the like of a vehicle in advance and substitutes the physical parameters into a vehicle dynamics equation to calculate the relation between the control quantity and the vehicle dynamic response, but the existing problems are that part of vehicle parameters are complex and changeable and are difficult to calibrate accurately; the friction force changes along with the ground state, so that the friction force is difficult to calibrate in advance; the empirical dynamic model and the actual vehicle state have deviation, the vehicle is out of control due to small calculation errors, and the accuracy of the vehicle drift control cannot be ensured by the existing mode due to the defects.
In order to solve the above technical problems, in this embodiment, a current state parameter of a vehicle is obtained; determining a parameter difference value between the current state parameter and a preset state parameter; calculating a target control parameter according to the parameter difference value and a vehicle state error model; and carrying out drift control on the vehicle according to the target control parameters, calculating the target control parameters according to the current state parameters of the vehicle and the preset state parameters to be achieved, and then directly carrying out drift control on the vehicle through the target control parameters without calibrating the physical parameters of the vehicle, and directly calibrating the control parameters without depending on an empirical dynamic model, thereby improving the accuracy of the drift control of the vehicle.
In a specific implementation, the embodiment does not depend on an empirical dynamics model, does not need to calibrate physical parameters of the vehicle, and can directly acquire current state parameters of the vehicle when the vehicle is required to drift control, wherein the current state parameters of the vehicle acquired in the embodiment include, but are not limited to, a centroid speed slip angle, a yaw speed and a longitudinal axis direction speed. When the vehicle enters a drifting balance state, the vehicle is a three-degree-of-freedom model. The different drift directions are designated, which can be simplified into a two-degree-of-freedom model, i.e. two linear independent dynamic parameters are specified to determine the vehicle state when all other drifts occur, as shown in fig. 3. In fig. 3, r represents the yaw rate of the vehicle, β represents the centroid speed slip angle of the vehicle, V represents the longitudinal axis direction speed of the vehicle, fxr and Fxy represent the tire driving force of the vehicle, and Φ represents the steering wheel angle of the vehicle.
In this embodiment, the centroid speed slip angle and the yaw rate are selected as the control variables, and the vertical axis direction speed is used as the parameter for focusing on the vehicle state, so that the current state of the vehicle can be determined by the above parameters, and it is emphasized that when the centroid speed slip angle, the yaw rate, and the vertical axis direction speed are in a stable state, particularly when the vertical axis direction speed is in the vicinity of the steady state drift point, the vehicle at this time can be considered to be in a steady state drift state. It should be noted that, the current state parameter is an example, and in a specific process, other parameters may be selected as the state parameter of the vehicle based on different control requirements, which is not limited in this embodiment.
Step S20: and determining a parameter difference value between the current state parameter and a preset state parameter.
In a specific implementation, after the current state parameter of the vehicle is obtained, in this embodiment, a parameter difference between the current state parameter and a preset state parameter is further required to be calculated, where the preset state parameter is a state parameter corresponding to a target steady state drift state, and the target steady state drift state is a preselected steady state drift state that needs to be implemented by the vehicle, and may be selected according to an actual requirement, which is not limited in this embodiment.
In this embodiment, for the above process, for example, the yaw rate and the centroid rate slip angle in the current state parameter and the preset state parameter are not changed, and the current state and the target steady-state drift state of the vehicle are only different in the longitudinal axis direction speed of the vehicle, and the parameter difference at this time can be calculated to be 1m/s assuming that the current longitudinal axis direction speed of the vehicle is 11m/s and the preset longitudinal axis direction speed is 10 m/s.
Step S30: and calculating target control parameters according to the parameter difference value and the vehicle state error model.
In a specific implementation, after the parameter difference is obtained by calculation, in this embodiment, the parameter difference may be substituted into the vehicle state error model to perform calculation, so as to obtain the target control parameter. Specifically, the parameter difference between the control parameters may be calculated based on the parameter difference of the state parameter, and the target control parameter may be calculated based on the parameter difference between the control parameters.
Step S40: and carrying out drift control on the vehicle according to the target control parameter.
In a specific implementation, when the vehicle is in different steady-state drift states, the corresponding control parameters are different, and the corresponding relation between the control parameters and the different steady-state drift states can be searched from a pre-constructed two-dimensional curved surface. After the corresponding target control parameters are found, the vehicle is controlled according to the steering wheel angle and the rear wheel driving force contained in the target control parameters in the embodiment, so that the vehicle is in a target steady-state drifting state, namely a steady-state drifting state which needs to be achieved by the vehicle.
The embodiment obtains the current state parameters of the vehicle; determining a parameter difference value between the current state parameter and a preset state parameter; calculating a target control parameter according to the parameter difference value and a vehicle state error model; and carrying out drift control on the vehicle according to the target control parameters, calculating the target control parameters according to the current state parameters of the vehicle and the preset state parameters to be achieved, and then directly carrying out drift control on the vehicle through the target control parameters without calibrating the physical parameters of the vehicle, and directly calibrating the control parameters without depending on an empirical dynamic model, thereby improving the accuracy of vehicle drift control.
Referring to fig. 4, fig. 4 is a flowchart of a second embodiment of a vehicle drift control method according to the present invention.
Based on the first embodiment, the vehicle drift control method of the present embodiment further includes, before the step S30:
step S301: and acquiring historical parameter information of the vehicle.
It should be noted that, before calculating the target control parameter, in this embodiment, the historical parameter information of the vehicle needs to be acquired first, and for a vehicle with an unknown parameter, in this embodiment, an open loop drift starting model is used to control the vehicle from a stationary state to a steady state drift, and the drift parameter is recorded, where a flowchart of the open loop drift starting model is shown in fig. 5, and by adjusting the open loop control parameter of the open loop drift starting model, the vehicle can be in different steady state drift states, and because one steady state drift state corresponds to one set of drift parameters, multiple sets of drift parameters of the vehicle can be finally recorded and obtained. The recorded drift parameters include at least longitudinal axis direction speed, steering wheel angle and rear wheel driving force, and centroid speed slip angle and yaw rate in different drift states. In this embodiment, other parameters may be recorded or selected according to the actual requirement for constructing the vehicle state error model, which is not limited.
Step S302: and constructing a vehicle state error model corresponding to the vehicle according to the historical parameter information.
In a specific implementation, after the historical parameter information is obtained, the historical steady state parameter and the historical steady state control parameter are further extracted from the historical parameter information in the embodiment. Specifically, the historical centroid speed slip angle and the historical yaw rate of the vehicle can be obtained from the obtained historical parameter information, then a plurality of groups of parameters recorded in an open loop drift model under different steady-state drift states, namely a plurality of reference state parameters and a plurality of reference control parameters are utilized to construct a two-dimensional curved surface, wherein the reference state parameters comprise longitudinal axis direction speed, centroid speed slip angle and yaw rate, the two-dimensional curved surface of the state parameters can be constructed according to the parameters, the reference control parameters comprise steering wheel rotation angle and rear wheel driving force, and the two-dimensional curved surface of the control parameters can be constructed according to the parameters. After the two parameter curved surfaces are obtained, the historical centroid speed slip angle and the historical yaw rate obtained from the historical parameter information can be combined with the two parameter curved surfaces in the embodiment, so that the historical longitudinal axis direction speed, the historical steering wheel rotation angle and the historical rear wheel driving force can be determined.
The curved surfaces of the two parameters obtained in the process are shown in fig. 6-8. Referring to fig. 6, fig. 6 is a curved surface of state parameters, where u_x_low shown in fig. 6 represents a vertical axis direction speed, yaw_rate_low represents a yaw rate, bata_low represents a centroid speed slip angle, and coordinate points in the graph represent vertical axis direction speed, centroid speed slip angle, and yaw rate corresponding to different steady-state drift states. Fig. 7 and 8 are control parameter curves, delta_low in fig. 7 represents a steering wheel angle, and fx_r_low in fig. 8 represents a rear wheel driving force.
Further, after the historical steady state parameters and the historical steady state control parameters are obtained, in this embodiment, model parameters of a vehicle state error model may be determined according to the parameters, and then a vehicle state error model corresponding to the vehicle may be constructed based on the model parameters.
In a specific implementation, after the two-dimensional curved surface with the parameters is built, a coordinate point corresponding to the historical centroid speed slip angle and the historical yaw rate can be found according to the unique corresponding relation in the two-dimensional curved surface with the state parameters, the coordinate value corresponding to the coordinate point comprises the historical longitudinal axis direction speed, so that the historical longitudinal axis direction speed can be obtained, similarly, the historical steering wheel corner and the historical rear wheel driving force can be found according to the historical centroid speed slip angle and the historical yaw rate, and all the state and control parameters are found according to the historical centroid speed slip angle and the historical yaw rate. The obtained historical centroid speed slip angle, the historical yaw rate and the historical longitudinal axis direction speed determine the steady-state drift state of the vehicle, and the historical steering wheel angle and the historical rear wheel driving force are control parameters required by the steady-state drift state.
After the above parameters are obtained, in this embodiment, the above parameters may be substituted into an equation to solve, for example, d (Δx) =a×Δx+b×Δu, where Δx is a parameter difference of the state parameters, Δu is a parameter difference of the control parameters, and the above parameters are substituted into the equation to solve to obtain a and B, where it is to be noted that a and B in different steady-state drift states are different, and each steady-state drift state corresponds to a group of a and B.
According to the method, the device and the system, the historical parameter information of the vehicle is obtained, the historical steady state parameter and the historical steady state control parameter are extracted from the historical parameter information, the model parameter is determined according to the historical steady state parameter and the historical steady state control parameter, the vehicle state error model corresponding to the vehicle is built according to the model parameter, and the vehicle state error model corresponding to the unknown parameter can be accurately built for the vehicle, so that the accuracy of the follow-up vehicle drift control is improved.
Referring to fig. 9, fig. 9 is a flowchart of a third embodiment of a vehicle drift control method according to the present invention.
Based on the first embodiment and the second embodiment, a third embodiment of the vehicle drift control method according to the present invention is provided.
In this embodiment, the step S30 specifically includes:
step S303: and inputting the parameter difference value into a vehicle state error model to obtain the correction quantity of the control parameter.
In this embodiment, after the construction of the vehicle state error model is completed, a set of model parameters corresponding to the vehicle state error model may be determined according to the target steady-state drift state that the vehicle needs to reach, so that the correction amount of the control parameters may be calculated.
Step S304: and determining a target control parameter according to the correction quantity of the control parameter and the current control parameter.
In this embodiment, the vehicle state error model of this embodiment may be a differential equation of a vehicle state error, for example, d (Δx) =a×Δx+b×Δu, where Δx is a parameter difference between state parameters, a and B are a set of determined constant coefficients, and determined by a target steady-state drift state, and Δu may be calculated by the above equation, where Δu represents a parameter difference of a control parameter, that is, a parameter difference between a current control parameter and a target control parameter of the vehicle, and the target control parameter represents a control parameter required for the vehicle to reach the target steady-state drift state.
In the embodiment, the correction amount of the control parameter is obtained by inputting the parameter difference value into a vehicle state error model; and determining target control parameters according to the correction quantity of the control parameters and the current control parameters, and calculating final target control parameters through model parameters in different steady-state drift states, so that the accuracy of vehicle drift control is improved.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium stores a vehicle drift control program, and the vehicle drift control program realizes the steps of the vehicle drift control method when being executed by a processor.
Because the storage medium adopts all the technical schemes of all the embodiments, the storage medium has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
Referring to fig. 10, fig. 10 is a block diagram showing the construction of a first embodiment of a vehicle drift control device according to the present invention.
As shown in fig. 10, a vehicle drift control device according to an embodiment of the present invention includes:
an acquisition module 10 is configured to acquire a current state parameter of the vehicle.
A calculating module 20, configured to determine a parameter difference between the current state parameter and a preset state parameter.
The calculating module 20 is further configured to calculate a target control parameter according to the parameter difference and a vehicle state error model.
And the control module 30 is used for carrying out drift control on the vehicle according to the target control parameters.
The embodiment obtains the current state parameters of the vehicle; determining a parameter difference value between the current state parameter and a preset state parameter; calculating a target control parameter according to the parameter difference value and a vehicle state error model; and carrying out drift control on the vehicle according to the target control parameters, calculating the target control parameters according to the current state parameters of the vehicle and the preset state parameters to be achieved, and then directly carrying out drift control on the vehicle through the target control parameters without calibrating the physical parameters of the vehicle, and directly calibrating the control parameters without depending on an empirical dynamic model, thereby improving the accuracy of vehicle drift control.
In an embodiment, the vehicle drift control device further includes: constructing a module;
the construction module is used for acquiring historical parameter information of the vehicle; and constructing a vehicle state error model corresponding to the vehicle according to the historical parameter information.
In an embodiment, the construction module is further configured to extract a historical steady state status parameter and a historical steady state control parameter from the historical parameter information; determining model parameters according to the historical steady state parameters and the historical steady state control parameters; and constructing a vehicle state error model corresponding to the vehicle according to the model parameters.
In one embodiment, the historical steady state parameters include at least a historical centroid speed slip angle, a historical yaw rate, and a historical longitudinal axis direction speed, and the historical steady state control parameters include at least a historical steering wheel angle and a historical rear wheel drive force; the construction module is further used for acquiring a historical centroid speed slip angle and a historical yaw speed of the vehicle from the historical parameter information; constructing a state parameter two-dimensional curved surface according to a plurality of reference state parameters of the vehicle in different steady-state drift states; constructing a control parameter two-dimensional curved surface according to a plurality of reference control parameters of the vehicle in different steady-state drift states; and acquiring the historical longitudinal axis direction speed, the historical steering wheel corner and the historical rear wheel driving force of the vehicle according to the historical centroid speed slip angle, the historical yaw rate, the state parameter two-dimensional curved surface and the control parameter two-dimensional curved surface.
In an embodiment, the building module is further configured to find a historical longitudinal axis direction speed from the state parameter two-dimensional curved surface based on the historical centroid speed slip angle and the historical yaw angle speed; and searching a historical steering wheel corner and a historical rear wheel driving force from the control parameter two-dimensional curved surface based on the historical centroid speed slip angle and the historical yaw rate.
In one embodiment, the control module 30 is further configured to control the vehicle from a stationary state to a steady state drift state via an open loop drift model; and when the vehicle is in a steady-state drift state, adjusting open-loop control parameters of the open-loop drift model to change the vehicle from the current steady-state drift state to other steady-state drift states.
In one embodiment, the calculating module 20 is further configured to input the parameter difference value to a vehicle state error model to obtain a correction amount of the control parameter; and determining a target control parameter according to the correction quantity of the control parameter and the current control parameter.
It should be understood that the foregoing is illustrative only and is not limiting, and that in specific applications, those skilled in the art may set the invention as desired, and the invention is not limited thereto.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in the present embodiment may refer to the vehicle drift control method provided in any embodiment of the present invention, and are not described herein.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory)/RAM, magnetic disk, optical disk) and including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A vehicle drift control method, characterized by comprising:
acquiring current state parameters of a vehicle;
determining a parameter difference value between the current state parameter and a preset state parameter;
calculating a target control parameter according to the parameter difference value and a vehicle state error model;
and carrying out drift control on the vehicle according to the target control parameter.
2. The vehicle drift control method according to claim 1, characterized by further comprising, before the calculation of the target control parameter from the parameter difference and the vehicle state error model:
acquiring historical parameter information of the vehicle;
and constructing a vehicle state error model corresponding to the vehicle according to the historical parameter information.
3. The vehicle drift control method according to claim 2, wherein the constructing a vehicle state error model corresponding to the vehicle from the history parameter information includes:
extracting a historical steady state parameter and a historical steady state control parameter from the historical parameter information;
determining model parameters according to the historical steady state parameters and the historical steady state control parameters;
and constructing a vehicle state error model corresponding to the vehicle according to the model parameters.
4. The vehicle drift control method of claim 3, wherein the historical steady state condition parameters include at least a historical centroid speed slip angle, a historical yaw rate, and a historical vertical axis direction speed, the historical steady state control parameters include at least a historical steering wheel angle and a historical rear wheel drive force, and the extracting the historical steady state condition parameters and the historical steady state control parameters from the historical parameter information includes:
acquiring a historical centroid speed slip angle and a historical yaw rate of the vehicle from the historical parameter information;
constructing a state parameter two-dimensional curved surface according to a plurality of reference state parameters of the vehicle in different steady-state drift states;
constructing a control parameter two-dimensional curved surface according to a plurality of reference control parameters of the vehicle in different steady-state drift states;
and acquiring the historical longitudinal axis direction speed, the historical steering wheel corner and the historical rear wheel driving force of the vehicle according to the historical centroid speed slip angle, the historical yaw rate, the state parameter two-dimensional curved surface and the control parameter two-dimensional curved surface.
5. The vehicle drift control method according to claim 4, wherein the obtaining the historical longitudinal axis direction speed, the historical steering wheel angle, and the historical rear wheel driving force of the vehicle from the historical centroid speed slip angle, the historical yaw rate, the state parameter two-dimensional curved surface, and the control parameter two-dimensional curved surface includes:
searching a historical longitudinal axis direction speed from the state parameter two-dimensional curved surface based on the historical centroid speed slip angle and the historical yaw rate;
and searching a historical steering wheel corner and a historical rear wheel driving force from the control parameter two-dimensional curved surface based on the historical centroid speed slip angle and the historical yaw rate.
6. The vehicle drift control method of claim 4, wherein before constructing the state parameter two-dimensional curved surface according to the plurality of reference state parameters of the vehicle in different steady-state drift states, further comprising:
controlling the vehicle from a stationary state to a steady state drift state through an open loop drift model;
and when the vehicle is in a steady-state drift state, adjusting open-loop control parameters of the open-loop drift model to change the vehicle from the current steady-state drift state to other steady-state drift states.
7. The vehicle drift control method according to any one of claims 1 to 6, characterized in that the calculating a target control parameter from the parameter difference and a vehicle state error model includes;
inputting the parameter difference value into a vehicle state error model to obtain a correction quantity of a control parameter;
and determining a target control parameter according to the correction quantity of the control parameter and the current control parameter.
8. A vehicle drift control device, characterized by comprising:
the acquisition module is used for acquiring current state parameters of the vehicle;
the calculation module is used for determining a parameter difference value between the current state parameter and a preset state parameter;
the calculation module is also used for calculating a target control parameter according to the parameter difference value and a vehicle state error model;
and the control module is used for carrying out drift control on the vehicle according to the target control parameter.
9. A vehicle drift control apparatus, characterized by comprising: a memory, a processor, and a vehicle drift control program stored on the memory and running on the processor, the vehicle drift control program configured to implement the vehicle drift control method of any one of claims 1-7.
10. A storage medium having stored thereon a vehicle drift control program which, when executed by a processor, implements the vehicle drift control method according to any one of claims 1 to 7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310190851.6A CN116238479A (en) | 2023-02-28 | 2023-02-28 | Vehicle drift control method, device, equipment and storage medium |
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| CN202310190851.6A CN116238479A (en) | 2023-02-28 | 2023-02-28 | Vehicle drift control method, device, equipment and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116674556A (en) * | 2023-07-25 | 2023-09-01 | 小米汽车科技有限公司 | Vehicle drift control method and device, vehicle and medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116674556A (en) * | 2023-07-25 | 2023-09-01 | 小米汽车科技有限公司 | Vehicle drift control method and device, vehicle and medium |
| CN116674556B (en) * | 2023-07-25 | 2023-10-31 | 小米汽车科技有限公司 | Vehicle drift control method and device, vehicle and medium |
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