CN113232672B - Method and device for estimating vehicle mass center slip angle, electronic equipment and medium - Google Patents

Method and device for estimating vehicle mass center slip angle, electronic equipment and medium Download PDF

Info

Publication number
CN113232672B
CN113232672B CN202110781826.6A CN202110781826A CN113232672B CN 113232672 B CN113232672 B CN 113232672B CN 202110781826 A CN202110781826 A CN 202110781826A CN 113232672 B CN113232672 B CN 113232672B
Authority
CN
China
Prior art keywords
vehicle
slip angle
mass center
determining
speed
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202110781826.6A
Other languages
Chinese (zh)
Other versions
CN113232672A (en
Inventor
徐显杰
徐世寒
伦恺悦
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tianjin Soterea Automotive Technology Co Ltd
Zhejiang Suoto Ruian Technology Group Co Ltd
Original Assignee
Tianjin Soterea Automotive Technology Co Ltd
Zhejiang Suoto Ruian Technology Group Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tianjin Soterea Automotive Technology Co Ltd, Zhejiang Suoto Ruian Technology Group Co Ltd filed Critical Tianjin Soterea Automotive Technology Co Ltd
Priority to CN202110781826.6A priority Critical patent/CN113232672B/en
Publication of CN113232672A publication Critical patent/CN113232672A/en
Application granted granted Critical
Publication of CN113232672B publication Critical patent/CN113232672B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
    • B60W40/13—Load or weight
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105—Speed
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
    • B60W40/13—Load or weight
    • B60W2040/1315—Location of the centre of gravity
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • 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
    • B60W2530/00—Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00
    • B60W2530/10—Weight
    • 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
    • B60W2530/00—Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00
    • B60W2530/201—Dimensions of vehicle

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mathematical Physics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The invention relates to the field of vehicle running state parameter estimation, in particular to a method and a device for estimating a vehicle mass center slip angle, electronic equipment and a medium. The method comprises the following steps: determining a vehicle mass center slip angle observation value by adopting a sliding mode observer; determining a vehicle mass center slip angle integral value by adopting an inertia measurement unit; and determining the vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed. The method relieves the defects that the real mass center slip angle change state of the vehicle cannot be well reflected under the conditions of medium and high speed by adopting a sliding-mode observer estimation mode and the noise is high at low speed by adopting an inertial measurement unit estimation mode, the obtained vehicle mass center slip angle is more accurate and reliable, and a direct measurement unit except a basic sensor necessary for a vehicle transverse controller is not adopted, so that the cost is reduced.

Description

Method and device for estimating vehicle mass center slip angle, electronic equipment and medium
Technical Field
The invention relates to the field of vehicle running state parameter estimation, in particular to a method and a device for estimating a vehicle mass center slip angle, electronic equipment and a medium.
Background
With the vigorous development of the domestic automobile market, the quality of roads is continuously improved, and the reserve of domestic automobiles is rapidly increased. The rapid rise in the total number of automobiles has made various automobile manufacturers and related suppliers in China aware of the importance of active safety performance of vehicles, wherein lateral control is the key and difficult point of the active safety system of vehicles. In the transverse active safety control of the vehicle, the centroid slip angle directly reflects the stable and out-of-control states of the vehicle, so the centroid slip angle of the vehicle needs to be observed. The direct observation of the centroid slip angle through the sensors and other modes at present is high in cost and not beneficial to mass production.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
The invention aims to provide a method and a device for estimating a vehicle mass center slip angle, electronic equipment and a medium, so as to realize the effect of accurately estimating the vehicle mass center slip angle at low cost.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the present invention provides a method for estimating a centroid slip angle of a vehicle, comprising the steps of:
determining a vehicle mass center slip angle observation value by adopting a sliding mode observer;
determining a vehicle mass center slip angle integral value by adopting an inertia measurement unit;
and determining the vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed.
As a further preferable technical solution, the determining the vehicle centroid slip angle observed value by using the sliding-mode observer includes:
determining a sliding mode surface according to the actual yaw velocity of the vehicle and the observed value of the yaw velocity of the vehicle;
determining a sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total yaw stiffness of the front axle of the vehicle, the total yaw stiffness of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface, the symbolic function, an adjusting parameter optimization model and a saturation function; the sliding-mode observer expression is at least used for representing the coupling relation between the vehicle mass center slip angle and the vehicle yaw velocity;
and determining the observed value of the vehicle mass center slip angle according to the expression of the sliding-mode observer and the actual yaw velocity of the vehicle.
As a further preferred technical solution, determining a sliding mode observer expression according to a vehicle speed, a distance from a vehicle center of mass to a front axle, a distance from the vehicle center of mass to a rear axle, a total yaw stiffness of a front axle of the vehicle, a total yaw stiffness of a rear axle of the vehicle, a rotational inertia of the vehicle around a z-axis, a vehicle mass, the sliding mode surface, a sign function, an adjustment parameter optimization model, and a saturation function includes:
determining an initial sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total lateral deflection rigidity of the front axle of the vehicle, the total lateral deflection rigidity of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface and the symbolic function;
optimizing the adjusting parameters in the sliding mode observer expression according to the vehicle speed and the adjusting parameter optimization model;
and determining the sliding mode observer expression according to the initial sliding mode observer expression, the adjusting parameter and the saturation function.
As a further preferred technical solution, the adjustment parameter optimization model is:
Figure DEST_PATH_IMAGE001
(ii) a Wherein, c2For the regulating parameter, VxFor vehicle speed, V1V is not less than 10km/h and is the speed of the vehicle when the vehicle runs at low speed1≤30 km/h，V2V is more than or equal to 70km/h and is the speed of the vehicle in high-speed running2≤110 km/h，LV1Is 0.05, LV2Is 0.2.
As a further preferable technical solution, the determining the vehicle centroid slip angle integral value by using the inertia measurement unit includes:
determining a vehicle lateral speed integral value according to the lateral speed calculated by integration at the previous moment, the lateral acceleration output by the inertia measurement unit, the sampling time and the vehicle continuous straight-going time;
and determining a vehicle mass center slip angle integrated value according to the vehicle lateral speed integrated value and the vehicle speed.
As a further preferred embodiment, the determining the vehicle centroid slip angle by using a fuzzy logic method based on the observation value, the integral value, and the vehicle speed includes:
determining a fusion coefficient of the observed value and the integral value by using a fuzzy logic method by taking a vehicle speed as an input;
and determining the vehicle mass center slip angle according to the observed value, the integral value and the fusion coefficient.
As a further preferable aspect, the determining a fusion coefficient of the observed value and the integrated value by using a fuzzy logic method with a vehicle speed as an input includes:
setting a domain and a membership function of the vehicle speed; the universe of discourse of the vehicle speed is [10,70], the membership function of the vehicle speed boundary fuzzy set is a Gaussian membership function, and the membership function of the vehicle speed intermediate fuzzy set is a triangular membership function;
setting a domain and a membership function of the fusion coefficient; the universe of discourse of the fusion coefficient is [0.4,0.8], the membership function of the boundary fuzzy set of the fusion coefficient is a Gaussian membership function, and the membership function of the intermediate fuzzy set of the fusion coefficient is a triangular membership function;
and outputting the fusion coefficient of the observed value and the integral value according to the speed, the domain and membership function of the speed and the domain and membership function of the fusion coefficient.
In a second aspect, the present invention provides an apparatus for estimating a centroid slip angle of a vehicle, comprising:
the vehicle mass center slip angle observation value determining module is used for determining a vehicle mass center slip angle observation value by adopting a sliding-mode observer;
the vehicle mass center slip angle integral value determining module is used for determining a vehicle mass center slip angle integral value by adopting an inertia measuring unit;
and the vehicle mass center slip angle determining module is used for determining the vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed.
In a third aspect, the present invention provides an electronic device, comprising:
at least one processor, and a memory communicatively coupled to at least one of the processors;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method described above.
In a fourth aspect, the present invention provides a medium having stored thereon computer instructions for causing the computer to perform the method described above.
Compared with the prior art, the invention has the beneficial effects that:
the method for estimating the vehicle mass center slip angle provided by the invention adopts the sliding mode observer to determine the observed value of the vehicle mass center slip angle, adopts the inertia measurement unit to determine the integral value of the vehicle mass center slip angle, and then adopts the fuzzy logic method to determine the vehicle mass center slip angle according to the observed value, the integral value and the vehicle speed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flowchart of a method for estimating a centroid slip angle of a vehicle provided in embodiment 1;
FIG. 2 is a flowchart of a method for estimating a centroid slip angle of a vehicle provided in embodiment 2;
FIG. 3 is a flowchart of a method for estimating a centroid slip angle of a vehicle provided in embodiment 3;
FIG. 4 is a flowchart of a method of estimating a vehicle centroid slip angle provided in embodiment 4;
FIG. 5 is a graph showing the relationship between the velocity V and the membership function in example 4;
FIG. 6 is a diagram showing the relationship between the fusion coefficient K and the membership function in example 4;
FIG. 7 is a schematic configuration diagram of an apparatus for estimating the centroid slip angle of a vehicle according to embodiment 5;
fig. 8 is a schematic structural diagram of an electronic device provided in embodiment 6.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Example 1
Fig. 1 is a flowchart of a method for estimating a centroid slip angle of a vehicle according to the present embodiment, which is suitable for estimating the centroid slip angle of the vehicle during vehicle driving. The method may be performed by a device for estimating the yaw angle of the centroid of the vehicle, which may be constituted by software and/or hardware, and is generally integrated in an electronic apparatus.
Referring to fig. 1, the present embodiment provides a method for estimating a centroid slip angle of a vehicle, including the following steps:
and S110, determining the vehicle mass center slip angle observation value by adopting a sliding mode observer.
The "sliding mode observer" refers to a dynamic system that obtains an estimated value of a state variable from measured values of external variables (input variables and output variables) of the system, and is also referred to as a state reconstructor.
The vehicle mass center slip angle observation value is the vehicle mass center slip angle obtained by a sliding-mode observer.
And S120, determining a vehicle mass center slip angle integral value by adopting an inertia measurement unit.
The inertial Measurement unit is a device for measuring the three-axis attitude angle (or angular rate) and acceleration of an object, and is abbreviated as imu (inertial Measurement unit).
The 'vehicle mass center slip angle integral value' is the vehicle mass center slip angle obtained by integrating the IMU signals to obtain the vehicle lateral speed and then calculating.
And S130, determining the vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed.
According to the method for estimating the vehicle mass center slip angle, the sliding mode observer is adopted to determine the observed value of the vehicle mass center slip angle, the inertia measurement unit is adopted to determine the integral value of the vehicle mass center slip angle, and then the fuzzy logic method is adopted to determine the vehicle mass center slip angle according to the observed value, the integral value and the vehicle speed.
Example 2
As shown in fig. 2, the present embodiment provides another method for estimating the centroid slip angle of the vehicle, and the present embodiment is a further optimization of S110 in embodiment 1. Referring to fig. 2, the method comprises the steps of:
and S111, determining a sliding mode surface according to the actual vehicle yaw velocity and the vehicle yaw velocity observation value.
The sliding mode surface refers to a sliding mode switching hyperplane.
The sliding mode surface is obtained by adopting the following formula
Figure 944886DEST_PATH_IMAGE002
(ii) a Wherein the content of the first and second substances,sis a slip form surface and is provided with a plurality of slip forms,x 1as the actual yaw rate of the vehicle,
Figure 203698DEST_PATH_IMAGE003
is an observed value of the yaw rate of the vehicle.
Before S111, the method further comprises the steps of establishing a vehicle transverse two-degree-of-freedom model state equation, establishing a centroid slip angle expression and establishing a centroid slip angle speed expression.
The state equation of the vehicle transverse two-degree-of-freedom model is shown as the formula (1):
Figure 519273DEST_PATH_IMAGE004
in formula (1):
Figure 542855DEST_PATH_IMAGE005
the definitions of the parameters in the above equation of state are shown in table i:
TABLE I variable definitions
Figure 209460DEST_PATH_IMAGE006
The expression of the centroid slip angle is shown as formula (2):
Figure 147329DEST_PATH_IMAGE007
in the formula, VyIs the vehicle lateral velocity in m/s. The centroid slip angle is derived to obtain a centroid slip angle velocity expression as shown in formula (3):
Figure 910885DEST_PATH_IMAGE008
let interference term in equation (1):
Figure 370948DEST_PATH_IMAGE009
outputting the two-degree-of-freedom model
Figure 259269DEST_PATH_IMAGE011
And designing a second-order sliding mode observer as an input state quantity of the sliding mode observer.
S112, determining a sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total lateral deflection rigidity of the front axle of the vehicle, the total lateral deflection rigidity of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface, the symbolic function, the adjusting parameter optimization model and the saturation function; the sliding-mode observer expression is at least used for representing the coupling relation between the vehicle mass center slip angle and the vehicle yaw angular speed.
Preferably, the determining of the sliding mode observer expression according to the vehicle speed, the distance from the vehicle center of mass to the front axle, the distance from the vehicle center of mass to the rear axle, the total yaw stiffness of the front axle of the vehicle, the total yaw stiffness of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the vehicle mass, the sliding mode surface, the sign function, the adjustment parameter optimization model and the saturation function includes:
determining an initial sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total lateral deflection rigidity of the front axle of the vehicle, the total lateral deflection rigidity of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface and the symbolic function;
optimizing the adjusting parameters in the sliding mode observer expression according to the vehicle speed and the adjusting parameter optimization model;
and determining the sliding mode observer expression according to the initial sliding mode observer expression, the adjusting parameter and the saturation function.
The 'adjusting parameter optimization model' refers to an optimization model of adjusting parameters in a sliding-mode observer expression.
Preferably, the initial sliding-mode observer expression is as shown in equation (5):
Figure 594305DEST_PATH_IMAGE012
in the formula (I), the compound is shown in the specification,
Figure 884472DEST_PATH_IMAGE013
；
Figure 718698DEST_PATH_IMAGE014
；
Figure 94315DEST_PATH_IMAGE015
；
Figure 701883DEST_PATH_IMAGE016
；
Figure 377715DEST_PATH_IMAGE017
；
Figure 835372DEST_PATH_IMAGE018
；
Figure 589964DEST_PATH_IMAGE019
in order to be a function of the sign,x 2is the side slip angle of the mass center,
Figure 204485DEST_PATH_IMAGE020
is the observed value of the centroid slip angle,c 1is the first adjusting parameter of the second-order sliding mode observer,c 2The two adjusting parameters mainly affect the observation performance of the observer, and are the second adjusting parameters of the second-order sliding mode observer.
Wherein the content of the first and second substances,c 1=c 2 2/2。
in the actual observation process, when the speed of the vehicle changes, the adjustment parameters required for observation cannot be changed in a self-adaptive manner, which can cause the robustness of the observation system to be reduced. Preferably, therefore, the tuning parameter optimization model is an optimization model of the second tuning parameter, which is a linear function of the vehicle speed, as follows:
Figure 734823DEST_PATH_IMAGE021
(ii) a Wherein, c2For the regulating parameter, VxFor vehicle speed, V1V is not less than 10km/h and is the speed of the vehicle when the vehicle runs at low speed1≤30 km/h，V2V is more than or equal to 70km/h and is the speed of the vehicle in high-speed running2≤110 km/h，LV1Is 0.05, LV2Is 0.2.
The adoption of the sign function as the sliding mode switching function can cause the system to generate large buffeting, and the saturation value of the sign function is 1, so that the system is not reasonable for the centroid slip angle estimation system. Therefore, the saturation function shown in equation (6) is adopted as the switching function of the second-order sliding-mode observer.
Figure 114114DEST_PATH_IMAGE022
In the formula (I), the compound is shown in the specification,k 1saturation boundary values are saturation functions. Because the magnitude order of the mass center side deflection angle is smaller, the mass center side deflection angle is less than or equal to 0.1k 1≤0.5，k 1May adopt one hundred adjacent sampling periods
Figure 979171DEST_PATH_IMAGE023
Is calculated, and when the calculated value is less than 0.1,k 1taking 0.1, when the calculated value is more than 0.5,k 1take 0.5.
Preferably, the sliding-mode observer expression is as shown in equation (7):
Figure 367689DEST_PATH_IMAGE024
the vehicle mass center slip angle observation value output by the second-order sliding-mode observer is set as
Figure 752534DEST_PATH_IMAGE025
。
And S113, determining the observed value of the mass center and the side slip angle of the vehicle according to the expression of the sliding mode observer and the actual yaw velocity of the vehicle.
Specifically, the determining the observed value of the vehicle mass center slip angle according to the sliding-mode observer expression and the actual yaw rate of the vehicle includes:
and inputting the actual yaw velocity of the vehicle into the sliding mode observer expression, and outputting the observed value of the mass center and the side slip angle of the vehicle.
And S120, determining a vehicle mass center slip angle integral value by adopting an inertia measurement unit.
And S130, determining the vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed.
S120 and S130 are the same as those in embodiment 1, and are not described again here.
According to the sliding mode observer, the sliding mode surface is determined in a specific mode, and the sliding mode observer expression is determined in a specific mode, so that the robustness and the buffeting resistance of the sliding mode observer are better, and the observation performance of the sliding mode observer is improved.
Example 3
As shown in fig. 3, the present embodiment provides another method for estimating the centroid slip angle of the vehicle, and the present embodiment is a further optimization of S120 in embodiment 2. Referring to fig. 3, the method comprises the steps of:
and S111, determining a sliding mode surface according to the actual vehicle yaw velocity and the vehicle yaw velocity observation value.
S112, determining a sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total lateral deflection rigidity of the front axle of the vehicle, the total lateral deflection rigidity of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface, the symbolic function, the adjusting parameter optimization model and the saturation function; the sliding-mode observer expression is at least used for representing the coupling relation between the vehicle mass center slip angle and the vehicle yaw angular speed.
And S113, determining the observed value of the mass center and the side slip angle of the vehicle according to the expression of the sliding mode observer and the actual yaw velocity of the vehicle.
And S121, determining a vehicle lateral speed integral value according to the lateral speed integrated and calculated at the previous moment, the lateral acceleration output by the inertia measurement unit, the sampling time and the vehicle continuous straight-going time.
The lateral speed integrated and calculated at the previous time refers to the lateral speed calculated in an integration mode at the previous sampling time of the current sampling.
The "vehicle straight-ahead duration" refers to a duration for which the vehicle remains in a straight-ahead state.
The "vehicle lateral speed integrated value" refers to the vehicle lateral speed calculated mainly by integration.
For the lateral control of the vehicle, an IMU device (an inertial measurement unit) is indispensable, so that the hardware cost of the system is not increased by adopting an IMU signal in the centroid slip angle estimation link. The IMU outputs the actual lateral acceleration signal of the vehicle to carry out integration so as to obtain the lateral speed of the vehicle, as shown in a formula (8).
Figure 801262DEST_PATH_IMAGE026
In the formula (I), the compound is shown in the specification,a y outputting a lateral acceleration signal for the IMU in m/s2；
Figure 401219DEST_PATH_IMAGE027
Is the sampling time in units of s;V yIN-1 the lateral velocity is calculated as an integral in m/s;Last_V yIN the calculated lateral velocity is integrated for the previous moment in m/s.
Because the disadvantage that the lateral speed integral value is too large and insensitive to change due to long-time integration in practical application occurs, the lateral speed integral value is optimized by adding the integration zero clearing logic:
Figure 905013DEST_PATH_IMAGE028
in the formula (I), the compound is shown in the specification,V yIN is an integrated value of the lateral speed of the vehicle,StraCounteris a vehicle straight running counter, in units of s. As can be seen from equation (9), when the vehicle keeps going straight for more than 0.5s, the lateral speed integral value is cleared.
And S122, determining a vehicle mass center slip angle integral value according to the vehicle lateral speed integral value and the vehicle speed.
Specifically, the vehicle centroid slip angle integral valueβ IN Calculated using equation (10):
Figure 393632DEST_PATH_IMAGE029
。
and S130, determining the vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed.
The above S111, S112, S113, and S130 are the same as those in embodiment 2, and are not described again here.
The embodiment can effectively overcome the defects of overlarge lateral speed integral value and insensitive change caused by long-time integration by adding the integral value zero clearing logic.
Example 4
As shown in fig. 4, the present embodiment provides another method for estimating the centroid slip angle of the vehicle, and the present embodiment is a further optimization of S130 in embodiment 3. Referring to fig. 4, the method includes the steps of:
and S111, determining a sliding mode surface according to the actual vehicle yaw velocity and the vehicle yaw velocity observation value.
S112, determining a sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total lateral deflection rigidity of the front axle of the vehicle, the total lateral deflection rigidity of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface, the symbolic function, the adjusting parameter optimization model and the saturation function; the sliding-mode observer expression is at least used for representing the coupling relation between the vehicle mass center slip angle and the vehicle yaw angular speed.
And S113, determining the observed value of the mass center and the side slip angle of the vehicle according to the expression of the sliding mode observer and the actual yaw velocity of the vehicle.
And S121, determining a vehicle lateral speed integral value according to the lateral speed integrated and calculated at the previous moment, the lateral acceleration output by the inertia measurement unit, the sampling time and the vehicle continuous straight-going time.
And S122, determining a vehicle mass center slip angle integral value according to the vehicle lateral speed integral value and the vehicle speed.
The above S111, S112, S113, S121, and S122 are the same as those in embodiment 3, and are not described again here.
And S131, determining a fusion coefficient of the observed value and the integral value by using a fuzzy logic method with the vehicle speed as input.
The "fusion coefficient" refers to a fusion ratio of the centroid slip angle observed value and the integral value.
Preferably, the determining a fusion coefficient of the observed value and the integral value by using the vehicle speed as an input and using a fuzzy logic method includes:
setting a domain and a membership function of the vehicle speed; the universe of discourse of the vehicle speed is [10,70], the membership function of the vehicle speed boundary fuzzy set is a Gaussian membership function, and the membership function of the vehicle speed intermediate fuzzy set is a triangular membership function;
setting a domain and a membership function of the fusion coefficient; the universe of discourse of the fusion coefficient is [0.4,0.8], the membership function of the boundary fuzzy set of the fusion coefficient is a Gaussian membership function, and the membership function of the intermediate fuzzy set of the fusion coefficient is a triangular membership function;
and outputting the fusion coefficient of the observed value and the integral value according to the speed, the domain and membership function of the speed and the domain and membership function of the fusion coefficient.
The term "vehicle speed boundary fuzzy set" refers to a fuzzy set of two boundaries located in the domain of the vehicle speed in all fuzzy sets of the vehicle speed.
The "vehicle speed middle fuzzy set" refers to a fuzzy set located in the middle of the discourse field of the vehicle speed in the fuzzy sets of all the vehicle speeds.
"fused coefficient boundary fuzzy set" refers to a fuzzy set of two boundaries located at the universe of discourse of the fused coefficients, in the fuzzy sets of all fused coefficients.
The "intermediate fuzzy set of fusion coefficients" refers to a fuzzy set located in the middle of the domain of discourse of the fusion coefficients among the fuzzy sets of all fusion coefficients.
For example, the input vehicle speed is divided into 5 fuzzy sets, and the input values are set for low speed (LV), small Speed (SV), medium speed (MV), normal speed (NV), and large speed (BV), respectivelyVHas a discourse field of [10,70]]. In order to avoid the situation that the switching rate of the system state is larger at the boundary of the input state quantity to cause the output of the estimator to generate catastrophe, the fuzzy sets LV and BV at the boundary adopt Gaussian membership functions, the fuzzy sets SV, MV and NV adopt triangular membership functions, and the final speed is calculatedVThe relationship to the membership function is shown in fig. 5.
The output fusion coefficient K is divided into 5 fuzzy sets, a lower K value (LK), a small K value (SK), a medium K value (MK), a normal K value (NK), a large K value (BK), and the domain of the output fusion coefficient K is set to [0.4,0.8 ]. Similarly, in order to avoid the situation that the switching rate of the system state is high at the boundary of the output fusion coefficient, which causes the output of the estimator to generate a shock change, the fuzzy sets LK and BK at the boundary adopt gaussian membership functions, and the other fuzzy sets SK, MK and NK adopt triangular membership functions, so that the relationship between the fusion coefficient K and the membership functions is shown in fig. 6.
And S132, determining the vehicle mass center slip angle according to the observed value, the integral value and the fusion coefficient.
The vehicle mass center slip angleβ EST The formula is adopted to calculate the following formula:
Figure 19785DEST_PATH_IMAGE030
。
according to the method, the fusion coefficient is determined firstly, and then the mass center slip angle of the vehicle is determined by adopting the observation value, the integral value and the fusion coefficient, so that the observation value and the integral value can be better coordinated, and the estimation value of the mass center slip angle is more reliable.
Example 5
As shown in fig. 7, the present embodiment provides an estimation apparatus of a centroid slip angle of a vehicle, including:
the vehicle mass center slip angle observation value determining module 101 is used for determining a vehicle mass center slip angle observation value by adopting a sliding mode observer;
the vehicle mass center slip angle integral value determining module 102 is used for determining a vehicle mass center slip angle integral value by adopting an inertia measuring unit;
and the vehicle mass center slip angle determining module 103 is used for determining the vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed.
Further, the vehicle centroid slip angle observation determination module 101 includes: the sliding mode surface determining unit is used for determining a sliding mode surface according to the actual yaw velocity of the vehicle and the observed value of the yaw velocity of the vehicle; the sliding mode observer expression determining unit is used for determining a sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total lateral deflection rigidity of the front axle of the vehicle, the total lateral deflection rigidity of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the vehicle mass, the sliding mode surface, the symbolic function, the adjusting parameter optimization model and the saturation function; the sliding-mode observer expression is at least used for representing the coupling relation between the vehicle mass center slip angle and the vehicle yaw velocity; and the vehicle mass center slip angle observed value determining unit is used for determining the vehicle mass center slip angle observed value according to the sliding mode observer expression and the actual yaw velocity of the vehicle.
Further, the vehicle center of mass slip angle integrated value determination module 102 includes: the vehicle lateral speed integral value determining unit is used for determining a vehicle lateral speed integral value according to the lateral speed integrated and calculated at the previous moment, the lateral acceleration output by the inertia measuring unit, the sampling time and the vehicle continuous straight-going time; and the vehicle mass center slip angle integrated value determining unit is used for determining the vehicle mass center slip angle integrated value according to the vehicle lateral speed integrated value and the vehicle speed.
Further, the vehicle centroid slip angle determination module 103 includes: a fusion coefficient determining unit, configured to determine a fusion coefficient of the observed value and the integral value by using a fuzzy logic method with a vehicle speed as an input; and the vehicle mass center slip angle determining unit is used for determining the vehicle mass center slip angle according to the observed value, the integrated value and the fusion coefficient.
The vehicle centroid slip angle estimation device is used for executing the vehicle centroid slip angle estimation method of the embodiment, and therefore at least has functional modules and beneficial effects corresponding to the method.
Example 6
As shown in fig. 8, the present embodiment provides an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to at least one of the processors; wherein the content of the first and second substances,
the memory stores instructions executable by at least one of the processors to enable the at least one of the processors to perform the method described above. The at least one processor in the electronic device is capable of performing the above method and thus has at least the same advantages as the above method.
Optionally, the electronic device further includes an interface for connecting the components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display Graphical information for a GUI (Graphical User Interface) on an external input/output device, such as a display device coupled to the Interface. In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 8 illustrates an example of a processor 201.
The memory 202, as a computer-readable storage medium, may be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the estimation method of the vehicle centroid slip angle in the embodiment of the present invention (for example, the vehicle centroid slip angle observation value determination module 101, the vehicle centroid slip angle integrated value determination module 102, and the vehicle centroid slip angle determination module 103 in the estimation device of the vehicle centroid slip angle). The processor 201 executes various functional applications of the device and data processing by executing software programs, instructions and modules stored in the memory 202, namely, realizes the estimation method of the vehicle centroid slip angle.
The memory 202 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 202 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 202 may further include memory located remotely from the processor 201, which may be connected to the device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device may further include: an input device 203 and an output device 204. The processor 201, the memory 202, the input device 203 and the output device 204 may be connected by a bus or other means, and fig. 8 illustrates the connection by a bus as an example.
The input device 203 may receive input numeric or character information, and the output device 204 may include a display device, an auxiliary lighting device (e.g., an LED), a tactile feedback device (e.g., a vibration motor), and the like. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Example 7
The present embodiment provides a medium having stored thereon computer instructions for causing the computer to perform the method described above. The computer instructions on the medium for causing a computer to perform the method described above thus have at least the same advantages as the method described above.
The medium of the present invention may take the form of any combination of one or more computer-readable media. The medium may be a computer readable signal medium or a computer readable storage medium. The medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the medium include: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF (Radio Frequency), etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present application can be achieved, and the present invention is not limited herein.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims (8)

1. A method for estimating a vehicle centroid slip angle is characterized by comprising the following steps:
determining a vehicle mass center slip angle observation value by adopting a sliding mode observer;
determining a vehicle mass center slip angle integral value by adopting an inertia measurement unit;
determining a vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed;
the sliding-mode observer is adopted to determine the vehicle mass center slip angle observed value, and the method comprises the following steps:
determining a sliding mode surface according to the actual yaw velocity of the vehicle and the observed value of the yaw velocity of the vehicle;
determining a sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total yaw stiffness of the front axle of the vehicle, the total yaw stiffness of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface, the symbolic function, an adjusting parameter optimization model and a saturation function; the sliding-mode observer expression is at least used for representing the coupling relation between the vehicle mass center slip angle and the vehicle yaw velocity;
determining an observed value of a vehicle mass center slip angle according to a sliding mode observer expression and the actual yaw velocity of the vehicle;
the adjusting parameter optimization model is as follows:
Figure FDA0003228562840000011
Figure FDA0003228562840000012
wherein, c2For the regulating parameter, VxFor vehicle speed, V1V is not less than 10km/h and is the speed of the vehicle when the vehicle runs at low speed1≤30km/h，V2V is more than or equal to 70km/h and is the speed of the vehicle in high-speed running2≤110km/h，LV1Is 0.05, LV2Is 0.2.
2. The method for estimating the vehicle centroid slip angle according to claim 1, wherein the determining the sliding mode observer expression according to the vehicle speed, the vehicle centroid to front axle distance, the vehicle centroid to rear axle distance, the vehicle front axle total yaw stiffness, the vehicle rear axle total yaw stiffness, the vehicle rotational inertia around the z-axis, the vehicle mass, the sliding mode surface, the sign function, the adjustment parameter optimization model and the saturation function comprises:
determining an initial sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total lateral deflection rigidity of the front axle of the vehicle, the total lateral deflection rigidity of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface and the symbolic function;
optimizing the adjusting parameters in the sliding mode observer expression according to the vehicle speed and the adjusting parameter optimization model;
and determining the sliding mode observer expression according to the initial sliding mode observer expression, the adjusting parameter and the saturation function.
3. The method of estimating vehicle centroid slip angle according to claim 1, wherein said determining vehicle centroid slip angle integral value using inertial measurement unit comprises:
determining a vehicle lateral speed integral value according to the lateral speed calculated by integration at the previous moment, the lateral acceleration output by the inertia measurement unit, the sampling time and the vehicle continuous straight-going time;
and determining a vehicle mass center slip angle integrated value according to the vehicle lateral speed integrated value and the vehicle speed.
4. The method of estimating the vehicle centroid slip angle according to any one of claims 1-3, wherein said determining the vehicle centroid slip angle using a fuzzy logic method based on said observation value, said integration value and the vehicle speed comprises:
determining a fusion coefficient of the observed value and the integral value by using a fuzzy logic method by taking a vehicle speed as an input;
and determining the vehicle mass center slip angle according to the observed value, the integral value and the fusion coefficient.
5. The method of estimating the vehicle centroid slip angle according to claim 4, wherein said determining the fusion coefficient of the observed value and the integrated value using fuzzy logic method with the vehicle speed as input comprises:
setting a domain and a membership function of the vehicle speed; the universe of discourse of the vehicle speed is [10,70], the membership function of the vehicle speed boundary fuzzy set is a Gaussian membership function, and the membership function of the vehicle speed intermediate fuzzy set is a triangular membership function;
setting a domain and a membership function of the fusion coefficient; the universe of discourse of the fusion coefficient is [0.4,0.8], the membership function of the boundary fuzzy set of the fusion coefficient is a Gaussian membership function, and the membership function of the intermediate fuzzy set of the fusion coefficient is a triangular membership function;
and outputting the fusion coefficient of the observed value and the integral value according to the speed, the domain and membership function of the speed and the domain and membership function of the fusion coefficient.
6. An apparatus for estimating a centroid slip angle of a vehicle, comprising:
the vehicle mass center slip angle observation value determining module is used for determining a vehicle mass center slip angle observation value by adopting a sliding-mode observer;
the vehicle mass center slip angle integral value determining module is used for determining a vehicle mass center slip angle integral value by adopting an inertia measuring unit;
the vehicle mass center slip angle determining module is used for determining a vehicle mass center slip angle by adopting a fuzzy logic method according to the observed value, the integral value and the vehicle speed;
the sliding-mode observer is adopted to determine the vehicle mass center slip angle observed value, and the method comprises the following steps:
determining a sliding mode surface according to the actual yaw velocity of the vehicle and the observed value of the yaw velocity of the vehicle;
determining a sliding mode observer expression according to the vehicle speed, the distance from the vehicle mass center to the front axle, the distance from the vehicle mass center to the rear axle, the total yaw stiffness of the front axle of the vehicle, the total yaw stiffness of the rear axle of the vehicle, the rotational inertia of the vehicle around the z-axis, the whole vehicle mass, the sliding mode surface, the symbolic function, an adjusting parameter optimization model and a saturation function; the sliding-mode observer expression is at least used for representing the coupling relation between the vehicle mass center slip angle and the vehicle yaw velocity;
determining an observed value of a vehicle mass center slip angle according to a sliding mode observer expression and the actual yaw velocity of the vehicle;
the adjusting parameter optimization model is as follows:
Figure FDA0003228562840000041
Figure FDA0003228562840000042
wherein, c2For the regulating parameter, VxFor vehicle speed, V1V is not less than 10km/h and is the speed of the vehicle when the vehicle runs at low speed1≤30km/h，V2V is more than or equal to 70km/h and is the speed of the vehicle in high-speed running2≤110km/h，LV1Is 0.05, LV2Is 0.2.
7. An electronic device, comprising:
at least one processor, and a memory communicatively coupled to at least one of the processors;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
8. A medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1-5.
CN202110781826.6A 2021-07-12 2021-07-12 Method and device for estimating vehicle mass center slip angle, electronic equipment and medium Active CN113232672B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110781826.6A CN113232672B (en) 2021-07-12 2021-07-12 Method and device for estimating vehicle mass center slip angle, electronic equipment and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110781826.6A CN113232672B (en) 2021-07-12 2021-07-12 Method and device for estimating vehicle mass center slip angle, electronic equipment and medium

Publications (2)

Publication Number Publication Date
CN113232672A CN113232672A (en) 2021-08-10
CN113232672B true CN113232672B (en) 2021-10-19

Family

ID=77135294

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110781826.6A Active CN113232672B (en) 2021-07-12 2021-07-12 Method and device for estimating vehicle mass center slip angle, electronic equipment and medium

Country Status (1)

Country Link
CN (1) CN113232672B (en)

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102009653B (en) * 2010-11-10 2013-03-27 清华大学 Wheel barycenter distortion angle observation method integrated with Kalman filtering and acceleration integral
US9663115B2 (en) * 2015-10-09 2017-05-30 The Goodyear Tire & Rubber Company Method for estimating tire forces from CAN-bus accessible sensor inputs
CN107031654B (en) * 2017-02-20 2019-03-01 同济大学 A kind of automobile slip angle estimation method of multi-information fusion
CN107992681B (en) * 2017-12-04 2020-06-05 江苏大学 Composite control method for active front wheel steering system of electric automobile
DE102019210219A1 (en) * 2019-07-10 2021-01-14 Volkswagen Aktiengesellschaft Method for determining at least one vehicle parameter of a wheel-driven vehicle and measuring system

Also Published As

Publication number Publication date
CN113232672A (en) 2021-08-10

Similar Documents

Publication Publication Date Title
JP6884276B2 (en) Systems and methods for controlling vehicles
EP3842746A2 (en) Dead reckoning method and apparatus for vehicle, device and storage medium
CN111879957B (en) Vehicle dynamics determination based on fuzzy logic and enhanced machine learning
CN110217239B (en) Method and equipment for measuring yaw rate of vehicle
CN112579966B (en) Method and device for calculating ABS reference vehicle speed, electronic equipment and medium
CN114987607B (en) Steering control method, device and equipment for vehicle and storage medium
CN113183975B (en) Control method, device, equipment and storage medium for automatic driving vehicle
CN115617051B (en) Vehicle control method, device, equipment and computer readable medium
CN113291294B (en) Vehicle lateral control method and device and vehicle
CN113232672B (en) Method and device for estimating vehicle mass center slip angle, electronic equipment and medium
CN113771857A (en) Longitudinal speed estimation method and system for vehicle control
CN115476881B (en) Vehicle track tracking control method, device, equipment and medium
CN110816654A (en) Signal estimation method, device, vehicle and storage medium
CN113353074B (en) Vehicle control method and device, electronic equipment and storage medium
CN111337051B (en) Method and device for calibrating forward axis of vehicle accelerometer
CN114834529A (en) Vehicle control method, device, equipment and medium
JP2023018538A (en) Tire management device, program, and tire management method
WO2022218547A1 (en) Method for in-motion friction estimation based on steering pulses, computer program, computer readable medium, control device and vehicle
CN117864172B (en) Automatic driving control method, device and equipment
CN115482687B (en) Method, device, equipment and medium for vehicle lane change risk assessment
US20230294669A1 (en) Control method, vehicle, and storage medium
CN116572972B (en) Transverse control method and device of vehicle, electronic equipment and storage medium
CN116653635A (en) Motor torque distribution method and device
CN117227759A (en) Automatic driving transverse control method, device, equipment and storage medium
CN117184063A (en) Vehicle transverse path tracking method, device, equipment and storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant