CN110626353B - Vehicle dangerous state early warning method based on roll risk index - Google Patents

Vehicle dangerous state early warning method based on roll risk index Download PDF

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CN110626353B
CN110626353B CN201910846340.9A CN201910846340A CN110626353B CN 110626353 B CN110626353 B CN 110626353B CN 201910846340 A CN201910846340 A CN 201910846340A CN 110626353 B CN110626353 B CN 110626353B
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roll
vehicle
center
height
error
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CN110626353A (en
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贺宜
杨鑫炜
吴超仲
孙昌鑫
杨硕
李泽
陶妍
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Wuhan University of Technology WUT
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/02—Control of vehicle driving stability
    • B60W30/04—Control of vehicle driving stability related to roll-over prevention
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/02—Control of vehicle driving stability
    • B60W30/04—Control of vehicle driving stability related to roll-over prevention
    • B60W2030/043—Control of vehicle driving stability related to roll-over prevention about the roll axis
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • B60W2050/146—Display means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/109—Lateral acceleration

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Abstract

The invention discloses a vehicle dangerous state early warning method based on a roll risk index, which comprises the following steps: establishing a moment balance equation and a vertical direction dynamic model of a vehicle roll center, and providing a roll risk index of a ratio of the difference of vertical loads of vehicle tires and the sum of the vertical loads; establishing a vehicle state parameter error identification model related to the change of the vehicle roll height, the roll center moment of inertia, the equivalent roll stiffness of the suspension and the equivalent damping coefficient of the suspension; calculating real-time roll height, roll center moment of inertia, suspension equivalent roll stiffness and suspension equivalent damping coefficient change through a minimum recursion quadratic multiple algorithm; establishing an improved roll index model based on real-time correction of roll height; and establishing vehicle roll risk early warning based on a reasonable RI threshold. The invention effectively warns the driver that the vehicle has the risk of side turning and improves the driving safety.

Description

Vehicle dangerous state early warning method based on roll risk index
Technical Field
The invention belongs to the technical field of intelligent driving of automobiles, and particularly relates to a vehicle dangerous state early warning method based on a roll risk index.
Background
At present, vehicle rollover accidents frequently occur, although the proportion of the vehicle rollover accidents in the total number of all accidents is small, once the accidents occur, serious casualties and property loss can be caused, according to investigation, the vehicle rollover accidents account for 3% of the total accident rate, but the accident death rate is 33%. According to the NHTSA report in the United states, the number of vehicle rollover accidents and deaths in the United states showed an increasing trend year by year during the year 2013 and 2016. The driver is difficult to perceive the vehicle instability and the vehicle rollover accident possibly under the emergency operation condition. Therefore, active monitoring and early warning research on the vehicle rollover accident is necessary, so that the vehicle rollover accident rate is reduced. The vehicle roll early warning research is mainly focused on the aspects of vehicle roll static indexes, vehicle roll time estimation, curve dangerous vehicle speed and the like. At present, the roll index analysis covering a plurality of vehicle dynamic parameters and structural parameters is lacked, and the roll index can be more accurate only by comprehensively considering parameters such as a vehicle roll angle, a vehicle roll angle rate, a lateral acceleration, a roll height change and the like, so that the risk early warning precision is further reduced, a driver is given more accurate early warning, and the vehicle rollover accident rate is reduced.
The existing vehicle roll risk early warning, such as application number CN201710429872.3, is a vehicle rollover index prediction method based on gravity center height on-line estimation, and a relevant gravity center height identification model is mainly obtained through an adaptive filtering theory, wherein data needs to be updated through a large amount of adaptive learning, the calculation amount is large, the requirement on hardware is high, and the problem of time lag exists. For example, the application number CN201710363190.7, the rollover prevention early warning control system and method for the liquid tank truck in curve running only consider the critical rollover speed of the vehicle, and when the common influence of parameters such as the lateral acceleration, the roll angle and the like of the vehicle is neglected, the index precision is low. For example, application number CN201410128767.2, a driver interactive commercial vehicle rollover warning method and system judge the rollover tendency of the vehicle in the future in the curve by inquiring a MAP table when the vehicle enters the curve, only consider the vehicle speed problem, and ignore other status parameters with larger influence completely.
The prior patent shows that the prior vehicle rollover early warning method mainly considers the limitations of the vehicle speed, the height of the center of gravity of the vehicle and the like on one side, neglects the influence of structural parameters and state parameters of a plurality of vehicles, and greatly reduces the early warning precision. Therefore, the influence of various parameters is considered comprehensively, and the risk early warning can be provided for the driver more effectively.
Disclosure of Invention
The invention mainly solves the problems that: how to build a vehicle roll risk estimation index and comprehensively consider dynamic estimation of vehicle roll parameters to improve the accuracy of the roll risk estimation index, and finally, a vehicle danger state early warning system based on the roll risk index is built according to the improved roll risk estimation index.
The invention provides a roll risk index based on vehicle roll parameter estimation, which establishes a vehicle roll risk model through a vehicle dynamic model, an error identification model and a minimum recursive two-times parameter estimation algorithm, and provides real-time and accurate danger early warning for a vehicle.
The invention solves the technical problem and adopts a scheme that a vehicle dangerous state early warning method based on a roll risk index is characterized by comprising the following steps:
step 1: the method comprises the steps of establishing a moment balance model of the vehicle in the roll direction of the sprung and unsprung roll centers, calculating the vertical load difference of the left wheel and the right wheel of the whole vehicle, establishing a dynamic model of the vehicle in the vertical direction of the sprung mass center, calculating the vertical load sum of the wheels at the two sides of the vehicle, and calculating a roll risk index according to the vertical load difference of the left wheel and the right wheel and the vertical load sum of the wheels at the two sides of the vehicle;
step 2: the method comprises the steps that a vehicle transverse acceleration is combined with a roll direction moment balance model of a vehicle roll center to respectively obtain a roll angle, a roll angle rate and a roll angle acceleration of a fixed roll center, and a vehicle state parameter error identification model is established further in combination with the actually measured roll angle, roll angle rate and roll angle acceleration;
and step 3: calculating the real-time change conditions of the vehicle roll height, the roll center moment of inertia, the suspension equivalent roll stiffness and the suspension equivalent damping coefficient through a minimum recursive quadratic model so as to obtain the roll height error, the roll center moment of inertia error, the suspension equivalent roll stiffness error and the suspension equivalent damping coefficient error of the vehicle;
and 4, step 4: the method comprises the steps of measuring lateral acceleration, a roll angle rate and a roll angle acceleration through a sensor, correcting roll height, a suspension equivalent damping coefficient, a suspension equivalent roll stiffness and a roll center rotational inertia in real time, and establishing a roll risk index model based on the roll height corrected in real time;
and 5: and calibrating a roll risk threshold value through a roll risk index model based on real-time correction parameters, and judging whether rollover risks occur or not according to the roll risk threshold value.
Preferably, the step 1 of establishing a roll direction moment balance model of the roll center of the vehicle is as follows:
step 1.1, establishing a vehicle dynamic model of vehicle rolling along the y axis, and assuming that a vehicle tire model is not considered, a rolling direction moment balance model of a vehicle rolling center is as follows:
Figure GDA0002538553170000031
wherein m issIs the sprung mass of the vehicle, hsThe distance from the center of the sprung mass to the center of roll, i.e., the roll height, g is the gravitational acceleration g, theta is the road surface transverse slope angle, kφFor suspension equivalent roll stiffness, cφFor the suspension equivalent roll damping coefficient, Ixx_oMoment of inertia at roll center: (
Figure GDA0002538553170000032
IxxMoment of inertia of center of mass on spring), ayIs the lateral acceleration, phi is the roll angle,
Figure GDA0002538553170000033
in order to be the roll angle rate,
Figure GDA0002538553170000034
is the roll angular acceleration;
step 1.2, when the center of mass under the spring of the vehicle is taken as the moment center, the moment balance equation of the roll center is as follows:
Figure GDA0002538553170000035
wherein, FzrFor vertical loading of the right wheel of the vehicle, FzlVertical load of left wheel of vehicle, T wheel track, hRAs vehiclesHeight of center of roll from ground, huIs the height of the center of mass under the spring from the ground, Ixx_uIs unsprung mass center moment of inertia, Fy＝may-mgsinθ，m＝ms+mu；
Step 1.3, if the roll angle is smaller, cos phi is approximately equal to 1, sin phi is approximately equal to phi, and the vertical load difference expression of the left wheel and the right wheel can be obtained through the moment balance equation:
Figure GDA0002538553170000036
step 1.4, the height H of the mass center of the whole vehicle can be expressed as:
Figure GDA0002538553170000037
thus, the vertical load difference expression for the left and right wheels of the vehicle of step 1.3:
Figure GDA0002538553170000038
the dynamic model of the vehicle on-spring center of mass in the vertical direction in the step 1 is as follows:
establishing a stress balance equation of the vehicle sprung mass in the z-axis direction:
Figure GDA0002538553170000039
wherein the content of the first and second substances,
Figure GDA00025385531700000310
the sum of the vertical loads of the wheels at two sides of the vehicle can be obtained:
Figure GDA00025385531700000311
wherein the content of the first and second substances,
Figure GDA0002538553170000041
is the vertical acceleration of the sprung mass centre along the z-axis;
the roll risk indicators in step 1 are:
suppose that
Figure GDA0002538553170000042
The term is smaller and approaches to zero, and the ratio is calculated by the difference of the vertical loads of the vehicle tires and the sum of the vertical loads, so that the improved vehicle roll risk index can be obtained:
Figure GDA0002538553170000043
preferably, the vehicle lateral acceleration in step 2 is ayAcquiring through a vehicle transverse acceleration sensor;
step 1 roll direction moment balance model of vehicle roll center by ayThe roll angle of the fixed roll center can be calculated separately for known inputs as phioThe roll angle rate of the fixed roll center is
Figure GDA0002538553170000044
The roll angular acceleration of the fixed roll center is
Figure GDA0002538553170000045
The roll angle measured by the roll angle sensor of the mass center of the real vehicle is phimThe rate of roll angle measured by the gyroscope is
Figure GDA0002538553170000046
The roll angular acceleration measured by the roll angular acceleration sensor is
Figure GDA0002538553170000047
Carrying out comprehensive calculation and establishing a vehicle state parameter error identification model;
the vehicle state parameter error identification model in the step 2 is as follows:
step 2.1, measuring the lateral acceleration a by a vehicle lateral acceleration sensoryAnd the rolling moment model with fixed rolling center of the vehicle is substituted to calculate and obtain the on-side of the vehicleVehicle roll angle phi with fixed roll centeroRoll rate
Figure GDA0002538553170000048
Acceleration of roll angle
Figure GDA0002538553170000049
At the moment, certain errors exist between the calculated vehicle state parameters and the actual measured values, so that an error identification model needs to be established;
the roll moment balance equation for the initial position of the vehicle is:
Figure GDA00025385531700000410
wherein
Figure GDA00025385531700000411
A vehicle roll height for fixing a roll center,
Figure GDA00025385531700000412
The equivalent roll stiffness of the suspension for fixing the roll center,
Figure GDA00025385531700000413
The equivalent roll damping coefficient of the suspension for fixing the roll center,
Figure GDA00025385531700000414
Roll center moment of inertia, which is a fixed roll center. Phi is aoA vehicle roll angle at which a roll center is fixed,
Figure GDA00025385531700000415
The roll angular velocity of the fixed roll center,
Figure GDA00025385531700000416
Roll angular acceleration being a fixed roll center;
step 2.2, because the roll height of the actual vehicle is changed, similarly, the roll moment balance equation of the vehicle is as follows:
Figure GDA0002538553170000051
in the same way, in the formula,
Figure GDA0002538553170000052
is the side-tipping height of the real vehicle,
Figure GDA0002538553170000053
The equivalent roll stiffness of the suspension of the real vehicle,
Figure GDA0002538553170000054
The equivalent roll damping coefficient of the suspension of the real vehicle,
Figure GDA0002538553170000055
The roll center moment of inertia of the real vehicle. Phi is amThe measured roll angle of the real vehicle,
Figure GDA0002538553170000056
The measured roll angle speed of the real vehicle,
Figure GDA0002538553170000057
Measured roll angular acceleration for a real vehicle;
step 2.3, at the same transverse acceleration ayAnd then, utilizing the vehicle roll model to identify the vehicle roll height in real time, and defining the parameter increment between the two models as follows:
Figure GDA0002538553170000058
Figure GDA0002538553170000059
Figure GDA00025385531700000510
Figure GDA00025385531700000512
wherein,. DELTA.hsRoll height error, Δ I, for real and vehicle modelsxxIs the roll center moment of inertia error, Δ kφIs the suspension equivalent roll stiffness error, Δ cφIs the equivalent damping coefficient error of the suspension, delta hcg,sAnd Δ hRRespectively the height error of the center of mass on the spring and the height error of the center of lateral inclination;
subtracting the real vehicle dynamic roll equation and the roll model with the fixed roll height, and then establishing a parameter increment model in a simultaneous manner to obtain an expression of a vehicle parameter error identification model:
Figure GDA00025385531700000511
preferably, the step 3 of establishing a minimum recursive two-times model to estimate the real-time changes of the roll height, the roll center moment of inertia, the suspension equivalent roll stiffness and the suspension equivalent damping coefficient of the vehicle;
the minimum recursive quadratic model is:
Y(t)＝XT(t)θ(t)+η(t)
wherein:
Figure GDA0002538553170000061
Figure GDA0002538553170000062
θ(t)＝[Δhcg,sΔhRΔIxx_oΔcφΔkφ]T
wherein Y (t) is a known output, X (t) is a regression vector, η (t) is system noise, θ (t) is a parameter vector to be estimated, Δ hsIs the roll height error of the vehicle, Delta Ixx_oError of moment of inertia of roll center, Δ kφFor suspension equivalent roll stiffness error, Δ cφTo hang inFrame equivalent damping coefficient error;
by adopting the RLS algorithm to pre-estimate the parameters of the error identification model, the unknown disturbance can be effectively estimated and compensated, so that the parameter identification precision and the robust characteristic are improved;
the algorithm is as follows:
Figure GDA0002538553170000063
P(t)＝P(t-1)-P(t-1)X(t)[I+XT(t)P(t-1)X(t)]-1XT(t)P(t-1)
Figure GDA0002538553170000064
in the formula (I), the compound is shown in the specification,
Figure GDA0002538553170000065
is the parameter vector to be estimated, P (t) is the covariance matrix,
Figure GDA0002538553170000066
Is the perturbation value, Q (z) is the filter;
preferably, in step 4, the roll risk indicator based on the real-time corrected roll height is:
step 4.1, the known Y (t), X (t), η (t) can calculate the estimated parameter vector theta (t) to calculate the rolling height error of the vehicle as delta hsThe error of the rotational inertia of the roll center is delta Ixx_oThe equivalent roll stiffness error of the suspension is delta kφThe equivalent damping coefficient error of the suspension is Delta cφOn the basis of which the corrected roll height of the vehicle can be obtained
Figure GDA0002538553170000067
Correcting height of center of mass on spring
Figure GDA0002538553170000068
Correcting height of center of mass under spring
Figure GDA0002538553170000069
Correcting the height of the mass center of the whole vehicle
Figure GDA00025385531700000610
Modified suspension equivalent damping coefficient
Figure GDA00025385531700000611
Correcting suspension equivalent roll stiffness
Figure GDA00025385531700000612
And correcting roll center moment of inertia
Figure GDA00025385531700000613
Step 4.2, the roll risk index based on the real-time corrected roll height and the whole vehicle mass center height is based on the improved vehicle roll risk index:
Figure GDA0002538553170000071
preferably, the roll risk threshold value is set to | RI in step 5TH|＝0.8；
The method for judging whether the rollover danger occurs or not in the step 5 comprises the following steps:
when RI < 0.8, the vehicle is in a safe state;
when RI is more than or equal to 0.8, the vehicle is about to be in a rollover dangerous state;
a vehicle risk condition warning system for roll risk indicator based vehicle, comprising:
the device comprises a vehicle mass center side inclination angle sensor, a transverse acceleration sensor, a gyroscope, a side inclination angle acceleration sensor, a microprocessor, a display screen early warning module, a steering wheel motor driving module, a steering wheel motor and an eccentric rotating block;
the microprocessor is respectively connected with the vehicle mass center side inclination angle sensor, the transverse acceleration sensor, the gyroscope and the side inclination angle acceleration sensor in sequence through leads; the microprocessor is respectively connected with the display screen early warning module and the steering wheel motor driving module in sequence through leads; the steering wheel motor driving module, the steering wheel motor and the eccentric rotating block are sequentially connected in series through a lead.
The invention has the advantages that: the vehicle roll index based on the vehicle dynamics model is set up, the dynamic response of the vehicle state parameters and the inherent parameters is comprehensively considered, the rollover risk detection precision of the vehicle under the over-bending control can be improved, unnecessary error early warning can be avoided, the driver or a control mechanism can be given more advanced response time, and accurate risk avoiding response can be made. The vehicle dangerous state early warning system based on the roll risk index is simple in structure, can effectively warn a driver that the vehicle has a roll-over risk, and avoids violent driving.
Drawings
FIG. 1: the invention provides a schematic diagram of a vehicle roll dynamics model;
FIG. 2: a diagram of a roll risk early warning system proposed by the present invention;
FIG. 3: the invention provides a flow chart of a roll risk early warning method.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A vehicle dangerous state early warning system and method based on a roll risk index are disclosed, wherein FIG. 1 is a vehicle roll dynamic model schematic diagram, which shows that the change of the roll center height during the roll of a vehicle is shown when the vehicle is over-bent, relevant parameters are labeled, and the vehicle dynamic model can be briefly described. Fig. 2 is a schematic diagram of the system structure of the present invention.
A vehicle risk state early warning system based on a roll risk indicator, as shown in fig. 3, includes:
the device comprises a vehicle mass center side inclination angle sensor, a transverse acceleration sensor, a gyroscope, a side inclination angle acceleration sensor, a microprocessor, a display screen early warning module, a steering wheel motor driving module, a steering wheel motor and an eccentric rotating block;
the microprocessor is respectively connected with the vehicle mass center side inclination angle sensor, the transverse acceleration sensor, the gyroscope and the side inclination angle acceleration sensor in sequence through leads; the microprocessor is respectively connected with the display screen early warning module and the steering wheel motor driving module in sequence through leads; the steering wheel motor driving module, the steering wheel motor and the eccentric rotating block are sequentially connected in series through a lead; the eccentric rotating block is contacted with the rim of the steering wheel.
The vehicle mass center roll angle sensor is selected to be ACT926T and is used for measuring the real-time mass center roll angle of the vehicle;
the transverse acceleration sensor is AD100-3X in type and is used for measuring the real-time transverse acceleration of the vehicle;
the gyroscope is selected to be PA-LAMI and used for measuring the real-time centroid roll angle rate of the vehicle;
the roll angle acceleration sensor is 7302BM5 in model selection and is used for measuring the real-time centroid roll angle acceleration of the vehicle;
the microprocessor is selected as follows: the STM32F042F6P6 is used for calculating the real-time roll height, roll center moment of inertia, suspension equivalent roll stiffness and suspension equivalent damping coefficient correction values of the vehicle and RI values based on the correction parameters; judging whether the RI value exceeds a threshold value or not to determine the working modes of the display screen early warning module and the steering wheel motor driving module;
the display screen early warning module is selected as follows: HX078401G06 for displaying the current roll state of the vehicle;
the steering wheel motor driving module is selected from TMCM-1160 and is used for driving a steering wheel motor;
the steering wheel motor is selected to be OT-CM1013 and used for driving the eccentric rotating block;
the eccentric rotating block is 100752904K2 in a selected type and is used for generating slight vibration by rotation;
the following describes a vehicle dangerous state early warning method based on a roll risk indicator with reference to fig. 1 to 3, and specifically includes the following steps:
step 1: establishing a roll direction moment balance model of a roll center of the vehicle for calculating a vertical load difference F of left and right wheels of the whole vehiclezr-FzlEstablishing a vertical direction dynamic model of the mass center on the spring of the vehicle, and calculating the vertical load sum F of the wheels at two sides of the vehiclezr+FzlAnd calculating the roll risk index RI through the vertical load difference of the left wheel and the right wheel and the vertical load sum of the wheels on the two sides of the vehicle.
Establishing a roll direction moment balance model of vehicle sprung and unsprung roll centers in the step 1:
step 1.1, establishing a vehicle dynamic model of vehicle rolling along the y axis, and assuming that a vehicle tire model is not considered, a rolling direction moment balance model of a vehicle rolling center is as follows:
Figure GDA0002538553170000091
wherein m issIs the sprung mass of the vehicle, hsThe distance from the center of the sprung mass to the center of roll, i.e., the roll height, g is the gravitational acceleration g, theta is the road surface transverse slope angle, kφFor suspension equivalent roll stiffness, cφFor the suspension equivalent roll damping coefficient, Ixx_oMoment of inertia at roll center: (
Figure GDA0002538553170000092
IxxMoment of inertia of center of mass on spring), ayIs the lateral acceleration, phi is the roll angle,
Figure GDA0002538553170000093
in order to be the roll angle rate,
Figure GDA0002538553170000094
is the roll angular acceleration;
step 1.2, when the center of mass under the spring of the vehicle is taken as the moment center, the moment balance equation of the roll center is as follows:
Figure GDA0002538553170000095
wherein, FzrFor vertical loading of the right wheel of the vehicle, FzlVertical load of left wheel of vehicle, T wheel track, hRHeight h from the center of vehicle roll to the grounduIs the height of the center of mass under the spring from the ground, Ixx_uIs unsprung mass center moment of inertia, Fy＝may-mgsinθ，m＝ms+mu；
Step 1.3, if the roll angle is smaller, cos phi is approximately equal to 1, sin phi is approximately equal to phi, and the vertical load difference expression of the left wheel and the right wheel can be obtained through the moment balance equation:
Figure GDA0002538553170000096
step 1.4, the height H of the mass center of the whole vehicle can be expressed as:
Figure GDA0002538553170000097
thus, the vertical load difference expression for the left and right wheels of the vehicle of step 1.3:
Figure GDA0002538553170000098
the dynamic model of the vehicle on-spring center of mass in the vertical direction in the step 1 is as follows:
establishing a stress balance equation of the vehicle sprung mass in the z-axis direction:
Figure GDA0002538553170000101
wherein the content of the first and second substances,
Figure GDA0002538553170000102
the sum of the vertical loads of the wheels at two sides of the vehicle can be obtained:
Figure GDA0002538553170000103
wherein the content of the first and second substances,
Figure GDA0002538553170000104
is the vertical acceleration of the sprung mass centre along the z-axis;
the roll risk indicators in step 1 are:
suppose that
Figure GDA0002538553170000105
The term is smaller and approaches to zero, and the ratio is calculated by the difference of the vertical loads of the vehicle tires and the sum of the vertical loads, so that the improved vehicle roll risk index can be obtained:
Figure GDA0002538553170000106
step 2: the method comprises the steps that a vehicle transverse acceleration is combined with a roll direction moment balance model of a vehicle roll center to respectively obtain a roll angle, a roll angle rate and a roll angle acceleration of a fixed roll center, and a vehicle state parameter error identification model is established further in combination with the actually measured roll angle, roll angle rate and roll angle acceleration;
the vehicle state parameter error identification model in the step 2 is as follows:
in step 2, the lateral acceleration of the vehicle is ayAcquiring through a vehicle transverse acceleration sensor;
step 2.1, ayThe roll moment model with the fixed roll center of the vehicle, which is substituted into the step 1, calculates the roll angle phi of the vehicle under the condition that the roll center of the vehicle is fixedoRoll rate
Figure GDA0002538553170000107
Acceleration of roll angle
Figure GDA0002538553170000108
The roll angle measured by the roll angle sensor of the mass center of the real vehicle is phimThe rate of roll angle measured by the gyroscope is
Figure GDA0002538553170000109
The roll angular acceleration measured by the roll angular acceleration sensor is
Figure GDA00025385531700001010
Carrying out comprehensive calculation and establishing a vehicle state parameter error identification model;
at the moment, certain errors exist between the calculated vehicle state parameters and the actual measured values, so that an error identification model needs to be established;
the roll moment balance equation for the initial position of the vehicle is:
Figure GDA0002538553170000111
wherein
Figure GDA0002538553170000112
A vehicle roll height for fixing a roll center,
Figure GDA0002538553170000113
The equivalent roll stiffness of the suspension for fixing the roll center,
Figure GDA0002538553170000114
The equivalent roll damping coefficient of the suspension for fixing the roll center,
Figure GDA0002538553170000115
Roll center moment of inertia, which is a fixed roll center. Phi is aoA vehicle roll angle at which a roll center is fixed,
Figure GDA0002538553170000116
The roll angular velocity of the fixed roll center,
Figure GDA0002538553170000117
Roll angular acceleration being a fixed roll center;
step 2.2, because the roll height of the actual vehicle is changed, similarly, the roll moment balance equation of the vehicle is as follows:
Figure GDA0002538553170000118
in the same way, in the formula,
Figure GDA0002538553170000119
is the side-tipping height of the real vehicle,
Figure GDA00025385531700001110
The equivalent roll stiffness of the suspension of the real vehicle,
Figure GDA00025385531700001111
The equivalent roll damping coefficient of the suspension of the real vehicle,
Figure GDA00025385531700001112
The roll center moment of inertia of the real vehicle. Phi is amThe measured roll angle of the real vehicle,
Figure GDA00025385531700001113
The measured roll angle speed of the real vehicle,
Figure GDA00025385531700001114
Measured roll angular acceleration for a real vehicle;
step 2.3, at the same transverse acceleration ayAnd then, utilizing the vehicle roll model to identify the vehicle roll height in real time, and defining the parameter increment between the two models as follows:
Figure GDA00025385531700001115
Figure GDA00025385531700001116
Figure GDA00025385531700001117
Figure GDA00025385531700001118
wherein,. DELTA.hsRoll height error, Δ I, for real and vehicle modelsxxIs the roll center moment of inertia error, Δ kφIs the suspension equivalent roll stiffness error, Δ cφIs the equivalent damping coefficient error of the suspension, delta hcg,sAnd Δ hRRespectively the height error of the center of mass on the spring and the height error of the center of lateral inclination;
subtracting the real vehicle dynamic roll equation and the roll model with the fixed roll height, and then establishing a parameter increment model in a simultaneous manner to obtain an expression of a vehicle parameter error identification model:
Figure GDA00025385531700001119
and step 3: calculating the real-time change conditions of the vehicle roll height, the roll center moment of inertia, the suspension equivalent roll stiffness and the suspension equivalent damping coefficient through a minimum recursive quadratic model so as to obtain the roll height error, the roll center moment of inertia error, the suspension equivalent roll stiffness error and the suspension equivalent damping coefficient error of the vehicle;
establishing a minimum recursion quadratic model to estimate the real-time change of the vehicle roll height, the roll center rotational inertia, the suspension equivalent roll stiffness and the suspension equivalent damping coefficient in the step 3;
the minimum recursive quadratic model is:
Y(t)＝XT(t)θ(t)+η(t)
wherein:
Figure GDA0002538553170000121
Figure GDA0002538553170000122
θ(t)＝[Δhcg,sΔhRΔIxx_oΔcφΔkφ]T
wherein Y (t) is a known output, X (t) is a regression vector, η (t) is system noise, θ (t) is a parameter vector to be estimated, Δ hsIs the roll height error of the vehicle, Delta Ixx_oError of moment of inertia of roll center, Δ kφFor suspension equivalent roll stiffness error, Δ cφIs the suspension equivalent damping coefficient error;
by adopting the RLS algorithm to pre-estimate the parameters of the error identification model, the unknown disturbance can be effectively estimated and compensated, so that the parameter identification precision and the robust characteristic are improved;
the algorithm is as follows:
Figure GDA0002538553170000123
P(t)＝P(t-1)-P(t-1)X(t)[I+XT(t)P(t-1)X(t)]-1XT(t)P(t-1)
Figure GDA0002538553170000124
in the formula (I), the compound is shown in the specification,
Figure GDA0002538553170000125
is the parameter vector to be estimated, P (t) is the covariance matrix,
Figure GDA0002538553170000126
Is the perturbation value, Q (z) is the filter;
and 4, step 4: the method comprises the steps of measuring lateral acceleration, a roll angle rate and a roll angle acceleration through a sensor, correcting roll height, a suspension equivalent damping coefficient, a suspension equivalent roll stiffness and a roll center rotational inertia in real time, and establishing a roll risk index model based on the roll height corrected in real time;
step 4, the roll risk index based on the real-time corrected roll height is as follows:
step 4.1, the known Y (t), X (t), η (t) can calculate the estimated parameter vector theta (t) to calculate the rolling height error of the vehicle as delta hsThe error of the rotational inertia of the roll center is delta Ixx_oThe equivalent roll stiffness error of the suspension is delta kφThe equivalent damping coefficient error of the suspension is Delta cφOn the basis of which the corrected roll height of the vehicle can be obtained
Figure GDA0002538553170000131
Correcting height of center of mass on spring
Figure GDA0002538553170000132
Correcting height of center of mass under spring
Figure GDA0002538553170000133
Correcting the height of the mass center of the whole vehicle
Figure GDA0002538553170000134
Modified suspension equivalent damping coefficient
Figure GDA0002538553170000135
Correcting suspension equivalent roll stiffness
Figure GDA0002538553170000136
And correcting roll center moment of inertia
Figure GDA0002538553170000137
Step 4.2, the roll risk index model based on the real-time corrected roll height and the finished automobile mass center height is as follows:
Figure GDA0002538553170000138
and 5: calibrating a roll risk threshold value through a roll risk index model based on real-time correction parameters, and judging whether a rollover risk occurs or not according to the roll risk threshold value;
the roll risk threshold is set to | RI in step 5TH|＝0.8；
The method for judging whether the rollover danger occurs or not in the step 5 comprises the following steps:
when RI < 0.8, the vehicle is in a safe state;
when RI is more than or equal to 0.8, the vehicle is about to be in a rollover dangerous state;
when RI | < 0.8, the microprocessor does not drive the steering wheel motor driving module, the display screen early warning module displays safety, when RI | > 0.8, the microprocessor drives the steering wheel motor module, the steering wheel motor driving module drives the steering wheel motor to drive the eccentric rotating block to move, so that the rim of the steering wheel emits slight vibration, the display screen early warning module displays ' speed reduction and forward direction return ' to the steering wheel ', and therefore the vehicle danger state early warning system based on the heeling risk index is formed, the driver is warned that the vehicle has the rollover risk, and violent driving is avoided.
It should be understood that parts of the specification not set forth in detail are well within the prior art.
It should be understood that the above-mentioned embodiments are described in some detail, and not intended to limit the scope of the invention, and those skilled in the art will be able to make alterations and modifications without departing from the scope of the invention as defined by the appended claims.

Claims (6)

1. A vehicle dangerous state early warning method based on a roll risk index is characterized by comprising a vehicle dangerous state early warning system based on the roll risk index;
the vehicle dangerous state early warning system based on the roll risk index comprises:
the device comprises a vehicle mass center side inclination angle sensor, a transverse acceleration sensor, a gyroscope, a side inclination angle acceleration sensor, a microprocessor, a display screen early warning module, a steering wheel motor driving module, a steering wheel motor and an eccentric rotating block; the microprocessor is respectively connected with the vehicle mass center side inclination angle sensor, the transverse acceleration sensor, the gyroscope and the side inclination angle acceleration sensor in sequence through leads; the microprocessor is respectively connected with the display screen early warning module and the steering wheel motor driving module in sequence through leads; the steering wheel motor driving module, the steering wheel motor and the eccentric rotating block are sequentially connected in series through a lead;
the vehicle dangerous state early warning method based on the roll risk index comprises the following steps:
step 1: the method comprises the steps of establishing a moment balance model of the vehicle in the roll direction of the sprung and unsprung roll centers, calculating the vertical load difference of the left wheel and the right wheel of the whole vehicle, establishing a dynamic model of the vehicle in the vertical direction of the sprung mass center, calculating the vertical load sum of the wheels at the two sides of the vehicle, and calculating a roll risk index according to the vertical load difference of the left wheel and the right wheel and the vertical load sum of the wheels at the two sides of the vehicle;
step 2: the method comprises the steps that a vehicle transverse acceleration is combined with a roll direction moment balance model of a vehicle roll center to respectively obtain a roll angle, a roll angle rate and a roll angle acceleration of a fixed roll center, and a vehicle state parameter error identification model is established further in combination with the actually measured roll angle, roll angle rate and roll angle acceleration;
and step 3: calculating the real-time change conditions of the vehicle roll height, the roll center moment of inertia, the suspension equivalent roll stiffness and the suspension equivalent damping coefficient through a minimum recursive quadratic model so as to obtain the roll height error, the roll center moment of inertia error, the suspension equivalent roll stiffness error and the suspension equivalent damping coefficient error of the vehicle;
and 4, step 4: the method comprises the steps of measuring lateral acceleration, a roll angle rate and a roll angle acceleration through a sensor, correcting roll height, a suspension equivalent damping coefficient, a suspension equivalent roll stiffness and a roll center rotational inertia in real time, and establishing a roll risk index model based on the roll height corrected in real time;
and 5: calibrating a roll risk threshold value through a roll risk index model based on real-time correction parameters, and judging whether a rollover risk occurs or not according to the roll risk threshold value;
2. the roll risk indicator-based vehicle risk state warning method according to claim 1, wherein: the step 1 of establishing a roll direction moment balance model of the roll center of the vehicle comprises the following steps:
step 1.1, establishing a vehicle dynamic model of vehicle rolling along the y axis, and assuming that a vehicle tire model is not considered, a rolling direction moment balance model of a vehicle rolling center is as follows:
Figure FDA0002538553160000021
wherein m issIs the sprung mass of the vehicle, hsThe distance from the center of the sprung mass to the center of roll, i.e., the roll height, g is the gravitational acceleration g, theta is the road surface transverse slope angle, kφFor suspension equivalent roll stiffness, cφFor the suspension equivalent roll damping coefficient, Ixx_oMoment of inertia at roll center: (
Figure FDA0002538553160000022
IxxMoment of inertia of center of mass on spring), ayIs the lateral acceleration, phi is the roll angle,
Figure FDA0002538553160000023
in order to be the roll angle rate,
Figure FDA0002538553160000024
is the roll angular acceleration;
step 1.2, when the center of mass under the spring of the vehicle is taken as the moment center, the moment balance equation of the roll center is as follows:
Figure FDA0002538553160000025
wherein, FzrFor vertical loading of the right wheel of the vehicle, FzlVertical load of left wheel of vehicle, T wheel track, hRHeight h from the center of vehicle roll to the grounduIs the height of the center of mass under the spring from the ground, Ixx_uIs unsprung mass center moment of inertia, Fy＝may-mgsinθ，m＝ms+mu；
Step 1.3, if the roll angle is smaller, cos phi is approximately equal to 1, sin phi is approximately equal to phi, and the vertical load difference expression of the left wheel and the right wheel can be obtained through the moment balance equation:
Figure FDA0002538553160000026
step 1.4, the height H of the mass center of the whole vehicle can be expressed as:
Figure FDA0002538553160000027
thus, the vertical load difference expression for the left and right wheels of the vehicle of step 1.3:
Figure FDA0002538553160000028
the dynamic model of the vehicle on-spring center of mass in the vertical direction in the step 1 is as follows:
establishing a stress balance equation of the vehicle sprung mass in the z-axis direction:
Figure FDA0002538553160000029
wherein the content of the first and second substances,
Figure FDA00025385531600000210
the sum of the vertical loads of the wheels at two sides of the vehicle can be obtained:
Figure FDA0002538553160000031
wherein the content of the first and second substances,
Figure FDA0002538553160000032
is the vertical acceleration of the sprung mass centre along the z-axis;
the roll risk indicators in step 1 are:
suppose that
Figure FDA0002538553160000033
The term is smaller and approaches to zero, and the ratio is calculated by the difference of the vertical loads of the vehicle tires and the sum of the vertical loads, so that the improved vehicle roll risk index can be obtained:
Figure FDA0002538553160000034
3. the roll risk indicator-based vehicle risk state warning method according to claim 1, wherein: in step 2, the lateral acceleration of the vehicle is ayAcquiring through a vehicle transverse acceleration sensor;
step 1 roll direction moment balance model of vehicle roll center by ayThe roll angle of the fixed roll center can be calculated separately for known inputs as phioThe roll angle rate of the fixed roll center is
Figure FDA0002538553160000035
The roll angular acceleration of the fixed roll center is
Figure FDA0002538553160000036
The roll angle measured by the roll angle sensor of the mass center of the real vehicle is phimThe rate of roll angle measured by the gyroscope is
Figure FDA0002538553160000037
The roll angular acceleration measured by the roll angular acceleration sensor is
Figure FDA0002538553160000038
Carrying out comprehensive calculation and establishing a vehicle state parameter error identification model;
the vehicle state parameter error identification model in the step 2 is as follows:
step 2.1, measuring the lateral acceleration a by a vehicle lateral acceleration sensoryThe roll moment model with the fixed roll center of the vehicle is brought into calculation to obtain the roll angle phi of the vehicle under the condition that the roll center of the vehicle is fixedoRoll rate
Figure FDA0002538553160000039
Acceleration of roll angle
Figure FDA00025385531600000310
At the moment, certain errors exist between the calculated vehicle state parameters and the actual measured values, so that an error identification model needs to be established;
the roll moment balance equation for the initial position of the vehicle is:
Figure FDA00025385531600000311
wherein
Figure FDA00025385531600000312
A vehicle roll height for fixing a roll center,
Figure FDA00025385531600000313
The equivalent roll stiffness of the suspension for fixing the roll center,
Figure FDA00025385531600000314
The equivalent roll damping coefficient of the suspension for fixing the roll center,
Figure FDA00025385531600000315
Roll center moment of inertia, which is a fixed roll center. Phi is aoA vehicle roll angle at which a roll center is fixed,
Figure FDA0002538553160000041
The roll angular velocity of the fixed roll center,
Figure FDA0002538553160000042
Roll angular acceleration being a fixed roll center;
step 2.2, because the roll height of the actual vehicle is changed, similarly, the roll moment balance equation of the vehicle is as follows:
Figure FDA0002538553160000043
in the same way, in the formula,
Figure FDA0002538553160000044
is the side-tipping height of the real vehicle,
Figure FDA0002538553160000045
The equivalent roll stiffness of the suspension of the real vehicle,
Figure FDA0002538553160000046
The equivalent roll damping coefficient of the suspension of the real vehicle,
Figure FDA0002538553160000047
The roll center moment of inertia of the real vehicle. Phi is amThe measured roll angle of the real vehicle,
Figure FDA0002538553160000048
The measured roll angle speed of the real vehicle,
Figure FDA0002538553160000049
Measured roll angular acceleration for a real vehicle;
step 2.3, at the same transverse acceleration ayThen, the roll height of the vehicle is identified in real time by using a roll model of the vehicle, and the parameter increment between the two models is defined as：
Figure FDA00025385531600000410
Figure FDA00025385531600000411
Figure FDA00025385531600000412
Figure FDA00025385531600000413
Wherein,. DELTA.hsRoll height error, Δ I, for real and vehicle modelsxxIs the roll center moment of inertia error, Δ kφIs the suspension equivalent roll stiffness error, Δ cφIs the equivalent damping coefficient error of the suspension, delta hcg,sAnd Δ hRRespectively the height error of the center of mass on the spring and the height error of the center of lateral inclination;
subtracting the real vehicle dynamic roll equation and the roll model with the fixed roll height, and then establishing a parameter increment model in a simultaneous manner to obtain an expression of a vehicle parameter error identification model:
Figure FDA00025385531600000414
4. the roll risk indicator-based vehicle risk state warning method according to claim 1, wherein: establishing a minimum recursion quadratic model to estimate the real-time change of the vehicle roll height, the roll center rotational inertia, the suspension equivalent roll stiffness and the suspension equivalent damping coefficient in the step 3;
the minimum recursive quadratic model is:
Y(t)＝XT(t)θ(t)+η(t)
wherein:
Figure FDA0002538553160000051
Figure FDA0002538553160000052
θ(t)＝[Δhcg,sΔhRΔIxx_oΔcφΔkφ]T
wherein Y (t) is a known output, X (t) is a regression vector, η (t) is system noise, θ (t) is a parameter vector to be estimated, Δ hsIs the roll height error of the vehicle, Delta Ixx_oError of moment of inertia of roll center, Δ kφFor suspension equivalent roll stiffness error, Δ cφIs the suspension equivalent damping coefficient error;
by adopting the RLS algorithm to pre-estimate the parameters of the error identification model, the unknown disturbance can be effectively estimated and compensated, so that the parameter identification precision and the robust characteristic are improved;
the algorithm is as follows:
Figure FDA0002538553160000053
P(t)＝P(t-1)-P(t-1)X(t)[I+XT(t)P(t-1)X(t)]-1XT(t)P(t-1)
Figure FDA0002538553160000054
in the formula (I), the compound is shown in the specification,
Figure FDA0002538553160000055
is the parameter vector to be estimated, P (t) is the covariance matrix,
Figure FDA0002538553160000056
Is the perturbation value, Q (z) is the filter;
5. the roll risk indicator-based vehicle risk state warning method according to claim 1, wherein: step 4, the roll risk index based on the real-time corrected roll height is as follows:
step 4.1, the known Y (t), X (t), η (t) can calculate the estimated parameter vector theta (t) to calculate the rolling height error of the vehicle as delta hsThe error of the rotational inertia of the roll center is delta Ixx_oThe equivalent roll stiffness error of the suspension is delta kφThe equivalent damping coefficient error of the suspension is Delta cφOn the basis of which the corrected roll height of the vehicle can be obtained
Figure FDA0002538553160000057
Correcting height of center of mass on spring
Figure FDA0002538553160000058
Correcting height of center of mass under spring
Figure FDA0002538553160000059
Correcting the height of the mass center of the whole vehicle
Figure FDA00025385531600000510
Modified suspension equivalent damping coefficient
Figure FDA00025385531600000511
Correcting suspension equivalent roll stiffness
Figure FDA00025385531600000512
And correcting roll center moment of inertia
Figure FDA0002538553160000061
Step 4.2, the roll risk index model based on the real-time corrected roll height and the finished automobile mass center height is as follows:
Figure FDA0002538553160000062
6. the roll risk indicator-based vehicle risk state warning method according to claim 1, wherein: the roll risk threshold is set to | RI in step 5TH|＝0.8；
The method for judging whether the rollover danger occurs or not in the step 5 comprises the following steps:
when RI < 0.8, the vehicle is in a safe state;
when RI ≧ 0.8, the vehicle is about to be in a rollover hazard state.
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