Control method and device of vehicle magnetorheological damper and electronic device

Abstract

The application discloses a control method and device of a vehicle magnetorheological damper and electronic equipment, and relates to the field of vehicles. The method comprises the following steps: obtaining an initial control current of the magnetorheological damper, wherein the initial control current is used for controlling the magnetorheological damper to output an initial damping force; obtaining a test damping force based on the initial control current and measurement noise; performing multiple iteration learning by using the test damping force, the initial control current and an expected damping force to obtain a target control current, wherein the target control current is used for controlling the magnetorheological damper to output a target damping force; and controlling the magnetorheological damper to output the target damping force according to the target control current, so as to track the expected damping force. The application solves the technical problem that, in the prior art, the expected damping force tracking error of the magnetorheological damper is large due to the large modeling difficulty of the magnetorheological damper.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicles, in particular to a control method and device of a vehicle magneto-rheological damper and an electronic device. BACKGROUND

[0002] Suspension is the core element of the automobile chassis control system, and is the key link to ensure the safety, stability and comfort of intelligent networked vehicles. Semi-active suspension has simple structure, low energy consumption and low cost, and can adjust the damping coefficient or stiffness coefficient of the magneto-rheological damper (MRD) within a certain range. MRD has the advantages of low energy consumption, large output, fast response speed, and continuous and adjustable damping force.

[0003] In related technologies, the control strategy of MRD is an open-loop control strategy based on its inverse model. This method predicts the required control current according to the expected control force and piston motion state. Due to the strong nonlinearity and hysteresis saturation characteristics of MRD, it takes a long time and large design cost to establish its inverse model. Moreover, in actual production, different batches and cycles of products require different modeling, so it is necessary to model each batch or cycle of product, thereby inevitably increasing the error caused by model uncertainty and resisting external interference.

[0004] At present, no effective solution has been proposed for the above problems. SUMMARY

[0005] The embodiments of the present application provide a control method, device and electronic device of a vehicle magneto-rheological damper, to at least solve the technical problem of large expected damping force tracking error of the magneto-rheological damper due to large modeling difficulty of the magneto-rheological damper in related technologies.

[0006] According to one of the embodiments of the present application, a control method of a vehicle magneto-rheological damper is provided, comprising:

[0007] obtaining an initial control current of the magneto-rheological damper, wherein the initial control current is used to control the magneto-rheological damper to output an initial damping force; obtaining a test damping force based on the initial control current and a measurement noise; performing multiple iteration learning by using the test damping force, the initial control current and an expected damping force to obtain a target control current, wherein the target control current is used to control the magneto-rheological damper to output a target damping force; and controlling the magneto-rheological damper to output the target damping force according to the target control current to track the expected damping force.

[0008] Optionally, the control method of the vehicle magneto-rheological damper further comprises: performing a performance test on the magneto-rheological damper to obtain a test result, wherein the test result is used to analyze the energy consumption characteristics and speed characteristics of the magneto-rheological damper.

[0009] Optionally, the obtaining the initial control current of the MR damper comprises: obtaining a preselected parameter and a desired damping force; and determining the initial control current based on the preselected parameter and the desired damping force.

[0010] Optionally, the performing the multiple iteration learning with the test damping force, the initial control current and the desired damping force comprises: performing the multiple iteration learning with the test damping force, the initial control current and the desired damping force by using a target iteration control system, to obtain a target control current, wherein the target iteration control system is configured to correct the iteration control current of the MR damper according to a historical control current and a historical damping force.

[0011] Optionally, the performing the multiple iteration learning with the test damping force, the initial control current and the desired damping force comprises:

[0012] repeatedly performing the following steps by using the target iteration control system: updating a first control current offline based on the historical control current, wherein the first control current is configured to control the MR damper to output a corresponding first damping force; mixing the first damping force and a measurement noise to obtain a second damping force; and determining a second control current based on the second damping force, the first control current and the desired damping force.

[0013] Optionally, the control method of the MR damper of the vehicle further comprises: determining that the target damping force successfully tracks the desired damping force in response to a ratio between the test noise and the desired damping force converging to a preset value.

[0014] According to an embodiment of the present application, a control device of a MR damper of a vehicle is provided, comprising:

[0015] a first obtaining module configured to obtain an initial control current of the MR damper, wherein the initial control current is configured to control the MR damper to output an initial damping force; a second obtaining module configured to obtain a test damping force based on the initial control current and a measurement noise; an iteration module configured to perform multiple iteration learning with the test damping force, the initial control current and a desired damping force, to obtain a target control current, wherein the target control current is configured to control the MR damper to output a target damping force; and a processing module configured to control the MR damper to output the target damping force according to the target control current, to track the desired damping force.

[0016] Optionally, the control device of the MR damper of the vehicle further comprises: a testing module configured to perform a performance test on the MR damper, to obtain a test result, wherein the test result is configured to analyze energy consumption characteristics and speed characteristics of the MR damper.

[0017] Optionally, the first acquisition module is further configured to: acquire preselected parameters and a desired damping force; and determine an initial control current based on the preselected parameters and the desired damping force.

[0018] Optionally, the iterative module is also used to: use the target iterative control system to perform multiple iterative learning on the test damping force, initial control current and expected damping force to obtain the target control current, wherein the target iterative control system is used to correct the iterative control current of the magnetorheological damper based on the historical control current and historical damping force.

[0019] Optionally, the iteration module is also used to: repeatedly perform the following steps using the target iterative control system: offline update the first control current based on the historical control current, wherein the first control current is used to control the first damping force corresponding to the output of the magnetorheological damper; perform mixed processing on the first damping force and the measurement noise to obtain a second damping force; determine the second control current using the second damping force, the first control current and the expected damping force.

[0020] Optionally, the control device of the vehicle magnetorheological damper further includes: a determination module for determining that the target damping force successfully tracks the expected damping force in response to the ratio between the test noise and the expected damping force converging to a preset value.

[0021] According to one embodiment of the present invention, a non-volatile storage medium is further provided, in which a computer program is stored. The computer program is configured to execute any of the above-mentioned methods for controlling a magnetorheological damper of a vehicle when running.

[0022] According to one embodiment of the present invention, a processor is further provided, which is used to run a program, wherein the program is configured to execute any of the above-mentioned methods for controlling a magnetorheological damper for a vehicle when running.

[0023] According to one embodiment of the present invention, an electronic device is further provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the above-mentioned vehicle magnetorheological damper control methods.

[0024] In an embodiment of the present invention, the initial control current of the magnetorheological damper is obtained, and the test damping force is obtained based on the initial control current and the measurement noise. Then, the test damping force, the initial control current and the expected damping force are used to perform multiple iterative learning to obtain the target control current. Finally, the magnetorheological damper is controlled to output the target damping force according to the target control current to track the expected damping force, thereby achieving the purpose of accurately tracking the expected damping force without modeling, thereby achieving the technical effect of improving the tracking accuracy of the expected damping force, and thus solving the technical problem in the related art of large tracking error of the expected damping force of the magnetorheological damper due to the difficulty in modeling the magnetorheological damper. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0026] Figure 1 is a flow chart of a method for controlling a magnetorheological damper of a vehicle according to one embodiment of the present invention;

[0027] FIG2( a ) is a schematic diagram of an external characteristic curve of a magnetorheological damper according to one embodiment of the present invention;

[0028] FIG2( b ) is a schematic diagram of an external characteristic curve of another magnetorheological damper according to one embodiment of the present invention;

[0029] Figure 3 is a schematic diagram of a target iterative control system according to one embodiment of the present invention;

[0030] FIG4( a ) is a schematic diagram of a desired damping force tracking curve according to one embodiment of the present invention;

[0031] FIG4( b ) is a schematic diagram of a desired damping force tracking error curve according to one embodiment of the present invention;

[0032] Figure 5 The figure is a structural block diagram of a control device for a vehicle magnetorheological damper according to one embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] According to an embodiment of the present invention, a method for controlling a magnetorheological damper of a vehicle is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] The embodiment of the method can be executed in an electronic device or a similar computing device in a vehicle that includes a memory and a processor. Taking the operation on the electronic device of the vehicle as an example, the electronic device of the vehicle may include one or more processors (the processor may include but is not limited to a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microprocessor (MCU), a programmable logic device (FPGA), a neural network processor (NPU), a tensor processor (TPU), an artificial intelligence (AI) type processor, etc.) and a memory for storing data. Optionally, the electronic device of the above-mentioned vehicle may also include a transmission device, an input and output device, and a display device for communication functions. It will be understood by those skilled in the art that the above-mentioned structural description is only illustrative and does not limit the structure of the electronic device of the above-mentioned vehicle. For example, the electronic device of the vehicle may also include more or fewer components than the above-mentioned structural description, or have a configuration different from the above-mentioned structural description.

[0037] The memory can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the control method of the vehicle magnetorheological damper in the embodiment of the present invention. The processor executes the computer program stored in the memory to perform various functional applications and data processing, thereby implementing the above-mentioned control method of the vehicle magnetorheological damper. The memory may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory remotely located relative to the processor, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, corporate intranet, local area network, mobile communication network, and combinations thereof.

[0038] The transmission device is used to receive or send data via a network. Specific examples of the aforementioned network may include a wireless network provided by the mobile terminal's communications provider. In one embodiment, the transmission device includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In one embodiment, the transmission device may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0039] The display device can be, for example, a touch-screen liquid crystal display (LCD) and a touch display (also referred to as a "touch screen" or "touch display screen"). The liquid crystal display can enable a user to interact with the user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), and the user can interact with the GUI by finger contacts and / or gestures on the touch-sensitive surface. The human-computer interaction functions here optionally include the following interactions: creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music and / or web browsing, etc. The executable instructions for performing the above-mentioned human-computer interaction functions are configured / stored in a computer program product or readable storage medium executable by one or more processors.

[0040] Figure 1 FIG. 1 is a flow chart of a method for controlling a magnetorheological damper of a vehicle according to one embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0041] Step S12, obtaining an initial control current of the magnetorheological damper, wherein the initial control current is used to control the magnetorheological damper to output an initial damping force;

[0042] Step S14, obtaining a test damping force based on the initial control current and the measurement noise;

[0043] Step S16, performing multiple iterative learning using the test damping force, the initial control current, and the desired damping force to obtain a target control current, wherein the target control current is used to control the magnetorheological damper to output a target damping force;

[0044] Step S18: controlling the magnetorheological damper to output a target damping force according to the target control current to track the desired damping force.

[0045] Specifically, a magnetorheological damper is an actuator for a semi-active automotive suspension. The measured noise can be sensor noise, and the test damping force is the output damping force mixed with the measured noise. Multi-iteration learning involves using the k-2th data to correct the k-1th data, then using the k-1th data to correct the kth data, and then performing several iterations to obtain the final result.

[0046] Obtain the initial control current I0 of the magnetorheological damper, control the output initial damping force F0 of the magnetorheological damper based on the initial control current I0, and obtain the output damping force of the mixed measurement noise by combining the measurement noise; then use the output damping force of the mixed measurement noise, the initial control current I0 and the expected damping force F * Perform multiple iterative learning to obtain the kth control current I k , and finally according to the kth control current I k Control the magnetorheological damper to output the target damping force F k , to track the desired damping force F * .

[0047] Based on the above steps S12 to S18, the initial control current of the magnetorheological damper is obtained, and the test damping force is obtained based on the initial control current and the measurement noise. Then, the test damping force, the initial control current and the expected damping force are used for multiple iterative learning to obtain the target control current. Finally, the magnetorheological damper is controlled to output the target damping force according to the target control current to track the expected damping force, thereby achieving the purpose of accurately tracking the expected damping force without modeling, thereby achieving the technical effect of improving the tracking accuracy of the expected damping force, and thus solving the technical problem in the related art of large tracking error of the expected damping force of the magnetorheological damper due to the difficulty in modeling the magnetorheological damper.

[0048] Optionally, the control method of the vehicle magnetorheological damper further includes: performing a performance test on the magnetorheological damper to obtain a test result, wherein the test result is used to analyze energy consumption characteristics and speed characteristics of the magnetorheological damper.

[0049] Specifically, the energy dissipation characteristics of the magnetorheological damper can be analyzed based on the relationship between the damping force and the piston displacement change; the speed characteristics of the magnetorheological damper can be analyzed based on the relationship between the damping force and the piston speed change.

[0050] FIG2( a ) is a schematic diagram of an external characteristic curve of a magnetorheological damper according to one embodiment of the present invention; FIG2( b ) is a schematic diagram of an external characteristic curve of another magnetorheological damper according to one embodiment of the present invention.

[0051] The performance test of the magnetorheological damper can include the following steps: first, the test amplitude is determined to be ±20mm based on the total stroke of the MRD, and four groups of excitation speeds are selected, namely 0.052m / s, 0.131m / s, 0.262m / s, and 0.524m / s. Then, a vertical test is adopted, and the initial position of the piston rod is in the middle position of the shock absorber. Finally, the control currents are 0A, 0.1A, ..., 0.9A, and 1.0A in sequence. Among them, the excitation speed is 0.131m / s and the amplitude is ±20mm. The energy dissipation curve of this magnetorheological damper is shown in Figure 2(a), and the speed curve is shown in Figure 2(b).

[0052] As shown in Figure 2(a), the energy dissipation curves of this magnetorheological damper are very full, both in tension and compression, indicating that the MRD has excellent damping dissipation characteristics. At all excitation speeds, the damping force increases with increasing coil current. As shown in Figure 2(b), the damping force of the magnetorheological damper exhibits a significant hysteresis characteristic as it varies with speed, and the hysteresis loop becomes larger and more pronounced as the current increases.

[0053] Based on the above steps, by performing performance testing on the magnetorheological damper, the energy dissipation characteristics and speed characteristics of the damper can be analyzed.

[0054] Optionally, in step S12, obtaining the initial control current of the magnetorheological damper includes:

[0055] Step S121, obtaining preselected parameters and desired damping force;

[0056] Step S122 : determining an initial control current based on preselected parameters and a desired damping force.

[0057] Specifically, the preselected parameter α can be determined by a trial-and-error method. Since the control amount will be corrected in an iterative manner, the selection of the parameter value does not need to be too precise. It is only necessary to ensure that the output damping force conforms to the change trend of the expected damping force.

[0058] Using the preselected parameter α and the desired damping force F * , the initial control current I0 can be determined according to formula (1).

[0059] I0(t)=αF * (t) (1)

[0060] Based on the above steps S121 to S122, by obtaining preselected parameters and desired damping force, and determining an initial control current based on the preselected parameters and desired damping force, so as to substitute the initial control current into the system, the output initial damping force is obtained.

[0061] Optionally, in step S16, performing multiple iterative learning using the test damping force, the initial control current and the desired damping force includes: performing multiple iterative learning on the test damping force, the initial control current and the desired damping force using a target iterative control system to obtain a target control current, wherein the target iterative control system is used to correct the iterative control current of the magnetorheological damper based on the historical control current and the historical damping force.

[0062] Specifically, the target iterative control system is a modeling-free inversion-based iterative feed forward control (MIIFC).

[0063] Based on the above steps, the target control current is obtained by performing multiple iterative learning on the test damping force, initial control current and desired damping force using the target iterative control system. The magnetorheological damper can be controlled to output the target damping force to track the desired damping force.

[0064] Optionally, in step S16, performing multiple iterative learning on the test damping force, the initial control current, and the desired damping force using the target iterative control system includes:

[0065] The following steps are repeated using the target iterative control system:

[0066] Step S161: Offline updating of a first control current based on a historical control current, wherein the first control current is used to control a first damping force outputted by the magnetorheological damper;

[0067] Step S162, performing a mixing process on the first damping force and the measurement noise to obtain a second damping force;

[0068] Step S163: determining a second control current using the second damping force, the first control current, and the desired damping force.

[0069] Figure 3 FIG. 1 is a schematic diagram of a target iterative control system according to one embodiment of the present invention. Figure 3 As shown, I k-1 is the first control current, i.e. the control current in the k-1th iteration process; F k-1，ris the first damping force, i.e. the model output damping force during the k-1th iteration; F k-1，n is the measurement noise during the k-1th iteration; F k-1 is the second damping force, i.e. the test damping force during the k-1th iteration; F * is the expected damping force; I k is the second control current, that is, the control current during the k-th iteration.

[0070] Specifically, the first control current I k-1 is controlled by the historical current I k-2 The first control current I obtained by offline update k-1 Control the first damping force F corresponding to the output of the magnetorheological damper k-1，r , and then the first damping force F k-1，r and measurement noise F k-1，n Mix and get the second damping force F k-1 , and finally use the second damping force F k-1 , the first control current I k-1 and the desired damping force F * Determine the second control current I k .

[0071] Calculate the second control current I k When you can use The structure replaces the inverse model construction process, that is, the second control current I can be calculated using formula (2) k :

[0072]

[0073] Where t∈{0, 1,…, T} is a finite tracking interval and T is a finite positive integer.

[0074] It should be noted that when the iteration starts, the previous output damping force and the expected damping force cannot be 0, otherwise the control current I k =0.

[0075] Based on the above steps S161 to S163, the first control current is updated offline based on the historical control current, and then the first damping force and the measurement noise are mixed to obtain the second damping force. Finally, the second damping force, the first control current and the expected damping force are used to determine the second control current, which can improve the tracking accuracy of the magnetorheological damper for the expected damping force.

[0076] Optionally, the control method of the vehicle magnetorheological damper further includes: in response to the ratio between the test noise and the expected damping force converging to a preset value, determining that the target damping force successfully tracks the expected damping force.

[0077] Specifically, define the test noise F k，n and the expected damping force F * The ratio between them is δ, as shown in formula (3):

[0078]

[0079] When the ratio δ between the test noise and the expected damping force converges to the preset value, it means that the system relative tracking error value is closer to the preset value, that is, the damping force output by the magnetorheological damper is closer to the expected damping force, thereby achieving accurate tracking of the expected damping force.

[0080] The smaller δ is, the more obvious the improvement of system tracking performance is. When δ is closer to 0, the system relative tracking error value is closer to 0, which also shows that the algorithm has a certain anti-interference ability.

[0081] When the piston rod moves repeatedly according to a certain rule, the only controllable variable is the current, and the MRD system can be approximately regarded as a single-input single-output system. The transfer function of the system is defined as G d (t), in the algorithm convergence proof G d (t) exists as an intermediate term.

[0082] F k，r (t) can be written as formula (4), F * (t) can be written as formula (5):

[0083] F k，r (t) = I k (t)G d (t) (4)

[0084] F * (t) = I d (t)G d (t) (5)

[0085] Among them, I d (t) is the preset current, which is only used as a symbolic expression in the convergence proof.

[0086] Assume G d (t) is a stable single-input-single-output system. Combined with the control law (2), at the kth iteration, the control current I k (t) and the preset current I d The ratio of (t) can be written as formula (6):

[0087]

[0088] Among them, S k (t) is P k The accumulation of items (t), Pk (t) is the product of δ in all past iterations at frequency ω, where P k The specific expression of (t) is shown in formula (7), S k The specific expression of (t) is shown in formula (8):

[0089]

[0090]

[0091] From this we can infer that: when δ is less than When , that is, when the measurement noise or disturbance is less than the preset threshold, the convergence of the iterative algorithm can be guaranteed.

[0092] It will be shown below that if δ is less than hour, The term converges to 0, as follows:

[0093]

[0094] As the number of iterations increases, the control current I k (t) and the preset current I d The ratio of (t) can be written as formula (10):

[0095]

[0096] When δ is less than hour, The term converges to 0, and formula (10) can be written as formula (11):

[0097]

[0098] If δ is less than a positive integer ε in each iteration, then:

[0099]

[0100] From the power series summation formula, formula (12) can be written as formula (13):

[0101]

[0102] when When |S ∞ (t)|<1.

[0103] F k (t) is defined as formula (14):

[0104] F k (t) = F k，r (t)+F k，n(t) (14)

[0105] Combining formulas (4) and (5), the relative tracking error of the system can be written as formula (15):

[0106]

[0107] Combining formulas (6) and (11), the relative tracking error of the system can be written as formula (16):

[0108]

[0109] The result in formula (12) |S ∞ (t)| is substituted into formula (16), when When , we can get formula (17):

[0110]

[0111] Then the relative tracking error of the system can be written as formula (18):

[0112]

[0113] because Therefore, as ε decreases, Reduce further:

[0114]

[0115] The smaller δ is, the more obvious the improvement in system tracking performance is. When δ is closer to 0, the relative tracking error value of the system is closer to 0, which also shows that the algorithm has a certain anti-interference ability.

[0116] Based on the above steps, by responding to the ratio between the test noise and the expected damping force converging to a preset value, it is determined that the target damping force successfully tracks the expected damping force, thereby achieving accurate tracking of the expected damping force and strong anti-interference capability.

[0117] To verify the effectiveness of the target iterative control system, a damping force tracking control simulation experiment was conducted on the MRD. The initial coefficient α of the MIIFC controller was adjusted and set to 0.9. To verify the anti-interference performance of the MIIFC algorithm, a random error was added to the damping force output to simulate the measurement noise present when the DYMH-103 sensor outputs the damping force. Based on the accuracy of the DYMH-103 sensor, the mean of the measurement noise was set to 0, and the standard deviation was approximately 0.003N. The simulation results of the damping force tracking experiment are shown in Figure 4.

[0118] Fig. 4(a) is a schematic diagram of a desired damping force tracking curve according to an embodiment of the present application. Fig. 4(b) is a schematic diagram of a desired damping force tracking error curve according to an embodiment of the present application. As shown in Fig. 4(a) and Fig. 4(b), the MRD has a good tracking effect on the desired damping force and a small error under the MIIFC.

[0119] Those skilled in the art can clearly understand that the method according to the above-mentioned embodiments can be realized by means of software and a necessary general hardware platform, and of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disc) and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device) to execute the method described in the embodiments of the present application.

[0120] In the embodiments of the present application, a control device of a vehicle magneto-rheological damper is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware, or a combination of software and hardware is also possible and is contemplated.

[0121] Figure 5 is a structural block diagram of a control device of a vehicle magneto-rheological damper according to an embodiment of the present application, as shown in Figure 5 The device includes: a first acquisition module 501, configured to acquire an initial control current of the magneto-rheological damper, wherein the initial control current is used to control the magneto-rheological damper to output an initial damping force; a second acquisition module 502, configured to acquire a test damping force based on the initial control current and a measurement noise; an iteration module 503, configured to perform multiple iteration learning by using the test damping force, the initial control current, and a desired damping force to obtain a target control current, wherein the target control current is used to control the magneto-rheological damper to output a target damping force; and a processing module 504, configured to control the magneto-rheological damper to output the target damping force according to the target control current, so as to track the desired damping force.

[0122] Optionally, the control device of the vehicle magneto-rheological damper further includes a test module 505, configured to perform a performance test on the magneto-rheological damper to obtain a test result, wherein the test result is used to analyze energy consumption characteristics and speed characteristics of the magneto-rheological damper.

[0123] Optionally, the first acquisition module 501 is further configured to: acquire preselected parameters and a desired damping force; and determine an initial control current based on the preselected parameters and the desired damping force.

[0124] Optionally, the iterative module 503 is also used to: use the target iterative control system to perform multiple iterative learning on the test damping force, the initial control current and the expected damping force to obtain the target control current, wherein the target iterative control system is used to correct the iterative control current of the magnetorheological damper according to the historical control current and the historical damping force.

[0125] Optionally, the iteration module 503 is also used to: repeatedly perform the following steps using the target iterative control system: offline update the first control current based on the historical control current, wherein the first control current is used to control the first damping force corresponding to the output of the magnetorheological damper; perform mixed processing on the first damping force and the measurement noise to obtain a second damping force; and determine the second control current using the second damping force, the first control current and the expected damping force.

[0126] Optionally, the control device of the vehicle magnetorheological damper further includes: a determination module 506, configured to determine that the target damping force successfully tracks the expected damping force in response to the ratio between the test noise and the expected damping force converging to a preset value.

[0127] It should be noted that the above modules can be implemented through software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0128] In an embodiment of the present invention, a non-volatile storage medium is further provided, in which a computer program is stored. The computer program is configured to execute the steps of any one of the above method embodiments when running.

[0129] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0130] Step S1, obtaining an initial control current of the magnetorheological damper, wherein the initial control current is used to control the magnetorheological damper to output an initial damping force;

[0131] Step S2, obtaining a test damping force based on the initial control current and the measurement noise;

[0132] Step S3, performing multiple iterative learning using the test damping force, the initial control current, and the desired damping force to obtain a target control current, wherein the target control current is used to control the magnetorheological damper to output a target damping force;

[0133] Step S4: controlling the magnetorheological damper to output a target damping force according to the target control current to track the desired damping force.

[0134] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0135] An embodiment of the present invention further provides a processor for running a program, wherein the program is configured to execute the steps of any one of the above method embodiments when running.

[0136] Optionally, in this embodiment, the processor may be configured to execute the following steps through a computer program:

[0137] Step S1, obtaining an initial control current of the magnetorheological damper, wherein the initial control current is used to control the magnetorheological damper to output an initial damping force;

[0138] Step S2, obtaining a test damping force based on the initial control current and the measurement noise;

[0139] Step S3, performing multiple iterative learning using the test damping force, the initial control current, and the desired damping force to obtain a target control current, wherein the target control current is used to control the magnetorheological damper to output a target damping force;

[0140] Step S4: controlling the magnetorheological damper to output a target damping force according to the target control current to track the desired damping force.

[0141] An embodiment of the present invention further provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps of any of the above method embodiments.

[0142] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0143] Optionally, in this embodiment, the processor may be configured to execute the following steps through a computer program:

[0144] Step S1, obtaining an initial control current of the magnetorheological damper, wherein the initial control current is used to control the magnetorheological damper to output an initial damping force;

[0145] Step S2, obtaining a test damping force based on the initial control current and the measurement noise;

[0146] Step S3, using the test damping force, the initial control current and the expected damping force to perform multiple iteration learning to obtain a target control current, wherein the target control current is used to control the magnetorheological damper to output a target damping force;

[0147] Step S4, controlling the magnetorheological damper to output the target damping force according to the target control current to track the expected damping force.

[0148] Optionally, specific examples in the embodiments can refer to the examples described in the above embodiments and optional implementation manners, and the embodiments will not be described here again.

[0149] The serial numbers of the above embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0150] In the above embodiments of the application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0151] In several embodiments provided by the present application, it should be understood that the disclosed technology can be implemented in other ways. Of course, the unit embodiment described above is only illustrative, and for example, the division of units can be a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, unit or module, and can be electrical or other forms.

[0152] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0153] In addition, each functional unit in each embodiment of the application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0154] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0155] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for controlling a vehicle magnetorheological damper, characterized in that: include: Acquiring an initial control current of the magnetorheological damper, wherein the initial control current is used to control the magnetorheological damper to output an initial damping force; obtaining a test damping force based on the initial control current and the measurement noise; Performing multiple iterative learning using the test damping force, the initial control current, and the desired damping force to obtain a target control current, wherein the target control current is used to control the magnetorheological damper to output a target damping force; controlling the magnetorheological damper to output the target damping force according to the target control current to track the desired damping force; The performing multiple iterative learning using the test damping force, the initial control current, and the desired damping force includes: The target iterative control system is used to repeatedly perform the following steps: offline updating a first control current based on a historical control current, wherein the first control current is used to control a first damping force corresponding to the output of the magnetorheological damper; mixing the first damping force and the measurement noise to obtain a second damping force; determining a second control current using the second damping force, the first control current, and the desired damping force to obtain the target control current, wherein the target iterative control system is used to correct the iterative control current of the magnetorheological damper according to the historical control current and the historical damping force.

2. The control method of a vehicle magnetorheological damper according to claim 1, characterized in that: The method further comprises: A performance test is performed on the magnetorheological damper to obtain a test result, wherein the test result is used to analyze the energy dissipation characteristics and speed characteristics of the magnetorheological damper.

3. The control method of a vehicle magnetorheological damper according to claim 1, characterized in that: Obtaining the initial control current of the magnetorheological damper includes: Obtaining preselected parameters and the desired damping force; The initial control current is determined based on the preselected parameters and the desired damping force.

4. The control method of a vehicle magnetorheological damper according to claim 1, characterized in that: The method further comprises: In response to the ratio between the measurement noise and the desired damping force converging to a preset value, it is determined that the target damping force successfully tracks the desired damping force.

5. A control device for a vehicle magnetorheological damper, characterized in that: include: a first acquisition module, configured to acquire an initial control current of the magnetorheological damper, wherein the initial control current is used to control the magnetorheological damper to output an initial damping force; a second acquisition module, configured to acquire a test damping force based on the initial control current and the measurement noise; an iterative module, configured to perform multiple iterative learning using the test damping force, the initial control current, and the desired damping force to obtain a target control current, wherein the target control current is used to control the magnetorheological damper to output a target damping force; a processing module, configured to control the magnetorheological damper to output the target damping force according to the target control current, so as to track the desired damping force; Wherein, the iteration module is also used to: repeatedly perform the following steps using the target iterative control system: offline updating the first control current based on the historical control current, wherein the first control current is used to control the first damping force corresponding to the output of the magnetorheological damper; mixing the first damping force and the measurement noise to obtain a second damping force; determining the second control current using the second damping force, the first control current and the expected damping force to obtain the target control current, wherein the target iterative control system is used to correct the iterative control current of the magnetorheological damper according to the historical control current and the historical damping force.

6. A non-volatile storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method for controlling a vehicle magnetorheological damper according to any one of claims 1 to 4 when running.

7. A processor, characterized in that: The processor is configured to run a program, wherein the program is configured to execute the method for controlling a vehicle magnetorheological damper according to any one of claims 1 to 4 when running.

8. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the method for controlling the magnetorheological damper of a vehicle as claimed in any one of claims 1 to 4.

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