Vehicle body height adjustment method, device, equipment and storage medium

Abstract

The application discloses a vehicle body height adjusting method, which comprises the following steps: obtaining a plurality of actual vehicle body heights obtained by multiple vehicle body height adjustments; determining a plurality of vehicle body height differences between the plurality of actual vehicle body heights and a target vehicle body height of the vehicle; inputting the plurality of vehicle body height differences and the corresponding change rates into a fuzzy PID controller as input variables, and obtaining a constant speed approach law coefficient output by the fuzzy PID controller; taking the constant speed approach law coefficient output by the fuzzy PID controller as a constant speed approach law coefficient of an SMC sliding mode controller, and obtaining a sliding mode control variable output by the SMC sliding mode controller; the sliding mode control variable is an opening value of an electromagnetic valve of an air spring; and based on the opening value of the electromagnetic valve, the vehicle is adjusted once under the condition that the inflation and deflation speeds of the air spring are constant.

Description

Technical Field

[0001] This application relates to, but is not limited to, the field of automotive safety, and particularly to a method, device, equipment, and storage medium for adjusting vehicle height. Background Technology

[0002] Air suspension uses air springs instead of metal coil springs. The electronic control system uses an air pump and solenoid valves to adjust the amount and pressure of air in the air spring cylinders, changing the stiffness and spring rate of the air springs (allowing for arbitrary adjustment of the suspension's firmness). By adjusting the amount of air pumped in, the stroke and length of the air spring cylinder piston can be adjusted, allowing the vehicle chassis to be raised or lowered while maintaining both comfort and handling. However, during the inflation and deflation of air springs, over-inflation and over-distension often occur, resulting in a discrepancy between the actual vehicle height and the ideal target height, making it impossible to precisely control the vehicle's height at the desired level. Summary of the Invention

[0003] In view of this, embodiments of this application provide at least one method, apparatus, device, and storage medium for adjusting vehicle height.

[0004] The technical solution of this application embodiment is implemented as follows:

[0005] On one hand, this application provides a vehicle body height adjustment method applied to a vehicle. The method includes: acquiring multiple actual vehicle body heights obtained by performing multiple vehicle body height adjustments on the vehicle; determining multiple vehicle body height differences between the multiple actual vehicle body heights and the target vehicle body height; inputting the multiple vehicle body height differences and the corresponding rates of change of the multiple vehicle body height differences as input variables into a fuzzy PID controller, and acquiring the constant velocity reaching law coefficient output by the fuzzy PID controller; using the constant velocity reaching law coefficient output by the fuzzy PID controller as the constant velocity reaching law coefficient of an SMC sliding diaphragm controller, and acquiring the sliding diaphragm control quantity output by the SMC sliding diaphragm controller; the sliding diaphragm control quantity being the opening value of the solenoid valve of an air spring; and, while keeping the inflation and deflation speeds of the air spring constant, adjusting the vehicle body height once based on the opening value of the solenoid valve.

[0006] On the other hand, this application provides a vehicle height adjustment device applied to a vehicle. The device includes: a first acquisition module for acquiring multiple actual vehicle heights obtained by performing multiple vehicle height adjustments on the vehicle; a first determination module for determining multiple vehicle height differences between the multiple actual vehicle heights and the target vehicle height; a second acquisition module for inputting the multiple vehicle height differences and the corresponding rates of change of the multiple vehicle height differences as input variables into a fuzzy PID controller, and acquiring the constant velocity reaching law coefficient output by the fuzzy PID controller; a third acquisition module for using the constant velocity reaching law coefficient output by the fuzzy PID controller as the constant velocity reaching law coefficient of an SMC sliding diaphragm controller, and acquiring the sliding diaphragm control quantity output by the SMC sliding diaphragm controller; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring; and a first adjustment module for adjusting the vehicle height once based on the opening value of the solenoid valve while keeping the inflation and deflation speed of the air spring constant.

[0007] In another aspect, embodiments of this application provide a computer device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the program to implement some or all of the steps in the above-described method.

[0008] In another aspect, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements some or all of the steps in the above-described method.

[0009] In this embodiment, the difference between the actual vehicle height and the target vehicle height obtained when adjusting the vehicle height is used as the input of the fuzzy PID controller. The constant velocity approach rate coefficient of the SMC sliding diaphragm controller is continuously updated with the constant velocity approach rate coefficient output by the fuzzy PID controller. Using this method, the actual vehicle height continuously approaches the target vehicle height, achieving the purpose of precise control of the vehicle height, avoiding the occurrence of "overcharging" and "over-discharging" phenomena, and ensuring that the vehicle reaches the ideal target vehicle height.

[0010] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and are not intended to limit the technical solutions of this disclosure. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein:

[0012] Figure 1 A schematic diagram illustrating the implementation process of a vehicle body height adjustment method provided in this application embodiment;

[0013] Figure 2 Examples of this application Figure 1 A schematic diagram of the implementation process of step S103;

[0014] Figure 3 Examples of this application Figure 2 A schematic diagram of the implementation process of step S104;

[0015] Figure 4 Examples of this application Figure 3 A schematic diagram of the implementation process of step S304;

[0016] Figure 5 Examples of this application Figure 1 A schematic diagram illustrating the process of adjusting the vehicle's height after one adjustment.

[0017] Figure 6 Examples of this application Figure 1 The diagram illustrates the implementation process of using the vehicle height difference obtained by adjusting the vehicle height using the SMC sliding mode controller as the input of the fuzzy PID controller.

[0018] Figure 7 Examples of this application Figure 1 A schematic diagram of the implementation process of step S105;

[0019] Figure 8 A quarter-vehicle suspension vibration model;

[0020] Figure 9 This is a schematic diagram of the composition structure of a vehicle height adjustment device provided in an embodiment of this application;

[0021] Figure 10 This is a schematic diagram of the hardware entity of a computer device provided in an embodiment of this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application are further described in detail below with reference to the accompanying drawings and embodiments. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0024] It should be noted that the terms "first, second, and third" used in the embodiments of this application are merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, and third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0025] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments of this application pertain. It should also be understood that terms such as those defined in general dictionaries should be understood to have a meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0026] A PID controller (Proportion Integration Differential) consists of a proportional unit (P), an integral unit (I), and a derivative unit (D). K is set. P K i and K d Three parameters. PID controllers are mainly suitable for systems with basic linearity and dynamic characteristics that do not change over time.

[0027] The first law of thermodynamics states that the increase in internal energy is equal to the heat absorbed or released plus the work done by the object on the surroundings or the work done by the surroundings on the object. The formula is ΔU = QW, where ΔU is the change in internal energy of the system, Q is the heat absorbed by the system, and W is the work done by the system.

[0028] Specific enthalpy: the energy per unit mass of a substance under constant pressure, usually represented by the symbol H.

[0029] Equation of state: A functional relationship characterizing three thermodynamic parameters of a fluid: pressure, density, and temperature. Different fluid models have different equations of state, which can be expressed by the following relationship: p = p(ρT) or U = U(ρT), where p is the pressure; ρ is the fluid density; T is the thermodynamic temperature; and U is the internal energy per unit mass of fluid.

[0030] SMC (Sliding Mode Control): This refers to sliding mode control, a nonlinear control structure. The sliding mode can be designed and is independent of object parameters and disturbances, featuring fast response, insensitivity to parameter changes and disturbances (robustness), no need for online system identification, and simple physical implementation. However, when the state trajectory reaches the sliding mode surface, it is difficult to strictly slide along the sliding mode surface to the equilibrium point. Instead, it approaches the equilibrium point by traversing back and forth on both sides, thus producing chattering.

[0031] Air suspension uses air springs instead of metal coil springs. The electronic control system uses an air pump and solenoid valves to adjust the amount and pressure of air in the air spring cylinders, changing the stiffness and spring rate of the air springs (allowing for arbitrary adjustment of suspension firmness). By adjusting the amount of air pumped in, the stroke and length of the air spring cylinder piston can be adjusted, allowing the vehicle chassis to be raised or lowered while maintaining both comfort and handling. However, during the inflation and deflation of air springs, over-inflation and over-distension can occur, leading to a discrepancy between the actual vehicle height and the ideal target height, preventing precise control of the vehicle's height.

[0032] In this embodiment, to precisely control the vehicle height of the air-suspension vehicle, multiple differences between the actual vehicle height obtained from multiple adjustments and the target vehicle height are input variables to a fuzzy PID controller, and the constant velocity approach law coefficient output by the fuzzy PID controller is obtained. The constant velocity approach law coefficient output by the fuzzy PID controller is used as the constant velocity approach law coefficient of the SMC diaphragm controller to obtain the diaphragm control quantity output by the diaphragm controller. The diaphragm control quantity is the opening value of the solenoid valve of the air spring. The vehicle height is adjusted by the opening value of the solenoid valve to obtain the target vehicle height.

[0033] This application provides a vehicle body height adjustment method, applied to vehicles, such as... Figure 1 As shown, the method may include steps S101 to S105:

[0034] Step S101: Obtain multiple actual vehicle heights obtained by adjusting the vehicle height multiple times;

[0035] Here, the actual vehicle height is the vehicle height obtained by the vehicle's built-in sensors.

[0036] Step S102: Determine the multiple vehicle height differences between the multiple actual vehicle heights and the target vehicle height;

[0037] Step S103: Input the multiple vehicle height differences and the corresponding rate of change of the multiple vehicle height differences as input variables into the fuzzy PID controller, and obtain the constant velocity approach law coefficients output by the fuzzy PID controller;

[0038] Here, the input variables first need to be fuzzified. During fuzzification, the triangular membership function is used. Based on the fuzzified input variables, K is established respectively. P K i and K d A fuzzy rule table with three parameters; secondly, for K P Ki and K d The three parameters are defuzzified using the centroid method, which has good continuity. Finally, based on the defuzzified K... P K i and K d The constant velocity reaching law coefficients of the fuzzy PID controller output are obtained from the three parameters.

[0039] Step S104: Use the constant velocity approach law coefficient output by the fuzzy PID controller as the constant velocity approach law coefficient of the SMC sliding diaphragm controller, and obtain the sliding diaphragm control quantity output by the SMC sliding diaphragm controller; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring.

[0040] Based on the mass and displacement of the vehicle's air suspension, the opening value of the solenoid valve of the air spring, and the derived pressure gradient equation of the air spring, the state equation of the SMC sliding mode controller is determined; the surface that can achieve sliding mode motion is selected as the sliding surface; the constant velocity approaching law coefficient output by the fuzzy PID controller is used as the coefficient of the constant velocity approaching law function; the sliding control quantity output by the sliding mode controller is adjusted through the control function constant velocity approaching law function.

[0041] Step S105: With the inflation and deflation speed of the air spring remaining constant, adjust the vehicle height once based on the opening value of the solenoid valve.

[0042] Since the air pump's output power is constant, the inflation and deflation speeds remain essentially unchanged. The opening signal of the solenoid valve output from the SMC sliding mode controller is transmitted to the controller. There's a direct correlation between the solenoid valve's opening and the current controlling it; ultimately, the inflation and deflation operations are controlled by adjusting the current. At this point, there will be a difference between the actual height and the target height. This difference becomes the control input for the subsequent fuzzy PID controller. After a series of calculations, the fuzzy PID controller outputs a constant velocity approximation coefficient. By updating this coefficient, the opening of the solenoid valve output from the sliding mode controller is controlled, thus forming a closed loop for real-time optimization.

[0043] In some embodiments, in step S103 above, the plurality of vehicle height differences and the corresponding rates of change of the plurality of vehicle height differences are input as input variables to the fuzzy PID controller, and the constant velocity reaching law coefficients output by the fuzzy PID controller are obtained, such as... Figure 2 As shown, steps S201 to S205 may be included:

[0044] Step S201: Based on the triangular membership function, the initial input variables are fuzzified to obtain the fuzzified input variables;

[0045] Here, the triangular membership function is used when performing fuzzification.

[0046] Step S202: Based on the fuzzified input variables, establish fuzzy rule tables for the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller respectively;

[0047] Step S203: Based on the fuzzy rule table of the three parameters of the fuzzy PID controller (proportional unit, integral unit, and derivative unit), obtain the fuzzified three parameters of the fuzzy PID controller (proportional unit, integral unit, and derivative unit).

[0048] Step S204: Perform a defuzzification operation on the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller to obtain the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller after defuzzification.

[0049] Step S205: Adjust the output of the fuzzy PID controller based on the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller after the defuzzification is completed, and obtain the constant velocity approach law coefficient of the fuzzy PID controller output.

[0050] In some embodiments, in step S104 above, the constant velocity reaching law coefficient output by the fuzzy PID controller is used as the constant velocity reaching law coefficient of the SMC sliding diaphragm controller, and the sliding control quantity output by the SMC sliding diaphragm controller is obtained, such as... Figure 3 As shown, steps S301 to S304 may be included:

[0051] Step S301: Based on the mass and mass displacement of the vehicle's air suspension, the opening value of the solenoid valve of the air spring, and the pressure gradient equation of the air spring, determine the state equation of the SMC diaphragm controller.

[0052] Step S302: Select the surface that can achieve sliding mode motion and define it as the sliding surface;

[0053] Step S303: Determine the constant-rate reaching law function based on the constant-rate reaching law coefficients output by the fuzzy PID controller;

[0054] Step S304: Based on the state equation of the SMC sliding controller, the sliding surface, and the isotropic approaching law function, determine the sliding control quantity output by the sliding controller.

[0055] In some embodiments, in step S304 above, determining the sliding control quantity output by the sliding controller based on the state equation of the SMC sliding controller, the sliding surface, and the isotropic reaching law function, such as... Figure 4As shown, steps S401 to S404 may be included:

[0056] Step S401: Based on the state equation of the sliding diaphragm controller, solve for the opening value of the solenoid valve of the air spring;

[0057] Step S402: Determine the constant velocity approach law function as the control function in the formula for solving the opening value of the solenoid valve of the air spring;

[0058] Step S403: The opening value of the solenoid valve of the air spring continuously approaches the target value along the sliding surface under the control of the constant velocity approaching law function;

[0059] Step S404: Determine the opening value of the solenoid valve of the air spring as the sliding control quantity output by the sliding controller.

[0060] In some embodiments, after the vehicle height is adjusted once, such as Figure 5 As shown, steps S501 to S503 may be included:

[0061] Step S501: Input the first body height difference between the actual body height obtained during the first body height adjustment and the target body height of the vehicle, and the rate of change corresponding to the first body height difference, as input variables into the fuzzy PID controller, and obtain the constant velocity approach law coefficient output by the fuzzy PID controller.

[0062] Step S502: Use the constant velocity approach law coefficient output by the fuzzy PID controller as the constant velocity approach law coefficient of the SMC sliding diaphragm controller, and obtain the sliding diaphragm control quantity output by the SMC sliding diaphragm controller; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring.

[0063] Step S503: With the inflation and deflation speed of the air spring remaining constant, the vehicle body height is adjusted again based on the opening value of the solenoid valve of the air spring until the error of the vehicle body height difference approaches zero.

[0064] In some embodiments, such as Figure 6 As shown, it may include steps S601 and S602:

[0065] Step S601: After each adjustment of the vehicle height, determine the difference between the actual vehicle height and the target vehicle height for each adjustment;

[0066] Step S602: Determine the difference between the actual vehicle height and the target vehicle height for each time as the input of the fuzzy PID controller for the next time.

[0067] In some embodiments, in step S105 above, while the inflation and deflation speeds of the air spring remain constant, the vehicle height is adjusted once based on the opening value of the solenoid valve. Figure 7 As shown, steps S701 to S203 may be included:

[0068] Step S701: With the inflation and deflation speed of the air spring remaining constant, determine the current of the solenoid valve based on the opening value of the solenoid valve;

[0069] The output of the diaphragm control is the opening degree of the solenoid valve, which is then transmitted to the controller. When the inflation and deflation speed of the air spring remains constant, there is a corresponding relationship between the opening degree of the solenoid valve and the magnitude of the current controlling the solenoid valve.

[0070] Step S702: Adjust the height of the air spring by controlling the current of the solenoid valve;

[0071] The height of the air spring is adjusted by changing the current of the solenoid valve to charge and deflate the air spring.

[0072] Step S703: Adjust the vehicle height by changing the height of the air spring.

[0073] The above-described vehicle height adjustment method will be described in detail below with reference to a specific embodiment. However, it is worth noting that this specific embodiment is only for better illustration of this application and does not constitute an improper limitation of this application.

[0074] This application provides an overall technical solution for vehicle height adjustment, which may include steps S801 to S804:

[0075] Step S801: Combining the three processes of inflation / deflation and solenoid valve closure, derive the pressure gradient equation of the gas inside the air spring;

[0076] This application's embodiment selects the suspension of one-quarter of a vehicle for analysis, such as... Figure 8 The vibration model is a quarter-vehicle suspension model. The corresponding dynamic model is obtained by force analysis based on the quarter-vehicle suspension model, as shown in formula (1).

[0077]

[0078] In formula (1), m s Z represents the sprung mass of the air suspension in a quarter-vehicle. s Z represents the sprung mass displacement of a quarter-vehicle air suspension; up represents the unsprung mass displacement of a quarter-vehicle air suspension; p represents the absolute air pressure of the air spring; p0 represents atmospheric pressure; m u A represents the unsprung mass of a quarter-vehicle air suspension; e Indicates the effective area of ​​the air spring; k l Indicates the stiffness of the air spring; Z r denoted by , where c is the road surface excitation displacement; is the damping coefficient; and g is the gravitational acceleration.

[0079] According to the first law of thermodynamics, the gas equation inside the air spring is given by equation (2):

[0080] dU1+dW1+h1dm1=dQ1+h2dm2 (2);

[0081] Wherein, dU1 is the change in internal energy of the gas inside the air spring; dW1 is the expansion work done by the change in volume of the gas inside the air spring; h1 is the specific enthalpy of the gas entering the atmosphere from the air spring; dm1 is the mass of the gas entering the atmosphere from the air spring; dQ1 is the heat exchanged between the gas inside the air spring and the outside world; h2 is the specific enthalpy of the gas entering the air spring from the gas storage tank; and dm2 is the mass of the gas entering the air spring from the gas storage tank.

[0082] Force analysis was performed on a quarter of the vehicle suspension model to obtain the corresponding dynamic model and gas equations within the air spring. The analysis covered three scenarios: inflation, deflation, and solenoid valve closure.

[0083] Scenario 1: Inflation process:

[0084] Since the inflation process is short, it can be considered an adiabatic process, so dQ1 = 0, dm1 = 0; formulas (3), (4), and (5) can be obtained:

[0085] dU1=c v d(T2m2) (3);

[0086] In formula (3), T2 is the thermodynamic temperature inside the gas storage tank; c v The specific heat capacity of a gas at constant pressure. k is the gas adiabatic index, k = 1.35; R is the gas constant.

[0087] dW1=p1dV1 (4);

[0088] In formula (4), p1 is the absolute pressure of the gas inside the air spring; V1 is the gas volume inside the air spring, V1 = V 10 +β(Z s -Z u );V 10β is the initial volume of the air spring; β is the rate of change of the air spring's volume.

[0089] h2 = c p T2 (5);

[0090] In formula (5), c p The specific heat capacity of a gas at constant volume.

[0091] Substituting formulas (3), (4), and (5) into formula (2), we obtain formula (6):

[0092] kRT2dm2=kp1dV1+V1dp1 (6);

[0093] Scenario 2: The venting process:

[0094] The venting process is an adiabatic process, and no gas enters the air spring from the storage tank, so dQ1 = 0 and dm2 = 0 can be obtained; formulas (7), (8) and (9) can also be obtained:

[0095] dU1=c v d(T1m1) (7);

[0096] dW1=p1dV1 (8);

[0097] h1 = c p T1 (9);

[0098] Substituting formulas (7), (8), and (9) into formula (2), we obtain formula (10):

[0099] -kRT1dm1=kp1dV1+V1dp1 (10);

[0100] Scenario 3: Solenoid valve closed:

[0101] When the solenoid valve is closed, the gas inside the air spring undergoes a polytropic process, which can be expressed by formula (11):

[0102] kp1dV1+V1dp1=0 (11);

[0103] The ideal gas law can be found in equation (12):

[0104] p1V1 k =p0V0 k =const (12);

[0105] In formula (12), p0 is the pressure of the air spring when it returns to its equilibrium position after the solenoid valve is closed; V0 is the volume of the air spring when it returns to its equilibrium position after the solenoid valve is closed.

[0106] Combining the inflation / deflation process and the solenoid valve closing process, the pressure gradient equation of the gas inside the air spring can be obtained (see formula (13)).

[0107]

[0108] Where, q m This represents the gas mass flow rate when the solenoid valve is fully open, with positive values ​​for charging and negative values ​​for discharging.

[0109] Step S802: Based on the pressure gradient equation derived in step S801, determine the pressure term in the state equation of the sliding mode controller; based on the state equation and the established sliding surface, obtain the sliding control quantity output by the sliding mode controller.

[0110] The SMC sliding mode controller is a nonlinear control structure. Its sliding mode can be designed and is independent of object parameters and disturbances, offering advantages such as fast response, insensitivity to parameter changes and disturbances (robustness), no need for online system identification, and simple physical implementation. However, once the state trajectory reaches the sliding mode surface, it is difficult to slide strictly along the surface to the equilibrium point. Instead, it approaches the equilibrium point by traversing back and forth on both sides, resulting in chattering. The SMC sliding mode controller uses the constant velocity approach rate coefficient of the fuzzy PID output as its constant velocity approach rate coefficient. Through repeated adjustments, the output of the sliding mode controller continuously approaches the target value, thereby achieving adjustment of the target height. The SMC-fuzzy PID controller can fully utilize the advantages of both control structures to achieve superior control performance.

[0111] The design of the sliding mode controller may include steps S811 to S813:

[0112] Step S811: Based on the pressure gradient equation derived in step S801, determine the pressure term in the state equation of the sliding mode controller; determine the other terms in the state equation based on the mass and mass displacement of the quarter-air suspension system.

[0113] First, select the state variables of the state equation, as shown in formula (14):

[0114]

[0115] The definition of the output variable can be found in formula (15):

[0116] y = x s -x u =x1-x2 (15);

[0117] Therefore, the state equation can be found in formula (16):

[0118]

[0119] In formula (16), u is the input value of the solenoid valve opening degree;

[0120]

[0121]

[0122] y = h(x) (17);

[0123] In formula (17), h(x) = [x1 - x2 0 0 0] T .

[0124] Step S812: Based on the state equation determined in step S811, establish a sliding surface that can achieve sliding mode motion;

[0125] First, the error vector of the sliding surface needs to be determined, as shown in formula (18):

[0126]

[0127] Secondly, based on the error vector of the sliding surface, the sliding surface is established, as shown in formula (19):

[0128]

[0129] Step S813: Use the constant velocity approach rate function as the control function so that the sliding mode control quantity continuously approaches the target value on the sliding mode surface, and obtain the sliding mode control quantity output by the sliding mode controller;

[0130] The approach law used by this synovial controller is as shown in formula (20):

[0131]

[0132] In formula (20), k represents the coefficient of the constant-rate approach law.

[0133] Based on the established sliding surface and the approaching law function, the calculation formula for the sliding control quantity is obtained, which can be found in formula (21):

[0134]

[0135] In formula (21), v e Indicates the equivalent control quantity. v s Represented as the switching control quantity, v s = -ksgn(s), where k represents the coefficient of the constant-rate approach law, and k is greater than 0.

[0136] Finally, the sliding mode control quantity is the opening degree of the solenoid valve. Therefore, the opening degree of the solenoid valve can be obtained from formula (22):

[0137]

[0138] The control output of the diaphragm controller is the opening degree of the solenoid valve, which is then transmitted to the controller. The opening degree of the solenoid valve and the magnitude of the current controlling the solenoid valve are related. Ultimately, the subsequent inflation and deflation operations are performed by changing the current magnitude. At this time, there will be a difference between the actual height and the target height. This difference is the control input of the subsequent fuzzy PID controller. After a series of calculations, a constant velocity approximation coefficient is output. By updating the constant velocity approximation coefficient, the opening degree of the solenoid valve output by the diaphragm controller is controlled again, thus forming a closed loop for real-time optimization.

[0139] Step S803: Based on the difference between the actual vehicle height and the target vehicle height obtained when adjusting the vehicle height using the SMC sliding diaphragm controller, and the rate of change of the difference between the vehicle height obtained from multiple vehicle height adjustments, the fuzzy PID controller is used as the input to obtain the constant velocity approach rate coefficient output by the fuzzy PID controller.

[0140] The fuzzy PID controller uses the vehicle height difference Δh and its rate of change as inputs, and the constant velocity reaching law coefficient as output. The vehicle height difference Δh is the difference between the target vehicle height and the actual vehicle height. The specific process may include steps S821 to S825:

[0141] Step S821: Use the triangular membership function to fuzzify the input variables of the fuzzy controller;

[0142] In this embodiment of the application, the vehicle height difference Δh and the rate of change of Δh are used as inputs, and the fuzzy subsets of both are defined as {NB, NM, NS, ZO, PS, PM, PB}, where negative large [NB], negative medium [NM], negative small [NS], zero [ZO], positive small [PS], positive medium [PM], and positive large [PB], and the universe of discourse is set to {-6, 6}.

[0143] When performing fuzzification, the membership function used is the triangular membership function.

[0144] Step S822: Based on the fuzzy input variables, establish the k-value of the fuzzy PID controller. p k i k d A fuzzy rule table with three parameters;

[0145] In this embodiment of the application, the specific fuzzy rules include Δk p Fuzzy rules, △k i Fuzzy rules and △k i The fuzzy rules are shown in Tables 1, 2, and 3 below:

[0146] Table 1 △k p Fuzzy rules

[0147]

[0148] Table 2 △k i Fuzzy rules

[0149]

[0150] Table 3 △k d Fuzzy rules

[0151]

[0152] Step S823: The blurred k obtained in step S822... p k i k d The three parameters are used for defuzzification.

[0153] In this embodiment, the centroid method, which has better continuity, is used for defuzzification. After defuzzification, k is obtained. p k i k d Three parameters.

[0154] Step S824: Based on the k of the fuzzy PID controller obtained after defuzzification... p k i k d The output of the fuzzy PID controller is adjusted by three parameters to obtain the constant-rate approach law coefficients of the fuzzy PID controller output.

[0155] Step S825: Update the obtained constant velocity approach law coefficients to the opening degree of the solenoid valve output by the sliding diaphragm controller in step S813.

[0156] Step S804: The air compressor adjusts the vehicle height according to the solenoid valve opening value output by the SMC diaphragm controller.

[0157] The control output of the diaphragm controller is the opening degree of the solenoid valve. Subsequent inflation and deflation operations are performed based on the opening degree of the solenoid valve. At this time, there will be a difference between the actual height and the target height. This difference is the control input of the fuzzy PID controller. After a series of calculations, a constant velocity approximation coefficient is output. By updating the constant velocity approximation coefficient, the opening degree of the solenoid valve output by the diaphragm controller is controlled again, thus forming a closed loop for real-time optimization.

[0158] The vehicle height is adjusted by changing the opening of the solenoid valve. By repeating this process, the error between the actual vehicle height and the target vehicle height can be brought close to zero.

[0159] To address the aforementioned implementation process, this application proposes a method for adjusting vehicle body height. This method uses the constant velocity approach rate coefficient output by a fuzzy controller to update the constant velocity approach rate coefficient of the SMC sliding diaphragm control, thereby obtaining the opening value of the solenoid valve of the air spring. The vehicle body height is adjusted by controlling the opening value of the solenoid valve; through repeated adjustments, the error between the actual vehicle body height and the target vehicle body height approaches zero. This method avoids the phenomena of "overcharging" and "over-discharging," ensuring that the vehicle reaches the ideal target body height.

[0160] Based on the foregoing embodiments, this application provides a vehicle height adjustment device, which includes various modules and units included in each module. It can be implemented by a processor in a computer device; of course, it can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0161] Based on the foregoing embodiments, this application provides a vehicle height adjustment device applied to a vehicle. The device includes various modules and units included in each module, which can be implemented by a processor in a computer device; of course, it can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0162] This application provides a vehicle height adjustment device applied to air suspension vehicles, such as... Figure 9 As shown, the device 900 includes:

[0163] The first acquisition module 901 is used to acquire multiple actual vehicle heights obtained by adjusting the vehicle height multiple times.

[0164] The first determining module 902 is used to determine multiple body height differences between the multiple actual body heights and the target body height of the vehicle;

[0165] The second acquisition module 903 is used to input the multiple vehicle height differences and the corresponding rate of change of the multiple vehicle height differences as input variables into the fuzzy PID controller, and to acquire the constant velocity approach law coefficients output by the fuzzy PID controller.

[0166] The third acquisition module 904 is used to take the constant velocity approach law coefficient output by the fuzzy PID controller as the constant velocity approach law coefficient of the SMC sliding diaphragm controller, and acquire the sliding diaphragm control quantity output by the SMC sliding diaphragm controller; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring.

[0167] The first adjustment module 905 is used to adjust the vehicle height once based on the opening value of the solenoid valve, while keeping the inflation and deflation speed of the air spring constant.

[0168] In some embodiments, the second acquisition module includes:

[0169] The first obtaining unit is used to perform fuzzification processing on the initial input variable based on the triangular membership function to obtain the fuzzified input variable;

[0170] Establish a unit to create fuzzy rule tables for the proportional unit, integral unit, and derivative unit of the fuzzy PID controller based on the fuzzified input variables.

[0171] The second obtaining unit is used to obtain the fuzzified proportional unit, integral unit, and derivative unit parameters of the fuzzy PID controller based on the fuzzy rule table of the three parameters of the fuzzy PID controller.

[0172] The third obtaining unit is used to perform a defuzzification operation on the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller to obtain the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller after defuzzification.

[0173] The fourth obtaining unit adjusts the output of the fuzzy PID controller based on the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller after the defuzzification is completed, and obtains the constant velocity approach law coefficients output by the fuzzy PID controller.

[0174] In some embodiments, the third acquisition module includes:

[0175] The first determining unit is used to determine the state equation of the SMC diaphragm controller based on the mass and mass displacement of the vehicle's air suspension, the opening value of the solenoid valve of the air spring, and the pressure gradient equation of the air spring.

[0176] The second determining unit is used to select the surface that can achieve sliding mode motion and determine it as the sliding surface;

[0177] The third determining unit is used to determine the constant velocity approaching law function based on the constant velocity approaching law coefficients output by the fuzzy PID controller.

[0178] The fourth determining unit is used to determine the sliding control quantity output by the sliding controller based on the state equation of the SMC sliding controller, the sliding surface, and the isotropic approaching law function.

[0179] In some embodiments, the fourth determining unit includes:

[0180] The solution subunit is used to solve for the opening value of the solenoid valve of the air spring based on the state equation of the sliding diaphragm controller.

[0181] The first determining subunit is used to determine the constant velocity approach law function as the control function in the formula for solving the opening value of the solenoid valve of the air spring;

[0182] The opening value of the solenoid valve used for the air spring in the approaching subunit is controlled by the constant velocity approaching law function to continuously approach the target value along the sliding surface;

[0183] The second determining subunit is used to determine the opening value of the solenoid valve of the air spring as the sliding control quantity output by the sliding controller.

[0184] In some embodiments, the apparatus further includes:

[0185] The fourth acquisition module is used to input the first body height difference between the actual body height obtained during the first body height adjustment and the target body height of the vehicle, as well as the rate of change corresponding to the first body height difference, into the fuzzy PID controller as input variables, and to obtain the constant velocity approach law coefficient output by the fuzzy PID controller.

[0186] The fifth acquisition module is used to take the constant velocity approach law coefficient output by the fuzzy PID controller as the constant velocity approach law coefficient of the SMC sliding diaphragm controller, and to acquire the sliding diaphragm control quantity output by the SMC sliding diaphragm controller; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring.

[0187] The second adjustment module is used to adjust the vehicle height again based on the opening value of the solenoid valve of the air spring, while keeping the inflation and deflation speed of the air spring constant, until the error of the vehicle height difference approaches zero.

[0188] In some embodiments, the apparatus further includes:

[0189] The second determining module is used to determine the difference between the actual vehicle height and the target vehicle height after each adjustment of the vehicle height.

[0190] The third determining module is used to determine the difference between the actual vehicle height and the target vehicle height for each time as the input of the fuzzy PID controller for the next time.

[0191] In some embodiments, the first adjustment module includes:

[0192] The fifth determining unit is used to determine the magnitude of the current of the solenoid valve based on the opening value of the solenoid valve, while the inflation and deflation speed of the air spring remains constant.

[0193] The first adjustment unit is used to adjust the height of the air spring by controlling the current of the solenoid valve;

[0194] The second adjustment unit is used to adjust the vehicle height once by changing the height of the air spring.

[0195] The descriptions of the apparatus embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. In some embodiments, the functions or modules included in the apparatus provided in this application can be used to perform the methods described in the method embodiments above. For technical details not disclosed in the apparatus embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0196] It should be noted that, in the embodiments of this application, if the above-described methods are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware, software, or firmware, or any combination of hardware, software, and firmware.

[0197] This application provides a computer device including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the program, it implements some or all of the steps in the above-described method.

[0198] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements some or all of the steps in the above-described method. The computer-readable storage medium can be transient or non-transient.

[0199] This application provides a computer program including computer-readable code, wherein when the computer-readable code is executed in a computer device, a processor in the computer device performs some or all of the steps in the above-described method.

[0200] This application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the above-described method. This computer program product can be implemented specifically through hardware, software, or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium; in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0201] It should be noted that the descriptions of the various embodiments above tend to emphasize the differences between them, while their similarities or commonalities can be referred to interchangeably. The descriptions of the above embodiments of the device, storage medium, computer program, and computer program product are similar to the descriptions of the above method embodiments and have similar beneficial effects. For technical details not disclosed in the embodiments of the device, storage medium, computer program, and computer program product of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0202] This application provides a computer device, such as... Figure 10 As shown, the hardware entities of the computer device 1000 include: a processor 1001, a communication interface 1002, and a memory 1003. The processor 1001 typically controls the overall operation of the computer device 1000. The communication interface 1002 enables the computer device to communicate with other terminals or servers via a network. The memory 1003 is configured to store instructions and applications executable by the processor 1001, and can also cache data to be processed or already processed (e.g., image data, audio data, voice communication data, and video communication data) in the processor 1001 and various modules of the computer device 1000. It can be implemented using flash memory (FLASH) or random access memory (RAM). Data transfer between the processor 1001, the communication interface 1002, and the memory 1003 can be performed via a bus 1004.

[0203] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above steps / processes do not imply a sequential order of execution; the execution order of each step / process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above embodiments of this application are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0204] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0205] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0206] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this application may all be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the integrated unit may be implemented in hardware or in a combination of hardware and software functional units.

[0207] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0208] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence or the part that contributes to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, magnetic disks, or optical disks.

[0209] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for adjusting vehicle body height, characterized in that, Applied to vehicles, the method includes: Obtain multiple actual vehicle heights obtained by performing multiple vehicle height adjustments; Determine the multiple vehicle height differences between the multiple actual vehicle heights and the target vehicle height; The multiple vehicle height differences and the corresponding rates of change of the multiple vehicle height differences are input variables into the fuzzy PID controller, and the constant velocity approach law coefficients output by the fuzzy PID controller are obtained. The constant velocity approaching law coefficient output by the fuzzy PID controller is used as the constant velocity approaching law coefficient of the SMC sliding diaphragm controller, and the sliding diaphragm control quantity output by the SMC sliding diaphragm controller is obtained; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring. With the inflation and deflation speeds of the air spring remaining constant, the vehicle height is adjusted once based on the opening value of the solenoid valve.

2. The method based on claim 1, characterized in that, The step of inputting the plurality of vehicle height differences and the corresponding rates of change of the plurality of vehicle height differences as initial input variables into the fuzzy PID controller, and obtaining the constant velocity reaching law coefficients output by the fuzzy PID controller, includes: Based on the triangular membership function, the initial input variables are fuzzified to obtain the fuzzified input variables; Based on the fuzzified input variables, fuzzy rule tables for the proportional unit, integral unit, and derivative unit of the fuzzy PID controller are established respectively. Based on the fuzzy rule table of the three parameters of the fuzzy PID controller (proportional unit, integral unit, and derivative unit), the fuzzified three parameters of the fuzzy PID controller (proportional unit, integral unit, and derivative unit) are obtained. The proportional unit, integral unit, and derivative unit parameters of the fuzzy PID controller are defuzzified to obtain the defuzzified proportional unit, integral unit, and derivative unit parameters of the fuzzy PID controller. Based on the three parameters of the proportional unit, integral unit, and derivative unit of the fuzzy PID controller after the defuzzification is completed, the output of the fuzzy PID controller is adjusted to obtain the constant velocity approach law coefficients output by the fuzzy PID controller.

3. The method based on claim 1, characterized in that, The step of using the constant velocity reaching law coefficient output by the fuzzy PID controller as the constant velocity reaching law coefficient of the SMC sliding diaphragm controller, and obtaining the sliding control quantity output by the SMC sliding diaphragm controller, includes: Based on the mass and mass displacement of the vehicle's air suspension, the opening value of the solenoid valve of the air spring, and the pressure gradient equation of the air spring, the state equation of the SMC diaphragm controller is determined. The surface that can achieve sliding mode motion is selected as the sliding surface; Based on the constant-velocity reaching law coefficients output by the fuzzy PID controller, the constant-velocity reaching law function is determined; Based on the state equation of the SMC sliding mode controller, the sliding surface, and the isotropic approaching law function, the sliding mode control quantity output by the sliding mode controller is determined.

4. The method based on claim 3, characterized in that, The determination of the sliding control quantity output by the sliding controller based on the state equation of the sliding controller, the sliding surface, and the isotropic reaching law function includes: Based on the state equation of the sliding diaphragm controller, the opening value of the solenoid valve of the air spring is solved; The constant velocity approach law function is determined as the control function in the formula for solving the opening value of the solenoid valve of the air spring; The opening value of the solenoid valve of the air spring is controlled by the constant velocity approaching law function, and continuously approaches the target value along the sliding surface. The opening value of the solenoid valve of the air spring is determined as the sliding control quantity output by the sliding controller.

5. The method according to any one of claims 1 to 4, characterized in that, After the vehicle height is adjusted once, the method further includes: The first body height difference between the actual body height obtained during the first body height adjustment and the target body height of the vehicle, as well as the rate of change corresponding to the first body height difference, are input as input variables to the fuzzy PID controller, and the constant velocity approach law coefficients output by the fuzzy PID controller are obtained. The constant velocity approaching law coefficient output by the fuzzy PID controller is used as the constant velocity approaching law coefficient of the SMC sliding diaphragm controller, and the sliding diaphragm control quantity output by the SMC sliding diaphragm controller is obtained; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring. With the inflation and deflation speed of the air spring remaining constant, the vehicle height is adjusted again based on the opening value of the solenoid valve of the air spring until the error of the vehicle height difference approaches zero.

6. The method according to any one of claims 1 to 4, characterized in that, The method further includes: After each adjustment of the vehicle height, determine the difference between the actual vehicle height and the target vehicle height. The difference between the actual vehicle height and the target vehicle height for each time is determined as the input of the fuzzy PID controller for the next time.

7. The method according to any one of claims 1 to 4, characterized in that, While maintaining a constant inflation and deflation rate of the air spring, the vehicle height is adjusted once based on the opening value of the solenoid valve, including: With the inflation and deflation speeds of the air spring remaining constant, the current of the solenoid valve is determined based on the opening value of the solenoid valve. The height of the air spring is adjusted by controlling the current of the solenoid valve. The vehicle's height is adjusted by changing the height of the air springs.

8. A vehicle height adjustment device, characterized in that, Applied to vehicles, the device includes: The first acquisition module is used to acquire multiple actual vehicle heights obtained by adjusting the vehicle height multiple times. The first determining module is used to determine multiple body height differences between the multiple actual body heights and the target body height of the vehicle; The second acquisition module is used to input the multiple vehicle height differences and the corresponding rate of change of the multiple vehicle height differences as input variables into the fuzzy PID controller, and to acquire the constant velocity approach law coefficients output by the fuzzy PID controller. The third acquisition module is used to take the constant velocity approach law coefficient output by the fuzzy PID controller as the constant velocity approach law coefficient of the SMC sliding diaphragm controller, and to acquire the sliding diaphragm control quantity output by the SMC sliding diaphragm controller; the sliding diaphragm control quantity is the opening value of the solenoid valve of the air spring. The first adjustment module is used to adjust the vehicle height once based on the opening value of the solenoid valve, while keeping the inflation and deflation speed of the air spring constant.

9. A vehicle comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 7.

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