A control method for a special vehicle suspension system

Abstract

The present invention relates to a control method for a special vehicle suspension system, which optimizes an objective function by using a genetic algorithm to calculate the optimized suspension system stiffness k s , suspension system damping c s ; The controller is based on the optimized suspension system damping c s Send a command to the magnetorheological damper so that its damping is the optimized damping value; the controller is based on the optimized suspension system stiffness k s Send a command to the air spring so that its stiffness is the optimized stiffness value. This method obtains the best damping coefficient and stiffness coefficient through the optimization algorithm, and controls the damping of the magnetorheological shock absorber and the stiffness of the air spring through the controller, thereby greatly improving the vibration reduction performance of the suspension system.

Description

Technical Field

[0001] The invention belongs to the field of suspension systems for special vehicles, and in particular relates to a special vehicle suspension system and a control method thereof. Background Art

[0002] As an important component of a vehicle, the suspension system directly affects the vehicle's driving stability, comfort and durability. For special vehicles, such as military vehicles, engineering vehicles or off-road vehicles, the performance requirements for the suspension system are more stringent because they often face complex and changeable driving environments. However, the existing special vehicle suspension systems often have problems such as poor shock absorption and insufficient stability when dealing with harsh road conditions, which seriously affects the vehicle's performance and life. Therefore, how to design a special vehicle suspension system that can adapt to complex environments and has excellent performance is a problem that needs to be solved urgently. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a special vehicle suspension system that can recover vibration energy and achieve good vibration reduction effect. The present invention is achieved through the following technical solutions:

[0004] A special vehicle suspension system comprises: a vehicle frame, a wheel, a steering knuckle, and a shock absorber; the steering knuckle is rotatably connected to the wheel; an upper cantilever, one end of the upper cantilever is hinged to the vehicle frame, and the other end is connected to the steering knuckle ball joint through a spherical joint; a lower cantilever, one end of the lower cantilever is hinged to the vehicle frame, and the other end is connected to the steering knuckle ball joint through a spherical joint; a controller, the controller is fixed to the vehicle frame or the upper cantilever; wherein a friction generator is also arranged in the spherical joint, and the friction generator is electrically connected to the controller; the shock absorber comprises a magnetorheological shock absorber and an air spring arranged in parallel, one end of the magnetorheological shock absorber and the air spring are connected to the lower cantilever, and the other end is connected to the vehicle frame, and the controller outputs control instructions to the air spring and the magnetorheological shock absorber to change the stiffness characteristics of the air spring and the damping characteristics of the magnetorheological shock absorber.

[0005] Further, the spherical joint includes a conical ball head rod and a connecting cover; the conical ball head rod is connected to the steering knuckle, including a conical rod and a ball head arranged on the big end side of the conical rod, and a first friction body assembly is arranged on the surface of the ball head; the connecting cover is connected to the upper cantilever or the lower cantilever, and a spherical groove matching the ball head is arranged therein, and a second friction body assembly is arranged on the surface of the spherical groove, and the first friction body assembly and the second friction body assembly constitute the friction generator.

[0006] Furthermore, it also includes a limiting member, which is conical in shape, one end is open and the other end has an opening, the maximum diameter of the conical rod is larger than the diameter of the opening and the minimum diameter is smaller than the diameter of the opening, the small end of the conical rod passes through the opening, and the large end is limited in the limiting member, and the open end of the limiting member is fixedly connected to the connecting cover to limit the ball head in the cavity surrounded by the limiting member and the connecting cover.

[0007] The present application also relates to a control method for a special vehicle suspension system as described above, comprising the following steps:

[0008] (1) Select the suspension system stiffness k s , suspension system damping c s is the optimization amount, according to the optimization variable X = [k s ,c s ] establish an objective function, the objective function f obj as follows:

[0009] f obj =αf1+βf2, where α and β are weight coefficients, and the sum of the two is, f2=RMS|x u -x q |; RMS means root mean square, x s 、x u 、x q They represent the vehicle body vertical displacement, tire vertical displacement, and road surface displacement input respectively;

[0010] (2) Determine the constraints of the objective function, which are as follows: Among them, A s The limit of the root mean square value of the vehicle body acceleration; g2=|x s -x u |-D s ≤0,D s is the travel limit of the suspension during vehicle operation; g3=|x u -x q |-D uq ≤0,D uq is the limit of tire dynamic deformation;

[0011] (3) Using genetic algorithm to optimize the objective function to calculate the optimized suspension system stiffness k s , suspension system damping c s ;

[0012] (4) The controller is based on the optimized suspension system damping c sSending a command to the magnetorheological damper so that its damping is the optimized damping value; the controller is based on the optimized suspension system stiffness k s A command is issued to the air spring so that the stiffness of the air spring is an optimized stiffness value.

[0013] Furthermore, the objective function is optimized by using a genetic algorithm to calculate the optimized suspension system stiffness k s , suspension system damping c s , the fitness function of individuals in the genetic algorithm is determined as follows:

[0014]

[0015] in, f obj_max =max{f obj (X1),…,f obj (X N )},f obj_min =min{f obj (X1),…,f obj (X N )};

[0016] f vio_max =max{f vio (X1),…f vio (X N )},

[0017] f vio_min =min{f vio (X1),…f vio (X N )}, N represents the number of individuals in the population, is the constraint function value, m represents the number of constraints; where the operator <> is defined as: R a represents the feasible solution region; fit(X) is the fitness function.

[0018] The positive effects that can be achieved by adopting the technical solution of the present invention are:

[0019] 1) A friction generator is set at the ball joint position of the cantilever (upper cantilever or lower cantilever) and the steering knuckle. Through the generator, the vibration energy can be recovered and used by the controller, which greatly improves the vibration reduction performance and realizes the conversion and utilization of energy;

[0020] 2) The processing method of the constraint function in the optimization algorithm of the present invention does not need to calculate the weighted sum of the objective function value and the constraint function value like the general penalty function, but only needs to calculate the individual objective function value or constraint function value separately, so there is no need to introduce any penalty parameters, which solves the problem that the penalty parameters in the traditional penalty function method are difficult to determine in advance;

[0021] 3) The objective function and constraint function are processed to prevent the distortion of genetic information caused by one of the objective function value and the constraint function value being much greater than the other, which results in the inability of the genetic algorithm to comprehensively utilize the genetic information of feasible solutions and infeasible solutions during the evolution process;

[0022] 4) The present application obtains the best damping coefficient and stiffness coefficient through an optimization algorithm, and controls the damping of the magnetorheological shock absorber and the stiffness of the air spring through a controller, thereby greatly improving the vibration reduction performance of the suspension system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is an overall structural diagram of a special vehicle suspension system in a first embodiment of the present invention;

[0024] Figure 2 for Figure 1 Medium enlarged image;

[0025] Figure 3 is an exploded schematic diagram of the spherical joint in the first embodiment;

[0026] Figure 4 This is a schematic diagram of the connecting cover structure in the first embodiment;

[0027] Figure 5 It is a simplified schematic diagram of a quarter-car two-degree-of-freedom nonlinear automobile suspension system model in the first embodiment;

[0028] Figure 6 It is the flow chart of genetic algorithm; DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0030] First embodiment

[0031] See also Figure 1The special vehicle suspension system in this embodiment includes: a frame 50, a wheel 90, a steering knuckle 30, and a shock absorber 40; the steering knuckle 30 is rotatably connected to the wheel 90; an upper cantilever 10, one end of which is hinged to the frame 50, and the other end is connected to the steering knuckle 30 through a ball joint 70; a lower cantilever 20, one end of which is hinged to the frame 50, and the other end is connected to the steering knuckle 30 through a ball joint 70; a controller 80, the controller 80 is fixed On the frame 50 or the upper cantilever 10; wherein, a friction generator is also arranged in the ball joint 70, and the friction generator is electrically connected to the controller 80; the shock absorber 40 includes a magnetorheological shock absorber and an air spring arranged in parallel, one end of the magnetorheological shock absorber and the air spring is connected to the lower cantilever 20, and the other end is connected to the frame 50, and the controller 80 outputs control instructions to the air spring and the magnetorheological shock absorber to change the stiffness characteristics of the air spring and the damping characteristics of the magnetorheological shock absorber.

[0032] See also Figure 2-3 As shown, the spherical joint 70 includes a conical ball head rod 73 and a connecting cover 71; the conical ball head rod 73 is connected to the steering knuckle 30, including a conical rod 735 and a ball head 733 arranged on the large end side of the conical rod 735, and a first friction body assembly 731 is arranged on the surface of the ball head 733; the connecting cover 71 is connected to the upper cantilever 10 or the lower cantilever 20, and a spherical groove 721 matching with the ball head 733 is arranged therein, and a second friction body assembly 722 is arranged on the surface of the spherical groove 721, and the first friction body assembly 731 and the second friction body assembly 722 constitute the friction generator.

[0033] See also Figure 3-4 The ball joint in this embodiment further includes a stopper 72, which is conical, open at one end and has an opening at the other end, the maximum diameter of the tapered rod 73 is greater than the diameter of the opening and the minimum diameter is less than the diameter of the opening, the small end of the tapered rod 73 passes through the opening, and the large end is limited in the stopper 72, and the open end of the stopper 72 is fixedly connected to the connection cover 71 to limit the ball head 733 in the cavity surrounded by the stopper 72 and the connection cover 71. In this way, through the limiting effect of the stopper 72, it can be ensured that the first friction body assembly 731 on the ball head 733 and the second friction body assembly 722 provided on the connection cover 71 are always in contact, thereby ensuring that power generation is achieved when the suspension system starts to work during the operation of the vehicle.

[0034] Figure 5 FIG. 1 is a simplified schematic diagram of a quarter-car 2-DOF nonlinear automobile suspension system model corresponding to an embodiment of the present invention, wherein m s、m u Represents one quarter of the vehicle body mass and tire mass, k s , k t They represent the stiffness of the suspension system and the stiffness of the tire, c s 、c t Respectively represent the damping coefficient of the suspension system and the tire damping coefficient, x s 、x u 、x q They represent the vehicle body vertical displacement, tire vertical displacement, and road surface displacement input respectively.

[0035] In this embodiment, the motion differential equation of a quarter vehicle model with 2 degrees of freedom is established using a matrix expression, as follows:

[0036]

[0037] in,

[0038]

[0039] Pick x s -x u 、x u -x q is a state variable, then the state vector The established state equation is as follows:

[0040]

[0041] Among them, A, B, and C are coefficient matrices.

[0042]

[0043] Represents the input vector, which is a 1-dimensional vector and is equivalent to a scalar. The input vector can be determined using the following formula:

[0044]

[0045] x q (t) represents the road surface displacement, G0 represents the roadside roughness coefficient, f0 represents the lower cutoff frequency, u represents the vehicle speed, and w(t) represents the Gaussian white noise with zero mean.

[0046] Represents the output vector.

[0047] Considering that in the design of vehicle suspension, there are three main performance indicators that need to be considered: body acceleration, suspension dynamic travel, tire dynamic load and displacement, among which the vehicle driving smoothness is evaluated by the root mean square of body acceleration. The size of the road dynamic load directly affects the tire ground contact performance and vehicle handling stability, and the dynamic load is closely related to the dynamic displacement of the tire, so the root mean square of the dynamic displacement is used as the evaluation indicator.

[0048] Select the suspension system stiffness k s , suspension system damping c s is the optimization variable, that is, the optimization variable X = [k s ,c s ], establish the objective function with the vehicle body acceleration and tire dynamic displacement as the minimum, f2=RMS|x u -x q |. RMS stands for root mean square. In this embodiment, the vehicle body acceleration and tire dynamic displacement are comprehensively considered to establish a multi-objective optimization objective function, which is as follows: obj =αf1+βf2, where α and β are weight coefficients, and the sum of the two is 1. In this embodiment, the two can be 0.5 and 0.5 respectively. In other embodiments, other values ​​can also be taken, such as 0.1 and 0.9 or 0.6 and 0.4.

[0049] The constraints corresponding to the above objective function are as follows: Among them, A s is the limit value of the root mean square value of the vehicle body acceleration; g2=|x s -x u |-D s ≤0,D s is the travel limit of the suspension during vehicle operation, g3=|x u -x q |-D uq ≤0,D uq is the limit of tire dynamic deformation.

[0050] Considering that the suspension system model is a nonlinear system model, an improved genetic algorithm is used to solve the above process. The calculation steps of the improved genetic algorithm are as follows:

[0051] 1) Initial variables, determine population size, maximum number of evolutionary generations, crossover probability and mutation probability;

[0052] 2) Determine the encoding method, use real number or binary encoding method, and generate the initial population;

[0053] 3) Calculate the fitness value of each individual;

[0054] 4) According to the fitness value of each individual, the population is selected, crossed, and mutated, and individuals are selected using a selection mode that combines random league selection with elite retention.

[0055] 5) Determine whether the genetic termination condition is met. If so, output the optimized final value. Otherwise, go to step 3) to continue the next round of optimization.

[0056] Among them, for step 3), the method of calculating the fitness of each is as follows:

[0057] 1) Redefine the objective function,

[0058]

[0059] in, f obj max =max{f obj (X1),…,f obj (X N )},f obj min =min{f obj (X1),…,f obj (X N )}

[0060]

[0061] f vio_max =max{f vio (X1),…f vio (X N )},f vio_min =min{f vio (X1),…f vio (X N )}, N represents the number of individuals in the population, is the constraint function value

[0062] The operator <> is defined as:

[0063] R a represents the feasible solution region.

[0064] fit(X) is the fitness function, which indicates the fitness value of the individual.

[0065] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A control method for a special vehicle suspension system, comprising the following steps: (1) Select the suspension system stiffness k s , suspension system damping c s is the optimization amount, according to the optimization variable X = [k s ,c s ] establish an objective function, the objective function f obj as follows: f obj =αf1+βf2, where Among them, α and β are weight coefficients, and their sum is 1. f2=RMS|x u -x q |; RMS means root mean square, x s represents the vertical displacement of the vehicle body, x u represents the vertical displacement of the tire, x q represents the road surface displacement input; (2) Determine the constraints of the objective function, which are as follows: Among them, A s is the limit value of the root mean square value of the vehicle body acceleration; g2=|x s -x u |-D s ≤0,D s is the travel limit of the suspension during vehicle operation; g3=|x u -x q |-D uq ≤0,D uq is the limit of tire dynamic deformation; (3) Using genetic algorithm to optimize the objective function to calculate the optimized suspension system stiffness k s , suspension system damping c s ; (4) The controller is based on the optimized suspension system damping c s Sending a command to the magnetorheological damper so that its damping is the optimized damping value; the controller is based on the optimized suspension system stiffness k s Sending a command to the air spring so that its stiffness is the optimized stiffness value; wherein the objective function is optimized by using a genetic algorithm to calculate the optimized suspension system stiffness k s , suspension system damping c s , including the following steps: 1) Determine the population size, maximum number of evolutionary generations, crossover probability and mutation probability; 2) Determine the encoding method, use real number or binary encoding method, and generate the initial population; 3) Calculate the fitness value of each genetic individual; 4) According to the fitness value of each genetic individual, the population is selected, crossed, and mutated, and the genetic individuals are selected by using a selection mode combining random league selection and elite retention; 5) Determine whether the genetic termination condition is met, if so, output the optimized final value, otherwise go to step 3) to continue the next round of optimization; wherein, the fitness value of each genetic individual is calculated, and the fitness function fit(X) of the genetic individual is determined in the following manner: in, f obj_max =max{f obj (X1),…,f obj (X N )},f obj_min =min{f obj (X1),…,f obj (X N )}; f vio_max =max{f vio (X1),…f vio (X N )}, f vio_min =min{f vio (X1),…f vio (X N )}, N represents the number of individuals in the population, is the constraint function value, m represents the number of constraint conditions; where the operator < > is defined as: R a represents the feasible solution region; fit(X) is a fitness function; according to the fitness function fit(X), the fitness value of each genetic individual is calculated.

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