CN110516311A - A kind of comprehensive compensation construction of strategy method for automobile-used acceleration transducer constant error - Google Patents
A kind of comprehensive compensation construction of strategy method for automobile-used acceleration transducer constant error Download PDFInfo
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- CN110516311A CN110516311A CN201910700562.XA CN201910700562A CN110516311A CN 110516311 A CN110516311 A CN 110516311A CN 201910700562 A CN201910700562 A CN 201910700562A CN 110516311 A CN110516311 A CN 110516311A
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Abstract
The invention discloses a kind of comprehensive compensation construction of strategy method for automobile-used acceleration transducer constant error, laterally and the kinetic expression of weaving observation of the realization to vehicle side velocity is initially set up about vehicle；Secondly the quantity of state and measurement that estimator is determined according to the horizontal and vertical kinematic relation of acceleration transducer error drift model and vehicle, utilize Kalman filter estimated acceleration sensor constant error；Finally by the amendment to tire normal pressure model and tire cornering stiffness and to the feedback of vehicle lateral speed observer input information, the compensation for completing acceleration transducer constant error updates.The present invention can realize that the estimation of automobile-used acceleration transducer constant error and iteration are updated with higher frequency, do not lose real-time too much while improving state of motion of vehicle estimation overall precision, have the characteristics that be simple and efficient.
Description
Technical field
The invention belongs to automobile sensor estimation errors and compensation field, more particularly to one kind to be directed to automobile-used acceleration sensing
The comprehensive compensation construction of strategy method of device constant error, it is therefore intended that further promoted vehicle running state estimation accuracy and
Real-time.
Background technique
With the development of vehicle active safety technologies, intelligent sensing theory has become its important one of research hotspot.It is right
For automobile, anti-lock braking system needs to differentiate according to the output of wheel speed sensors the sliding degree of wheel, and electronic stability controls
Program then determines the motor pattern of automobile to realize direct yaw moment control according to the signal of yaw-rate sensor.But
Being includes unavoidable noise in the output signal of these sensors, other some sensor (such as automobile-used acceleration
Degree sensor etc.) output the phenomenon that even drifting about at any time there are error.Time-domain integration operation is being carried out to sensor signal
When, these noises and drift all can be such that the error of output signal constantly amplifies.
Summary of the invention
It is of the existing technology in order to solve the problems, such as, sensor error drift bring loss of significance is reduced, the present invention mentions
A kind of comprehensive compensation construction of strategy method for automobile-used acceleration transducer constant error out.
The present invention is achieved through the following technical solutions above-mentioned technical purpose.
A kind of comprehensive compensation construction of strategy method for automobile-used acceleration transducer constant error, construction side velocity are seen
The data pre-processing that device is estimated as acceleration transducer constant error is surveyed, the observed result of vehicle side velocity is obtained, according to
The result of observation and the state equation of fusion realize the On-line Estimation of acceleration transducer constant error, and then pass through construction tire
Normal pressure error compensation model realizes the amendment to tire cornering stiffness, finally feeds back correction result to side velocity observer
In, the compensation for completing acceleration transducer constant error updates.
Further, the state equation that the estimation of the constant error uses has merged vehicle kinematics model and acceleration passes
Sensor error model.
Further, the state equation are as follows:Wherein ax,mes、ay,mesTo accelerate
Spend the measurement output of sensor, ax,bias、ay,biasFor the constant error of acceleration transducer, w1、w2、w3、w4Respectively white Gaussian
Noise, vxFor the longitudinal velocity of vehicle, vyFor the side velocity of vehicle, r is the yaw velocity of vehicle.
Further, the state equation chooses measurementv'xFor the longitudinal direction of driven wheel wheel speed sensors
Speed,For the observation of side velocity.
Further, the cornering stiffness CσThe normal pressure F being subject to four tireszBetween relationship are as follows: Cσ=a1sin
[a2arctan(a3Fz)], wherein a1、a2、a3For to fitting parameter.
Further, the normal pressure is calculated according to the correction result of acceleration signal, the acceleration signal
Correction result is determined by the constant error of acceleration transducer.
Further, the correction result of the acceleration signalMeet:Wherein
ax,mes、ay,mesIt is exported for the measurement of acceleration transducer,Optimal for acceleration transducer constant error is estimated
Evaluation.
Further, the error compensation model of the normal pressure are as follows:Wherein
M is automobile body quality, and i={ F, R }, F indicate that front-wheel, R indicate rear-wheel；J={ L, R }, L indicate that revolver, R indicate right wheel；H is
The vertical height of automobile mass center from the ground, l=lf+lrThe distance between automobile antero posterior axis, bF、bRFor automobile front and rear wheel away from.
The invention has the benefit that
1. the present invention merges vehicle kinematics model while modeling to sensor error, while constructing lateral speed
Observer is spent, the side velocity that side velocity observer is obtained improves acceleration sensing as the measurement of Fusion Model
The renewal speed of device constant error, compared with the error estimation assisted using GPS, data renewal frequency is high, simultaneously
It is at low cost；This method does not lose real-time while improving state of motion of vehicle estimation overall precision too much, has letter
Single efficient feature, and it is capable of the error drift of tracking acceleration sensor well.
2. the acceleration transducer constant error optimal estimation value that the present invention is obtained according to estimation may be implemented to add to automobile-used
The compensation and amendment of velocity sensor constant error, thus for the measurement and other vehicle control schemes of state of motion of vehicle
Accurate information is provided.
Detailed description of the invention
Fig. 1 is error compensation strategic process figure.
Specific embodiment
Below in conjunction with attached drawing, concrete scheme of the invention is further described, but protection scope of the present invention
It is not limited to this.
As shown in Figure 1, a kind of comprehensive compensation construction of strategy method for automobile-used acceleration transducer constant error includes
Following steps:
Step (1), the observation of vehicle side velocity
Vehicle uses front-wheel drive mode, and provides that the mass center of vehicle is bodywork reference frame origin, horizontally forward just for x-axis
To horizontal positive for y-axis to the left, vertical-horizontal is z-axis forward direction upwardly, and all angles of revolution and torque are in horizontal plane
Counter clockwise direction be positive.
Firstly, determining vehicle about lateral and weaving kinetics equation:
Wherein, vy, r be respectively the side velocity of vehicle, yaw velocity, Cf、CrThe respectively lateral deviation of automobile front and rear wheel
Rigidity, δ are the front wheel angle of vehicle, lf、lrFor respectively vehicle centroid with a distance from axle, m is automobile body quality, IzFor
Rotary inertia of the vehicle around z-axis, vxFor the longitudinal velocity of vehicle, andReffIndicate effectively the half of tire
Diameter, ω3And ω4Respectively left back, off hind wheel wheel speed.
Secondly, the data pre-processing that design Luenberger observer is estimated as acceleration transducer constant error, realization pair
The observation of vehicle side velocity.
Assuming that true vehicle side velocity observation model are as follows:
Wherein, quantity of state X=[vy r]T, control amount U=δ, measurement Y=r,
Lateral and weaving vehicle dynamic model matrix
Lateral and weaving Study on Vehicle Dynamic Control matrixLateral and weaving dynamics of vehicle measures
Matrix C=[0 1].
Using following Luenberger observer structure:
Wherein, L=[k1k2]TFor the POLE PLACEMENT USING observed for vehicle side velocity.
In order to which the error between the true value for observing side velocity and estimated value rapidly converges to 0, by formula (2) and formula
(3) subtracted each other, obtain the state equation of error:
The characteristic value of order matrix A-LC is less than zero, that is, POLE PLACEMENT USING parameter k needed for can determine side velocity observation1And k2,
k1、k2Be chosen at and meet in the minus situation of matrix A-LC characteristic value, need to consider the convergence rate of state error.
Step (2), establishes the error model of acceleration transducer
Wherein, ax,mes、ay,mesIt is exported for the measurement of acceleration transducer, ax、ayFor the longitudinally, laterally acceleration of vehicle,
ax,bias、ay,biasFor the constant error of acceleration transducer, w1、w2、w3、w4Respectively white Gaussian noise.In the present embodiment, closely
Seemingly think that acceleration transducer error model is random walk model, it may be assumed that
Step (3) utilizes Kalman filter estimated acceleration sensor constant error
It establishes about longitudinal direction of car and lateral kinematics model, it may be assumed that
Acceleration transducer error model and vehicle kinematics model are merged into (hereinafter referred to as Fusion Model), i.e., will
The error model of sensor is updated to vehicle about in kinematics model longitudinally and laterally, available following state side
Journey:
Choose quantity of state x=[vx ax,bias vy ay,bias]T, control amount u=[ax,mes ay,mes]T, measurementWhereinFor the observation of side velocity, and there is the longitudinal velocity v' of driven wheel wheel speed sensorsx=vx, shape
State equation and measurement equation can further indicate that are as follows:
Wherein, Fusion Model state matrixFusion Model controls matrixMelt
Molding type measurement matrixWhite Gaussian noise
Automobile-used acceleration constant error estimation based on Kalman filtering algorithm including the following steps:
1) time updates
One-step prediction is carried out to the quantity of states such as longitudinal direction of car, side velocity and longitudinal direction of car, side acceleration constant value deviation:
xk|k-1=Φk-1xk-1|k-1+Guk-1 (10)
Wherein: xk|k-1It is transmitted to the predicted state at k moment using state equation from the state at k -1 moment for Fusion Model,
uk-1For the control amount at Fusion Model k -1 moment；
Calculate the error covariance predicted value of the quantity of state:
Pk|k-1=Φk-1Pk-1|k-1Φk-1 T+Q (11)
Wherein, Q is the noise covariance of estimation procedure, Pk-1|k-1For the optimal association side at Fusion Model quantity of state k -1 moment
Difference, Pk|k-1For the prediction covariance at Fusion Model quantity of state k moment, and stateful transfer matrix:
Φk-1=exp (Fk-1Tt)≈I+Fk-1Tt (12)
Wherein, TtFor the update step-length of Kalman filtering algorithm, Fk-1For k -1 moment Fusion Model state matrix, I is single
Bit matrix, dimension are consistent with the dimension of quantity of state x.
2) it measures and updates
Determine the kalman gain of quantity of state estimation:
Kk=Pk|k-1Hk T(HkPk|k-1Hk T+R)-1 (13)
Wherein, HkFor the measurement matrix at k moment, R is the covariance for measuring noise；
The quantity of states such as longitudinal direction of car, side velocity and longitudinal direction of car, side acceleration constant value deviation are updated:
xk|k=xk|k-1+Kk(yk-Hkxk|k-1) (14)
Wherein, ykFor the measuring value of k moment state, including longitudinal velocity and side velocity, the longitudinal velocity is by wheel speed
Sensor provides, and side velocity is provided by Luenberger observer.
Update the error covariance of the quantity of state:
Pk|k=(I-KkHk)Pk|k-1(I-KkHk)T+KkRKk T (15)
In view of Kalman filtering is only limitted to Gaussian Profile to the processing of noise characteristic, noise covariance initial value is being chosen
When, the order of accuarcy for the model (formula (8)) for needing comprehensive reference to be established and the accuracy class of sensor in the model, are constituted
Longitudinal velocity v ' of the information of measurement from driven wheel wheel speed sensorsxWith the observation of side velocity
The sensor-based error model of Kalman filtering and about vehicle two longitudinally and laterally kinematics model to constant value miss
Poor quantity of state is constantly predicted and is corrected, to finally obtain accurate acceleration transducer constant error.
Step (4) determines the correction result of acceleration signal according to the acceleration transducer constant error that estimation obtains
Wherein,For the optimal estimation value for the acceleration transducer constant error that Fusion Model is estimated.
Step (5) calculates the normal pressure F that four tires are subject to according to the correction result of acceleration signalzij
According to formula (17) it is found that the tire normal pressure error F of compensationzij,biasCompensation model are as follows:
Wherein, g is acceleration of gravity, and i={ F, R }, F indicate that front-wheel, R indicate rear-wheel；J={ L, R }, L indicate revolver, R
Indicate right wheel；H is the vertical height of automobile mass center from the ground, l=lf+lrThe distance between automobile antero posterior axis, bF、bRFor automobile
Front and rear wheel away from.
Step (6), calculates the cornering stiffness of front and back wheel
Since the load of wheel in driving process is time-varying, the cornering stiffness of corresponding tire can also change, wheel
Tire cornering stiffness CσWith normal pressure FzBetween relationship it is as follows:
Cσ=a1sin[a2arctan(a3Fz)] (19)
Wherein, a1、a2、a3To carry out data fitting using the Tester module in CarSim software to fitting parameter；
Convolution (17) determines the cornering stiffness C of front and rear wheel in auto modelf、Cr:
Wherein, CσFL、CσFR、CσRL、CσRRRespectively vehicle front left, front right, rear left, rear right wheel tire cornering stiffness.
Step (7), by the tire cornering stiffness being calculated feedback into the Luenberger observer in step (1), due to
Luenberger observer is the vehicle dynamic model about lateral and weaving, and it is rigid to contain tire parameter-lateral deviation in model
Degree, is estimated by the constant error to acceleration, using revised tire cornering stiffness as institute in Luenberger observer
The tire cornering stiffness needed, the compensation for completing acceleration transducer constant error update, to realize that vehicle side velocity is observed
Update.
Side velocity observation based on Luenberger observer and the acceleration transducer constant error based on Kalman filtering
By mutual iteration between estimation, complementary closed loop configuration is formed, it is final to realize gradually mentioning for state of motion of vehicle estimated accuracy
It rises.
The above briefly describes the present invention, as long as thinking and working method of the present invention is taken simply to be repaired
Change, or make the equal behaviors of improvements and modifications in the case where not changing central scope principle of the present invention, in protection scope of the present invention
Within.
Claims (8)
1. a kind of comprehensive compensation construction of strategy method for automobile-used acceleration transducer constant error, which is characterized in that construction
The data pre-processing that side velocity observer is estimated as acceleration transducer constant error obtains the observation of vehicle side velocity
As a result, realizing the On-line Estimation of acceleration transducer constant error, Jin Ertong according to the result of observation and the state equation of fusion
Amendment of the construction tire normal pressure error compensation model realization to tire cornering stiffness is crossed, finally feeds back correction result to lateral
In speed observer, the compensation for completing acceleration transducer constant error updates.
2. the comprehensive compensation construction of strategy method according to claim 1 for automobile-used acceleration transducer constant error,
It is characterized in that, the state equation that the estimation of the constant error uses has merged vehicle kinematics model and acceleration transducer
Error model.
3. the comprehensive compensation construction of strategy method according to claim 2 for automobile-used acceleration transducer constant error,
It is characterized in that, the state equation are as follows:Wherein ax,mes、ay,mesFor acceleration sensing
The measurement of device exports, ax,bias、ay,biasFor acceleration transducer constant error, w1、w2、w3、w4Respectively white Gaussian noise, vxFor
The longitudinal velocity of vehicle, vyFor the side velocity of vehicle, r is the yaw velocity of vehicle.
4. the comprehensive compensation construction of strategy method according to claim 3 for automobile-used acceleration transducer constant error,
It is characterized in that, the state equation chooses measurementv'xFor the longitudinal velocity of driven wheel wheel speed sensors,For the observation of side velocity.
5. the comprehensive compensation construction of strategy method according to claim 1 for automobile-used acceleration transducer constant error,
It is characterized in that, the cornering stiffness CσThe normal pressure F being subject to four tireszBetween relationship are as follows: Cσ=a1 sin
[a2arctan(a3Fz)], wherein a1、a2、a3For to fitting parameter.
6. the comprehensive compensation construction of strategy method according to claim 5 for automobile-used acceleration transducer constant error,
It is characterized in that, the normal pressure is calculated according to the correction result of acceleration signal, the amendment knot of the acceleration signal
Fruit is determined by the constant error of acceleration transducer.
7. the comprehensive compensation construction of strategy method according to claim 6 for automobile-used acceleration transducer constant error,
It is characterized in that, the correction result of the acceleration signalMeet:Wherein ax,mes、ay,mes
It is exported for the measurement of acceleration transducer,For the optimal estimation value of acceleration transducer constant error.
8. the comprehensive compensation construction of strategy method according to claim 7 for automobile-used acceleration transducer constant error,
It is characterized in that, the error compensation model of the normal pressure are as follows:Wherein m is vehicle
Body quality, i={ F, R }, F indicate that front-wheel, R indicate rear-wheel；J={ L, R }, L indicate that revolver, R indicate right wheel；H is automobile
The vertical height of mass center from the ground, l=lf+lrThe distance between automobile antero posterior axis, bF、bRFor automobile front and rear wheel away from.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112950812A (en) * | 2021-02-04 | 2021-06-11 | 南京航空航天大学 | Vehicle state fault-tolerant estimation method based on long-time and short-time memory neural network |
| CN114684159A (en) * | 2022-03-21 | 2022-07-01 | 潍柴动力股份有限公司 | Vehicle mass estimation method and device, electronic equipment and storage medium |
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| CN108594652A (en) * | 2018-03-19 | 2018-09-28 | 江苏大学 | A kind of vehicle-state fusion method of estimation based on observer information iteration |
| CN109606378A (en) * | 2018-11-19 | 2019-04-12 | 江苏大学 | Vehicle running state estimation method towards non-Gaussian noise environment |
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| CN108594652A (en) * | 2018-03-19 | 2018-09-28 | 江苏大学 | A kind of vehicle-state fusion method of estimation based on observer information iteration |
| CN109606378A (en) * | 2018-11-19 | 2019-04-12 | 江苏大学 | Vehicle running state estimation method towards non-Gaussian noise environment |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112950812A (en) * | 2021-02-04 | 2021-06-11 | 南京航空航天大学 | Vehicle state fault-tolerant estimation method based on long-time and short-time memory neural network |
| CN112950812B (en) * | 2021-02-04 | 2022-07-26 | 南京航空航天大学 | Vehicle state fault-tolerant estimation method based on long-time and short-time memory neural network |
| CN114684159A (en) * | 2022-03-21 | 2022-07-01 | 潍柴动力股份有限公司 | Vehicle mass estimation method and device, electronic equipment and storage medium |
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