CN103213582A - Anti-rollover warning control method based on vehicle roll angle estimation - Google Patents

Anti-rollover warning control method based on vehicle roll angle estimation Download PDF

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CN103213582A
CN103213582A CN2013101354719A CN201310135471A CN103213582A CN 103213582 A CN103213582 A CN 103213582A CN 2013101354719 A CN2013101354719 A CN 2013101354719A CN 201310135471 A CN201310135471 A CN 201310135471A CN 103213582 A CN103213582 A CN 103213582A
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孙涛
和好
朱红全
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University of Shanghai for Science and Technology
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Abstract

The invention relates to an anti-rollover warning control method based on vehicle roll angle estimation. The method comprises the following specific steps of establishing a vehicle rollover model, adopting a Kalman filtering estimation algorithm, predicting state parameters of a real vehicle by using the vehicle rollover model, taking the running state of the vehicle at the current time as an initial value, calculating a rollover indicator LTR (Lateral-Load Transfer Ratio) of the model according to vehicle rollover rules in a manner of taking T5 as step length, and recording calculated step number N when the rollover indicator LTR meets rollover conditions for the first time, thereby obtaining vehicle rollover warning time N*T5. According to the anti-rollover warning control method based on the vehicle roll angle estimation, through a strategy that the size of the vehicle roll angle of a heavy-duty vehicle during traveling is accurately estimated in real time by using a classical Kalman filtering state estimation technique, a novel solution for a heavy-duty vehicle rollover warning algorithm is provided.

Description

Anti-rollover pre-warning and control method based on the vehicle roll angle estimation
Technical field
The present invention relates to a kind of preventing vehicle rollover pre-warning and control method, especially a kind of adopt estimate heavy-duty vehicle in the process of moving the size of vehicle roll angle come the anti-rollover pre-warning and control method.
Background technology
Heavy-duty vehicle has that centroid position height, complete vehicle quality and volume are big, wheel base is with respect to characteristics such as the car load height are narrow, and the stable threshold of therefore turning on one's side is less, and the rollover accident takes place easily.Generally speaking, when the rollover accident took place, chaufeur was difficult to the generation of the accident of perceiving.According to U.S.'s highway traffic safety administration (NHTSA) statistics, in the non-collision traffic accident, have 90% to cause, and the mortality that it causes has also reached 75% by vehicle side turning, in these rollover accidents, heavy-duty vehicle has nearly accounted for about 70%.The rollover of heavy-duty vehicle has become the major issue that influences safety traffic.Therefore, the driving safety of heavy-duty vehicle, the roll stability problem in especially travelling is the focus of vehicle active safety research all the time.
Vehicle rollover is meant that vehicle rotates 90 ° or bigger angle around its longitudinal axis in the process of moving, so that the contacted a kind of extremely dangerous sideway movement in vehicle body and ground.There is several factors may cause the rollover of vehicle, comprises vehicle structure, chaufeur and road conditions etc.Vehicle rollover can be divided into two big classes substantially, and a class is the rollover that curvilinear motion causes, another kind of is to trip rollover.When the former refers to that vehicle travels on road (comprising the side direction ramp),, make that the vertical reaction of vehicle interior side wheel is zero rollover that causes because the lateral acceleration of vehicle surpasses a threshold value; Produce lateral sliding when the latter is meant running car, it " is tripped " with obstacle lateral impact on the road surface.What the present invention studied is the non-heavy-duty vehicle rollover warning algorithm that trips under the type rollover situation.
In recent years, the roll stability of the rollover forewarn system application in the heavy-duty vehicle Stability Control raising greatly vehicle, and then effectively avoided the generation of heavy-duty vehicle rollover accident.But the problem that some key parameter is difficult to directly measure is not considered in these researchs in the vehicle ' process, thereby causes can not accurately obtaining as the dynamic gate limit value of the dangerous criterion of rollover.
Summary of the invention
The present invention proposes a kind of anti-rollover pre-warning and control method of estimating based on vehicle roll angle, promptly adopt classical Kalman filter state estimation technique accurately to estimate the heavy-duty vehicle size of vehicle roll angle in the process of moving in real time, and calculate the dynamic gate limit value of vehicle rollover early warning control thus.On this basis, design is based on rollover time (Time-To-Rollover, TTR) heavy-duty vehicle rollover warning algorithm, finally reach the purpose of heavy-duty vehicle rollover early warning, thisly estimate the heavy-duty vehicle strategy of the size of vehicle roll angle in the process of moving real-time and accurately, for heavy vehicle rollover warning algorithm provides a kind of new solution by classical Kalman filter state estimation technique.
Technical scheme of the present invention is: a kind of anti-rollover pre-warning and control method of estimating based on vehicle roll angle, concrete steps are: at first set up the vehicle rollover model, adopt Kalman Filtering Estimation algorithm, utilize the vehicle rollover model to predict the state parameter of real vehicles, running state with the vehicle current time is an initial value, according to the vehicle rollover rule with
Figure 234081DEST_PATH_IMAGE002
Be the rollover index LTR of step size computation model, when this rollover index LTR satisfies the rollover condition for the first time, write down the calculating step number
Figure 151222DEST_PATH_IMAGE004
, promptly can obtain the vehicle rollover pre-warning time and be
Figure 930959DEST_PATH_IMAGE006
The vehicle rollover model is according to dAlembert principle, sets up three equation of equilibriums:
(1) moment-equilibrium equation around the Z axle is:
（6）
(2) equilibrium equation along Y-axis is:
Figure 140541DEST_PATH_IMAGE010
（7）
(3) moment-equilibrium equation around X-axis is:
Figure 274588DEST_PATH_IMAGE012
（8）
Simultaneously, satisfy:
Figure 541621DEST_PATH_IMAGE014
（9）
（10）
Figure 409400DEST_PATH_IMAGE018
（11）
Meeting geometric relation under little tyre slip angle:
Figure 654961DEST_PATH_IMAGE020
（12）
Figure 409290DEST_PATH_IMAGE022
（13）
Figure 146302DEST_PATH_IMAGE024
（14）
In the formula,
Figure 669687DEST_PATH_IMAGE026
Be the rotor inertia of complete vehicle quality around the longitudinal axis of vehicle body barycenter;
Figure 161848DEST_PATH_IMAGE028
Be the rotor inertia of complete vehicle quality around roll axis;
Figure 403474DEST_PATH_IMAGE030
,
Figure 678597DEST_PATH_IMAGE032
Be respectively total cornering stiffness of forward and backward tire;
Figure 322068DEST_PATH_IMAGE034
Be suspension equivalence roll rate;
Figure 657235DEST_PATH_IMAGE036
Be suspension equivalence inclination damping coefficient.
Adopt Kalman Filtering Estimation algorithm to be to the vehicle state estimation step:
(1) the initial condition variable of setting vehicle rollover model is:
Figure 199206DEST_PATH_IMAGE038
Figure 278020DEST_PATH_IMAGE040
；
(2) setting Kalman Filtering Estimation device coefficient is:
Measure noise covariance R=1;
The procedure activation noise covariance
Figure 775998DEST_PATH_IMAGE042
(3) the Kalman Filtering Estimation device time more new portion be:
Figure 547644DEST_PATH_IMAGE044
；（1）
Figure 560600DEST_PATH_IMAGE046
；（2）
(4) Kalman Filtering Estimation device state updating section is:
Figure 443105DEST_PATH_IMAGE048
；（3）
Figure 795589DEST_PATH_IMAGE050
；（4）
Figure 738137DEST_PATH_IMAGE052
；（5）
In the formula,
Figure 176072DEST_PATH_IMAGE054
Be error covariance,
Figure 908273DEST_PATH_IMAGE056
Be the Kalman gain factor,
Figure 380843DEST_PATH_IMAGE058
Be state estimator, ,
Figure 419523DEST_PATH_IMAGE062
,
Figure 706148DEST_PATH_IMAGE064
,
Figure 767645DEST_PATH_IMAGE066
Be matrix of coefficient.
The concrete computing formula of calculating the rollover index LTR of auto model is:
Figure 51996DEST_PATH_IMAGE068
（16）
In the formula,
Figure 464523DEST_PATH_IMAGE070
Be the vehicle roll center height,
Figure 492522DEST_PATH_IMAGE072
Be car gage.
The invention has the beneficial effects as follows:
The present invention adopts classical Kalman filtering technique.The Kalman filter is with the method estimation procedure state of controlled reset: the state in a certain moment of filter estimation procedure, the mode with (containing noise) measurand obtains feedback then.Therefore the Kalman filter can be divided into two parts: time renewal equation and measurement renewal equation.The time renewal equation is responsible for calculating forward in real time the value of current state variable and error covariance estimation, so that be a prior estimate of next time state structure.Promptly adopt classical Kalman filter state estimation technique accurately to estimate the heavy-duty vehicle size of vehicle roll angle in the process of moving in real time, and calculate the dynamic gate limit value of vehicle rollover early warning control thus.On this basis, design is based on rollover time (Time-To-Rollover, TTR) heavy-duty vehicle rollover warning algorithm, finally reach the purpose of heavy-duty vehicle rollover early warning, thisly estimate the heavy-duty vehicle strategy of the size of vehicle roll angle in the process of moving real-time and accurately, for heavy vehicle rollover warning algorithm provides a kind of new solution by classical Kalman filter state estimation technique.
Description of drawings
Fig. 1 is Kalman Filtering Estimation algorithm principle figure;
Fig. 2 is a heavy-duty vehicle model scheme drawing;
Fig. 3 improves TTR rollover warning algorithm building-block of logic;
Fig. 4 is fish hook steering situation simulation result figure;
Wherein: (a) being time and steering wheel angle graph of a relation, (b) is time and angle of roll graph of a relation, (c) is time and LTR graph of a relation, (d) is time and TTR graph of a relation;
Fig. 5 is sinusoidal steering situation simulation result figure;
Wherein: (a) being time and steering wheel angle graph of a relation, (b) is time and angle of roll graph of a relation, (c) is time and LTR graph of a relation, (d) is time and TTR graph of a relation.
The specific embodiment
The invention will be further described below in conjunction with accompanying drawing and embodiment.
The anti-rollover pre-warning and control method of estimating based on vehicle roll angle of the present invention, concrete steps are: at first set up the vehicle rollover model, adopt Kalman Filtering Estimation algorithm, utilize the vehicle rollover model to predict the state parameter of real vehicles, running state with the vehicle current time is an initial value, according to the vehicle rollover rule with
Figure 487153DEST_PATH_IMAGE002
Be the rollover index LTR of step size computation model, when this rollover index LTR satisfies the rollover condition for the first time, write down the calculating step number , promptly can obtain the vehicle rollover pre-warning time and be
Figure 576649DEST_PATH_IMAGE006
Kalman Filtering Estimation algorithm principle of work as shown in Figure 1.
Concrete vehicle-state Kalman Filtering Estimation device design procedure is:
(5) the initial condition variable of vehicle rollover model is set at:
Figure 205077DEST_PATH_IMAGE038
Figure 506745DEST_PATH_IMAGE040
；
(6) Kalman Filtering Estimation device coefficient settings is:
Measure noise covariance R=1;
The procedure activation noise covariance
(7) the Kalman Filtering Estimation device time more new portion be:
Figure 254438DEST_PATH_IMAGE044
；（1）
Figure 938754DEST_PATH_IMAGE046
；（2）
(8) Kalman Filtering Estimation device state updating section is:
Figure DEST_PATH_IMAGE073
；（3）
Figure 829349DEST_PATH_IMAGE074
；（4）
Figure 626404DEST_PATH_IMAGE052
；（5）
In the formula,
Figure 235240DEST_PATH_IMAGE054
Be error covariance,
Figure 471049DEST_PATH_IMAGE056
Be the Kalman gain factor,
Figure 481731DEST_PATH_IMAGE058
Be state estimator,
Figure 449687DEST_PATH_IMAGE060
,
Figure 545819DEST_PATH_IMAGE062
,
Figure 70472DEST_PATH_IMAGE064
,
Figure 935660DEST_PATH_IMAGE066
Be matrix of coefficient.
The present invention adopts the linear auto model of three degree of freedom to design heavy-duty vehicle rollover forewarn system.As shown in Figure 2, the three degree of freedom of this linear model is respectively sideway movement, weaving and inclination campaign.Among the figure
Figure 74517DEST_PATH_IMAGE076
Be complete vehicle quality;
Figure 657945DEST_PATH_IMAGE078
Be the distance of barycenter to roll center;
Figure 907661DEST_PATH_IMAGE080
Be front wheel angle;
Figure 955251DEST_PATH_IMAGE082
Be angle of roll;
Figure 265010DEST_PATH_IMAGE084
Be yaw velocity;
Figure 335734DEST_PATH_IMAGE086
,
Figure 389141DEST_PATH_IMAGE088
Be respectively the front and rear wheel sideslip angle;
Figure 540505DEST_PATH_IMAGE090
Be side slip angle;
Figure 21165DEST_PATH_IMAGE092
,
Figure 313606DEST_PATH_IMAGE094
Be respectively barycenter to forward and backward wheelbase from;
Figure 170704DEST_PATH_IMAGE096
,
Figure 864990DEST_PATH_IMAGE098
Be respectively vertical, side velocity;
Figure 578869DEST_PATH_IMAGE100
,
Figure 624185DEST_PATH_IMAGE102
Be respectively the total side force of front and rear wheel; Be barycenter place lateral acceleration.Be simplified model, do following hypothesis:
(1) ignore the steering system influence, model is imported with front wheel steering angle.
(2) do not consider the luffing of vehicle.
(3) ignore the effect of air resistance.
(4) suppose that vehicle travels at level road, ignore the catenary motion of vehicle.
(5) longitudinal velocity of supposing vehicle barycenter place is a constant.
(6) ignore the variation of the tire characteristics that the left and right tire of vehicle causes owing to the variation of load and the effect of tyre moment.
(7) ignore the non-linear effects of tire and suspension, simplifying suspension rate and damping is equivalent roll rate and equivalent inclination damping.
(8) nonspring carried mass is less for spring carried mass.
(9) spring carried mass is very little around the product of inertia of X, Z axle, does not consider.
Heavy-duty vehicle model thus, according to dAlembert principle, can list following three equation of equilibriums:
(4) moment-equilibrium equation around the Z axle is:
（6）
(5) equilibrium equation along Y-axis is:
Figure DEST_PATH_IMAGE105
（7）
(6) moment-equilibrium equation around X-axis is:
（8）
Simultaneously, satisfy:
Figure 469278DEST_PATH_IMAGE014
（9）
（10）
Figure 935212DEST_PATH_IMAGE018
（11）
Meeting geometric relation under little tyre slip angle:
Figure DEST_PATH_IMAGE107
（12）
Figure 400828DEST_PATH_IMAGE022
（13）
Figure 659771DEST_PATH_IMAGE024
（14）
In the formula, Be the rotor inertia of complete vehicle quality around the longitudinal axis of vehicle body barycenter; Be the rotor inertia of complete vehicle quality around roll axis;
Figure DEST_PATH_IMAGE110
,
Figure DEST_PATH_IMAGE111
Be respectively total cornering stiffness of forward and backward tire;
Figure 728615DEST_PATH_IMAGE034
Be suspension equivalence roll rate; Be suspension equivalence inclination damping coefficient.
TTR rollover warning algorithm based on the vehicle roll angle estimation.Concrete algorithm is as follows: at first select the vehicle dynamic transverse load rate of transform (Lateral-load transfer rate, LTR) the early warning threshold value of the dangerous criterion of conduct rollover.Such threshold value is selected to make warning algorithm have universality more; Secondly, for the dynamic early warning threshold value of accurate more acquisition, in the rollover warning algorithm, use parameter estimator based on Kalman Filter Technology.
On the traditional sense, lateral direction of car load transfer rate (LTR) can be defined as the ratio of the difference and the vertical load sum of the vertical load on the wheel of vehicle both sides, that is:
（15）
When left and right sides tyre load equated, the value of LTR was 0; When rollover danger takes place when, the single wheel built on stilts, this moment, the absolute value of LTR was 1, promptly for different vehicles and different driving conditions, rollover early warning threshold value can be defined as certain value, and for guaranteeing the driving safety of vehicle, this paper is made as 0.9 with dynamic transverse load rate of transform early warning threshold value.
Because vehicle left and right wheels vertical load in the process of moving constantly changes and is difficult for directly measuring, so be difficult to directly calculate according to definition the value of dynamic LTR.This paper chooses the algorithm that a cover calculates transverse load rate of transform LTR in real time, and concrete computing formula is:
Figure 527943DEST_PATH_IMAGE068
（16）
In the formula,
Figure 51329DEST_PATH_IMAGE070
Be the vehicle roll center height,
Figure 481173DEST_PATH_IMAGE072
Be car gage.So, seek out the accurate dynamically transverse load rate of transform, must at first obtain these two quantity of states of vehicle lateral acceleration and actual angle of roll.The vehicle lateral acceleration can directly be measured by sensor, and the actual angle of roll of vehicle is difficult to directly obtain by onboard sensor, needs by kalman Filtering Estimation technology it to be carried out real-time estimation.
Based on the TTR rollover warning algorithm logical organization of kalman filtered side inclination angle estimation, as shown in Figure 3.Algorithm is based on the state parameter that reference model is predicted real vehicles, and the vehicle rollover model that utilizes the front to set up is an initial value with the running state of vehicle current time, according to the vehicle rollover rule with
Figure DEST_PATH_IMAGE115
Rollover index LTR for the step size computation model.When satisfying the rollover condition for the first time, this index writes down the calculating step number
Figure DEST_PATH_IMAGE116
, promptly can obtain the vehicle rollover pre-warning time and be
Figure 270268DEST_PATH_IMAGE006
In the rollover forewarn system, for reducing computational effort, default usually TTR rollover early warning threshold value is X second.Index LTR does not satisfy the rollover condition if X turned on one's side in second, and vehicle can not turned on one's side in promptly following X time second, thinks that then vehicle is in a safe condition, and stops the calculating in this cycle.It is 3 seconds that this paper sets TTR threshold value X.
The early warning process is a countdown process, and the value of TTR is more little, and then that the risk of rollover takes place is big more for vehicle, and the value of TTR is 0 o'clock, illustrates that vehicle turns on one's side.
Application example:
Under the Matlab/Simuink environment, set up the heavy-duty vehicle rollover warning algorithm of estimating based on angle of roll, and utilize Trucksim software that the rollover algorithm is carried out simulating, verifying.When initially the speed of a motor vehicle is for 50km/h, carry out the fish hook diversion experiments, when initially the speed of a motor vehicle is for 70km/h, carry out sinusoidal input redirect experiment, simulation result such as Fig. 4, shown in Figure 5 of rollover warning algorithm.

Claims (4)

1. anti-rollover pre-warning and control method of estimating based on vehicle roll angle, it is characterized in that, concrete steps are: at first set up the vehicle rollover model, adopt Kalman Filtering Estimation algorithm, utilize the vehicle rollover model to predict the state parameter of real vehicles, running state with the vehicle current time is an initial value, according to the vehicle rollover rule with Be the rollover index (LTR) of step size computation model, when this rollover index (LTR) satisfies the rollover condition, write down the calculating step number for the first time , promptly can obtain the vehicle rollover pre-warning time and be
2. the anti-rollover pre-warning and control method of estimating based on vehicle roll angle according to claim 1, it is characterized in that: described vehicle rollover model is according to dAlembert principle, sets up three equation of equilibriums:
Moment-equilibrium equation around the Z axle is:
Figure 2013101354719100001DEST_PATH_IMAGE007
（6）
Equilibrium equation along Y-axis is:
Figure DEST_PATH_IMAGE009
（7）
Moment-equilibrium equation around X-axis is:
Figure DEST_PATH_IMAGE011
（8）
Simultaneously, satisfy:
Figure DEST_PATH_IMAGE013
（9）
Figure DEST_PATH_IMAGE015
（10）
Figure DEST_PATH_IMAGE017
（11）
Meeting geometric relation under little tyre slip angle:
Figure DEST_PATH_IMAGE019
（12）
Figure DEST_PATH_IMAGE021
（13）
Figure DEST_PATH_IMAGE023
（14）
In the formula, Be the rotor inertia of complete vehicle quality around the longitudinal axis of vehicle body barycenter;
Figure DEST_PATH_IMAGE027
Be the rotor inertia of complete vehicle quality around roll axis;
Figure DEST_PATH_IMAGE029
, Be respectively total cornering stiffness of forward and backward tire;
Figure DEST_PATH_IMAGE033
Be suspension equivalence roll rate;
Figure DEST_PATH_IMAGE035
Be suspension equivalence inclination damping coefficient.
3. the anti-rollover pre-warning and control method of estimating based on vehicle roll angle according to claim 1, it is characterized in that: described employing Kalman Filtering Estimation algorithm to the vehicle state estimation step is:
The initial condition variable of setting the vehicle rollover model is:
Figure DEST_PATH_IMAGE037
Figure DEST_PATH_IMAGE039
；
Setting Kalman Filtering Estimation device coefficient is:
Measure noise covariance R=1;
The procedure activation noise covariance
Figure DEST_PATH_IMAGE041
The Kalman Filtering Estimation device time more new portion be:
Figure DEST_PATH_IMAGE043
；（1）
Figure DEST_PATH_IMAGE045
；（2）
Kalman Filtering Estimation device state updating section is:
Figure DEST_PATH_IMAGE047
；（3）
Figure DEST_PATH_IMAGE049
；（4）
；（5）
In the formula, Be error covariance,
Figure DEST_PATH_IMAGE055
Be the Kalman gain factor,
Figure DEST_PATH_IMAGE057
Be state estimator,
Figure DEST_PATH_IMAGE059
,
Figure DEST_PATH_IMAGE061
,
Figure DEST_PATH_IMAGE063
,
Figure DEST_PATH_IMAGE065
Be matrix of coefficient.
4. the anti-rollover pre-warning and control method of estimating based on vehicle roll angle according to claim 1, it is characterized in that: the concrete computing formula of the rollover index (LTR) of described calculating auto model is:
（16）
In the formula,
Figure DEST_PATH_IMAGE069
Be the vehicle roll center height,
Figure DEST_PATH_IMAGE071
Be car gage.
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