CN117445876A - CDP dynamic deceleration control method and system - Google Patents

CDP dynamic deceleration control method and system Download PDF

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Publication number
CN117445876A
CN117445876A CN202311486109.6A CN202311486109A CN117445876A CN 117445876 A CN117445876 A CN 117445876A CN 202311486109 A CN202311486109 A CN 202311486109A CN 117445876 A CN117445876 A CN 117445876A
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China
Prior art keywords
cdp
vehicle
real
deceleration
deceleration control
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Pending
Application number
CN202311486109.6A
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Chinese (zh)
Inventor
刘兆勇
余子祥
张莉莉
周翔
吴佳枝
薛梦洁
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Global Tech Co ltd
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Global Tech Co ltd
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Priority to CN202311486109.6A priority Critical patent/CN117445876A/en
Publication of CN117445876A publication Critical patent/CN117445876A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
    • B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
    • B60T8/17—Using electrical or electronic regulation means to control braking
    • B60T8/171—Detecting parameters used in the regulation; Measuring values used in the regulation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
    • B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
    • B60T8/17—Using electrical or electronic regulation means to control braking
    • B60T8/1755—Brake regulation specially adapted to control the stability of the vehicle, e.g. taking into account yaw rate or transverse acceleration in a curve
    • B60T8/17551—Brake regulation specially adapted to control the stability of the vehicle, e.g. taking into account yaw rate or transverse acceleration in a curve determining control parameters related to vehicle stability used in the regulation, e.g. by calculations involving measured or detected parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
    • B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
    • B60T8/32—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force responsive to a speed condition, e.g. acceleration or deceleration
    • B60T8/58—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force responsive to a speed condition, e.g. acceleration or deceleration responsive to speed and another condition or to plural speed conditions

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  • Engineering & Computer Science (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The invention discloses a CDP dynamic deceleration control method and a system, which relate to the technical field of automobile electronic stability control, and the method and the system communicate with a CDP interface through an EPB controller, send a deceleration request signal and collect vehicle parameters; when the vehicle parameters are in the normal range, the CDP function is started, and the CDP system monitors the vehicle parameters; controlling the deceleration intensity through an ADRC control model according to the deceleration request signal; when the wheel speed sensor detects that the vehicle speed is reduced to a fixed speed, the braking force is determined according to the relation between the current vehicle speed, the deceleration, the gravity, the gradient value and the braking force. The invention controls the braking force in the vehicle deceleration process, especially in the later period of deceleration, so as to improve the smoothness of the vehicle in the later period of deceleration. And eliminates overshoot in the conventional PID by ADRC algorithm.

Description

CDP dynamic deceleration control method and system
Technical Field
The invention relates to the technical field of automobile electronic stability control, in particular to a CDP dynamic deceleration control method and system.
Background
Currently, CDP (vehicle dynamic deceleration control) is a system having an active brake pressure increasing function, which is divided into two modes of full active and partial active. In the full active mode, the CDP system can independently adjust the braking force of each wheel to achieve more efficient deceleration. In the partially active mode, the CDP system assists and adjusts the braking force applied by the driver based on the vehicle conditions. The CDP works in conjunction with the ESC system to provide better vehicle stability performance. In the ESC system, an HCU (hydraulic control unit) is used to apply braking force to all wheels to adjust target deceleration.
In the traditional automotive control field, classical PID control algorithms are widely used in control systems. It also has some drawbacks. First, the differential feedback of the error in the PID controller cannot fully function. Second, the simple linear weighted sum form (proportional P, integral I, derivative D) is not necessarily the optimal combination. Finally, uncertainty factors in the running process of the automobile have limited coping capability for the PID algorithm. In addition, when the brake pressure is adjusted too fast, the system may be overshot due to inertia and hysteresis of the system, thereby reducing comfort and safety of passengers.
In the braking process of an automobile, the whole process can be divided into three stages: early, mid and late braking. Wherein, the smoothness of the later stage and the middle stage of braking is equivalent to or slightly worse than the latter stage, and the smoothness of the later stage of braking is obviously worse than the former two stages.
Therefore, how to improve smoothness during deceleration is a problem that needs to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the present invention provides a CDP dynamic deceleration control method and system, so as to solve the problems in the background art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
in one aspect, a CDP dynamic deceleration control method is provided, including:
communicating with the CDP interface through the EPB controller, sending a deceleration request signal, and collecting vehicle parameters;
when the vehicle parameters are in the normal range, the CDP function is started, and the CDP system monitors the vehicle parameters;
simulating the braking system through an extended state observer in an ADRC control model according to the deceleration signal and estimating the total disturbance of the real-time system, so as to inhibit and compensate the total disturbance of the braking system;
when the wheel speed sensor detects that the vehicle speed is reduced to a fixed speed, the braking force is determined according to the relation between the current vehicle speed, the deceleration, the gravity, the gradient value and the braking force.
Optionally, the collecting vehicle parameters specifically includes: the vehicle body state signals including EPB button state signals, gradient signals, vehicle speed signals, brake light signals, brake pressure signals, steering wheel angle signals, vehicle weight and load data, and tire pressure detection system data are collected by various sensors.
Optionally, the gradient value is acquired and calculated by an acceleration sensor in the step 1; the gravity is obtained according to the weight and the load mass of the vehicle, and the weight and the load mass of the vehicle are obtained through the following dynamic formulas:
wherein F is t For the driving force of the vehicle, M is the vehicle mass and the load mass,for driving acceleration obtained by sensor, F Resistance resistor Comprises rolling resistance Fr and air resistance F w Slope resistance F α Acceleration resistance F a 。
Optionally, the vehicle driving force F t The calculation formula is as follows:
wherein T is tq For engine torque, i g I is the transmission ratio, i o N is the transmission ratio of the main speed reducer T R is the radius, which is the mechanical efficiency of the drive train;
the rolling resistance F r The calculation formula is as follows:
F r ＝C rr *M
wherein C is rr M represents the vehicle mass and the load mass as the rolling resistance coefficient;
the air resistance F w The calculation formula is as follows:
wherein C is D Air resistance, A windward area, ρ air density, u r Is the relative density;
the gradient resistance F α The calculation formula is as follows:
F α ＝Mgsinα
wherein M is the vehicle mass and the load mass, g is the gravitational acceleration, and alpha is the gradient value;
the acceleration resistance F a The calculation formula is as follows:
wherein delta is a conversion coefficient of the rotating mass of the automobile, M is the mass of the automobile and the load mass,is the running acceleration.
Alternatively to this, the method may comprise,
where y is the system output, b is the system gain, u is the system control quantity, f (y, w, t) is the uncertainty factor of the system, where w is the unknown external disturbance of the system.
Optionally, the mathematical expression of the extended state observer is:
where e is the systematic error, z 1 Is a real-time estimate of the state variable inside the system, z 2 Is a real-time estimate of system uncertainty, the parameter β is determined by the controlled object sampling time, fal (e, α 1 Delta) is a continuous power function, alpha is an exponent, delta is a limit distinguishing the magnitude of error e, and y is the system output.
Optionally, the mathematical expression of the state error feedback is:
wherein k (e 1 P) is a function of the systematic error, p is the controller parameter, ref is the reference input, e 1 Representing the deviation between the reference input and the estimated quantity.
On the other hand, a CDP dynamic deceleration control system is provided, which comprises a state error feedback module, an extended state observer and a controlled object, wherein the error is input into the state error feedback module by comparing the real-time estimated quantity of the state variable in the system with a reference value, is compared with the real-time estimated quantity of the uncertain factors of the system, and acts on the controlled object; wherein the real-time estimates of the system internal state variables and the real-time estimates of the system uncertainty factors are determined by the extended state observer.
Optionally, the mathematical expression of the extended state observer is:
where e is the systematic error, z 1 Is a real-time estimate of the state variable inside the system, z 2 Is a real-time estimate of system uncertainty, the parameter β is determined by the controlled object sampling time, fal (e, α 1 Delta) is a continuous power function, alpha is an exponent, delta is a limit distinguishing the magnitude of error e, and y is the system output.
Optionally, the mathematical expression of the state error feedback is:
wherein k (e 1 P) is a function of the systematic error, p is the controller parameter, ref is the reference input, e 1 Representing the deviation between the reference input and the estimated quantity.
Compared with the prior art, the CDP dynamic deceleration control method and system provided by the invention have the advantages that the braking force is controlled particularly in the late deceleration stage in the deceleration process of the automobile, so that the smoothness in the late deceleration stage of the automobile is improved. And eliminates overshoot in the conventional PID by ADRC algorithm.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a control method provided by the present invention.
Fig. 2 is a structural diagram of a control system provided by the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
On the one hand, the embodiment of the invention discloses a CDP dynamic deceleration control method, which is shown in fig. 1 and comprises the following steps:
communicating with the CDP interface through the EPB controller, sending a deceleration request signal, and collecting vehicle parameters;
when the vehicle parameters are in the normal range, the CDP function is started, and the CDP system monitors the vehicle parameters;
according to the deceleration signal, simulating a braking system through an extended state observer in an ADRC control model and estimating total disturbance of a real-time system, so that the total disturbance of the braking system is restrained and compensated, and the braking effect is improved;
when the wheel speed sensor detects that the vehicle speed has fallen to a fixed speed, such as 5km/h, a braking force is determined according to the relationship between the current vehicle speed, the deceleration, the gravity, the gradient value and the braking force.
In a specific embodiment, the collecting vehicle parameters is specifically: the vehicle body state signals including EPB button state signals, gradient signals, vehicle speed signals, brake light signals, brake pressure signals, steering wheel angle signals, vehicle weight and load data, and tire pressure detection system data are collected by various sensors.
In a specific embodiment, the gradient value is acquired and calculated by the acceleration sensor in the step 1; gravity is derived from the vehicle weight and load mass, which are derived from the following kinetic formulas:
wherein F is t For the driving force of the vehicle, M is the vehicle mass and the load mass,for driving acceleration obtained by sensor, F Resistance resistor Comprises rolling resistance Fr and air resistance F w Slope resistance F α Acceleration resistance F a 。
In a specific embodiment, the vehicle driving force F t The calculation formula is as follows:
wherein T is tq For engine torque, i g I is the transmission ratio, i o N is the transmission ratio of the main speed reducer T R is the radius, which is the mechanical efficiency of the drive train;
rolling resistance F r The calculation formula is as follows:
F r ＝C rr *M
wherein C is rr M represents the vehicle mass and the load mass as the rolling resistance coefficient;
air resistance F w The calculation formula is as follows:
wherein C is D Air resistance, A windward area, ρ air density, u r Is the relative density;
gradient resistance F α The calculation formula is as follows:
F α ＝Mgsinα
wherein M is the vehicle mass and the load mass, g is the gravitational acceleration, and alpha is the gradient value;
acceleration resistance F a The calculation formula is as follows:
wherein delta is a conversion coefficient of the rotating mass of the automobile, M is the mass of the automobile and the load mass,is the running acceleration.
In a specific embodiment, the first order system model of the ADRC control model is as follows:
where y is the system output, b is the system gain, u is the system control quantity, f (y, w, t) is the uncertainty factor of the system, where w is the unknown external disturbance of the system.
In a specific embodiment, optionally, the mathematical expression of the extended state observer is:
where e is the systematic error, z 1 Is a real-time estimate of the state variable inside the system, z 2 Is a real-time estimate of system uncertainty, the parameter β is determined by the controlled object sampling time, fal (e, α 1 Delta) is a continuous power function, alpha is an exponent, delta is a limit distinguishing the magnitude of error e, and y is the system output.
Optionally, the mathematical expression of the state error feedback is:
wherein k (e 1 P) is a function of the systematic error, p is the controller parameter, ref is the reference input, e 1 Representing the deviation between the reference input and the estimated quantity.
On the other hand, a CDP dynamic deceleration control system is provided, as shown in figure 2, comprising a state error feedback module, an extended state observer and a controlled object, wherein the error is input into the state error feedback module by comparing the real-time estimated quantity of the state variable in the system with a reference value, and is compared with the real-time estimated quantity of the uncertain factors of the system and acts on the controlled object; wherein the real-time estimates of the system internal state variables and the real-time estimates of the system uncertainty factors are determined by the extended state observer.
In a specific embodiment, the mathematical expression of the extended state observer is:
where e is the systematic error, z 1 Is a real-time estimate of the state variable inside the system, z 2 Is a real-time estimate of system uncertainty, the parameter β is determined by the controlled object sampling time, fal (e, α 1 Delta) is a continuous power function, alpha is an exponent, delta is a limit distinguishing the magnitude of error e, and y is the system output.
The mathematical expression of the state error feedback is:
wherein k (e 1 P) is a function of the systematic error, p is the controller parameter, ref is the reference input, e 1 Representing the deviation between the reference input and the estimated quantity.
When the vehicle is decelerated to 5km/h with a certain deceleration intensity, the speed of the vehicle is small, the front and rear axle braking forces of the vehicle are redundant, the front axle braking force can be properly reduced at the moment, the rear axle braking force is increased, and the corresponding braking pressure is obtained through the MAP table according to the current vehicle speed, the deceleration, the total mass of the vehicle and the gradient value. The speed, the deceleration, the total mass of the automobile and the gradient value under various different road conditions are collected, the obtained data are matched with a pre-established MAP table, and the braking pressure is regulated in real time through closed-loop control, so that the robustness of the system is improved.
The pre-established MAP table is shown in table 1 as a percentage of the corresponding released pressure for a total mass of the vehicle (mass of the whole vehicle equipment plus the mass of the driver and passengers) of 1.65 t.
TABLE 1 Pre-established MAP Table
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A CDP dynamic deceleration control method, comprising:
communicating with the CDP interface through the EPB controller, sending a deceleration request signal, and collecting vehicle parameters;
when the vehicle parameters are in the normal range, the CDP function is started, and the CDP system monitors the vehicle parameters;
simulating the braking system through an extended state observer in an ADRC control model according to the deceleration signal and estimating the total disturbance of the real-time system, so as to inhibit and compensate the total disturbance of the braking system;
when the wheel speed sensor detects that the vehicle speed is reduced to a fixed speed, the braking force is determined according to the relation between the current vehicle speed, the deceleration, the gravity, the gradient value and the braking force.
2. The CDP dynamic deceleration control method according to claim 1, wherein said collecting vehicle parameters is specifically: the vehicle body state signals including EPB button state signals, gradient signals, vehicle speed signals, brake light signals, brake pressure signals, steering wheel angle signals, vehicle weight and load data, and tire pressure detection system data are collected by various sensors.
3. The CDP dynamic deceleration control method according to claim 2, wherein the gradient value is obtained by the acceleration sensor acquisition calculation in step 1; the gravity is obtained according to the weight and the load mass of the vehicle, and the weight and the load mass of the vehicle are obtained through the following dynamic formulas:
wherein F is t For the driving force of the vehicle, M is the vehicle mass and the load mass,for driving acceleration obtained by sensor, F Resistance resistor Comprises rolling resistance Fr and air resistance F w Slope resistance F α Acceleration resistance F a 。
4. A CDP dynamic deceleration control method according to claim 3, wherein the vehicle driving force F t The calculation formula is as follows:
wherein T is tq Is an engineTorque, i g I is the transmission ratio, i o N is the transmission ratio of the main speed reducer T R is the radius, which is the mechanical efficiency of the drive train;
the rolling resistance F r The calculation formula is as follows:
F r ＝C rr *M
wherein C is rr M represents the vehicle mass and the load mass as the rolling resistance coefficient;
the air resistance F w The calculation formula is as follows:
wherein C is D Air resistance, A windward area, ρ air density, u r Is the relative density;
the gradient resistance F α The calculation formula is as follows:
F α ＝Mg sinα
wherein M is the vehicle mass and the load mass, g is the gravitational acceleration, and alpha is the gradient value;
the acceleration resistance F a The calculation formula is as follows:
wherein delta is a conversion coefficient of the rotating mass of the automobile, M is the mass of the automobile and the load mass,is the running acceleration.
5. The CDP dynamic deceleration control method according to claim 1, wherein the first order system model of the ADRC control model is as follows:
where y is the system output, b is the system gain, u is the system control quantity, f (y, w, t) is the uncertainty factor of the system, where w is the unknown external disturbance of the system.
6. The method for dynamic deceleration control of CDP according to claim 1, wherein,
where e is the systematic error, z 1 Is a real-time estimate of the state variable inside the system, z 2 Is a real-time estimate of system uncertainty, the parameter β is determined by the controlled object sampling time, fal (e, α 1 Delta) is a continuous power function, alpha is an exponent, delta is a limit distinguishing the magnitude of error e, and y is the system output.
7. The CDP dynamic deceleration control method according to claim 1, wherein the mathematical expression of the state error feedback is:
wherein k (e 1 P) is a function of the systematic error, p is the controller parameter, ref is the reference input, e 1 Representing the deviation between the reference input and the estimated quantity.
8. The CDP dynamic deceleration control system is characterized by comprising a state error feedback module, an extended state observer and a controlled object, wherein an error is input into the state error feedback module by comparing a real-time estimated value of a state variable in the system with a reference value, is compared with the real-time estimated value of an uncertain factor of the system, and acts on the controlled object; wherein the real-time estimates of the system internal state variables and the real-time estimates of the system uncertainty factors are determined by the extended state observer.
9. The CDP dynamic deceleration control system of claim 8, wherein the mathematical expression of the extended state observer is:
where e is the systematic error, z 1 Is a real-time estimate of the state variable inside the system, z 2 Is a real-time estimate of system uncertainty, the parameter β is determined by the controlled object sampling time, fal (e, α 1 Delta) is a continuous power function, alpha is an exponent, delta is a limit distinguishing the magnitude of error e, and y is the system output.
10. The CDP dynamic deceleration control system of claim 8, wherein the mathematical expression for the state error feedback is:
wherein k (e 1 P) is a function of the systematic error, p is the controller parameter, ref is the reference input, e 1 Representing the deviation between the reference input and the estimated quantity.
CN202311486109.6A 2023-11-09 2023-11-09 CDP dynamic deceleration control method and system Pending CN117445876A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311486109.6A CN117445876A (en) 2023-11-09 2023-11-09 CDP dynamic deceleration control method and system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311486109.6A CN117445876A (en) 2023-11-09 2023-11-09 CDP dynamic deceleration control method and system

Publications (1)

Publication Number Publication Date
CN117445876A true CN117445876A (en) 2024-01-26

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Application Number Title Priority Date Filing Date
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