CN102880048B - A kind of method of side force of tire LINEARIZED CONTROL - Google Patents
A kind of method of side force of tire LINEARIZED CONTROL Download PDFInfo
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- CN102880048B CN102880048B CN201210385492.1A CN201210385492A CN102880048B CN 102880048 B CN102880048 B CN 102880048B CN 201210385492 A CN201210385492 A CN 201210385492A CN 102880048 B CN102880048 B CN 102880048B
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Abstract
The present invention relates to a kind of method of side force of tire LINEARIZED CONTROL, for controlling the linearization of side force of tire non-linear factor.Present system determines tire model parameter by various vehicle sensors, such as side drift angle α, inner gas pressure P, vertical load Fz and speed of a motor vehicle u.By these model parameters, the error of this system-computed side force of tire desired value and side force of tire actual value.The error calculated is used for calculating feedback control amount.This system is exported to actuator according to the parameter change amount that error after feedback is zero and is taked suitable action.
Description
Technical field
The present invention relates in general to a kind of method providing side force of tire LINEARIZED CONTROL, described system is for controlling the linearization of side force of tire non-linear factor, more particularly, the present invention relates to a kind of system and method that side force of tire LINEARIZED CONTROL is provided, wherein determine that described method is that wherein said linearization refers to and utilizes feed back input control linear to export by nonlinear neural network model linearization.
Background technology
From again and again by the news causing motor turning car crash out of control owing to blowing out of media report, can find out that the problem of tire is taken seriously day by day.But also having many accidents to seem is that driver's misoperation causes, and underlying causes is often ignored by people--tyre performance is not good, so study of tire is the problem become more and more important future with mating of car load.
The rollover of vehicle with turn to out of control main relevant with the side force of tire, direct factor is exactly side drift angle, but also by tyre side inclination angle, vertical load, charge pressure, tire construction and material, and the even factor impact such as pavement behavior, shows the non-linear of complexity.Along with the fast development of artificial intelligence, tire model develops from linear model neuralward network nonlinear model.The system of nonlinear model of being coupled not only increases the dimension of institute's research object, meanwhile, also makes the non-linear behavior of system more complicated.And this nonlinear relationship we cannot to change, we only have and utilize the feature of neural network own by the feedback excitation in addition of other input quantities, along with being coupled of time delay feedback and space, retroactive effect will be transmitted to whole network, the unchangeability that final maintenance network exports, makes neural network be equivalent to a linear system.
Summary of the invention
The invention provides a kind of method of side force of tire LINEARIZED CONTROL, the invention solves when vehicle travels in tempo turn, be within the scope of higher side acceleration, tire characteristics are non-linear, side force nonlinearities change, turning efficiency weakens, the problem of handling stability difference.
Concrete steps of the present invention are:
A) lateral deviation angle value, the inner gas pressure value of tyre inflating air pressure, the vertical load value of tire vertical load, the vehicle speed value of the tire speed of a motor vehicle of slip angle of tire is detected;
B) according to described lateral deviation angle value, inner gas pressure value, vertical load signal and vehicle speed value, side force of tire desired value is estimated;
C) according to described lateral deviation angle value, inner gas pressure value, vertical load signal and vehicle speed value, side force of tire actual value is calculated;
D) according to described side force of tire desired value and side force of tire actual value, side force of tire departure is calculated;
E) calculate feedback control amount according to described side force of tire departure and export to actuator, complete the change of slip angle of tire, tyre inflating air pressure, tire vertical load, the tire speed of a motor vehicle.
The present invention determines tire model parameter by various vehicle sensors, such as side drift angle α, inner gas pressure P, vertical load Fz and speed of a motor vehicle u.By these model parameters, the error of this system-computed side force of tire desired value and side force of tire actual value.The error calculated is used for calculating feedback control amount.This system is exported to actuator according to the parameter change amount that error after feedback is zero and is taked suitable action.
When the invention has the beneficial effects as follows that decreasing vehicle travels on a highway, there is the possibility turning on one's side and turn to incontrollable accidents.
Accompanying drawing explanation
Fig. 1 is side force of tire neural network schematic diagram.
Fig. 2 be the present invention illustrate emulation tracking error curve figure.
Fig. 3 is workflow diagram of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the inventive method is elaborated.
As Fig. 1, tire model is made up of, comprising input layer, hidden layer and output layer neural network (such as formula 1).Input layer comprises 4 vectors and is respectively side drift angle α, inner gas pressure P, vertical load Fz and speed of a motor vehicle u.Hidden layer is made up of some layers of nonlinear transfer function.Output layer is that side force of tire Fy single vector is formed.
Patent citing of the present invention is to adopt Han Tai 165/65R13 radial.Gather moral forever to launch company on doughnut road rotatory testboard record tire ground connection force data, by the matching to test figure in Shanghai.Finally obtaining network structure is 4-8-1.
(1)
Being input as of this network hidden layer neuron
（2）
In formula, θ j (k) is the neuronic input value of jth in hidden layer, p
ik () is input layer output, w
ijfor input layer is to the connection weight weight values of hidden layer.Contact between the input and output of hidden layer adopts Sigmoid funtcional relationship, and namely the output of hidden layer neuron is expressed as:
（3）
ξ in formula
jfor the neuronic output of hidden layer jth, f [ψ]=1/ [1+exp (-ψ)], output layer comprises 1 neuron.The neuronic input function of output layer is:
（4）
V in formula
jlfor hidden layer is to the connection weight weight values of output layer.The output of output layer and contacting as Sigmoid funtcional relationship of input, be expressed as:
（5）
In formula, I
lfor the neuronic output of output layer.
Patent of the present invention carries out FEEDBACK CONTROL to neural network, makes system be linear from non-linear transfer.Be exactly specifically that certain input quantity of neural network is (such as formula x in 7
i) produce disturbance, by the in addition feedback excitation of other input quantities, along with being coupled of time delay feedback and space, retroactive effect will be transmitted to whole network, the final unchangeability keeping network output.Neural network is made to be equivalent to a linear system.The object of this controller is exactly that design of feedback amount u makes input and output linearly proportional
dy/dt=dx/dt （6）
Order
x =(x
1, x
2, x
3, x
4)
t=(
)
t; Y=
; Then
（7）
Set linear control objectives
（8）
Realize tracing control with the adaptive fuzzy control method based on input+linearization herein, namely will design fuzzy control rate u
c(x/ θ) and the adaptive law of adjustable parameter vector theta, make closed-loop system Existence of Global Stable and make tracking error
e=y-y
m（9）
Zero is converged to when t → ∞.Control law is as follows:
（10）
E can be met and converge on zero.
According to this paper model in order to control effects is described, choose the speed of a motor vehicle that vehicle often changes, and regulate body gesture to control to carry out emulation experiment to the vertical load of tire by Active suspension.Therefore, control for the situation that speed parameter occurs to perturb above in emulation.And obtain tracking error curve respectively as shown in Figure 2.In Fig. 2, e is front-wheel neural network model departure.When can work as systematic parameter existence perturbation, initially some disturbance, later with regard near linear, illustrative system can follow the tracks of the control objectives of expectation well.
Fig. 3 is a process flow diagram, which show one according to one embodiment of present invention.At square frame 2 place, described algorithm reads multiple sensor parameters from suitable sensor 1, such as slip angle of tire, tire pressure, load, the speed of a motor vehicle.There is provided the sensor 1 of this information can be any suitable sensor for this object, wherein many kinds be known, and will be understood by those skilled in the art.This algorithm then estimates side force of tire desired value at square frame 3 place according to formula (8).Calculate side force of tire actual value at square frame 4 according to formula (7) subsequently, then calculate side force of tire departure at square frame 5 place according to formula (9).Described algorithm calculates feedback control amount at square frame 6 place according to formula (10) and existing disclosed technology Adaptive Fuzzy Control, Adaptive Fuzzy Control is ripe and extensively knows, those skilled in the art can have been come by Adaptive Fuzzy Control tool box in retrieval pertinent literature and MATLAB.If final error is zero, the feedback control amount that square frame 6 place calculates is exported to the change that actuator 8 completes respective physical amount at square frame 7 place by this algorithm, such as slip angle of tire, tire pressure, load, the speed of a motor vehicle.Accepting the actuator 8 that feedback control amount exports can be any suitable actuator for this object, and wherein many kinds are existing apparatus, and will be understood by those skilled in the art.
It is only exemplary embodiment that citing above disclose and describes of the present invention.It will be appreciated by those skilled in the art that and to be illustrated and accompanying drawing and claims by these, various change, modifications and variations can be carried out when not deviating from the spirit and scope of the present invention limited by appended claims.
Claims (1)
1. a method for side force of tire LINEARIZED CONTROL, is characterized in that, concrete steps are:
A) lateral deviation angle value, the inner gas pressure value of tyre inflating air pressure, the vertical load value of tire vertical load, the vehicle speed value of the tire speed of a motor vehicle of slip angle of tire is detected;
B) according to described lateral deviation angle value, inner gas pressure value, vertical load signal and vehicle speed value, side force of tire desired value is estimated; Described estimation side force of tire desired value uses formula below:
Wherein,
x =(
)
t;
the lateral deviation angle value of slip angle of tire,
the inner gas pressure value of tyre inflating air pressure,
vertical load value, u vehicle speed value; Y=
;
C) according to described lateral deviation angle value, inner gas pressure value, vertical load signal and vehicle speed value, side force of tire actual value is calculated; Described calculating side force of tire actual value uses formula below:
Wherein, f [ψ]=1/ [1+exp (-ψ)], v
jfor hidden layer is to the connection weight weight values of output layer, w
ijfor input layer is to the connection weight weight values of hidden layer
D) according to described side force of tire desired value and side force of tire actual value, side force of tire departure is calculated; Described calculating side force of tire departure uses formula: e=y-y
m
E) calculate feedback control amount according to described side force of tire departure and export to actuator, complete the change of slip angle of tire, tyre inflating air pressure, tire vertical load, the tire speed of a motor vehicle; Described feedback control amount uses Adaptive Fuzzy Control to calculate.
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| CN201210385492.1A CN102880048B (en) | 2012-10-12 | 2012-10-12 | A kind of method of side force of tire LINEARIZED CONTROL |
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| CN102880048A CN102880048A (en) | 2013-01-16 |
| CN102880048B true CN102880048B (en) | 2015-10-28 |
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Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103278339B (en) * | 2013-03-28 | 2015-04-22 | 清华大学 | Method for estimating lateral force of tire |
| CN105667520B (en) * | 2016-02-26 | 2018-01-16 | 江苏大学 | A kind of front-wheel side force method of estimation of distributed driving electric car |
| CN112182477B (en) * | 2020-08-27 | 2022-06-03 | 清华大学 | Tire lateral force identification method and device |
| CN114840919B (en) * | 2022-04-20 | 2022-11-25 | 中国人民解放军32212部队 | Method for analyzing coupling degree between multi-dimensional wheel force sensors |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1357008A2 (en) * | 2002-04-23 | 2003-10-29 | Aisin Seiki Kabushiki Kaisha | Vehicle motion control apparatus |
| CN101710027A (en) * | 2009-11-24 | 2010-05-19 | 江苏大学 | Non-linear dynamic characteristic monitoring system and method of vehicle tyre |
| CN101979268A (en) * | 2010-09-25 | 2011-02-23 | 合肥工业大学 | Automobile steering wheel shimmy control method |
| CN102267460A (en) * | 2011-05-26 | 2011-12-07 | 上海理工大学 | Vehicle stability control method based on tire vertical loading distribution |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4465506B2 (en) * | 2004-10-14 | 2010-05-19 | 株式会社神戸製鋼所 | Tire HIL simulator |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1357008A2 (en) * | 2002-04-23 | 2003-10-29 | Aisin Seiki Kabushiki Kaisha | Vehicle motion control apparatus |
| CN101710027A (en) * | 2009-11-24 | 2010-05-19 | 江苏大学 | Non-linear dynamic characteristic monitoring system and method of vehicle tyre |
| CN101979268A (en) * | 2010-09-25 | 2011-02-23 | 合肥工业大学 | Automobile steering wheel shimmy control method |
| CN102267460A (en) * | 2011-05-26 | 2011-12-07 | 上海理工大学 | Vehicle stability control method based on tire vertical loading distribution |
Non-Patent Citations (1)
| Title |
|---|
| 基于智能体——神经网络的轮胎侧偏特性;陈龙等;《机械工程学报》;20120131;第48卷(第2期);153-158 * |
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Effective date of registration: 20230417 Address after: 201110, 3rd Floor, Building 1, No. 400 Fangchun Road, China (Shanghai) Pilot Free Trade Zone, Pudong New Area, Huangpu District, Shanghai Patentee after: SHANGHAI VEHINFO INFORMATION TECHNOLOGY CO.,LTD. Address before: Zhenjiang City, Jiangsu Province, 212013 Jingkou District Road No. 301 Patentee before: JIANGSU University |