CN111845710A - Method and system for controlling dynamic performance of whole vehicle based on pavement adhesion coefficient identification - Google Patents

Method and system for controlling dynamic performance of whole vehicle based on pavement adhesion coefficient identification Download PDF

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CN111845710A
CN111845710A CN202010768418.2A CN202010768418A CN111845710A CN 111845710 A CN111845710 A CN 111845710A CN 202010768418 A CN202010768418 A CN 202010768418A CN 111845710 A CN111845710 A CN 111845710A
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vehicle
acceleration
longitudinal
longitudinal acceleration
deceleration
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CN111845710B (en
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何洪文
李秦
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Beijing Institute of Technology BIT
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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
    • 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
    • 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
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • 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
    • B60W40/02—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 ambient conditions
    • B60W40/06—Road conditions
    • B60W40/064—Degree of grip
    • 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
    • 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
    • B60W40/107—Longitudinal acceleration
    • 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
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/18—Braking system

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  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Regulating Braking Force (AREA)

Abstract

A whole vehicle dynamic performance control method and a whole vehicle dynamic performance control system based on pavement adhesion coefficient recognition comprehensively consider a cooperative working mechanism of each subsystem of a vehicle and a transverse and longitudinal coupling influence mechanism of vehicle dynamics aiming at a traditional power four-wheel drive vehicle, and provide a global control strategy capable of improving the transverse and longitudinal dynamic performance of the whole vehicle. The method combines modern control theory and vehicle dynamics, improves the agility, the smoothness and the operation stability of the whole vehicle in the curve on different roads by using an agile dynamics control method, and improves the driving experience of a driver. Compared with the prior art, the whole vehicle steering response of the daily use working condition of a user can be improved, the safety, the driving stability and the over-bending smoothness of the vehicle are improved, and meanwhile, the control method can also be used for optimizing the control technology of the automatic driving vehicle in view of the control field of the automatic driving vehicle, and particularly can be used for coupling control in a curve.

Description

Method and system for controlling dynamic performance of whole vehicle based on pavement adhesion coefficient identification
Technical Field
The invention relates to the technical field of vehicle dynamic performance control, in particular to a global control strategy for improving the running performance of curved vehicles based on a road adhesion coefficient.
Background
Since the middle of the 80 th century, some well-known automobile manufacturers and researchers at home and abroad successively carry out research on chassis integration control, and more research results are obtained. Various chassis integrated control modes provide diversified whole vehicle control strategies, and various algorithm schemes enable the performance of the whole vehicle to be not improved to different degrees. For example, a dynamics integrated management system arranged in some existing commercially available vehicle models can integrate a chassis control system to the maximum extent from two aspects of software and hardware, and perform integrated management on driving, braking and steering control, so that the dynamic performance of the vehicle is improved, and intervention control of the vehicle is realized before instability occurs. In the prior art where integrated control of braking and steering is achieved in part by algorithms, global integrated control of braking, steering and suspension is also well established. However, the prior art currently has fewer considerations in identifying the maximum road adhesion coefficient under the normal driving condition of the vehicle, so that the provided overall vehicle global control strategy obviously has a defect in dynamics, and the adaptability to the actual driving condition of the vehicle still has an insurmountable defect.
Disclosure of Invention
The invention provides a whole vehicle dynamic performance control method based on maximum road surface attachment coefficient identification, which mainly comprises the following steps:
judging the working condition of the vehicle based on the driving data of the vehicle, and identifying the current conditions that the vehicle enters, exits a curve or drives in a non-curve;
calibrating vehicle agility control parameters corresponding to different road surfaces and different vehicle speeds by using driving experience data, namely, anticipating longitudinal acceleration;
thirdly, judging the intention of the driver and deciding to output a longitudinal acceleration instruction by combining the working condition judged in the first step, the expected longitudinal acceleration, the actual longitudinal acceleration and the pressure of the brake pedal;
calculating the longitudinal tangent rigidity and the longitudinal secant rigidity of the vehicle based on the single-wheel longitudinal use adhesion coefficient and the longitudinal slip ratio, and estimating the maximum road adhesion coefficient by utilizing the recursion of Gaussian distribution;
and fifthly, aiming at the longitudinal acceleration instruction output in the third step, providing gain for the longitudinal acceleration instruction by using the estimated maximum road adhesion coefficient, and realizing dynamic torque regulation according to the gained acceleration so as to realize acceleration and deceleration following regulation of the vehicle.
Further, the working condition is judged in the step one based on the driving data of the vehicle, and the following data are specifically adopted: lateral acceleration G of vehicleyTransverse impact strength
Figure BDA0002615565890000011
Steering wheel angle theta and steering wheel angular velocity
Figure BDA0002615565890000012
Further, the second step specifically utilizes driving experience data: first-order inertial system delay time T and system gain CxyThe understeer k, the measured vehicle wheel base L, the transmission ratio i from the steering wheel angle to the front wheel angle, the steering wheel angle and the steering wheel angular speed are obtained through data analysis
Figure RE-GDA0002686989280000021
Vehicle speed V, obtaining the following desired longitudinal acceleration GxWherein s represents the Ralstonian factor:
Figure BDA0002615565890000022
further, the step three of judging the intention of the driver and deciding to output the longitudinal acceleration instruction specifically includes the following processes:
when the working condition is judged to be that the vehicle enters the curve, if the current longitudinal acceleration a of the vehicle isxNot more than 0, and brake pedal pressure is more than 0, shows that the driver has the intention of slowing down, then corresponds following several kinds of condition respectively:
(1) if carCurrent longitudinal acceleration a of the vehiclex≤GxIf the braking intensity of the driver is insufficient and needs to be increased, the longitudinal acceleration of the decision should be Gx；
(2) If the current longitudinal acceleration a of the vehicle isx＞GxWhen the driver is likely to avoid an obstacle or stop in an emergency, the longitudinal acceleration of the decision is a to ensure the driving safety of the driverx；
(3) If the current longitudinal acceleration a of the vehicle isxIf the acceleration is more than 0, the driving experience of the driver is insufficient, and the decided longitudinal acceleration is Gx；
When the working condition is judged to be that the vehicle is driven out of the curve, the following conditions are respectively corresponding to the following conditions:
(1) if the current acceleration a of the vehicle isxIf the acceleration is more than 0, the driver has an acceleration intention, and the longitudinal acceleration is determined to be a in order to avoid the abrupt acceleration feeling brought to the driverxAnd GxA minimum value in between;
(2) if the current acceleration a of the vehicle isxWhen the value is 0, the determined longitudinal acceleration is Gx；
(3) If the current acceleration a of the vehicle isxIf the acceleration is less than 0, the driver is possible to avoid the obstacle or stop emergently, and the longitudinal acceleration determined at the moment is a to ensure the driving safety of the driverx。
Further, the specific process of outputting the maximum road adhesion coefficient in the fourth step is as follows:
by passing
Figure BDA0002615565890000023
The relationship estimation of (2) obtains the single-round longitudinal use adhesion coefficient mux(ii) a Wherein the content of the first and second substances,
Figure BDA0002615565890000024
the estimated value of the single-wheel pure longitudinal force is estimated by the wheel-side driving torque, and the calculation formula is
Figure BDA0002615565890000025
WhereinRe is the effective rolling radius of the tire; wherein, Fz,iAnd Tt,iThe vertical force and the wheel side torque of a single wheel are respectively, and the upper mark ^ represents the estimated value of the corresponding parameter. Whether the SUV or the four-wheel hub motor-driven automobile, the wheel-side driving torque is the reason for accelerating the automobile. In other words, the adhesion coefficient used, which is estimated from the wheel-side drive torque, always "leads" in phase to the vehicle body acceleration, and therefore
Figure BDA0002615565890000026
The longitudinal tangential stiffness of a vehicle is defined as
Figure BDA0002615565890000027
However, since the vehicle does not have a large gradient and does not enter a strong non-linear region in most of the time when the vehicle is running, the vertical load transfer ratio of the tire due to acceleration, braking, and lateral movement of the vehicle itself is small, and thus, the influence of the vertical load change rate is ignored, so that the tangential stiffness can be further defined as
Figure BDA0002615565890000031
The linear region of the tire in the slip ratio-use adhesion coefficient curve, i.e. the corresponding curve slope of the curve starting point, is the secant stiffness k of the vehicle, wherein the longitudinal secant stiffness is kx. According to the unitire model, the product of the real-time normalized secant stiffness and the real-time slip ratio is the use attachment coefficient mux＝KxSxThat is, the current secant stiffness can be calculated by using the adhesion coefficient and the current slip ratio in the longitudinal direction, and thus, the secant stiffness can be obtained
Figure BDA0002615565890000032
Wherein the content of the first and second substances,
Figure BDA0002615565890000033
for single round normalization of the pure longitudinal secant stiffness,
Figure BDA0002615565890000034
for single round normalization pure longitudinal tangent line steelAnd (4) degree. When in use
Figure BDA0002615565890000035
This shows that the corresponding slip ratio of the working point for gaussian recursion cannot be too small, and the obtained working point belongs to a section of data with the slip ratio increasing continuously under a certain drive;
Figure BDA0002615565890000036
this indicates that the working point for gaussian recursion, the corresponding longitudinal acceleration cannot be too small, and the obtained working point belongs to a segment of data in which the longitudinal acceleration is continuously increased under a certain driving; v. ofx＞vx，thro> 0, which indicates an operating point for the gaussian recursion, which corresponds to a longitudinal vehicle speed that cannot be too small. Selecting a section of data with continuously increased driving force under a certain driving condition to carry out mux，maxAnd (6) estimating. This is because, although there is disturbance of the tread vibration during the driving force increase, the tread is in a "tight" state during this process as compared with the driving force drop-back process, and the separation characteristic of the corresponding data points under different road surfaces is more "noticeable", and it is more suitable to perform μx，maxAnd (6) estimating. After the Save _ flag determination is completed, a Cnt _ flag determination needs to be performed, and the main determination logic is as follows: 1, namely at least meeting the Save _ flag condition;
Figure BDA0002615565890000037
in relation to the relationship between the normalized tangential stiffness XBS and the normalized secant stiffness k, when the tire force working point is from a linear region to a quasi-linear region, the original equal XBS and k are in the relationship of k being larger than XBS, and the difference between the XBS and the k is larger and larger as the slip degree is deepened. The significance of this condition is that the real-time values of XBS and k are used to approximately extract the operating point of the pseudo-linear region; XBSkAnd the value is more than 0.5, which indicates the tire force working point used for Gaussian recursion, the corresponding normalized tangential stiffness of the tire force working point cannot be too small, and the significance of the condition is to filter out the working point of a strong nonlinear region. At this point, after the recursive estimation input analysis aiming at the Gaussian distribution is finished, the road adhesion coefficient estimation and the road adhesion coefficient output are carried out based on the standard normal distributionThe maximum road surface adhesion coefficient is obtained.
Further, the acceleration and deceleration following and adjusting process of the vehicle in the fifth step specifically includes:
according to the decided longitudinal acceleration instruction, the ESC braking is used for realizing deceleration following, and the dynamic torque regulation of the EMS is used for realizing acceleration following; before the instruction is executed, a logic judgment needs to be performed on the current state, wherein whether the ESC is in a fault state is judged, if so, the execution of the acceleration and deceleration request is quitted, whether sub-function modules of the ESC are executed is judged, the sub-function modules include but not limited to ABS, HDC, HHC, VDC, DYC and the like, if yes, the execution of the acceleration and deceleration request is quitted, and if the RDU is in a fault bit, the execution of the acceleration and deceleration request is quitted, and similarly, the EMS and the TCU. And finally, when the TCU judges N, performing front-rear axis moment distribution according to the acceleration information through the RDU, executing an expected acceleration and deceleration following command, and performing appropriate gain according to the estimation of the current maximum adhesion coefficient, namely performing coefficient weighting on the current expected acceleration and deceleration. Acceleration following is performed by EMS torque dynamic adjustment when the desired acceleration is greater than or equal to zero, and a deceleration request is performed by the ESC when the desired acceleration is less than zero.
Correspondingly, the invention also provides a vehicle dynamic performance control system, which executes the method provided by the invention, and the system specifically comprises:
the curve identification module judges the working condition of the vehicle based on the driving data of the vehicle and identifies the current conditions that the vehicle enters, exits or drives in a non-curve;
the acceleration and deceleration calculation module is used for calibrating vehicle agility control parameters, namely expected longitudinal acceleration, corresponding to different road surfaces and different vehicle speeds by using driving experience data;
the acceleration and deceleration identification module is used for judging the intention of a driver and deciding to output a longitudinal acceleration instruction by combining the working condition judged by the curve identification module, the expected longitudinal acceleration, the actual longitudinal acceleration and the brake pedal pressure;
the road adhesion coefficient estimation module is used for calculating the longitudinal tangent rigidity and the longitudinal secant rigidity of the vehicle based on the single-wheel longitudinal application adhesion coefficient and the longitudinal slip rate, and estimating the maximum road adhesion coefficient by utilizing the recursion of Gaussian distribution;
and the acceleration and deceleration execution module is used for providing gains for the longitudinal acceleration instruction by utilizing the estimated maximum road adhesion coefficient according to the longitudinal acceleration instruction output by the acceleration and deceleration identification module, realizing dynamic torque adjustment according to the accelerated speed after the gains and realizing the acceleration and deceleration following adjustment of the vehicle.
The method and the system provided by the invention aim at solving the technical problems in the prior art, comprehensively consider the cooperative working mechanism of each subsystem of the vehicle and the transverse and longitudinal coupling influence mechanism of the vehicle dynamics for the traditional power four-wheel drive vehicle, and provide a global control strategy capable of improving the transverse and longitudinal performance of the whole vehicle. The method combines modern control theory and vehicle dynamics, improves the agility, the smoothness and the operation stability of the whole vehicle in the curve under different road surfaces by using an agile dynamics control method, and improves the driving experience of a driver. Compared with the prior art, the invention has at least the following beneficial effects:
1. the invention can improve the whole vehicle steering response of the daily use working condition of a user, and improve the safety, the running stability and the bending smoothness of the vehicle;
2. the invention can be used in the field of autonomous vehicle control for optimizing the control technology of autonomous vehicles, in particular for coupling control in curves.
Drawings
FIG. 1 is a schematic diagram of a curve identification process in the present invention;
FIG. 2 is a schematic diagram of an acceleration/deceleration recognition process in the present invention;
FIG. 3 is a schematic diagram of the maximum longitudinal road adhesion coefficient identification process in the present invention;
FIG. 4 is a schematic diagram of an acceleration/deceleration following process in the present invention;
FIG. 5 is a logical relationship diagram of the overall vehicle dynamic performance global control strategy of the present invention;
fig. 6 is a diagram of the hardware architecture employed in an example of the invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
The invention provides a whole vehicle dynamic performance control method based on pavement adhesion coefficient identification, which mainly comprises the following steps:
judging the working condition of the vehicle based on the driving data of the vehicle, and identifying the current conditions that the vehicle enters, exits a curve or drives in a non-curve;
calibrating vehicle agility control parameters corresponding to different road surfaces and different vehicle speeds by using driving experience data, namely, anticipating longitudinal acceleration;
thirdly, judging the intention of the driver and deciding to output a longitudinal acceleration instruction by combining the working condition judged in the first step, the expected longitudinal acceleration, the actual longitudinal acceleration and the pressure of the brake pedal;
calculating the longitudinal tangent rigidity and the longitudinal secant rigidity of the vehicle based on the single-wheel longitudinal use adhesion coefficient and the longitudinal slip ratio, and estimating the maximum road adhesion coefficient by utilizing the recursion of Gaussian distribution;
and fifthly, aiming at the longitudinal acceleration instruction output in the third step, providing gain for the longitudinal acceleration instruction by using the estimated maximum road adhesion coefficient, and realizing dynamic torque regulation according to the gained acceleration so as to realize acceleration and deceleration following regulation of the vehicle.
As shown in fig. 1, the first step determines the working condition based on the driving data of the vehicle, specifically using the following data: lateral acceleration G of vehicleyTransverse impact strength
Figure BDA0002615565890000051
Steering wheel angle theta and steering wheel angular velocity
Figure BDA0002615565890000052
As shown in fig. 2, the second step specifically utilizes driving experience data: first-order inertial system delay time T and system gain CxyThe understeer k, the measured vehicle wheel base L, the transmission ratio i from the steering wheel angle to the front wheel angle, the steering wheel angle and the steering wheel angular speed are obtained through data analysis
Figure BDA0002615565890000053
Vehicle speed V, obtaining the following desired longitudinal acceleration GxWherein s represents the Ralstonian factor:
Figure BDA0002615565890000054
as shown in fig. 3, the determining the intention of the driver and deciding to output the longitudinal acceleration command in the third step specifically includes the following processes:
when the working condition is judged to be that the vehicle enters the curve, if the current longitudinal acceleration a of the vehicle isxNot more than 0, and the pressure of the brake pedal is more than 0, which respectively corresponds to the following conditions:
(1) if the current longitudinal acceleration a of the vehicle isx≤GxThe longitudinal acceleration of the decision should be Gx；
(2) If the current longitudinal acceleration a of the vehicle isx＞GxThen the longitudinal acceleration of the decision is ax；
(3) If the current longitudinal acceleration a of the vehicle isxIf > 0, the decided longitudinal acceleration is Gx；
When the working condition is judged to be that the vehicle is driven out of the curve, the following conditions are respectively corresponding to the following conditions:
(1) if the current acceleration a of the vehicle isxIf the acceleration is more than 0, the decided longitudinal acceleration is axAnd GxA minimum value in between;
(2) if the current acceleration a of the vehicle isxWhen the value is 0, the determined longitudinal acceleration is Gx；
(3) If the current acceleration a of the vehicle isxIf < 0, the determined longitudinal acceleration is ax。
As shown in fig. 4, the specific process of outputting the maximum road adhesion coefficient in the fourth step is as follows:
by passing
Figure BDA0002615565890000061
The relationship estimation of (2) obtains the single-round longitudinal use adhesion coefficient mux(ii) a Wherein the content of the first and second substances,
Figure BDA0002615565890000062
the estimated value of the single-wheel pure longitudinal force is estimated by the wheel-side driving torque, and the calculation formula is
Figure BDA0002615565890000063
Wherein Re is the effective rolling radius of the tire; wherein, Fz,iAnd Tt,iVertical force and wheel side torque of a single wheel are respectively, and the upper mark ^ represents an estimated value of a corresponding parameter; calculating to obtain single-wheel longitudinal slip rate S based on longitudinal speed and wheel speed of tirex(ii) a The longitudinal tangential stiffness of the vehicle is defined as
Figure BDA0002615565890000064
The product of the longitudinal secant stiffness and the single-wheel longitudinal slip ratio is the coefficient of adhesion mux＝KxSx(ii) a Is normalized to obtain
Figure BDA0002615565890000065
Wherein the content of the first and second substances,
Figure BDA0002615565890000066
for single round normalization of the pure longitudinal secant stiffness,
Figure BDA0002615565890000067
for single round normalization of pure longitudinal tangential stiffness, it is highly weightedAnd (4) performing recursive estimation on the Gaussian distribution, and outputting to obtain the maximum road adhesion coefficient.
As shown in fig. 5, the acceleration and deceleration following and adjusting process of the vehicle in the fifth step specifically includes:
according to the decided longitudinal acceleration instruction, the ESC braking is used for realizing deceleration following, and the dynamic torque regulation of the EMS is used for realizing acceleration following; before the instruction is executed, a logic judgment needs to be performed on the current state, wherein whether the ESC is in a fault state is judged, if so, the execution of the acceleration and deceleration request is quitted, whether sub-function modules of the ESC are executed is judged, the sub-function modules include but not limited to ABS, HDC, HHC, VDC, DYC and the like, if yes, the execution of the acceleration and deceleration request is quitted, and if the RDU is in a fault bit, the execution of the acceleration and deceleration request is quitted, and similarly, the EMS and the TCU. And finally, when the TCU judges N, performing front-rear axis moment distribution according to the acceleration information through the RDU, executing an expected acceleration and deceleration following command, and performing appropriate gain according to the estimation of the current maximum adhesion coefficient, namely performing coefficient weighting on the current expected acceleration and deceleration. Acceleration following is performed by EMS torque dynamic adjustment when the desired acceleration is greater than or equal to zero, and a deceleration request is performed by the ESC when the desired acceleration is less than zero.
The invention provides a vehicle dynamic performance control system, which executes the method provided by the invention, and the system specifically comprises:
the curve identification module judges the working condition of the vehicle based on the driving data of the vehicle and identifies the current conditions that the vehicle enters, exits or drives in a non-curve;
the acceleration and deceleration calculation module is used for calibrating vehicle agility control parameters, namely expected longitudinal acceleration, corresponding to different road surfaces and different vehicle speeds by using driving experience data;
the acceleration and deceleration identification module is used for judging the intention of a driver and deciding to output a longitudinal acceleration instruction by combining the working condition judged by the curve identification module, the expected longitudinal acceleration, the actual longitudinal acceleration and the brake pedal pressure;
the road adhesion coefficient estimation module is used for calculating the longitudinal tangent rigidity and the longitudinal secant rigidity of the vehicle based on the single-wheel longitudinal application adhesion coefficient and the longitudinal slip rate, and estimating the maximum road adhesion coefficient by utilizing the recursion of Gaussian distribution;
and the acceleration and deceleration execution module is used for providing gains for the longitudinal acceleration instruction by utilizing the estimated maximum road adhesion coefficient according to the longitudinal acceleration instruction output by the acceleration and deceleration identification module, realizing dynamic torque adjustment according to the accelerated speed after the gains and realizing the acceleration and deceleration following adjustment of the vehicle.
The work flows of the modules are respectively shown in figures 1-5. Fig. 6 shows a hardware architecture diagram that can be used in an example of the present invention, and the hardware architecture diagram can be built by using existing common modules, and no additional functional module needs to be designed, so that better practicability can be provided.
It should be understood that, the sequence numbers of the steps in the embodiments of the present invention do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic of the process, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (7)

1. The whole vehicle dynamic performance control method based on the pavement adhesion coefficient identification is characterized by comprising the following steps of: the method mainly comprises the following steps:
judging the working condition of the vehicle based on the driving data of the vehicle, and identifying the current conditions that the vehicle enters, exits from a curve or drives in a non-curve;
calibrating vehicle agility control parameters corresponding to different road surfaces and different vehicle speeds by using driving experience data, namely, anticipating longitudinal acceleration;
thirdly, judging the intention of the driver and deciding to output a longitudinal acceleration instruction by combining the working condition judged in the first step, the expected longitudinal acceleration, the actual longitudinal acceleration and the pressure of the brake pedal;
calculating the longitudinal tangent rigidity and the longitudinal secant rigidity of the vehicle based on the single-wheel longitudinal use adhesion coefficient and the longitudinal slip ratio, and estimating the maximum road adhesion coefficient by utilizing the recursion of Gaussian distribution;
and fifthly, aiming at the longitudinal acceleration instruction output in the third step, providing gain for the longitudinal acceleration instruction by using the estimated maximum road adhesion coefficient, and realizing dynamic torque regulation according to the gained acceleration so as to realize acceleration and deceleration following regulation of the vehicle.
2. The method of claim 1, wherein: in the first step, the working condition is judged based on the driving data of the vehicle, and the following data are specifically adopted: lateral acceleration G of vehicleyTransverse impact strength
Figure FDA0002615565880000011
Steering wheel angle theta and steering wheel angular velocity
Figure FDA0002615565880000012
3. The method of claim 2, wherein: the second step specifically utilizes driving experience data: first-order inertial system delay time T and system gain CxyThe understeer k, the measured vehicle wheel base L, the transmission ratio i from the steering wheel angle to the front wheel angle, the steering wheel angle and the steering wheel angular speed are obtained through data analysis
Figure FDA0002615565880000013
Vehicle speed V, obtaining the following desired longitudinal acceleration GxWherein s represents the Ralstonian factor:
Figure FDA0002615565880000014
4. the method of claim 2, wherein: the third step of judging the intention of the driver and deciding to output the longitudinal acceleration instruction specifically comprises the following processes:
when the working condition is judged to be that the vehicle enters the curve, if the current longitudinal acceleration a of the vehicle isxNot more than 0, and the brake pedal pressure is more than 0, then correspond to following several kinds of condition respectively:
(1) if the current longitudinal acceleration a of the vehicle isx≤GxThe longitudinal acceleration of the decision should be Gx；
(2) If the current longitudinal acceleration a of the vehicle isx＞GxThen the longitudinal acceleration of the decision is ax；
(3) If the current longitudinal acceleration a of the vehicle isxIf > 0, the decided longitudinal acceleration is Gx；
When the working condition is judged to be that the vehicle is driven out of the curve, the following conditions are respectively corresponding to the following conditions:
(1) if the current acceleration a of the vehicle isxIf the acceleration is more than 0, the decided longitudinal acceleration is axAnd GxA minimum value in between;
(2) if the current acceleration a of the vehicle isxWhen the value is 0, the determined longitudinal acceleration is Gx；
(3) If the current acceleration a of the vehicle isxIf < 0, the determined longitudinal acceleration is ax。
5. The method of claim 2, wherein: the specific process of outputting the maximum road adhesion coefficient in the fourth step is as follows:
by passing
Figure FDA0002615565880000021
The relationship estimation of (2) obtains the single-round longitudinal use adhesion coefficient mux(ii) a Wherein the content of the first and second substances,
Figure FDA0002615565880000022
the estimated value of the pure longitudinal force of the single wheel is estimated by the driving moment of the wheel edge, and the calculation formula is
Figure FDA0002615565880000023
Wherein Re is the effective rolling radius of the tire; wherein, Fz,iAnd Tt,iVertical force and wheel side torque of a single wheel are respectively, and the upper mark ^ represents an estimated value of a corresponding parameter; calculating to obtain single-wheel longitudinal slip rate S based on longitudinal speed and wheel speed of tirex(ii) a The longitudinal tangential stiffness of the vehicle is defined as
Figure FDA0002615565880000024
The product of the longitudinal secant stiffness and the single-wheel longitudinal slip ratio is the coefficient of adhesion mux＝KxSx(ii) a Is normalized to obtain
Figure FDA0002615565880000025
Wherein the content of the first and second substances,
Figure FDA0002615565880000026
for single round normalization of the pure longitudinal secant stiffness,
Figure FDA0002615565880000027
and carrying out Gaussian distribution recursive estimation on the single-wheel normalized pure longitudinal tangential stiffness, and outputting to obtain the maximum road adhesion coefficient.
6. The method of claim 1, wherein: the acceleration and deceleration following and adjusting process of the vehicle in the fifth step specifically comprises the following steps:
according to the decided longitudinal acceleration instruction, the ESC braking is used for realizing deceleration following, and the dynamic torque regulation of the EMS is used for realizing acceleration following; before the instruction is executed, the current state needs to be logically judged, wherein whether the ESC is in a fault state is judged firstly, if the ESC is in the fault state, the execution of the acceleration and deceleration request is quitted, whether sub-function modules of the ESC are executed is judged, the sub-function modules include but are not limited to ABS, HDC, HHC, VDC, DYC and the like, if the ESC is executed, the execution of the acceleration and deceleration request is quitted, whether the RDU is in a fault bit, and if the ESC is in the fault bit, the execution of the acceleration and deceleration request is quitted, and the EMS and the; and finally, when the TCU judges N, performing front and rear axle torque distribution according to the acceleration information through the RDU, executing an expected acceleration and deceleration following instruction, performing gain weighting on the current expected acceleration and deceleration according to the estimation of the current maximum adhesion coefficient, performing acceleration following through EMS torque dynamic adjustment when the expected acceleration is greater than or equal to zero, and executing a deceleration request through the ESC when the expected acceleration is smaller than zero.
7. The utility model provides a whole car dynamic behavior control system which characterized in that: performing the method of any of claims 1-6, the system specifically comprising:
the curve identification module judges the working condition of the vehicle based on the driving data of the vehicle and identifies the current conditions that the vehicle enters, exits or drives in a non-curve;
the acceleration and deceleration calculation module is used for calibrating vehicle agility control parameters, namely expected longitudinal acceleration, corresponding to different road surfaces and different vehicle speeds by using driving experience data;
the acceleration and deceleration identification module is used for judging the intention of a driver and deciding to output a longitudinal acceleration instruction by combining the working condition judged by the curve identification module, the expected longitudinal acceleration, the actual longitudinal acceleration and the brake pedal pressure;
the road adhesion coefficient estimation module is used for calculating the longitudinal tangent rigidity and the longitudinal secant rigidity of the vehicle based on the single-wheel longitudinal use adhesion coefficient and the longitudinal slip rate, and estimating the maximum road adhesion coefficient by utilizing the recursion of Gaussian distribution;
and the acceleration and deceleration execution module is used for providing gains for the longitudinal acceleration instruction by utilizing the estimated maximum road adhesion coefficient according to the longitudinal acceleration instruction output by the acceleration and deceleration identification module, realizing dynamic torque adjustment according to the accelerated speed after the gains and realizing the acceleration and deceleration following adjustment of the vehicle.
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