CN117092909A - Vehicle stability control simulation method and system - Google Patents
Vehicle stability control simulation method and system Download PDFInfo
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- CN117092909A CN117092909A CN202310451105.8A CN202310451105A CN117092909A CN 117092909 A CN117092909 A CN 117092909A CN 202310451105 A CN202310451105 A CN 202310451105A CN 117092909 A CN117092909 A CN 117092909A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Abstract
The invention discloses a vehicle stability control simulation method, which comprises the following steps: s1: based on the two-degree-of-freedom vehicle dynamics model, establishing a stability control dynamics model; s2: by utilizing Lyapunov stability theory, the design model refers to the self-adaptive controller, and an additional automobile yaw moment delta Mz is added to adjust the stability of the automobile. According to the vehicle stability control simulation method and system, the self-adaptive control law is obtained through a Lyapunov stability theory and a Lyapunov equation based on a stability control dynamics model: adaptive feedback gain K p And adaptive feedforward gain K u The defects of poor real-time performance, lower control precision and the like in the vehicle stability control are overcome.
Description
Technical Field
The invention relates to the technical field of vehicle stability control, in particular to a vehicle stability control simulation method and system.
Background
Currently, the body Electronic Stability Program (ESP) of a vehicle generally controls the generation of an additional yaw moment by generating braking force vectors on the left and right wheels of the vehicle to improve vehicle stability. For example, when the steering force of the vehicle is insufficient, the vehicle can brake through the ESP on the inner rear wheels to generate an additional yaw moment which is the same as the steering direction so as to ensure that the vehicle is stable and runs according to the expected track of the driver, and for example, when the steering force of the vehicle is excessive, the vehicle can brake through the ESP on the outer front wheels to generate an additional yaw moment which is opposite to the steering scheme so as to ensure that the vehicle is stable and runs according to the expected track of the driver, however, the method for generating the yaw moment through braking force intervention generally sets later intervention and the braking intervention is stronger, and the use experience of the driver is reduced.
At present, the following method is generally adopted for rear wheel steering control: the control method includes the steps of taking the centroid slip angle as a control target, determining the rear wheel steering angle gain based on the vehicle speed, multiplying the steering wheel angle by the rear wheel steering angle gain, and taking the steering wheel angle and the rear wheel steering angle gain as the feedforward control quantity of the rear wheel steering angle. The feedback control amount is calculated based on the yaw rate deviation. The rear wheel steering angle feedforward control amount and the rear wheel steering angle feedback control amount are overlapped to form the rear wheel steering angle control amount for rear wheel steering control. However, in the existing rear wheel steering control technology, control layer constraint and execution layer constraint are not considered, stability control is only performed when the vehicle is in an emergency state, the stability boundary of the vehicle is not pre-judged, and the stability of the vehicle is difficult to ensure.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a vehicle stability control simulation method and system.
(II) technical scheme
In order to achieve the above purpose, the present invention provides the following technical solutions: a vehicle stability control simulation method comprises the following steps:
s1: based on the two-degree-of-freedom vehicle dynamics model, establishing a stability control dynamics model;
s2: by utilizing Lyapunov stability theory, designing a model reference self-adaptive controller, and adding an additional automobile yaw moment delta Mz to adjust the stability of the automobile;
s3: model reference self-adaptive controller designed according to Lyapunov stability theory and meeting the requirementsUnder the condition of Lyapunov stability theory, solving the adaptive feedforward gain K u And adaptive feedback gain K p ；
S4: according to adaptive feedforward gain K u And adaptive feedback gain K p The vehicle can dynamically adjust the additional yaw moment of the additional vehicle, so that the real-time control of the stability of the vehicle is realized;
s5: when the state of the vehicle is unstable, acquiring a required yaw moment, a front axle actual slip rate, a rear axle actual slip rate, a front axle initial torque and a rear axle initial torque of the vehicle at the current moment;
s6: determining the corresponding relation between the yaw moment of the vehicle and the front axle slip rate and the rear axle slip rate;
s7: determining a front axle target slip rate and a rear axle target slip rate according to the determined corresponding relation between the yaw moment and the front axle slip rate and the rear axle slip rate and the required yaw moment;
s8: determining a front axle target torque according to the difference between the front axle target slip rate and the front axle actual slip rate and the front axle initial torque;
s9: determining a rear axle target torque according to the difference between the rear axle target slip rate and the rear axle actual slip rate and the rear axle initial torque;
s10: and controlling the stability of the vehicle according to the front axle target torque and the rear axle target torque.
Preferably, the model in S1 is:
wherein x is a vehicle stability error state variable; a represents an input state matrix; b represents a feedback matrix.
Preferably, the expression of the additional yaw moment Δmz of the vehicle in S2 is:
ΔM z ＝-K p x+K u δ f
wherein delta f Is a carFront wheel corner; k (K) p For adaptive feedback gain matrix, K u Is an adaptive feedforward gain matrix.
Preferably, the method further comprises:
acquiring the longitudinal speed, the wheel steering angle and the actual yaw rate of the vehicle at the current moment;
determining a target yaw rate from the longitudinal vehicle speed, the wheel steering angle, and a stored steering characteristic factor, wherein the steering characteristic factor is a constant that characterizes a steering characteristic of the vehicle;
calculating an angular velocity error between the actual yaw rate and the target yaw rate;
and if the angular velocity error does not fall into a preset threshold interval, determining that the state of the vehicle is unstable, wherein the preset threshold interval is an interval formed by a first threshold and a second threshold, the first threshold is a positive number, and the second threshold is a negative number.
A vehicle stability control simulation system, comprising:
the system comprises a central control unit, a decision unit and at least one functional domain and a control system;
the decision unit is used for generating a control decision according to the vehicle state information and the surrounding environment information of the vehicle;
the central control unit is used for generating and displaying the current state information of the vehicle according to the control result of the decision unit.
Preferably, the central control unit is integrated with:
a central control system, a remote information processor,
a gateway; the central control unit is specifically configured to generate current state information of the vehicle according to a control result fed back by the at least one functional domain;
the central control unit is also used for realizing the functions of man-machine interaction, vehicle navigation, vehicle body video monitoring and wireless communication.
Preferably, the control system includes:
the stability constraint module is used for determining control layer constraint data and execution layer constraint data of the rear wheels of the vehicle according to the predicted environment information in the target time period;
the feedback control module is used for determining rear wheel steering feedback control data according to the control layer constraint data and/or the execution layer constraint data;
the feedforward control module is used for determining the feedforward control data of the rear wheel steering according to the running information of the vehicle;
the rear wheel steering angle determining module is used for determining first steering angle data of the rear wheels according to the rear wheel steering feedback control data and the rear wheel steering feedforward control data and determining target steering angle data according to second steering angle data determined by the running information of the vehicle;
and an execution control module for controlling steering operation of the rear wheels of the vehicle based on the target steering angle data.
Preferably, the decision unit is further configured to control the at least one functional domain according to the control decision.
(III) beneficial effects
Compared with the prior art, the invention provides a vehicle stability control simulation method and system, which have the following beneficial effects:
1. according to the vehicle stability control simulation method and system, the self-adaptive control law is obtained through a Lyapunov stability theory and a Lyapunov equation based on a stability control dynamics model: adaptive feedback gain K p And adaptive feedforward gain K u The defects of poor real-time performance, lower control precision and the like in the vehicle stability control are overcome.
2. According to the vehicle stability control simulation method and system, a central control system, a remote information processor and a gateway are integrated into a central control unit, and a decision generation function and a decision execution function are integrated into the decision control unit, so that the decision control unit can generate a control decision according to vehicle state information and environment information around a vehicle, and at least one functional domain is controlled according to the control decision; the central control unit can generate and display the current state information of the vehicle according to the control result of the decision control unit.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A vehicle stability control simulation method comprises the following steps:
s1: based on the two-degree-of-freedom vehicle dynamics model, establishing a stability control dynamics model;
s2: by utilizing Lyapunov stability theory, designing a model reference self-adaptive controller, and adding an additional automobile yaw moment delta Mz to adjust the stability of the automobile;
s3: model reference adaptive controller designed according to Lyapunov stability theory solves adaptive feedforward gain K under the condition of meeting Lyapunov stability theory u And adaptive feedback gain K p ；
S4: according to adaptive feedforward gain K u And adaptive feedback gain K p The vehicle can dynamically adjust the additional yaw moment of the additional vehicle, so that the real-time control of the stability of the vehicle is realized;
s5: when the state of the vehicle is unstable, acquiring a required yaw moment, a front axle actual slip rate, a rear axle actual slip rate, a front axle initial torque and a rear axle initial torque of the vehicle at the current moment;
s6: determining the corresponding relation between the yaw moment of the vehicle and the front axle slip rate and the rear axle slip rate;
s7: determining a front axle target slip rate and a rear axle target slip rate according to the corresponding relation between the determined yaw moment and the front axle slip rate and the rear axle slip rate and the required yaw moment;
s8: determining a front axle target torque according to the difference value between the front axle target slip rate and the front axle actual slip rate and the front axle initial torque;
s9: determining a rear axle target torque according to the difference value between the rear axle target slip rate and the rear axle actual slip rate and the rear axle initial torque;
s10: and controlling the stability of the vehicle according to the front axle target torque and the rear axle target torque.
In the embodiment of the present invention, the model in S1 is:
wherein x is a vehicle stability error state variable; a represents an input state matrix; b represents a feedback matrix.
Further, the state matrix a, the feedback matrix B, and the error state matrix x are respectively expressed as:
wherein K is f And K r The cornering stiffness of the front wheel and the rear wheel respectively; m is the total mass of the automobile; l (L) f And l r The distances from the front axle and the rear axle to the mass center of the automobile are respectively; i z The moment of inertia of the mass center of the automobile around the z axis; u is the longitudinal speed at the center of mass of the automobile; Δω=ω d ω is the difference between the ideal yaw rate and the actual yaw rate; Δβ=β d Beta is the difference between the ideal centroid slip angle and the actual centroid slip angle.
In the embodiment of the present invention, the expression of the vehicle additional yaw moment Δmz in S2 is:
ΔM z ＝-K p x+K u δ f
wherein delta f Is the front wheel corner of the automobile; k (K) p For adaptive feedback gain matrix, K u Is an adaptive feedforward gain matrix.
Further, in S3, the adaptive feedback gain K p And adaptive feedforward gain K u The specific expression is as follows:
A T P+PA＝-Q
wherein s1 and s2 are symmetric positive constant matrix with proper dimension; the matrix P is obtained by solving a Lyapunov equation of the formula (5); k (K) p (0)＝[00]，K u (0)＝[0]Respectively K p And K u Is set to an initial value of (1); q is an arbitrary symmetric positive definite matrix.
In an embodiment of the present invention, the method further includes:
acquiring the longitudinal speed, the wheel steering angle and the actual yaw rate of the vehicle at the current moment;
determining a target yaw rate based on the longitudinal vehicle speed, the wheel steering angle, and a stored steering characteristic factor, wherein the steering characteristic factor is a constant that characterizes a steering characteristic of the vehicle;
calculating an angular velocity error between the actual yaw rate and the target yaw rate;
if the angular velocity error does not fall within a preset threshold interval, determining that the state of the vehicle is unstable, wherein the preset threshold interval is an interval formed by a first threshold and a second threshold, the first threshold is a positive number, and the second threshold is a negative number.
A vehicle stability control simulation system, comprising:
the system comprises a central control unit, a decision unit and at least one functional domain and a control system;
the decision unit is used for generating a control decision according to the vehicle state information and the surrounding environment information of the vehicle;
and the central control unit is used for generating the current state information of the vehicle according to the control result of the decision unit and displaying the current state information.
In the embodiment of the invention, the central control unit is integrated with:
a central control system, a remote information processor,
a gateway; the central control unit is specifically used for generating current state information of the vehicle according to a control result fed back by at least one functional domain;
and the central control unit is also used for realizing the functions of man-machine interaction, vehicle navigation, vehicle body video monitoring and wireless communication.
In an embodiment of the present invention, a control system includes:
the stability constraint module is used for determining control layer constraint data and execution layer constraint data of the rear wheels of the vehicle according to the predicted environment information in the target time period;
the feedback control module is used for determining rear wheel steering feedback control data according to the control layer constraint data and/or the execution layer constraint data;
the feedforward control module is used for determining the feedforward control data of the rear wheel steering according to the running information of the vehicle;
the rear wheel steering angle determining module is used for determining first steering angle data of the rear wheels according to the rear wheel steering feedback control data and the rear wheel steering feedforward control data and determining target steering angle data according to second steering angle data determined by the running information of the vehicle;
and an execution control module for controlling steering operation of the rear wheels of the vehicle based on the target steering angle data.
In the embodiment of the invention, the decision unit is further configured to control at least one functional domain according to the control decision.
Further, the stability constraint module includes: a control layer constraint data determining unit for determining at least one of travel path deviation constraint data, yaw rate deviation constraint data, and centroid slip angle deviation constraint data; and the execution layer constraint data determining unit is used for determining the rear wheel steering angle limit constraint and/or the rear wheel steering angle change rate constraint.
Further, the method further comprises the following steps: the environment information input module is used for acquiring environment information and inputting the environment information to the vehicle stability control system, wherein the environment information comprises at least one of map information, weather information, topographic information and track information; the environment information decision module is used for receiving the environment information input by the environment information input module, determining the predicted environment information in the target time period according to the environment information, and the driving information input module is used for acquiring the driving information of the vehicle and inputting the driving information to the feedforward control module.
Further, the second corner data determining module is used for determining a corner proportion curve according to a two-dimensional interpolation table of the vehicle speed and the steering wheel corner, determining second corner data according to the running information and the corner proportion curve, and the first corner data determining unit is used for superposing the rear wheel steering feedback control data and the rear wheel steering feedforward control data to determine first corner data of the rear wheel; the weighting calculation unit is used for carrying out weighted summation on the first rotation angle data and the second rotation angle data, determining target rotation angle data and the actual rotation angle determination unit, and determining actual rotation angle data of the rear wheels of the vehicle; and the difference value calculation unit is used for calculating the difference value between the actual rotation angle data and the target rotation angle data and controlling the steering operation of the rear wheels of the vehicle according to the difference value.
Further, the actual rotation angle determination unit includes: a rear-wheel steering motor position sensor for determining first rack position data; the rear wheel steering assembly is provided with a line position sensor for determining second rack position data; the system comprises a first rack position data, a second rack position data, a state feedback module, a feed-forward control module, a feedback control module and an actual rotation angle calculation subunit, wherein the actual rotation angle calculation subunit is used for determining actual rack position data according to the first rack position data and the second rack position data, determining actual rotation angle data according to the line angle ratio parameter and the actual rack position data, and the state feedback module is used for acquiring running information of a vehicle after responding to the control of the execution control module and feeding back the running information to the feed-forward control module and the feedback control module.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The vehicle stability control simulation method is characterized by comprising the following steps of:
s1: based on the two-degree-of-freedom vehicle dynamics model, establishing a stability control dynamics model;
s2: by utilizing Lyapunov stability theory, designing a model reference self-adaptive controller, and adding an additional automobile yaw moment delta Mz to adjust the stability of the automobile;
s3: model reference adaptive controller designed according to Lyapunov stability theory solves adaptive feedforward gain K under the condition of meeting Lyapunov stability theory u And adaptive feedback gain K p ；
S4: according to adaptive feedforward gain K u And adaptive feedback gain K p The vehicle can dynamically adjust the additional yaw moment of the additional vehicle, so that the real-time control of the stability of the vehicle is realized;
s5: when the state of the vehicle is unstable, acquiring a required yaw moment, a front axle actual slip rate, a rear axle actual slip rate, a front axle initial torque and a rear axle initial torque of the vehicle at the current moment;
s6: determining the corresponding relation between the yaw moment of the vehicle and the front axle slip rate and the rear axle slip rate;
s7: determining a front axle target slip rate and a rear axle target slip rate according to the determined corresponding relation between the yaw moment and the front axle slip rate and the rear axle slip rate and the required yaw moment;
s8: determining a front axle target torque according to the difference between the front axle target slip rate and the front axle actual slip rate and the front axle initial torque;
s9: determining a rear axle target torque according to the difference between the rear axle target slip rate and the rear axle actual slip rate and the rear axle initial torque;
s10: and controlling the stability of the vehicle according to the front axle target torque and the rear axle target torque.
2. The vehicle stability control simulation method according to claim 1, wherein the model in S1 is:
wherein x is a vehicle stability error state variable; a represents an input state matrix; b represents a feedback matrix.
3. The vehicle stability control simulation method according to claim 1, wherein the expression of the vehicle additional yaw moment Δmz in S2 is:
ΔM z ＝-K p x+K u δ f
wherein delta f Is the front wheel corner of the automobile; k (K) p For adaptive feedback gain matrix, K u Is an adaptive feedforward gain matrix.
4. The vehicle stability control simulation method according to claim 1, characterized by further comprising:
acquiring the longitudinal speed, the wheel steering angle and the actual yaw rate of the vehicle at the current moment;
determining a target yaw rate from the longitudinal vehicle speed, the wheel steering angle, and a stored steering characteristic factor, wherein the steering characteristic factor is a constant that characterizes a steering characteristic of the vehicle;
calculating an angular velocity error between the actual yaw rate and the target yaw rate;
and if the angular velocity error does not fall into a preset threshold interval, determining that the state of the vehicle is unstable, wherein the preset threshold interval is an interval formed by a first threshold and a second threshold, the first threshold is a positive number, and the second threshold is a negative number.
5. A vehicle stability control simulation system, comprising:
the system comprises a central control unit, a decision unit and at least one functional domain and a control system;
the decision unit is used for generating a control decision according to the vehicle state information and the surrounding environment information of the vehicle;
the central control unit is used for generating and displaying the current state information of the vehicle according to the control result of the decision unit.
6. The vehicle stability control simulation system of claim 5, wherein the central control unit is integrated with:
a central control system, a remote information processor,
a gateway; the central control unit is specifically configured to generate current state information of the vehicle according to a control result fed back by the at least one functional domain;
the central control unit is also used for realizing the functions of man-machine interaction, vehicle navigation, vehicle body video monitoring and wireless communication.
7. The vehicle stability control simulation system of claim 5, wherein the control system comprises:
the stability constraint module is used for determining control layer constraint data and execution layer constraint data of the rear wheels of the vehicle according to the predicted environment information in the target time period;
the feedback control module is used for determining rear wheel steering feedback control data according to the control layer constraint data and/or the execution layer constraint data;
the feedforward control module is used for determining the feedforward control data of the rear wheel steering according to the running information of the vehicle;
the rear wheel steering angle determining module is used for determining first steering angle data of the rear wheels according to the rear wheel steering feedback control data and the rear wheel steering feedforward control data and determining target steering angle data according to second steering angle data determined by the running information of the vehicle;
and an execution control module for controlling steering operation of the rear wheels of the vehicle based on the target steering angle data.
8. The vehicle stability control simulation system of claim 5, wherein the decision unit is further configured to control the at least one functional domain based on the control decision.
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