阅读说明：本技术 一种阻尼多模式半主动悬架电控系统的模糊切换控制方法 (Fuzzy switching control method for damping multi-mode semi-active suspension electronic control system ) 是由 陈龙 马瑞 于 2019-10-24 设计创作，主要内容包括：本发明公开了一种阻尼多模式半主动悬架电控系统的模糊切换控制方法,首先利用传感器,获得簧上质量加速度,簧下质量加速度,将获得的加速度信号进行积分得到簧上和簧下质量的速度和位移信号。进而将速度位移信号进行处理,作为悬架此时拉伸压缩状态的判断依据,并以此作为模糊控制器的输入信号,进行模糊判别,输出为悬架的两个高速开关电磁阀的开闭信号。开闭信号控制高速开关电磁阀的通断状态,使得不论车辆处于何种状态时,悬架都能提供很好的减振效果。本发明可以实现悬架系统很好的阻尼切换控制效果,并且利用了模糊控制避免了传统控制计算量大的缺点,提高了车辆行驶平顺性。(The invention discloses a fuzzy switching control method of a damping multi-mode semi-active suspension electric control system. And further processing the speed displacement signal as a judgment basis of the tension and compression state of the suspension at the moment, taking the processed speed displacement signal as an input signal of a fuzzy controller to perform fuzzy judgment, and outputting the fuzzy judgment as opening and closing signals of two high-speed switching electromagnetic valves of the suspension. The on-off signal controls the on-off state of the high-speed switch electromagnetic valve, so that the suspension can provide good vibration reduction effect no matter what state the vehicle is in. The invention can realize the good damping switching control effect of the suspension system, and utilizes the fuzzy control to avoid the defect of large calculation amount of the traditional control, thereby improving the running smoothness of the vehicle.)

1. A damping switching control method of an automobile semi-active suspension system is characterized by comprising the following steps:

step 1, firstly, establishing a semi-active suspension system model, determining the optimal damping ratio of a suspension based on safety and comfort by the system model, and further determining each gear division and damping range in suspension damping switching control;

step 2, determining relevant parameter selection based on a suspension fluid mechanics equation according to the determined suspension gear division, establishing a mathematical model for simulation analysis, and obtaining a corresponding speed displacement characteristic curve under each mode;

step 3, measuring acceleration signals of the unsprung mass and the sprung mass of the vehicle by using the acceleration sensor respectively

step 4, respectively establishing the electromagnetic valves s₁And solenoid valves s₂The fuzzy controller carries out fuzzy discrimination on the input signals and outputs two continuous electromagnetic valve switching trend signals between (0, 1); establishing a fuzzy control rule selection standard, so that the suspension can obtain the optimal corresponding damping mode in both stretching and compressing working strokes;

and 5, rounding the fuzzy output switch control signal, outputting 0 and 1 control signals to control the opening and closing of the two electromagnetic valves, and enabling the damping mode to be changed.

2. The damping switching control method for the semi-active suspension system of the automobile according to claim 1, wherein the semi-active suspension system model established in the step 1 is as follows:

in the formula, m_sIs sprung mass, m_uIs unsprung mass, k is suspension equivalent spring rate, k_tIs the equivalent stiffness of the tire, z_sIs sprung mass displacement, z_uIs the unsprung mass displacement, z_rExcitation of the road surface, and c is a damping coefficient;

for convenience, the following variables were introduced:

in the formula: r is_kIs a stiffness ratio, r_mIs a mass ratio, ω₀The natural circle frequency of the vehicle body, and ξ the damping ratio of the suspension system;

the method comprises the following steps of taking the vertical acceleration of a vehicle body as a comfort judgment index, taking the dynamic load of a wheel as a safety judgment index, and respectively solving response analytic expressions related to comfort and safety under white noise vibration according to a semi-active suspension model established before:

in the formula: n is₀Is the spatial frequency, v is the vehicle speed, G_q(n₀) The road surface unevenness coefficient.

Are respectively provided withObtaining the optimal damping ratio of the suspension based on comfort:

suspension is based on the optimal damping ratio of safety:

root play ξ_ocAnd ξ_osDetermining a damping ratio range of the suspension switching control to [ ξ ]_oc,ξ_os]The multi-mode semi-active suspension is divided into 4 gears, and damping coefficients of a recovery stroke and a compression stroke from a mode 1 to a mode 4 are regulated to be respectively reduced to beLarge, suspension damping characteristics become successively stiffer, and therefore damping coefficient based on comfort

3. The damping switching control method of the semi-active suspension system of the automobile according to claim 1, characterized in that in the fuzzy control rule established in step 4, the following requirements are satisfied: when the dynamic stroke of the suspension meets the requirement, the damper is kept in a low-gear mode, the damping is small, the suspension can obtain good comfort performance, and the vertical acceleration is small; when the suspension dynamic stroke does not meet the requirement, the control electromagnetic valve is closed at the moment, so that the damper is changed into a high-gear mode, the damping is increased, and the suspension dynamic stroke and the dynamic load are reduced.

4. The damping switching control method of the semi-active suspension system of the automobile according to claim 2, wherein in step 4, the optimal corresponding damping mode can be obtained when the suspension is in two working strokes of tension and compression, and the specific process is as follows: the suspension being divided into two working strokes, i.e. z, in tension and in compression_s-z_u> 0, in which case the suspension is in the extension stroke, z_s-z_uIf the pressure is less than 0, the suspension is in a compression stroke; z is a radical of_s-z_uWhen greater than 0, if

5. The damping switching control method for the semi-active suspension system of the automobile as claimed in claim 1, wherein in step 4, the input stroke E and the derivative thereof to the fuzzy controller

6. The damping switching control method for the semi-active suspension system of the automobile as claimed in claim 5, wherein in step 4, for the solenoid valve s₁Establishing the fuzzy rule table may be specifically described as: when the input variable moves the journey language value E and becomesQuantity NB, another input variable, the derivative of the dynamic travel, speech value

for solenoid valve s₂Establishing the fuzzy rule table may be specifically described as: when the language value E of the input variable moving stroke is NB, the language value of the other input variable moving stroke derivative

7. The damping switching control method for the semi-active suspension system of the automobile as claimed in claim 1, wherein the step 5 further comprises that after the fuzzy controller receives the input, the output is the solenoid valve switch control trend which is continuous within the range of (0,1), therefore, rounding is needed for the output, rounding is conducted behind the fuzzy controller, when the output is 0, the solenoid valve is controlled to be closed, and when the output is 1, the solenoid valve is opened, and through fuzzy control and rounding, the switching of the suspension damping mode can be realized and the generation of frequent jumping of the switching system can be avoided.

Technical Field

The invention relates to the field of automobile suspension system control, in particular to an automobile damping multi-mode semi-active suspension fuzzy switching control method.

Background

In recent years, with the increasing demand for vehicle ride comfort, research on high-performance suspension systems has been receiving much attention. Compared with the traditional passive suspension and active suspension, the semi-active suspension can better meet the requirements of the suspension system in various aspects such as performance, cost, energy consumption and the like, so the development prospect is very wide. In general, a semi-active suspension of a vehicle realizes the self-adaptive adjustment of the damping characteristic of a suspension system through a damping continuous adjustable shock absorber. The different types of shock absorbers have excellent performance in the aspect of damping adjustment, but still face the problems of complex structure, high cost, high control difficulty and the like to a certain extent, and further restrict the rapid development of the semi-active suspension of the vehicle. Meanwhile, the existing research shows that the control effect of the semi-active suspension of the vehicle cannot be obviously influenced by small damping change, so that the further research on the multistage damping adjustable shock absorber with simple structure, low cost and small control difficulty has important academic significance and practical engineering application value.

At present, most of researches on damping multistage adjustable suspensions focus on the aspects of overall parameter determination of suspension shock absorbers, damping adjusting mechanism design and the like, and the researches are less related to the aspect of vehicle semi-active suspension control strategies comprising damping multi-mode switching shock absorbers.

Particularly for damping gear switching control, the traditional continuous adjustable suspension damping control method is not suitable any more, the requirement of continuous input and discrete output of a controller cannot be well met, the traditional control calculation amount is large, the requirement on model precision is high, and the control is not accurate enough.

Disclosure of Invention

The invention aims to provide a damping switching control method of an automobile semi-active suspension system, which is characterized in that fuzzy control is respectively carried out on two electromagnetic valves in a suspension damping adjusting structure, the displacement of the dynamic stroke of a suspension and the derivative thereof are used as input, an on-off control signal of each electromagnetic valve is output, switching of the damping gears of the suspension is realized by opening and closing the two electromagnetic valves, and the suspension performance and the smoothness of a vehicle are obviously improved.

In order to achieve the purpose, the invention adopts the following technical scheme: a damping switching control method of an automobile semi-active suspension system comprises the following steps:

step 1, firstly, establishing a semi-active suspension system model, determining the optimal damping ratio of a suspension based on safety and comfort by the system model, and further determining each gear division and damping range in suspension damping switching control;

step 2, determining relevant parameter selection based on a suspension fluid mechanics equation according to the determined suspension gear division, establishing a mathematical model for simulation analysis, and obtaining a corresponding speed displacement characteristic curve under each mode;

step 3, measuring acceleration signals of the unsprung mass and the sprung mass of the vehicle by using the acceleration sensor respectively

Andintegrating the unsprung mass acceleration signals and the sprung mass acceleration signals for multiple times to obtain corresponding speed and displacement signals, and further obtaining the dynamic stroke and derivatives of the suspension as the input of a fuzzy controller;

step 4, respectively establishing the electromagnetic valves s₁And solenoid valves s₂The fuzzy controller carries out fuzzy discrimination on the input signals and outputs two continuous electromagnetic valve switching trend signals between (0, 1); establishing a fuzzy control rule selection standard, so that the suspension can obtain the optimal corresponding damping mode in both stretching and compressing working strokes;

and 5, rounding the fuzzy output switch control signal, outputting 0 and 1 control signals to control the opening and closing of the two electromagnetic valves, and enabling the damping mode to be changed.

Further, the semi-active suspension system model established in step 1 is:

in the formula, m_sIs sprung mass, m_uIs unsprung mass, k is suspension equivalent spring rate, k_tIs the equivalent stiffness of the tire, z_sIs sprung mass displacement, z_uIs the unsprung mass displacement, z_rExcitation of the road surface, and c is a damping coefficient;

for convenience, the following variables were introduced:

in the formula: r is_kIs a stiffness ratio, r_mIs a mass ratio, ω₀The natural circle frequency of the vehicle body, and ξ the damping ratio of the suspension system;

the method comprises the following steps of taking the vertical acceleration of a vehicle body as a comfort judgment index, taking the dynamic load of a wheel as a safety judgment index, and respectively solving response analytic expressions related to comfort and safety under white noise vibration according to a semi-active suspension model established before:

in the formula: n is₀Is the spatial frequency, v is the vehicle speed, G_q(n₀) The road surface unevenness coefficient.

Are respectively provided with

Obtaining the optimal damping ratio of the suspension based on comfort:

suspension is based on the optimal damping ratio of safety:

root play ξ_ocAnd ξ_osDetermining a damping ratio range of the suspension switching control to [ ξ ]_oc,ξ_os]The multi-mode semi-active suspension is divided into 4 gears, damping coefficients of a specified recovery stroke and a specified compression stroke from a mode 1 to a mode 4 are respectively changed from small to large, and the damping characteristics of the suspension are sequentially hardened, so that the damping coefficient based on comfort is changedAs the basis for selecting the damping magnitude of mode 1,

as the basis for selecting the damping magnitude of the mode 4, the damping coefficients of the mode 2 and the mode 3 respectively take the middle value.

Further, in the fuzzy control rule established in step 4, it is required to satisfy: when the dynamic stroke of the suspension meets the requirement, the damper is kept in a low-gear mode, the damping is small, the suspension can obtain good comfort performance, and the vertical acceleration is small; when the suspension dynamic stroke does not meet the requirement, the control electromagnetic valve is closed at the moment, so that the damper is changed into a high-gear mode, the damping is increased, and the suspension dynamic stroke and the dynamic load are reduced.

Further, in step 4, the suspension is in a mode that the optimal corresponding damping mode can be obtained by stretching and compressing two working strokes, and the specific process is as follows: the suspension being divided into two working strokes, i.e. z, in tension and in compression_s-z_u> 0, in which case the suspension is in the extension stroke, z_s-z_uIf the pressure is less than 0, the suspension is in a compression stroke; z is a radical of_s-z_uWhen greater than 0, ifThe suspension is in a stretching stroke at the moment and tends to continue stretching, and the shock absorber tends to use a hard stretching mode, namely a mode 2 or a mode 4; if it is

At the moment, the compression trend is achieved, and a mode 3 is selected; z is a radical of_s-z_uIf < 0: if

The suspension is in a compression stroke at the moment and has a tendency of continuous compression, and the shock absorber should tend to use a hard compression mode, namely a mode 3 or a mode 4; if it is

When the material has a stretching tendency, selectingMode 2; if the suspension stroke and the derivative thereof are small, the mode 1 is adopted, and the shock absorber is kept in a soft compression soft recovery state.

Further, in step 4, the input stroke E and the derivative thereof to the fuzzy controller

Five fuzzy sets are adopted to represent fuzzy states of the fuzzy sets, and corresponding fuzzy subsets are PB is positive and large, PM is positive, PS is positive and small, ZE is zero, NS is negative and small, NM is negative and medium, and NB is negative and large; five fuzzy sets are adopted for the output electromagnetic valve opening and closing control signals to represent the trend of opening and closing control of the electromagnetic valve, namely ZE is closed, S is small, M is medium, B is large and K is open; in the design, the variables E and

are set to [ -0.1, respectively]And [ -0.5,05]The fundamental discourse domain of the fuzzy output is [0,1 ]](ii) a Selecting a membership function of fuzzy control: the input variable adopts a triangular function, and the output variable adopts a Gaussian function.

Further, in step 4, for the solenoid valve s₁Establishing the fuzzy rule table may be specifically described as: when the language value E of the input variable moving stroke is NB, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, S, ZE and ZE respectively; when the language value E of the input variable moving stroke is NM, the language value of the derivative of the moving stroke of another input variable is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, S, ZE and ZE respectively; when the language value E of the input variable is NS, the language value of the derivative of the input variable is NS

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are S, S, S, K, S, S and S respectively; when the language value E of the input variable dynamic travel is ZE, the language value of the derivative of the other input variable dynamic travel is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are respectively M, M, K, K, K, M and M; when the language value of the input variable moving stroke E is PS, the language value of the other input variable moving stroke derivativeThe variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding output variable electromagnetic valve opening and closing trend language values are B, B, B, K, B, B and B respectively; when the language value E of the input variable moving stroke is PM, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are K, K, B, M, B, K and K respectively; when the language value E of the input variable moving stroke is PB, the language value of the derivative of the moving stroke of the other input variable isThe variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are K, K, B, M, B, K and K respectively;

for solenoid valve s₂Establishing the fuzzy rule table may be specifically described as: when the language value E of the input variable moving stroke is NB, the language value of the other input variable moving stroke derivativeThe variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding output variables are solenoid valve opening and closing trend languagesThe values are ZE, ZE, S, M, B, K, respectively. When the language value E of the input variable moving stroke is NM, the language value of the derivative of the moving stroke of another input variable is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, B, K and K respectively; when the language value E of the input variable is NS, the language value of the derivative of the input variable is NS

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are S, S, S, K, B, B and B respectively; when the language value E of the input variable dynamic travel is ZE, the language value of the derivative of the other input variable dynamic travel is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are respectively M, M, K, K, B, B and B; when the language value of the input variable moving stroke E is PS, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are S, S, S, K, S, S and S respectively; when the language value E of the input variable moving stroke is PM, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, S, ZE and ZE respectively; when the language value E of the input variable moving stroke is PB, the language value of the derivative of the moving stroke of the other input variable is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding output variable electromagnetic valve opening and closing trend language values are ZE, ZE, S, M, S, ZE and ZE respectively.

Further, step 5 also includes that after the fuzzy controller receives the input, the output is the continuous electromagnetic valve switch control trend in the range of (0,1), so that rounding is needed to be carried out on the output, rounding is carried out behind the fuzzy controller, when the output is 0, the electromagnetic valve is controlled to be closed, when the output is 1, the electromagnetic valve is opened, and through fuzzy control and rounding, the switching of the damping mode of the suspension can be realized and the frequent jumping of the switching system can be avoided.

Advantages and positive effects of the invention

1. The invention determines the damping range and gear division of the suspension based on two different optimal damping ratios, and balances the safety and the comfort of the suspension respectively, thereby providing an effective basis for the gear division of the suspension damping.

2. The invention adopts a fuzzy control method and well realizes the switching control of the damping gears of the suspension. The fuzzy control is adopted to avoid the defects of large calculation amount and accurate requirement on the model in the traditional control, and the fault tolerance rate is higher. And by a fuzzy control discretization method and fuzzy control and rounding, the possibility of jumping in switching control is effectively avoided, and the controller is stable.

3. According to the invention, a fuzzy rule is formulated according to the stretching and compressing conditions of the suspension, so that the suspension can obtain the optimal corresponding damping mode in stretching and compressing working strokes, the excessive stretching and compressing trends generated by the suspension are effectively avoided, and the vertical vibration of the suspension can be well inhibited. Through simulation analysis, the dynamic stroke and the vertical acceleration of the suspension are well optimized by adopting the multi-damping-mode semi-active suspension with fuzzy control.

Drawings

FIG. 1: semi-active suspension system schematic

FIG. 2: multi-damping mode suspension shock absorber structure schematic diagram

FIG. 3: suspension solenoid valve s₁Fuzzy input and outputGraph of curved surface

FIG. 4: suspension solenoid valve s₂Fuzzy input and output curved surface diagram

FIG. 5: lower electromagnetic valve s for random road surface input₁Fuzzy control of output switching signal

FIG. 6: lower electromagnetic valve s for random road surface input₂Fuzzy control of output switching signal

FIG. 7: damping mode switching mode under random road surface input

FIG. 8: random road surface input semi-active suspension vehicle body vertical acceleration response comparison adopting different control strategies

FIG. 9: semi-active suspension dynamic stroke response comparison by adopting different control strategies in random road surface input

FIG. 10: damping force-speed characteristic curve of different damping modes of suspension

In the figure: 1. air chamber 2, floating piston 3, compression chamber 4, hydraulic valve 5, switch electromagnetic valve 6, recovery valve 7, piston 8, compression valve 9, piston rod 10, recovery chamber

Detailed Description

The present invention will be described in detail below with reference to specific embodiments in order to make the technical features of the present invention clear to those skilled in the art.

Firstly, step 1, establishing a semi-active suspension model, and determining a suspension damping range and gear division according to an optimal damping ratio. The vertical acceleration of the vehicle body is used as a comfort judgment index, and the dynamic load of the wheels is used as a safety judgment index. According to the semi-active suspension model established in the past, response analytic expressions related to comfort and safety under the condition of white noise vibration are respectively obtained:

in the formula: n is₀Is the spatial frequency, v is the vehicle speed, G_q(n₀) The road surface unevenness coefficient.

Are respectively provided with

Obtaining the optimal damping ratio of the suspension based on comfort:

suspension is based on the optimal damping ratio of safety:

root play ξ_ocAnd ξ_osDetermining a damping ratio range of the suspension switching control to [ ξ ]_oc,ξ_os]. The multi-mode semi-active suspension is divided into 4 gears, damping coefficients of a specified recovery stroke and a specified compression stroke from a mode 1 to a mode 4 are respectively changed from small to large, and the damping characteristics of the suspension are sequentially hardened. Therefore damping coefficient based on comfort

As the basis for selecting the damping magnitude of mode 1,

as the basis for selecting the damping magnitude of the mode 4, the damping coefficients of the mode 2 and the mode 3 respectively take the middle value.

And 2, determining related parameter selection based on a suspension fluid mechanics equation according to the determined suspension damping gear division, establishing a mathematical model for simulation analysis, and obtaining a corresponding speed displacement characteristic curve under each mode.

The suspension damping switching mechanism results as shown in figure 2, where it can be seen that the mechanism comprises 6 hydraulic valves, where s₁，s₂Two on-off solenoid valves with the same dimensional parameters, a, b, c, d are 4 one-way check valves. To enable four different damping modes, the oil pressure loss of each one-way check valve is not the same. The structure realizes the change of the oil way by controlling the open and close states of the two electromagnetic valvesAnd the multistage adjustable characteristic of damping is ensured. Wherein, the suspension damping force equation can be expressed as:

in the formula: f_rIs the total damping force in the return stroke, F_cIs the total damping force of the compression stroke; p_rIs the oil recovery chamber pressure, P_cThe pressure of an oil compression cavity; delta P_rcAnd Δ P_crPressure difference between the recovery chamber and the compression chamber, A_p,A_rThe effective areas of the compression chamber and the recovery chamber pistons, respectively. In the damping adjustment mechanism, the oil is respectively passed through the solenoid valves s₁,s₂And four one-way check valves fluidly connecting the upper and lower chambers. The switching solenoid valve can be regarded as a thin-wall orifice plate, and the pressure loss passing through can be calculated as:

in the formula: delta P_rc-sv1And Δ P_rc-sv2Respectively an on-off solenoid valve s₁，s₂Pressure loss of (2); rho is the density of oil in the shock absorber; c is a pressure loss coefficient; a. the_svThe area of the thin-wall pore plate passing through; q_rc-acIndicating the flow of oil through the damping adjustment actuator. On the basis of the established mathematical model of the damping mechanism of the suspension, dynamic simulation is carried out, and the damping speed characteristic curve of the suspension can be obtained as shown in fig. 10, and the equivalent damping force is shown in table 3.

TABLE 3

Step 3, measuring acceleration signals of the unsprung mass and the sprung mass of the vehicle by using the acceleration sensor respectively

And

and (3) carrying out multiple integration on the unsprung mass acceleration signals and the sprung mass acceleration signals to obtain corresponding speed and displacement signals, and further obtaining the suspension dynamic stroke and derivatives thereof as the input of the fuzzy controller.

And 4, establishing fuzzy controllers corresponding to the two electromagnetic valves. With regard to the established fuzzy controller, the selected controller inputs are the suspension stroke and the derivative thereof, and the controller outputs opening and closing control signals of the two electromagnetic valves. Through a fuzzy controller, three indexes of a dynamic stroke and a vertical acceleration representing the comfort of the suspension and a dynamic load representing the safety are optimized. According to the vibration characteristic mechanism of the suspension, along with the increase of the damping ratio, the root mean square value of the vertical acceleration of the suspension is also improved, and the performance of the dynamic stroke and the dynamic load is improved. Therefore, the design criterion of the fuzzy controller is that when the dynamic stroke of the suspension meets the requirement, the damper is kept in a low-gear mode, the damping is small, the suspension can obtain good comfort performance, and the vertical acceleration is small. When the suspension dynamic stroke does not meet the requirement, the control electromagnetic valve is closed at the moment, so that the damper is changed into a high-gear mode, the damping ratio is increased, and the suspension dynamic stroke and the dynamic load are reduced.

The suspension being divided into two working strokes, i.e. z, in tension and in compression_s-z_u> 0, in which case the suspension is in the extension stroke, z_s-z_u< 0, the suspension is in compression stroke. z is a radical of_s-z_uWhen greater than 0, if

The suspension is in tension stroke and tends to continue to be in tension, and the damper should tend to use a hard tension mode, either mode 2 or mode 4. If it is

There is a compression trend and mode 3 is selected. z is a radical of_s-z_uIf < 0: if

The suspension is now under compressionOn the compression stroke and with a tendency to continue to compress, the shock absorber should tend to use a hard compression mode, either mode 3 or mode 4. If it is

In this case, the stretching tendency is observed, and mode 2 is selected. If the suspension stroke and the derivative thereof are small, the mode 1 is adopted, and the shock absorber is kept in a soft compression soft recovery state. Based on the principle, the fuzzy rule is used as a selection basis for the fuzzy rule of the fuzzy controller.

Input stroke E and derivative thereof to fuzzy controller according to actual control objectFive fuzzy sets are adopted to represent fuzzy states of the fuzzy sets, and corresponding fuzzy subsets are PB is positive and large, PM is positive, PS is positive and small, ZE is zero, NS is negative and small, NM is negative and medium, and NB is negative and large; five fuzzy sets are adopted for the output electromagnetic valve opening and closing control signals to represent the trend of opening and closing control of the electromagnetic valve, namely ZE is closed, S is small, M is medium, B is large and K is open; . In the design, the variables E and

are set to [ -0.1, respectively]And [ -0.5,05]The fundamental discourse domain of the fuzzy output is [0,1 ]]. According to the previous analysis of the suspension motion process, the solenoid valves s can be obtained respectively₁,s₂The fuzzy rule tables are shown in tables 1 and 2.

TABLE 1

TABLE 2

For electricityMagnetic valve s₁Establishing the fuzzy rule table may be specifically described as: when the language value E of the input variable moving stroke is NB, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, S, ZE and ZE respectively; when the language value E of the input variable moving stroke is NM, the language value of the derivative of the moving stroke of another input variable isThe variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, S, ZE and ZE respectively; when the language value E of the input variable is NS, the language value of the derivative of the input variable is NS

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are S, S, S, K, S, S and S respectively; when the language value E of the input variable dynamic travel is ZE, the language value of the derivative of the other input variable dynamic travel is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are respectively M, M, K, K, K, M and M; when the language value of the input variable moving stroke E is PS, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding output variable electromagnetic valve opening and closing trend language values are B, B, B, K, B, B and B respectively; when the language value E of the input variable moving stroke is PM, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are K, K, B, M, B, K and K respectively; when the language value E of the input variable moving stroke is PB, the language value of the derivative of the moving stroke of the other input variable is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are K, K, B, M, B, K and K respectively;

for solenoid valve s₂Establishing the fuzzy rule table may be specifically described as: when the language value E of the input variable moving stroke is NB, the language value of the other input variable moving stroke derivativeThe variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding output variable electromagnetic valve opening and closing trend language values are ZE, ZE, S, M, B, K and K respectively. When the language value E of the input variable moving stroke is NM, the language value of the derivative of the moving stroke of another input variable isThe variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, B, K and K respectively; when the language value E of the input variable is NS, the language value of the derivative of the input variable is NS

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are S, S, S, K, B, B and B respectively; when the language value E of the input variable dynamic travel is ZE, the language value of the derivative of the other input variable dynamic travel is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are respectively M, M, K, K, B, B and B; when inputtingThe variable moving stroke linguistic value E is PS, and the other input variable moving stroke derivative linguistic value

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding language values of the opening and closing trend of the electromagnetic valves of the output variables are S, S, S, K, S, S and S respectively; when the language value E of the input variable moving stroke is PM, the language value of the other input variable moving stroke derivative

The variables are NB, NM, NS, ZE, PS, PM and PB, and the language values of the opening and closing trends of the corresponding output variable electromagnetic valves are ZE, ZE, S, M, S, ZE and ZE respectively; when the language value E of the input variable moving stroke is PB, the language value of the derivative of the moving stroke of the other input variable is

The variables are NB, NM, NS, ZE, PS, PM and PB, and the corresponding output variable electromagnetic valve opening and closing trend language values are ZE, ZE, S, M, S, ZE and ZE respectively.

Generally speaking, the selection of the membership function has great subjectivity, and needs to be specifically analyzed according to actual conditions. The input variable of the invention adopts a triangular function, and the output variable adopts a Gaussian function.

And 5, outputting the trend of continuous electromagnetic valve switches in the range of (0,1) by the fuzzy controller after receiving the input, and therefore, rounding the output. Therefore, rounding is carried out behind the fuzzy controller, when the output is 0, the electromagnetic valve is controlled to be closed, and when the output is 1, the electromagnetic valve is opened.

In order to verify the effect of the designed controller, the established whole suspension system is subjected to simulation analysis in a Matlab/Simulink environment, the suspension system takes the moving stroke and the derivative thereof as control signals to be transmitted to a fuzzy control module, the controller outputs an electromagnetic valve control signal to perform mode switching on the multi-mode damping shock absorber, and the shock absorber realizes the adjustment of damping parameters according to working conditions. In fig. 5 and 6, the on-off states of the two solenoid valves when a random road surface is input are shown. On this basis, the overall controller damping mode output is shown in fig. 7. To further evaluate the effectiveness of the semi-active suspension control designed with the multi-mode damping shock absorber, a semi-active suspension with a continuously adjustable damping shock absorber and with a skyhook control was used for comparison. In general, the skyhook control is often regarded as a benchmark control method for verifying the effect of a novel control strategy for a vehicle suspension, and the damping force of a skyhook controller is as follows:

in the formula: k_skyIs the ceiling damping coefficient. The simulation results of the system, namely the designed damping multi-mode adjustable semi-active suspension and the designed ceiling control semi-active suspension vertical vibration acceleration and dynamic stroke pair are shown in fig. 8 and 9, and the simulation results in the figures are further analyzed and processed to obtain the root mean square value change results shown in table 4.

As can be seen from fig. 8,9 and table 4, the damped multi-mode semi-active suspension with the fuzzy controller effectively improves the vertical acceleration and the dynamic stroke performance of the suspension, and shows that the designed control method achieves the purpose of improving the comfort of the suspension and can be well matched with the multi-mode damped suspension.

TABLE 4

In conclusion, the fuzzy switching control method of the damping multi-mode semi-active suspension electronic control system determines the gear division and the damping range of damping switching through the optimal damping ratio characteristic of the suspension. Four different damping working modes of the adjustable suspension can be realized by controlling the on-off states of the two high-speed switching electromagnetic valves, so that the damping control of the semi-active suspension of the vehicle is more efficient and energy-saving. Firstly, the sprung mass acceleration and the unsprung mass acceleration are obtained by using a sensor, and the obtained acceleration signals are integrated to obtain velocity and displacement signals of the sprung mass and the unsprung mass. And further processing the speed displacement signal as a judgment basis of the tension and compression state of the suspension at the moment, taking the processed speed displacement signal as an input signal of a fuzzy controller to perform fuzzy judgment, and outputting the fuzzy judgment as opening and closing signals of two high-speed switching electromagnetic valves of the suspension. The on-off signal controls the on-off state of the high-speed switch electromagnetic valve, so that the suspension can provide good vibration reduction effect no matter what state the vehicle is in. The invention can realize the good damping switching control effect of the suspension system, and utilizes the fuzzy control to avoid the defect of large calculation amount of the traditional control, thereby improving the running smoothness of the vehicle.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.