CN109515102A - Vehicle lateral wind estimation method, device and vehicle - Google Patents
Vehicle lateral wind estimation method, device and vehicle Download PDFInfo
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- CN109515102A CN109515102A CN201710852524.7A CN201710852524A CN109515102A CN 109515102 A CN109515102 A CN 109515102A CN 201710852524 A CN201710852524 A CN 201710852524A CN 109515102 A CN109515102 A CN 109515102A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
- B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
- B60G17/016—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by their responsiveness, when the vehicle is travelling, to specific motion, a specific condition, or driver input
- B60G17/0165—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by their responsiveness, when the vehicle is travelling, to specific motion, a specific condition, or driver input to an external condition, e.g. rough road surface, side wind
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/20—Speed
- B60G2400/204—Vehicle speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/40—Steering conditions
- B60G2400/41—Steering angle
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/80—Exterior conditions
- B60G2400/84—Atmospheric conditions
- B60G2400/841—Wind
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/20—Stationary vehicle
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- Mechanical Engineering (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
- Vehicle Body Suspensions (AREA)
Abstract
This disclosure relates to which a kind of vehicle lateral wind estimation method, device and vehicle, can accurately estimate lateral wind.The described method includes: establishing the N number of lateral wind estimation model for corresponding respectively to N number of lateral wind parameter, N is positive integer according to N number of lateral wind parameter of setting；The wheel condition parameter of vehicle is inputted into N number of lateral wind estimation model respectively, obtains N number of response, the wheel condition parameter is used to characterize the moving situation of the wheel of the vehicle；According to the real response value that N number of response and vehicle are exported based on practical lateral wind, the N number of Identification Errors for corresponding respectively to N number of lateral wind estimation model are determined；According to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter.
Description
Technical field
This disclosure relates to technical field of vehicle, and in particular, to a kind of vehicle lateral wind estimation method, device and vehicle.
Background technique
With the continuous development of science and technology, the trip of people is also more and more convenient, various automobiles, electric vehicle etc.
Have become the essential vehicles in people's life, meanwhile, people also propose the stability of vehicle and safety
Increasingly higher demands.
Vehicle is in the process of moving often by the interference of lateral wind, and especially when running at high speed, lateral wind is produced
Raw lateral force may cause Wheel slip or unstable state to turn to, and cause vehicle to deviate driving direction, may occur when serious
The accidents such as sideslip, rollover, impact the safety of vehicle.Therefore, research of the determination of lateral wind for intact stability
It is very necessary.
However, since lateral wind has biggish uncertainty, and the research of lateral wind is lacked very much at present, at present
It there is no the preferable mode for determining lateral wind.
Summary of the invention
It, being capable of accurately opposite side purpose of this disclosure is to provide a kind of vehicle lateral wind estimation method, device and vehicle
Aweather estimated.
According to a first aspect of the embodiments of the present invention, a kind of vehicle lateral wind estimation method is provided, comprising:
According to N number of lateral wind parameter of setting, N number of lateral wind that foundation corresponds respectively to N number of lateral wind parameter is estimated
Model is counted, N is positive integer；
The wheel condition parameter of vehicle is inputted into N number of lateral wind estimation model respectively, obtains N number of response, it is described
Wheel condition parameter is used to characterize the moving situation of the wheel of the vehicle；
According to the real response value that N number of response and vehicle are exported based on practical lateral wind, determination is corresponded respectively to
N number of Identification Errors of N number of lateral wind estimation model；
According to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter.
Optionally, the real response value exported according to N number of response and vehicle based on practical lateral wind is determined and is divided
Not Dui Yingyu the N number of lateral wind estimation model N number of Identification Errors, comprising:
For each response in N number of response, by the difference between the response and the real response value
It is determined as the Identification Errors of the corresponding lateral wind estimation model of the response；
According to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter, comprising:
For each Identification Errors in N number of Identification Errors, cost function is established
Wherein, i=1,2,3 ... N, ei(t) instantaneous value of Model Distinguish error is estimated for i-th of lateral wind,It is i-th
Lateral wind estimates the steady-state value of Model Distinguish error, ρ1For the weight of Identification Errors instantaneous value, ρ2For the power of Identification Errors steady-state value
Weight；
In N number of lateral wind estimation model, J is determinediIt is worth the estimation mould of lateral wind corresponding to the smallest Identification Errors
Type is that the first lateral wind estimates model；
The corresponding lateral wind parameter of first lateral wind estimation model is determined as the lateral wind estimated value.
Optionally, the real response value exported according to N number of response and vehicle based on practical lateral wind is determined and is divided
Not Dui Yingyu the N number of lateral wind estimation model N number of Identification Errors, comprising:
For each response in N number of response, by the difference between the response and the real response value
It is determined as the Identification Errors of the corresponding lateral wind estimation model of the response；
According to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter, comprising:
In N number of lateral wind estimation model, lateral wind corresponding to the minimum value in N number of Identification Errors is determined
Estimate that model is that the second lateral wind estimates model；
The corresponding lateral wind parameter of second lateral wind estimation model is determined as the lateral wind estimated value.
Optionally, in N number of lateral wind parameter according to setting, foundation corresponds respectively to the N number of of N number of lateral wind parameter
Lateral wind is estimated before model, further includes:
According to preset N number of relative wind velocity, each side in N number of lateral wind parameter is set separately by following formula
Aweather parameter:
Wherein, i=1,2,3 ... N, FywiFor i-th of lateral wind parameter in N number of lateral wind parameter, ρaFor crosswind
Come current density, ALFor the lateral windward side projected area of vehicle, CyFor sideway force coefficient, βwFor incoming flow side drift angle, VwriIt is described N number of
I-th of relative wind velocity in characteristic point wind speed, the relative wind velocity is used to characterize wind speed and the velocity vector of speed is poor；
According to N number of lateral wind parameter of setting, N number of lateral wind that foundation corresponds respectively to N number of lateral wind parameter is estimated
Count model, comprising:
For each lateral wind parameter in N number of lateral wind parameter, it is as follows to establish corresponding lateral wind estimation model:
Wherein, vyiFor the corresponding side velocity of i-th of lateral wind parameter, m is the complete vehicle quality of the vehicle, FxfFor institute
State the front axle longitudinal force of vehicle, FyfFor the front axle lateral force of the vehicle, FyrFor the rear axle lateral force of the vehicle, δ is front-wheel
Corner, riFor the corresponding yaw velocity response of i-th of lateral wind parameter, vxFor longitudinal speed of the vehicle, IzFor the vehicle
Around z-axis rotary inertia, a be the vehicle mass center to the vehicle front axle distance, b arrives for the mass center of the vehicle
The distance of the rear axle of the vehicle, twFor two front-wheels of the vehicle or the wheelspan of two rear-wheels, FxflFor a left side for the vehicle
Front-wheel longitudinal force, FxfrFor the off-front wheel longitudinal force of the vehicle, FyflFor the near front wheel lateral force of the vehicle, FyfrIt is described
The off-front wheel lateral force of vehicle, FxrlFor the left rear wheel longitudinal force of the vehicle, FxrrFor the off hind wheel longitudinal force of the vehicle, ayi
For the corresponding transverse acceleration response of i-th of lateral wind parameter.Optionally, before the wheel condition parameter includes the vehicle
Take turns corner δ, the near front wheel rotational speed omegafl, off-front wheel rotational speed omegafr, left rear wheel rotational speed omegarlAnd off hind wheel rotational speed omegarr, by the vehicle of vehicle
Wheel state parameter inputs N number of lateral wind estimation model respectively, obtains N number of response, comprising:
According to the left front wheel speed, the off-front wheel revolving speed, the left back wheel speed and off hind wheel revolving speed, institute is obtained
State longitudinal speed v of the vehiclex；
By the front wheel angle δ and longitudinal speed vxEach of described N number of lateral wind estimation model is inputted respectively
Lateral wind estimates model, obtains N number of response, wherein i-th of response in N number of response is (ayi,ri)。
Optionally, after determining lateral wind estimated value in N number of lateral wind parameter, further includes:
According to the lateral wind estimated value, to the Active suspension control of the vehicle, so that when the vehicle roll, vertically
Load is redistributed in left and right wheels.
According to a second aspect of the embodiments of the present invention, a kind of vehicle lateral wind estimation device is provided, comprising:
Module is established, for N number of lateral wind parameter according to setting, foundation corresponds respectively to N number of lateral wind parameter
N number of lateral wind estimate model, N is positive integer；
Module is obtained, model is estimated for the wheel condition parameter of vehicle to be inputted N number of lateral wind respectively, obtains N
A response, the wheel condition parameter are used to characterize the moving situation of the wheel of the vehicle；
First determining module, the real response for being exported according to N number of response and vehicle based on practical lateral wind
Value determines the N number of Identification Errors for corresponding respectively to N number of lateral wind estimation model；
Second determining module, for determining lateral wind from N number of lateral wind parameter according to N number of Identification Errors
Estimated value.
Optionally, first determining module is used for:
For each response in N number of response, by the difference between the response and the real response value
It is determined as the Identification Errors of the corresponding lateral wind estimation model of the response；
Second determining module is used for:
For each Identification Errors in N number of Identification Errors, cost function is established
Wherein, i=1,2,3 ... N, ei(t) instantaneous value of Model Distinguish error is estimated for i-th of lateral wind,It is i-th
Lateral wind estimates the steady-state value of Model Distinguish error, ρ1For the weight of Identification Errors instantaneous value, ρ2For the power of Identification Errors steady-state value
Weight；
In N number of lateral wind estimation model, J is determinediIt is worth the estimation mould of lateral wind corresponding to the smallest Identification Errors
Type is that the first lateral wind estimates model；
The corresponding lateral wind parameter of first lateral wind estimation model is determined as the lateral wind estimated value.
Optionally, first determining module is used for:
For each response in N number of response, by the difference between the response and the real response value
It is determined as the Identification Errors of the corresponding lateral wind estimation model of the response；
Second determining module is used for:
In N number of lateral wind estimation model, lateral wind corresponding to the minimum value in N number of Identification Errors is determined
Estimate that model is that the second lateral wind estimates model；
The corresponding lateral wind parameter of second lateral wind estimation model is determined as the lateral wind estimated value.
Optionally, described device further include:
Setting module, in N number of lateral wind parameter according to setting, foundation to correspond respectively to N number of lateral wind ginseng
Before several N number of lateral wind estimation models, according to preset N number of relative wind velocity, N number of side is set separately by following formula
Aweather each lateral wind parameter in parameter:
Wherein, i=1,2,3 ... N, FywiFor i-th of lateral wind parameter in N number of lateral wind parameter, ρaFor crosswind
Come current density, ALFor the lateral windward side projected area of vehicle, CyFor sideway force coefficient, βwFor incoming flow side drift angle, VwriIt is described N number of
I-th of relative wind velocity in characteristic point wind speed, the relative wind velocity is used to characterize wind speed and the velocity vector of speed is poor；
The module of establishing is used for:
For each lateral wind parameter in N number of lateral wind parameter, it is as follows to establish corresponding lateral wind estimation model:
Wherein, vyiFor the corresponding side velocity of i-th of lateral wind parameter, m is the complete vehicle quality of the vehicle, FxfFor institute
State the front axle longitudinal force of vehicle, FyfFor the front axle lateral force of the vehicle, FyrFor the rear axle lateral force of the vehicle, δ is front-wheel
Corner, riFor the corresponding yaw velocity response of i-th of lateral wind parameter, vxFor longitudinal speed of the vehicle, IzFor the vehicle
Around z-axis rotary inertia, a be the vehicle mass center to the vehicle front axle distance, b arrives for the mass center of the vehicle
The distance of the rear axle of the vehicle, twFor two front-wheels of the vehicle or the wheelspan of two rear-wheels, FxflFor a left side for the vehicle
Front-wheel longitudinal force, FxfrFor the off-front wheel longitudinal force of the vehicle, FyflFor the near front wheel lateral force of the vehicle, FyfrIt is described
The off-front wheel lateral force of vehicle, FxrlFor the left rear wheel longitudinal force of the vehicle, FxrrFor the off hind wheel longitudinal force of the vehicle, ayi
For the corresponding transverse acceleration response of i-th of lateral wind parameter.
Optionally, the wheel condition parameter includes the front wheel angle δ of the vehicle, the near front wheel rotational speed omegafl, off-front wheel turn
Fast ωfr, left rear wheel rotational speed omegarlAnd off hind wheel rotational speed omegarr, the acquisition module is used for:
According to the near front wheel rotational speed omegafl, the off-front wheel rotational speed omegafr, the left rear wheel rotational speed omegarlAnd off hind wheel turns
Fast ωrr, obtain longitudinal speed v of the vehiclex；
By the front wheel angle δ and longitudinal speed vxEach of described N number of lateral wind estimation model is inputted respectively
Lateral wind estimates model, obtains N number of response, wherein i-th of response in N number of response is (ayi,ri)。
Optionally, described device further include:
Control module, for after determining lateral wind estimated value in N number of lateral wind parameter, according to described lateral
Wind estimated value, to the Active suspension control of the vehicle, so that vertical load is divided again in left and right wheels when the vehicle roll
Match.
According to a third aspect of the embodiments of the present invention, a kind of vehicle is provided, including vehicle lateral wind described in second aspect
Estimation device.
Through the above technical solutions, different lateral wind estimation moulds can be established for the different lateral wind parameters of setting
Then type is compared with the actual response of vehicle with the response of each lateral wind estimation model output, passes through Identification Errors
Find out with the immediate response of the actual response of vehicle, and then from the different lateral wind parameters of setting determine lateral wind
Estimated value.In this way, by way of establishing non-linear auto model and setting multi-model switching, it can be accurately to vehicle
The lateral wind being subject to is estimated that the research influenced for lateral wind on vehicle static and Dynamic Kinetic characteristic lays the foundation, and is had
Conducive to the control and research preferably to automobile body stability, and then improve the stability and safety of vehicle.
Other feature and advantage of the disclosure will the following detailed description will be given in the detailed implementation section.
Detailed description of the invention
Attached drawing is and to constitute part of specification for providing further understanding of the disclosure, with following tool
Body embodiment is used to explain the disclosure together, but does not constitute the limitation to the disclosure.In the accompanying drawings:
Fig. 1 is a kind of flow chart of vehicle lateral wind estimation method shown according to an exemplary embodiment；
Fig. 2 is a kind of schematic diagram of vehicle lateral wind estimation method shown according to an exemplary embodiment；
Fig. 3 is a kind of block diagram of vehicle lateral wind estimation device shown according to an exemplary embodiment；
Fig. 4 is a kind of another block diagram of vehicle lateral wind estimation device shown according to an exemplary embodiment；
Fig. 5 is a kind of another block diagram of vehicle lateral wind estimation device shown according to an exemplary embodiment.
Specific embodiment
It is described in detail below in conjunction with specific embodiment of the attached drawing to the disclosure.It should be understood that this place is retouched
The specific embodiment stated is only used for describing and explaining the disclosure, is not limited to the disclosure.
Fig. 1 is a kind of flow chart of vehicle lateral wind estimation method shown according to an exemplary embodiment, such as Fig. 1 institute
Show, which can be applied in vehicle, include the following steps.
Step S11: it according to N number of lateral wind parameter of setting, establishes and corresponds respectively to the N number of lateral of N number of lateral wind parameter
Wind estimates model, and N is positive integer.
Step S12: inputting N number of lateral wind for the wheel condition parameter of vehicle respectively and estimate model, obtain N number of response,
Wheel condition parameter is used to characterize the moving situation of the wheel of vehicle.
Step S13: the real response value exported according to N number of response and vehicle based on practical lateral wind, determination are right respectively
It should be in N number of Identification Errors of N number of lateral wind estimation model.
Step S14: according to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter.
Fig. 2 is referred to, Fig. 2 is the schematic diagram for the vehicle lateral wind estimation method that the embodiment of the present disclosure provides, and lateral wind is estimated
Meter model 1 corresponds respectively to N number of lateral wind parameter to lateral wind estimation model N, i.e., each lateral wind parameter is corresponding to construct one
Lateral wind estimates model, and wheel condition parameter is inputted each lateral wind and estimates model, obtains N number of response, N number of response point
It is not compared with the real response value of vehicle output, N number of Identification Errors can be respectively obtained, found out by Identification Errors optimal
Lateral wind estimates model, and then the optimal corresponding lateral wind parameter of lateral wind estimation model is estimated as lateral wind
Value.In this way, establish non-linear auto model and setting multi-model switching by way of, can accurately to vehicle by
Lateral wind estimated that the research influenced for lateral wind on vehicle static and Dynamic Kinetic characteristic lays the foundation, be conducive to
Preferably to the control and research of automobile body stability, and then improve the stability and safety of vehicle.
It optionally, can be according to lateral wind estimated value to vehicle after continuing with lateral wind estimated value referring to fig. 2, is obtained
Active suspension controlled so that vertical load is redistributed in left and right wheels when vehicle roll, and then reduce vehicle rollover
Possibility, promote the stability of vehicle.Certainly, the present disclosure is not limited to controlling Active suspension, adjustment vehicle can also be performed
The operation such as braking system, driving wheel corner, for example the left and right brake force of vehicle is redistributed, to prevent vehicle rollover, side
It is sliding, etc., as long as the stability of vehicle can be promoted by lateral wind estimated value.The lateral wind estimation side that the disclosure provides
Method, lateral wind that can be current to vehicle in real time is estimated, and then adjusts vehicle according to lateral wind estimated value in real time
Stability, be conducive to improve vehicle safety.
In the embodiment of the present disclosure, lateral wind parameter can be the lateral force F for being equivalent to lateral windyw.It is assumed that lateral force belongs to
One finite aggregate, i.e. Fyw∈Fw, N number of lateral force (N number of lateral wind parameter) can be include set in N number of characteristic point,
I.e.It is how many actually for the value of N, the embodiment of the present disclosure is not construed as limiting, it is contemplated that FwThe characteristic point for including
If number would potentially result in the computational efficiency decline of algorithm too much, arithmetic accuracy, the disclosure will affect if, whereas if very little
To choose 11 characteristic points, i.e. for N=11.
Optionally, it in N number of lateral wind parameter according to setting, establishes and corresponds respectively to the N number of lateral of N number of lateral wind parameter
Before wind estimates model, it can be set separately in N number of lateral wind parameter according to preset N number of relative wind velocity by following formula
Each lateral wind parameter:
Wherein, i=1,2,3 ... N, FywiFor i-th of lateral wind parameter in N number of lateral wind parameter, ρaFor crosswind incoming flow
Density, ALFor the lateral windward side projected area of vehicle, CyFor sideway force coefficient, βwFor incoming flow side drift angle, VwriFor N number of characteristic point wind
I-th of relative wind velocity in speed, relative wind velocity is used to characterize wind speed and the velocity vector of speed is poor.Sideway force coefficient CyIt is incoming flow
Side drift angle βwFunction such as C can be taken for convenience of calculatingy(βw)=2, etc..
In formula, VwriIn any relative wind velocity VwrIt can be determined by following formula, V in following formulawFor wind speed, V is
Speed, θwIt is the angle of true wind direction Yu the vehicle longitudinal axis for wind angle.
For example, according to " tropical cyclone intensity grade classification ", when taking N=11, under different wind scales, each characteristic point for obtaining
Lateral force Fywi(lateral wind parameter) is as shown in table 1 below.
1 wind speed range of table and lateral force FywiThe parameter value of each characteristic point
Wherein, the corresponding wind speed of each wind scale is limited to set value up and down, and characteristic point wind speed is characterized relative wind velocity a little, should
Relative wind velocity is used to characterize wind speed and the velocity vector of speed is poor.
Optionally, the selection principle of characteristic point is as follows: when taking the lateral wind by each different directions, the lateral windward side of vehicle
In be more overlapped a little for calculate lateral wind characteristic point.Generally the mid-point position of vehicular sideview is taken to be characterized a little, and
The wind speed (i.e. characteristic point wind speed) of this feature point when testing different grades of lateral wind, and the side of the characteristic point under the wind speed
The lateral force of the point is also known as the equivalent lateral force that vehicle is subject to by Xiang Li.When calculating the lateral wind that vehicle is subject to, and with
Characteristic point is to estimate the reference point of lateral wind to estimate equivalent lateral force that vehicle is subject to, and then determine the lateral wind that vehicle is subject to
Size.
Because during high vehicle speeds, due to the influence of speed, influence of the lateral wind to vehicle depend on wind speed with
The collective effect of speed, therefore we take the characteristic point wind speed in table to be characterized relative wind velocity a little, which is used for
The velocity vector for characterizing wind speed and speed is poor.
Optionally, for each lateral wind parameter in N number of lateral wind parameter, corresponding lateral wind estimation mould is established
Type is as follows:
Wherein, vyiFor the corresponding side velocity of i-th of lateral wind parameter, m is the complete vehicle quality of the vehicle, FxfFor institute
State the front axle longitudinal force of vehicle, FyfFor the front axle lateral force of the vehicle, FyrFor the rear axle lateral force of the vehicle, δ is front-wheel
Corner, riFor the corresponding yaw velocity response of i-th of lateral wind parameter, vxFor longitudinal speed of the vehicle, IzFor the vehicle
Around z-axis rotary inertia, a be the vehicle mass center to the vehicle front axle distance, b arrives for the mass center of the vehicle
The distance of the rear axle of the vehicle, twFor two front-wheels of the vehicle or the wheelspan of two rear-wheels, FxflFor a left side for the vehicle
Front-wheel longitudinal force, FxfrFor the off-front wheel longitudinal force of the vehicle, FyflFor the near front wheel lateral force of the vehicle, FyfrIt is described
The off-front wheel lateral force of vehicle, FxrlFor the left rear wheel longitudinal force of the vehicle, FxrrFor the off hind wheel longitudinal force of the vehicle, ayi
For the corresponding transverse acceleration response of i-th of lateral wind parameter.
In the above manner, can in conjunction with lateral wind parameter determination come from which further follow that lateral wind estimate model, propose
A kind of mode of preferable estimation lateral wind.
Optionally, wheel condition parameter includes the front wheel angle δ of vehicle, the near front wheel rotational speed omegafl, off-front wheel rotational speed omegafr、
Left rear wheel rotational speed omegarlAnd off hind wheel rotational speed omegarr, can be according to the near front wheel rotational speed omegafl, off-front wheel rotational speed omegafr, left back wheel speed
ωrlAnd off hind wheel rotational speed omegarr, obtain longitudinal speed v of vehiclex, then by front wheel angle δ and longitudinal speed vxN is inputted respectively
Each lateral wind in a lateral wind estimation model estimates model, obtains N number of response, wherein i-th in N number of response
Response is (ayi,ri)。
Longitudinal speed v of vehiclexThe near front wheel rotational speed omega can be passed throughfl, off-front wheel rotational speed omegafr, left rear wheel rotational speed omegarl, it is right after
Wheel speed ωrrIt is calculated.
In order to acquire the dynamic response (a of each modelyi,ri), consider lateral wind action but ignores caused by lateral wind
The differential equation of motion of i-th of lateral wind estimation model, i.e., above-mentioned model Chinese style (1) and formula (2) can be obtained in yaw moment.
Wheel condition parameter can be collected by the sensor being arranged on vehicle, and vehicle status parameters are inputted each side
Aweather estimate model, r can be obtained by formula (1) and formula (2)i(t), a is obtained by formula (3)yi(t)。
Real response value (a of vehicley, r) and it can be collected by the sensor being arranged on vehicle, ayLaterally to accelerate
Degree, r is yaw velocity.
In the above manner, the response of each lateral wind estimation model can be obtained preferably, further will be conducive to
Lateral wind estimation model output response be compared with the actual response of vehicle, and then relatively accurately to lateral wind into
Row estimation.
It optionally, can be by the difference between the response and real response value for each response in N number of response
Value is determined as the Identification Errors of the corresponding lateral wind estimation model of the response, then distinguishing for each of N number of Identification Errors
Know error, can establish cost functionWherein, i=1,2,3 ... N, ei(t) it is i-th
Lateral wind estimates the instantaneous value of Model Distinguish error,The steady-state value of Model Distinguish error is estimated for i-th of lateral wind,
ρ1For the weight of Identification Errors instantaneous value, ρ2For the weight of Identification Errors steady-state value.In N number of lateral wind estimation model, J is determinedi
Being worth the estimation model of lateral wind corresponding to the smallest Identification Errors is that the first lateral wind estimates model, and the first lateral wind is estimated mould
The corresponding lateral wind parameter of type is determined as lateral wind estimated value.
That is, actual vehicle response value is (ay, r), the response of i-th of lateral wind estimation model is (ayi,ri), then can
To determine Identification Errors ei(t) it is
Since there may be uncertain factor (such as non-linear factor) and random error, (for example measurement is missed in practical application
Difference), therefore should consider that the instantaneous value of Identification Errors considers the steady-state value of Identification Errors again, and then establish above-mentioned cost letter
Number.ρ therein1For the weight of Identification Errors instantaneous value, ρ2For the weight of Identification Errors steady-state value, ρ1> 0, ρ2> 0, for example, can
To set ρ1With ρ2For 1:1 or 1:2, etc..Find out cost function JiIt is worth the estimation of lateral wind corresponding to the smallest Identification Errors
Model (i.e. the first lateral wind estimates model), and then the corresponding lateral force of the first lateral wind estimation model is determined as lateral wind and is estimated
Evaluation.In this way, the lateral wind estimated value further determined that out can be made more accurate.
Optionally, Identification Errors can be directly used also to find out lateral wind estimated value, likewise, being directed to N number of response
In each response, the difference between the response and real response value can be determined as to the corresponding lateral wind of the response
The Identification Errors of model are estimated, then can estimate to determine the minimum value institute in N number of Identification Errors in model in N number of lateral wind
Corresponding lateral wind estimation model is that the second lateral wind estimates model, by the corresponding lateral wind parameter of the second lateral wind estimation model
It is determined as lateral wind estimated value.
That is, the smallest lateral wind estimation model (the second lateral wind estimates model) of Identification Errors is directly found out, then second
Lateral wind estimate the corresponding lateral force of model be it needs to be determined that lateral wind estimated value.It is efficiently obtained in this way, can be convenient
Lateral wind estimated value.
Fig. 3 is referred to, based on the same inventive concept, the embodiment of the present disclosure provides a kind of vehicle lateral wind estimation device 300,
The device 300 may include:
Module 301 is established, for N number of lateral wind parameter according to setting, foundation corresponds respectively to N number of lateral wind ginseng
Several N number of lateral winds estimates model, and N is positive integer；
Module 302 is obtained, model is estimated for the wheel condition parameter of vehicle to be inputted N number of lateral wind respectively, obtains
N number of response is obtained, the wheel condition parameter is used to characterize the moving situation of the wheel of the vehicle；
First determining module 303, the reality for being exported according to N number of response and vehicle based on practical lateral wind
Response determines the N number of Identification Errors for corresponding respectively to N number of lateral wind estimation model；
Second determining module 304, for according to N number of Identification Errors, determined from N number of lateral wind parameter side to
Wind estimated value.
Optionally, first determining module 303 is used for:
For each response in N number of response, by the difference between the response and the real response value
It is determined as the Identification Errors of the corresponding lateral wind estimation model of the response；
Second determining module 304 is used for:
For each Identification Errors in N number of Identification Errors, cost function is establishedWherein, i=1,2,3 ... N, ei(t) Model Distinguish error is estimated for i-th of lateral wind
Instantaneous value,The steady-state value of Model Distinguish error, ρ are estimated for i-th of lateral wind1For the power of Identification Errors instantaneous value
Weight, ρ2For the weight of Identification Errors steady-state value；
In N number of lateral wind estimation model, J is determinediIt is worth the estimation mould of lateral wind corresponding to the smallest Identification Errors
Type is that the first lateral wind estimates model；
The corresponding lateral wind parameter of first lateral wind estimation model is determined as the lateral wind estimated value.
Optionally, first determining module 303 is used for:
For each response in N number of response, by the difference between the response and the real response value
It is determined as the Identification Errors of the corresponding lateral wind estimation model of the response；
Second determining module 304 is used for:
In N number of lateral wind estimation model, lateral wind corresponding to the minimum value in N number of Identification Errors is determined
Estimate that model is that the second lateral wind estimates model；
The corresponding lateral wind parameter of second lateral wind estimation model is determined as the lateral wind estimated value.
Optionally, Fig. 4, described device 300 are referred to further include:
Setting module 305, in N number of lateral wind parameter according to setting, foundation to correspond respectively to N number of lateral wind
Before N number of lateral wind estimation model of parameter, according to preset N number of relative wind velocity, it is set separately by following formula described N number of
Each lateral wind parameter in lateral wind parameter:
Wherein, i=1,2,3 ... N, FywiFor i-th of lateral wind parameter in N number of lateral wind parameter, ρaFor crosswind
Come current density, ALFor the lateral windward side projected area of vehicle, CyFor sideway force coefficient, βwFor incoming flow side drift angle, VwriIt is described N number of
I-th of relative wind velocity in characteristic point wind speed, the relative wind velocity is used to characterize wind speed and the velocity vector of speed is poor；
The module 301 of establishing is used for:
For each lateral wind parameter in N number of lateral wind parameter, it is as follows to establish corresponding lateral wind estimation model:
Wherein, vyiFor the corresponding side velocity of i-th of lateral wind parameter, m is the complete vehicle quality of the vehicle, FxfFor institute
State the front axle longitudinal force of vehicle, FyfFor the front axle lateral force of the vehicle, FyrFor the rear axle lateral force of the vehicle, δ is front-wheel
Corner, riFor the corresponding yaw velocity response of i-th of lateral wind parameter, vxFor longitudinal speed of the vehicle, IzFor the vehicle
Around z-axis rotary inertia, a be the vehicle mass center to the vehicle front axle distance, b arrives for the mass center of the vehicle
The distance of the rear axle of the vehicle, twFor two front-wheels of the vehicle or the wheelspan of two rear-wheels, FxflFor a left side for the vehicle
Front-wheel longitudinal force, FxfrFor the off-front wheel longitudinal force of the vehicle, FyflFor the near front wheel lateral force of the vehicle, FyfrIt is described
The off-front wheel lateral force of vehicle, FxrlFor the left rear wheel longitudinal force of the vehicle, FxrrFor the off hind wheel longitudinal force of the vehicle, ayi
For the corresponding transverse acceleration response of i-th of lateral wind parameter.
Optionally, the wheel condition parameter includes the front wheel angle δ of the vehicle, the near front wheel rotational speed omegafl, off-front wheel turn
Fast ωfr, left rear wheel rotational speed omegarlAnd off hind wheel rotational speed omegarr, the acquisition module 302 is used for:
According to the near front wheel rotational speed omegafl, the off-front wheel rotational speed omegafr, the left rear wheel rotational speed omegarlAnd off hind wheel turns
Fast ωrr, obtain longitudinal speed v of the vehiclex；
By the front wheel angle δ and longitudinal speed vxEach of described N number of lateral wind estimation model is inputted respectively
Lateral wind estimates model, obtains N number of response, wherein i-th of response in N number of response is (ayi,ri)。
Optionally, Fig. 5, described device 300 are referred to further include:
Control module 306, for from N number of lateral wind parameter determine lateral wind estimated value after, according to described
Lateral wind estimated value controls the Active suspension of the vehicle, so that vertical load is in left and right vehicle when the vehicle roll
Wheel is redistributed.
Based on the same inventive concept, the embodiment of the present disclosure provides a kind of vehicle, including Fig. 3-Fig. 5 it is any shown in vehicle side
Aweather estimation device.
The preferred embodiment of the disclosure is described in detail in conjunction with attached drawing above, still, the disclosure is not limited to above-mentioned reality
The detail in mode is applied, in the range of the technology design of the disclosure, a variety of letters can be carried out to the technical solution of the disclosure
Monotropic type, these simple variants belong to the protection scope of the disclosure.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, can be combined in any appropriate way, in order to avoid unnecessary repetition, the disclosure to it is various can
No further explanation will be given for the combination of energy.
In addition, any combination can also be carried out between a variety of different embodiments of the disclosure, as long as it is without prejudice to originally
Disclosed thought equally should be considered as disclosure disclosure of that.
Claims (13)
1. a kind of vehicle lateral wind estimation method characterized by comprising
According to N number of lateral wind parameter of setting, the N number of lateral wind estimation mould for corresponding respectively to N number of lateral wind parameter is established
Type, N are positive integer；
The wheel condition parameter of vehicle is inputted into N number of lateral wind estimation model respectively, obtains N number of response, the wheel
State parameter is used to characterize the moving situation of the wheel of the vehicle；
According to the real response value that N number of response and vehicle are exported based on practical lateral wind, determine described in corresponding respectively to
N number of Identification Errors of N number of lateral wind estimation model；
According to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter.
2. vehicle lateral wind estimation method according to claim 1, which is characterized in that according to N number of response and vehicle
The real response value based on the output of practical lateral wind, determines the N number of identification for corresponding respectively to the N number of lateral wind estimation model
Error, comprising:
For each response in N number of response, the difference between the response and the real response value is determined
The Identification Errors of model are estimated for the corresponding lateral wind of the response；
According to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter, comprising:
For each Identification Errors in N number of Identification Errors, cost function is establishedIts
In, i=1,2,3 ... N, ei(t) instantaneous value of Model Distinguish error is estimated for i-th of lateral wind,For i-th of side
Aweather estimate the steady-state value of Model Distinguish error, ρ1For the weight of Identification Errors instantaneous value, ρ2For the power of Identification Errors steady-state value
Weight；
In N number of lateral wind estimation model, J is determinediBeing worth the estimation model of lateral wind corresponding to the smallest Identification Errors is the
One lateral wind estimates model；
The corresponding lateral wind parameter of first lateral wind estimation model is determined as the lateral wind estimated value.
3. vehicle lateral wind estimation method according to claim 1, which is characterized in that according to N number of response and vehicle
The real response value based on the output of practical lateral wind, determines the N number of identification for corresponding respectively to the N number of lateral wind estimation model
Error, comprising:
For each response in N number of response, the difference between the response and the real response value is determined
The Identification Errors of model are estimated for the corresponding lateral wind of the response；
According to N number of Identification Errors, lateral wind estimated value is determined from N number of lateral wind parameter, comprising:
In N number of lateral wind estimation model, determine that lateral wind corresponding to the minimum value in N number of Identification Errors is estimated
Model is that the second lateral wind estimates model；
The corresponding lateral wind parameter of second lateral wind estimation model is determined as the lateral wind estimated value.
4. vehicle lateral wind estimation method according to claim 1, which is characterized in that in N number of lateral wind according to setting
Parameter is established before the N number of lateral wind estimation model for corresponding respectively to N number of lateral wind parameter, further includes:
According to preset N number of relative wind velocity, each lateral wind in N number of lateral wind parameter is set separately by following formula
Parameter:
Wherein, i=1,2,3 ... N, FywiFor i-th of lateral wind parameter in N number of lateral wind parameter, ρaFor crosswind incoming flow
Density, ALFor the lateral windward side projected area of vehicle, CyFor sideway force coefficient, βwFor incoming flow side drift angle, VwriFor N number of feature
I-th of relative wind velocity in point wind speed, the relative wind velocity is used to characterize wind speed and the velocity vector of speed is poor；
According to N number of lateral wind parameter of setting, the N number of lateral wind estimation mould for corresponding respectively to N number of lateral wind parameter is established
Type, comprising:
For each lateral wind parameter in N number of lateral wind parameter, it is as follows to establish corresponding lateral wind estimation model:
Wherein, vyiFor the corresponding side velocity of i-th of lateral wind parameter, m is the complete vehicle quality of the vehicle, FxfFor the vehicle
Front axle longitudinal force, FyfFor the front axle lateral force of the vehicle, FyrFor the rear axle lateral force of the vehicle, δ is front wheel angle, ri
For the corresponding yaw velocity response of i-th of lateral wind parameter, vxFor longitudinal speed of the vehicle, IzIt is the vehicle around z-axis
Rotary inertia, a be the vehicle mass center to the vehicle front axle distance, b for the vehicle mass center to the vehicle
Rear axle distance, twFor two front-wheels of the vehicle or the wheelspan of two rear-wheels, FxflIt is vertical for the near front wheel of the vehicle
Xiang Li, FxfrFor the off-front wheel longitudinal force of the vehicle, FyflFor the near front wheel lateral force of the vehicle, FyfrFor the vehicle
Off-front wheel lateral force, FxrlFor the left rear wheel longitudinal force of the vehicle, FxrrFor the off hind wheel longitudinal force of the vehicle, ayiIt is i-th
The corresponding transverse acceleration response of a lateral wind parameter.
5. vehicle lateral wind estimation method according to claim 4, which is characterized in that the wheel condition parameter includes institute
State front wheel angle δ, the near front wheel rotational speed omega of vehiclefl, off-front wheel rotational speed omegafr, left rear wheel rotational speed omegarlAnd off hind wheel rotational speed omegarr,
The wheel condition parameter of vehicle is inputted into N number of lateral wind estimation model respectively, obtains N number of response, comprising:
According to the left front wheel speed, the off-front wheel revolving speed, the left back wheel speed and off hind wheel revolving speed, the vehicle is obtained
Longitudinal speed vx；
By the front wheel angle δ and longitudinal speed vxEach lateral wind in N number of lateral wind estimation model is inputted respectively
Estimate model, obtain N number of response, wherein i-th of response in N number of response is (ayi,ri)。
6. -5 any vehicle lateral wind estimation method according to claim 1, which is characterized in that from N number of side to
In wind parameter after determining lateral wind estimated value, further includes:
According to the lateral wind estimated value, the Active suspension of the vehicle is controlled, so that when the vehicle roll, vertically
Load is redistributed in left and right wheels.
7. a kind of vehicle lateral wind estimation device characterized by comprising
Module is established, for N number of lateral wind parameter according to setting, foundation corresponds respectively to the N number of of N number of lateral wind parameter
Lateral wind estimates model, and N is positive integer；
Module is obtained, model is estimated for the wheel condition parameter of vehicle to be inputted N number of lateral wind respectively, obtains N number of sound
It should be worth, the wheel condition parameter is used to characterize the moving situation of the wheel of the vehicle；
First determining module, the real response value for being exported according to N number of response and vehicle based on practical lateral wind,
Determine the N number of Identification Errors for corresponding respectively to N number of lateral wind estimation model；
Second determining module, for determining lateral wind estimation from N number of lateral wind parameter according to N number of Identification Errors
Value.
8. vehicle lateral wind estimation device according to claim 7, which is characterized in that first determining module is used for:
For each response in N number of response, the difference between the response and the real response value is determined
The Identification Errors of model are estimated for the corresponding lateral wind of the response；
Second determining module is used for:
For each Identification Errors in N number of Identification Errors, cost function is establishedIts
In, i=1,2,3 ... N, ei(t) instantaneous value of Model Distinguish error is estimated for i-th of lateral wind,For i-th of side
Aweather estimate the steady-state value of Model Distinguish error, ρ1For the weight of Identification Errors instantaneous value, ρ2For the power of Identification Errors steady-state value
Weight；
In N number of lateral wind estimation model, J is determinediBeing worth the estimation model of lateral wind corresponding to the smallest Identification Errors is the
One lateral wind estimates model；
The corresponding lateral wind parameter of first lateral wind estimation model is determined as the lateral wind estimated value.
9. vehicle lateral wind estimation device according to claim 7, which is characterized in that first determining module is used for:
For each response in N number of response, the difference between the response and the real response value is determined
The Identification Errors of model are estimated for the corresponding lateral wind of the response；
Second determining module is used for:
In N number of lateral wind estimation model, determine that lateral wind corresponding to the minimum value in N number of Identification Errors is estimated
Model is that the second lateral wind estimates model；
The corresponding lateral wind parameter of second lateral wind estimation model is determined as the lateral wind estimated value.
10. vehicle lateral wind estimation device according to claim 7, which is characterized in that described device further include:
Setting module, for establishing the N for corresponding respectively to N number of lateral wind parameter in N number of lateral wind parameter according to setting
Before a lateral wind estimation model, according to preset N number of relative wind velocity, N number of lateral wind is set separately by following formula
Each lateral wind parameter in parameter:
Wherein, i=1,2,3 ... N, FywiFor i-th of lateral wind parameter in N number of lateral wind parameter, ρaFor crosswind incoming flow
Density, ALFor the lateral windward side projected area of vehicle, CyFor sideway force coefficient, βwFor incoming flow side drift angle, VwriFor N number of feature
I-th of relative wind velocity in point wind speed, the relative wind velocity is used to characterize wind speed and the velocity vector of speed is poor；
The module of establishing is used for:
For each lateral wind parameter in N number of lateral wind parameter, it is as follows to establish corresponding lateral wind estimation model:
Wherein, vyiFor the corresponding side velocity of i-th of lateral wind parameter, m is the complete vehicle quality of the vehicle, FxfFor the vehicle
Front axle longitudinal force, FyfFor the front axle lateral force of the vehicle, FyrFor the rear axle lateral force of the vehicle, δ is front wheel angle, ri
For the corresponding yaw velocity response of i-th of lateral wind parameter, vxFor longitudinal speed of the vehicle, IzIt is the vehicle around z-axis
Rotary inertia, a be the vehicle mass center to the vehicle front axle distance, b for the vehicle mass center to the vehicle
Rear axle distance, twFor two front-wheels of the vehicle or the wheelspan of two rear-wheels, FxflIt is vertical for the near front wheel of the vehicle
Xiang Li, FxfrFor the off-front wheel longitudinal force of the vehicle, FyflFor the near front wheel lateral force of the vehicle, FyfrFor the vehicle
Off-front wheel lateral force, FxrlFor the left rear wheel longitudinal force of the vehicle, FxrrFor the off hind wheel longitudinal force of the vehicle, ayiIt is i-th
The corresponding transverse acceleration response of a lateral wind parameter.
11. vehicle lateral wind estimation device according to claim 10, which is characterized in that the wheel condition parameter includes
The front wheel angle δ of the vehicle, the near front wheel rotational speed omegafl, off-front wheel rotational speed omegafr, left rear wheel rotational speed omegarlAnd off hind wheel revolving speed
ωrr, the acquisition module is used for:
According to the near front wheel rotational speed omegafl, the off-front wheel rotational speed omegafr, the left rear wheel rotational speed omegarlAnd off hind wheel revolving speed
ωrr, obtain longitudinal speed v of the vehiclex；
By the front wheel angle δ and longitudinal speed vxEach lateral wind in N number of lateral wind estimation model is inputted respectively
Estimate model, obtain N number of response, wherein i-th of response in N number of response is (ayi,ri)。
12. according to any vehicle lateral wind estimation device of claim 7-11, which is characterized in that described device is also wrapped
It includes:
Control module, for being estimated according to the lateral wind after determining lateral wind estimated value in N number of lateral wind parameter
Evaluation controls the Active suspension of the vehicle, so that vertical load is divided again in left and right wheels when the vehicle roll
Match.
13. a kind of vehicle, which is characterized in that estimate dress including the vehicle lateral wind as described in any one of claim 7-12
It sets.
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