CN117360139A - ECAS system vehicle body control method based on fuzzy control - Google Patents
ECAS system vehicle body control method based on fuzzy control Download PDFInfo
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
- B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
- B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
- B60G17/016—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by their responsiveness, when the vehicle is travelling, to specific motion, a specific condition, or driver input
- B60G17/0161—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by their responsiveness, when the vehicle is travelling, to specific motion, a specific condition, or driver input mainly during straight-line motion
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
- B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
- B60G17/018—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by the use of a specific signal treatment or control method
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2600/00—Indexing codes relating to particular elements, systems or processes used on suspension systems or suspension control systems
- B60G2600/18—Automatic control means
- B60G2600/187—Digital Controller Details and Signal Treatment
- B60G2600/1879—Fuzzy Logic Control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
- B60G2800/90—System Controller type
- B60G2800/91—Suspension Control
- B60G2800/914—Height Control System
Abstract
The invention discloses a vehicle body control method of an ECAS system based on fuzzy control, which belongs to the technical field of automobile electronics and solves the problems of the prior art that a traditional control system is adopted, the principle is complex and the control precision is low. The invention is insensitive to the influence of parameter change and nonlinear characteristics, so that the fuzzy control is more reliable and stable in practical application, has strong robustness, can process uncertainty and nonlinear problems, has strong adaptability, and has faster response speed because the decision of the fuzzy control is deduced by fuzzy rule reasoning.
Description
Technical Field
The invention belongs to the technical field of automobile electronics, and particularly relates to an ECAS system vehicle body control method based on fuzzy control.
Background
With the rapid development of the automotive electronics industry, automotive electronic control systems have become an essential part of automotive china. The automobile sensor is used as an information source of an automobile electronic control system, and measures external physical quantities such as temperature, pressure, position, height, acceleration and the like accurately in real time, so that the performance of the automobile sensor becomes a key factor for measuring the level of the automobile electronic control system. The controller is the core of the electronically controlled air spring system, and its quality is directly related to the quality of the vehicle performance in which the ECAS system is installed. Compared with modern small-sized passenger vehicles, commercial vehicles have larger load and higher operation strength, but the development level of the automobile electronic control system is relatively backward. In particular, commercial vehicle suspension systems have developed to a high degree of mismatch with existing demands. Currently, electronically controlled air suspension systems (ECAS systems) have become a popular point of development for commercial vehicle electronic control systems. The ECAS system actively adjusts the height of the suspension according to the running condition, so that the vehicle can select different vehicle body heights according to different road conditions, and the ECAS system can adapt to more running conditions compared with the traditional air suspension controlled by a mechanical height valve. The ECAS system mainly comprises an Electronic Control Unit (ECU), an electromagnetic valve, a height sensor, a shock absorber, a guide mechanism, an air spring and the like. The basic wage principle is that a height sensor is responsible for detecting the change of the height of the vehicle and transmitting the information to an ECU, and then the ECU synthesizes the input information to judge the current vehicle state and excite an electromagnetic valve to work according to the control logic in the ECU, and the electromagnetic valve realizes the inflation and deflation adjustment of each air spring. The ECAS system can not only improve riding comfort, but also reduce the damage degree of wheels to the road surface, so the ECAS system is widely applied to high-grade passenger cars such as buses and trucks in developed countries such as Europe and America, and various large and well-known automobile manufacturers have own related ECAS products. The road surface damage degree is high due to the fact that the carrying capacity of each heavy truck is high, road surface damage caused by wheels can be reduced to a great extent by adopting the ECAS system, and therefore the method has great significance in truck equipment ECAS systems.
The existing ECAS system mainly controls the height of a vehicle body, the height switching control adopts a layered structure, the height of the vehicle body is adjusted according to signals acquired by sensors, unstable conditions such as yaw and the like are easy to occur when the vehicle is in emergency avoidance of obstacles, turning and the like, the vehicle deviates from an ideal track, and the steering stability and the safety of the vehicle are not strong. Although many scholars put forward some improvements to ECAS system, after the automobile is stimulated, the ECU still can appear handling the bad condition, for example when the automobile body height reaches the target value, the gasbag can continue to expand until the vertical force of air spring and its static load reach equilibrium, therefore, current ECAS system has certain limitation, need to select suitable control algorithm to realize accurate automobile body height adjustment, avoid "overcharge", "overdischarge" phenomenon to appear.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the ECAS system vehicle body control method based on fuzzy control, which adopts a fuzzy control system, has simple principle and effectively improves control precision.
In order to achieve the technical purpose, the ECAS system vehicle body control method based on fuzzy control adopts the following technical scheme:
a vehicle body control method of an ECAS system based on fuzzy control comprises a fuzzy controller, the ECAS system electrically connected with the fuzzy controller and a vehicle body control mode adopting the ECAS system;
the design of the fuzzy controller comprises the following steps:
(1) Determining input and output variables for fuzzy control
For a two-dimensional fuzzy controller, the deviation and the deviation change rate of the actual output value and the expected value of the system are generally adopted as the input of the control system, for the study of the height adjustment of the vehicle body, the deviation and the deviation change rate of four suspension moving strokes and the target lifting height are generally selected as the input, the switch signal of the electromagnetic valve is used as the output of the control system, and the air springs are inflated and deflated to achieve the purpose of adjusting the height of the vehicle body;
(2) Determining membership functions of fuzzy linguistic values, quantization factors, scale factors, and fuzzy variables of fuzzy control
Blurring is to find membership degrees of each fuzzy language according to a membership degree function, and the precise input quantity can be converted into different language values through blurring, and the input value and the output value are generally described by { Negative Big (NB), negative Medium (NM), negative Small (NS), zero (ZO), positive Small (PS), median (PM), positive Big (PB) } according to the magnitude and the positive and negative of the input value and the output value;
in the fuzzy control system, the actual variation ranges of the error e, the error change rate ec and the control quantity u are called as basic arguments of the variables, and the range of the height adjustment is set to be +/-0.04 m in the present application, so the basic arguments of the error e can be defined as [ -0.1,0.1)]At the same time, according to several simulation adjustments, the basic theory of the error change rate can be defined as [ -1,1]The argument of the fuzzy set E, EC taken by the error is set to be { -6-4-20246}, the quantization factor is k e =6/0.1=60，k ec =6/1=6, and similarly, the basic argument of the output is [ -3,3]The fuzzy argument of the defined output is also { -6-4-20246}, the scale factor is k u =3/6=0.5；
At present, more membership functions are applied to fuzzy control, namely 6 membership functions of Gaussian type, generalized bell type, S-shaped, trapezoid, triangle and Z-shaped, the more the membership function curve is sharp, the higher the resolution is, the higher the control sensitivity is, conversely, the more the membership function curve is smooth, the more the control characteristic is gentle, when the membership function is selected, in a smaller error area, in order to prevent error increase, the stability of the system is maintained, a fuzzy set with higher resolution is selected at the moment, and when the error is larger, a fuzzy set with lower resolution is selected for eliminating the error, and the trapezoidal and triangle membership functions are selected;
(3) Writing fuzzy control rules to perform fuzzy reasoning
The main work of fuzzy reasoning is to formulate a fuzzy rule, wherein when the fuzzy rule is obtained by summarizing expert experience or manual control strategy, a double-input-single-output fuzzy controller is adopted in the fuzzy rule, the formulation of the general fuzzy rule is composed of a series of IF and THEN sentences, the front part of the condition sentence is input, and the rear part is a control variable;
a three-dimensional graph of the input/output variable fuzzy rule;
(4) Defuzzification of
The fuzzy quantity is obtained through fuzzy reasoning, but the control quantity of an actual system is required to be a clear quantity, and the reverse fuzzy is a process of converting the fuzzy quantity into the clear quantity, and the reverse fuzzy calculation generally comprises a mean maximum membership method, a minimum membership method, a maximum membership maximum method, a median method, an area barycenter method and other methods, wherein the area barycenter method is adopted, the central thinking is that the barycenter of the area of an area surrounded by a membership function curve and an X axis is used as the final value of an input variable, and the formula is as follows:
preferably, the control signal output by the fuzzy controller is a continuous analog signal, the input signal of the high-speed electromagnetic valve is a digital signal of 1 or 0, a pulse width modulation control valve (Pulse Width Modulation, hereinafter referred to as PWM) needs to be added between the electromagnetic valve and the controller, and the purpose is achieved by controlling the duty ratio of the electromagnetic valve, the principle is that the control signal is compared with a sawtooth wave with a fixed period, and when the control signal is larger than the sawtooth wave, the PWM wave is 1, and the electromagnetic valve is fully opened; when the control signal is smaller than the sawtooth wave, the PWM wave is 0, and the electromagnetic valve is fully closed.
Preferably, positive signals in the control signals determined by the fuzzy controller represent inflation signals, and negative signals represent deflation signals.
Preferably, the fuzzy controller takes a sinusoidal signal as an input of a signal conversion model, separates positive and negative of an original control signal, and compares positive values of the control signal and absolute values of negative values of the control signal with saw-shaped carriers respectively. When the positive value of the control signal is larger than that of the saw-shaped carrier wave, PWM is 1; when the PWM signal is smaller than the saw-shaped carrier wave, the PWM signal is 0; when the absolute value of the negative value of the control signal is larger than that of the saw-shaped carrier wave, the PWM signal is-1; when the signal is smaller than the saw-shaped carrier wave, the PWM signal is 0, wherein the PWM signal is positive and indicates an inflation signal, the electromagnetic valve of the inflation loop is fully opened at the moment, the electromagnetic valve of the deflation loop is fully closed, and the air spring air bag is inflated from the air storage tank; when the PWM signal is negative, the air release signal is represented, the electromagnetic valve of the air charging loop is fully closed at the moment, the electromagnetic valve of the air release loop is fully opened, the air spring air bag releases air to the atmosphere, and when the PWM signal is 0, the electromagnetic valves of the air charging loop and the air release loop are fully closed, and at the moment, the air is not charged or discharged, so that the air quantity in the air spring is kept constant.
Preferably, the ECAS system can realize that the vehicle body height is adjustable in a stepwise manner, and the vehicle body height switching control is divided into three modes: a low position mode (40 mm lowered body), a medium position mode (original body height) and a high position mode (40 mm raised body).
Preferably, the vehicle body control method includes the following steps: s1, judging whether the vehicle is in a straight running condition or a turning running condition according to a lateral acceleration signal of the vehicle body acquired by a sensor; s2, if the vehicle is in a straight running state, the height of the vehicle body is adjusted according to a vehicle speed signal and a suspension moving stroke signal which are acquired by a sensor, and the vehicle is switched in three height modes; s3, if the vehicle is in a turning working condition, the vehicle body height is controlled to adversely affect the safety performance of the vehicle, so that when the vehicle turns, the current vehicle body height is locked, and inflation or deflation is not performed.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is insensitive to the influence of parameter variation and nonlinear characteristics, so that the fuzzy control is more reliable and stable in practical application, and has strong robustness;
2. the invention can process the problems of uncertainty and nonlinearity, and the facing problems are better than the traditional control system, and has stronger adaptability;
3. compared with the traditional control system, the invention adopts a fuzzy control system, does not need an accurate mathematical model and does not need a complex calculation process, so that the fuzzy control system is easier to realize in practical application;
4. the invention adopts the fuzzy control, and the decision of the fuzzy control is deduced by fuzzy rule, so the response speed is faster, and the fuzzy control system has advantages in the application requiring quick response.
Drawings
FIG. 1 is a flow chart of fuzzy control in the present invention;
FIG. 2 is a schematic diagram of the gas circuit of the ECAS system of the automobile according to the present invention;
FIG. 3 is a graph showing membership functions of error e, error rate of change ec, and control amount u according to the present invention;
FIG. 4 is a fuzzy rule table according to the present invention;
FIG. 5 is a three-dimensional diagram of the input/output variable fuzzy rule of the present invention;
FIG. 6 is a fuzzy controller Simulink model in accordance with the present invention;
FIG. 7 is a PWM signal model of the solenoid valve according to the present invention;
FIG. 8 is a schematic diagram of PWM wave generation in accordance with the present invention;
FIG. 9 is a raw (sinusoidal) control signal and control signal processing;
FIG. 10 is a front and rear suspension static height adjustment response;
FIG. 11 is a grade A road surface input elevation adjustment;
FIG. 12 is a B-stage road surface input altitude adjustment;
fig. 13 is a level D road surface input elevation adjustment.
Detailed Description
The invention is further described below with reference to the drawings and detailed description:
when the vehicle body control is performed, it is necessary to determine what state the vehicle is in by determining the main switching parameter. Firstly, the steering working condition is calculated when the lateral acceleration of the vehicle reaches the maximum, no theory is given at home and abroad, and the critical lateral acceleration a is calculated according to other documents and the snake-shaped experiment of the air suspension passenger car y0 Set to 1.5m/s 2 When the lateral acceleration is greater than the critical lateral acceleration during the running of the vehicle, the vehicle is considered to be inAnd (5) entering steering running conditions. Next, when the vehicle is in a straight running state, switching of the vehicle body height mode is performed based on the physical quantity of the running state of the vehicle as a judgment basis. Combining the actual running condition of the vehicle and the national regulation of speed limit of the passenger car, when 75km/h is selected as the critical speed u of the low-order mode a1 The method can judge that the vehicle runs on a good road surface at a high speed, has lower requirement on the vehicle passing performance, reduces the influence of the height of the vehicle on the vehicle passing performance, and can effectively improve the fuel economy and the steering stability of the vehicle. Switching to the high-order mode at this time can improve the passing and comfort of the vehicle when the vehicle is traveling on a rough road surface. Setting a critical speed u for entering a high-order mode by referring to the speed limit of China on a road surface with rough road facilities of a large bus a2 =30 km/h. When the vehicle speed u a Is smaller than critical speed u a1 Greater than or equal to critical vehicle speed u a2 For a period of time T, the vehicle will switch to neutral mode.
When the height of the vehicle body of the ECAS system is adjusted, the controller sends out a signal to control the switch of the electromagnetic valve, so that the air storage tank is controlled to charge and discharge air into the air bag. In the simulation, the absolute air pressure in the air storage tank is kept to be constant at 1.1Mpa, and the electromagnetic valve of the inflation or deflation loop is used as an equivalent throttling small hole, so that the air mass flow Qc flowing through the electromagnetic valve when the electromagnetic valve is opened can be obtained. Because the high-speed electromagnetic valve used by the ECAS system can only be opened and closed, when the height of the vehicle body reaches a target value due to the existence of damping force, the air bag can continuously expand until the vertical direction of the air spring and the static load of the air spring reach balance, so that the phenomena of over-charging and over-discharging easily occur in the process of charging and discharging, and a fuzzy control method is introduced to control the height of the vehicle body.
1-9, an ECAS system vehicle body control method based on fuzzy control comprises a fuzzy controller, an ECAS system electrically connected with the fuzzy controller and a vehicle body control mode adopting the ECAS system;
the design of the fuzzy controller comprises the following steps:
(1) Determining input and output variables for fuzzy control
For a two-dimensional fuzzy controller, the deviation and the deviation change rate of the actual output value and the expected value of the system are generally adopted as the input of the control system, for the study of the height adjustment of the vehicle body, the deviation and the deviation change rate of four suspension moving strokes and the target lifting height are generally selected as the input, the switch signal of the electromagnetic valve is used as the output of the control system, and the air springs are inflated and deflated to achieve the purpose of adjusting the height of the vehicle body;
(2) Determining membership functions of fuzzy linguistic values, quantization factors, scale factors, and fuzzy variables of fuzzy control
Blurring is to find membership degrees of each fuzzy language according to a membership degree function, and the precise input quantity can be converted into different language values through blurring, and the input value and the output value are generally described by { Negative Big (NB), negative Medium (NM), negative Small (NS), zero (ZO), positive Small (PS), median (PM), positive Big (PB) } according to the magnitude and the positive and negative of the input value and the output value;
in the fuzzy control system, the actual variation ranges of the error e, the error change rate ec and the control quantity u are called as basic arguments of the variables, and the range of the height adjustment is set to be +/-0.04 m in the present application, so the basic arguments of the error e can be defined as [ -0.1,0.1)]At the same time, according to several simulation adjustments, the basic theory of the error change rate can be defined as [ -1,1]The argument of the fuzzy set E, EC taken by the error is set to be { -6-4-20246}, the quantization factor is k e =6/0.1=60，k ec =6/1=6, and similarly, the basic argument of the output is [ -3,3]The fuzzy argument of the defined output is also { -6-4-20246}, the scale factor is k u =3/6=0.5；
At present, more membership functions are applied to fuzzy control, namely 6 membership functions of Gaussian type, generalized bell type, S-shaped, trapezoid, triangle and Z-shaped, the more the membership function curve is sharp, the higher the resolution is, the higher the control sensitivity is, conversely, the more the membership function curve is smooth, the more the control characteristic is gentle, when the membership function is selected, in a smaller error area, in order to prevent error increase, the stability of the system is maintained, a fuzzy set with higher resolution is selected at the moment, and when the error is larger, a fuzzy set with lower resolution is selected for eliminating the error, and the trapezoidal and triangle membership functions are selected;
(3) Writing fuzzy control rules to perform fuzzy reasoning
The main work of fuzzy reasoning is to formulate fuzzy rules, wherein when the fuzzy rules are summarized expert experience or manual control strategies, a group of fuzzy condition sentences are obtained, a dual-input-single-output fuzzy controller is adopted in the fuzzy rules, the formulation of the general fuzzy rules is composed of a series of IF and THEN sentences, the front part of the condition sentences is input, the rear part of the condition sentences is a control variable, and the rules are shown in figure 4;
a three-dimensional diagram of the input-output variable fuzzy rule is shown in figure 5;
(4) Defuzzification of
The fuzzy quantity is obtained through fuzzy reasoning, but the control quantity of an actual system is required to be a clear quantity, and the reverse fuzzy is a process of converting the fuzzy quantity into the clear quantity, and the reverse fuzzy calculation generally comprises a mean maximum membership method, a minimum membership method, a maximum membership maximum method, a median method, an area barycenter method and other methods, wherein the area barycenter method is adopted, the central thinking is that the barycenter of the area of an area surrounded by a membership function curve and an X axis is used as the final value of an input variable, and the formula is as follows:
preferably, the control signal output by the fuzzy controller is a continuous analog signal, the input signal of the high-speed electromagnetic valve is a digital signal of 1 or 0, a pulse width modulation control valve (Pulse Width Modulation, hereinafter referred to as PWM) needs to be added between the electromagnetic valve and the controller, and the purpose is achieved by controlling the duty ratio of the electromagnetic valve, the principle is that the control signal is compared with a sawtooth wave with a fixed period, and when the control signal is larger than the sawtooth wave, the PWM wave is 1, and the electromagnetic valve is fully opened; when the control signal is smaller than the sawtooth wave, the PWM wave is 0, and the electromagnetic valve is fully closed.
In the invention, positive signals in control signals decided by the fuzzy controller represent inflation signals, and negative signals represent deflation signals.
In the invention, the fuzzy controller takes a sinusoidal signal as the input of a signal conversion model, separates the positive and negative of an original control signal, and compares the positive value of the control signal and the absolute value of the negative value of the control signal with a saw-shaped carrier wave respectively. When the positive value of the control signal is larger than that of the saw-shaped carrier wave, PWM is 1; when the PWM signal is smaller than the saw-shaped carrier wave, the PWM signal is 0; when the absolute value of the negative value of the control signal is larger than that of the saw-shaped carrier wave, the PWM signal is-1; when the signal is smaller than the saw-shaped carrier wave, the PWM signal is 0, wherein the PWM signal is positive and indicates an inflation signal, the electromagnetic valve of the inflation loop is fully opened at the moment, the electromagnetic valve of the deflation loop is fully closed, and the air spring air bag is inflated from the air storage tank; when the PWM signal is negative, the air release signal is represented, the electromagnetic valve of the air charging loop is fully closed at the moment, the electromagnetic valve of the air release loop is fully opened, the air spring air bag releases air to the atmosphere, and when the PWM signal is 0, the electromagnetic valves of the air charging loop and the air release loop are fully closed, and at the moment, the air is not charged or discharged, so that the air quantity in the air spring is kept constant.
In the invention, the ECAS system can realize the gradual adjustment of the height of the vehicle body, and the height switching control of the vehicle body is divided into three modes: a low position mode (40 mm lowered body), a medium position mode (original body height) and a high position mode (40 mm raised body).
In the invention, the vehicle body control mode comprises the following steps: s1, judging whether the vehicle is in a straight running condition or a turning running condition according to a lateral acceleration signal of the vehicle body acquired by a sensor; s2, if the vehicle is in a straight running state, the height of the vehicle body is adjusted according to a vehicle speed signal and a suspension moving stroke signal which are acquired by a sensor, and the vehicle is switched in three height modes; s3, if the vehicle is in a turning working condition, the vehicle body height is controlled to adversely affect the safety performance of the vehicle, so that when the vehicle turns, the current vehicle body height is locked, and inflation or deflation is not performed.
After a complete vehicle body height control model is built in a Matlab/Simulink environment, height adjustment is respectively carried out on vehicles when the vehicles are stationary on a road surface and the vehicles are excited by random road surfaces.
Example 1
Static height adjustment
When the vehicle is stationary on the road surface, the outside has no road surface spectrum input, and at the moment, taking the reduction of the height of the vehicle body as an example, the vehicle is switched from a middle position mode to a low position mode, the height of the vehicle body needs to be adjusted downwards by 40mm, the simulation time is 6s, the step length is 0.001s, and the response result of the height adjustment of the vehicle body is shown in figure 10.
As can be seen from the simulation result of the static height adjustment, the static vehicle body height adjustment is good. The system reaches the target height for about 2 seconds for the first time, and then a certain overshoot is carried out, but the overshoot is controlled within 5mm, and within an acceptable range, the system is stable at the target height position for about 4 seconds, and the steady state error is small, so that the control precision is good.
Example 2
Dynamic height adjustment
Dynamic altitude adjustment is defined as the altitude control that occurs when the vehicle is driven by different road surface excitations. The dynamic height adjustment of the actual road is simulated, and specific simulation working conditions are set as follows: (1) The method comprises the steps of performing height adjustment on a good road surface, such as a class A road surface and a class B road surface, enabling a vehicle to run at a high speed at a speed of 80km/h, and switching the vehicle from a normal mode (namely a middle-position mode) to a high-speed mode (namely a low-position mode) in order to reduce the height of the mass center of the vehicle and improve the steering stability of the vehicle under the high-speed condition; (2) Considering the requirement of the height adjustment precision of the vehicle when the vehicle runs on a severe road, the vehicle runs at the speed of 30km/h under the drive of a D-level road, and the vehicle is switched from a middle-position mode to a high-position mode, so that the trafficability of the vehicle is improved.
Based on the setting of the simulation working condition, aiming at the working condition 1, the vehicle runs on the grade A road surface and the grade B road surface, the vehicle height mode is switched from the middle position mode to the low position mode, the control effect is shown in the attached drawings 11 and 12, and the simulation result of the vehicle body height adjustment is shown in the attached drawings 13 when the vehicle runs on the grade D road surface at a lower speed under the working condition 2.
The simulation result of the dynamic vehicle height adjustment can show that the built model can realize the vehicle height adjustment, and as can be seen from figures 11 and 12, on the level A and level B road surfaces, the vehicle can be adjusted to the target vehicle height value for the first time within 2 seconds, and can be basically maintained stable within 3 seconds, thereby meeting the requirement on the height adjustment function. Meanwhile, when the vehicle runs on the A-level road surface and the B-level road surface, the external interference to the vehicle is not so strong, so that the control precision of the controller is higher, and the controller can basically be stabilized at about the target height. When the vehicle runs on the D-level road surface, the vehicle is firstly adjusted to the target vehicle height value in 1 second, and basically can be kept stable in about 3 seconds, but the control precision is not very high due to the severe road surface, the large external interference, the gas compressibility and other reasons, the vehicle body height fluctuates up and down at the target height from the simulation result, the maximum value of the error after the control stability is basically kept within 0.02m, and the requirement on the vehicle body height adjusting function is met.
In summary, the present invention is not limited to the preferred embodiments, but includes all equivalent changes and modifications in shape, construction, characteristics and spirit according to the scope of the claims.
Claims (6)
1. A vehicle body control method of an ECAS system based on fuzzy control is characterized in that: the system comprises a fuzzy controller, an ECAS system electrically connected with the fuzzy controller and a vehicle body control mode adopting the ECAS system;
the design of the fuzzy controller comprises the following steps:
(1) Determining input and output variables for fuzzy control
For a two-dimensional fuzzy controller, the deviation and the deviation change rate of the actual output value and the expected value of the system are generally adopted as the input of the control system, for the study of the height adjustment of the vehicle body, the deviation and the deviation change rate of four suspension moving strokes and the target lifting height are generally selected as the input, the switch signal of the electromagnetic valve is used as the output of the control system, and the air springs are inflated and deflated to achieve the purpose of adjusting the height of the vehicle body;
(2) Determining membership functions of fuzzy linguistic values, quantization factors, scale factors, and fuzzy variables of fuzzy control
Blurring is to find membership degrees of each fuzzy language according to a membership degree function, and the precise input quantity can be converted into different language values through blurring, and the input value and the output value are generally described by { Negative Big (NB), negative Medium (NM), negative Small (NS), zero (ZO), positive Small (PS), median (PM), positive Big (PB) } according to the magnitude and the positive and negative of the input value and the output value;
in the fuzzy control system, the actual variation ranges of the error e, the error change rate ec and the control quantity u are called as basic arguments of the variables, and the range of the height adjustment is set to be +/-0.04 m in the present application, so the basic arguments of the error e can be defined as [ -0.1,0.1)]At the same time, according to several simulation adjustments, the basic theory of the error change rate can be defined as [ -1,1]The argument of the fuzzy set E, EC taken by the error is set to be { -6-4-20246}, the quantization factor is k e ＝6/0.1＝60，k ec =6/1=6, and similarly, the basic argument of the output is [ -3,3]The fuzzy argument of the defined output is also { -6-4-20246}, the scale factor is k u ＝3/6＝0.5；
At present, more membership functions are applied to fuzzy control, namely 6 membership functions of Gaussian type, generalized bell type, S-shaped, trapezoid, triangle and Z-shaped, the more the membership function curve is sharp, the higher the resolution is, the higher the control sensitivity is, conversely, the more the membership function curve is smooth, the more the control characteristic is gentle, when the membership function is selected, in a smaller error area, in order to prevent error increase, the stability of the system is maintained, a fuzzy set with higher resolution is selected at the moment, and when the error is larger, a fuzzy set with lower resolution is selected for eliminating the error, and the trapezoidal and triangle membership functions are selected;
(3) Writing fuzzy control rules to perform fuzzy reasoning
The main work of fuzzy reasoning is to formulate a fuzzy rule, wherein when the fuzzy rule is obtained by summarizing expert experience or manual control strategy, a double-input-single-output fuzzy controller is adopted in the fuzzy rule, the formulation of the general fuzzy rule is composed of a series of IF and THEN sentences, the front part of the condition sentence is input, and the rear part is a control variable;
a three-dimensional graph of the input/output variable fuzzy rule;
(4) Defuzzification of
The fuzzy quantity is obtained through fuzzy reasoning, but the control quantity of an actual system is required to be a clear quantity, and the reverse fuzzy is a process of converting the fuzzy quantity into the clear quantity, and the reverse fuzzy calculation generally comprises a mean maximum membership method, a minimum membership method, a maximum membership maximum method, a median method, an area barycenter method and other methods, wherein the area barycenter method is adopted, the central thinking is that the barycenter of the area of an area surrounded by a membership function curve and an X axis is used as the final value of an input variable, and the formula is as follows:
2. the ECAS system body control method based on the fuzzy control of claim 1, wherein: the control signal output by the fuzzy controller is a continuous analog signal, the input signal of the high-speed electromagnetic valve is a digital signal of 1 or 0, a pulse width modulation control valve (Pulse Width Modulation, hereinafter referred to as PWM) is needed to be added between the electromagnetic valve and the controller, the purpose is achieved by controlling the duty ratio of the electromagnetic valve, the principle is that the control signal is compared with a periodic fixed sawtooth wave, and when the control signal is larger than the sawtooth wave, the PWM wave is 1, and the electromagnetic valve is fully opened; when the control signal is smaller than the sawtooth wave, the PWM wave is 0, and the electromagnetic valve is fully closed.
3. The ECAS system body control method based on the fuzzy control of claim 1, wherein: the control signals decided by the fuzzy controller are positive signals representing inflation signals and negative signals representing deflation signals.
4. The ECAS system body control method based on the fuzzy control of claim 1, wherein: the fuzzy controller takes a sine signal as the input of a signal conversion model, separates the original control signal from the original control signal, and compares the positive value of the control signal and the absolute value of the negative value of the control signal with the saw-shaped carrier wave respectively. When the positive value of the control signal is larger than that of the saw-shaped carrier wave, PWM is 1; when the PWM signal is smaller than the saw-shaped carrier wave, the PWM signal is 0; when the absolute value of the negative value of the control signal is larger than that of the saw-shaped carrier wave, the PWM signal is-1; when the signal is smaller than the saw-shaped carrier wave, the PWM signal is 0, wherein the PWM signal is positive and indicates an inflation signal, the electromagnetic valve of the inflation loop is fully opened at the moment, the electromagnetic valve of the deflation loop is fully closed, and the air spring air bag is inflated from the air storage tank; when the PWM signal is negative, the air release signal is represented, the electromagnetic valve of the air charging loop is fully closed at the moment, the electromagnetic valve of the air release loop is fully opened, the air spring air bag releases air to the atmosphere, and when the PWM signal is 0, the electromagnetic valves of the air charging loop and the air release loop are fully closed, and at the moment, the air is not charged or discharged, so that the air quantity in the air spring is kept constant.
5. The ECAS system body control method based on the fuzzy control of claim 1, wherein: the ECAS system can realize the gradual adjustment of the height of the vehicle body, and the switching control of the height of the vehicle body is divided into three modes: a low position mode (40 mm lowered body), a medium position mode (original body height) and a high position mode (40 mm raised body).
6. The ECAS system body control method based on the fuzzy control of claim 1, wherein: the vehicle body control mode comprises the following steps: s1, judging whether the vehicle is in a straight running condition or a turning running condition according to a lateral acceleration signal of the vehicle body acquired by a sensor; s2, if the vehicle is in a straight running state, the height of the vehicle body is adjusted according to a vehicle speed signal and a suspension moving stroke signal which are acquired by a sensor, and the vehicle is switched in three height modes; s3, if the vehicle is in a turning working condition, the vehicle body height is controlled to adversely affect the safety performance of the vehicle, so that when the vehicle turns, the current vehicle body height is locked, and inflation or deflation is not performed.
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