Model representation method and device of linear motor and magnetorheological fluid composite active suspension

Abstract

The model characterization method and device of the linear motor and magnetorheological fluid composite active suspension provided by the present disclosure can uniformly characterize the dynamic characteristics of the linear motor, the nonlinear hysteresis characteristics of the magnetorheological fluid damper, and the multi-physical field coupling relationship of the suspension system, thereby improving the accuracy and integrity of the composite active suspension system model, and providing a reliable model basis for suspension control algorithm design, dynamic performance analysis, and energy consumption evaluation. As a result, the dynamic response and energy consumption characteristics of the composite active suspension system under different working conditions can be more accurately described, the characterization accuracy of the model on the actual system behavior is improved, and support is provided for the development and optimization of high-performance suspension control strategies.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle suspension modeling and control technology, and more specifically, to a model characterization method and apparatus for a composite active suspension of a linear motor and magnetorheological fluid. Background Technology

[0002] As an important component of the vehicle chassis system, the suspension system's main function is to mitigate the impact and vibration caused by uneven road surfaces on the vehicle body and maintain good contact between the wheels and the road surface, thereby balancing vehicle ride smoothness, handling stability, and ride comfort.

[0003] To improve the overall performance of suspension systems, semi-active and active suspensions have been gradually developed. A representative example of semi-active suspension is the magnetorheological fluid (MRF) suspension. The MRF damper adjusts the excitation current to change the yield stress and rheological state of the MRF fluid, thereby achieving continuously adjustable damping force. It offers advantages such as fast response, relatively compact structure, and low control power consumption. Fully active suspensions apply control forces to the suspension system through actuators, enhancing the vehicle's adaptability to complex operating conditions. Linear motors can directly convert electrical energy into linear motion mechanical energy, eliminating intermediate mechanical conversion steps. They offer advantages such as fast response, high control precision, good continuity of driving force adjustment, and energy recovery potential, thus gradually becoming an important development direction in the field of active suspension.

[0004] However, active suspension systems using linear motors alone also have certain limitations. To address this, related technologies propose a combined configuration of linear motors and magnetorheological fluid dampers. This allows the linear motor to provide active adjustment capabilities, while the magnetorheological fluid damper provides adjustable damping support, thus achieving a balance between active control performance and system stability to some extent.

[0005] However, the composite active suspension system of linear motor and magnetorheological fluid involves multiple physical processes, including electromagnetic drive, rheological damping, mechanical vibration, and control coupling. Magnetorheological fluid dampers typically exhibit significant nonlinear and hysteretic characteristics, while linear motors display complex behaviors such as electrical dynamics, magnetic flux coupling, and control closed-loop response. Their combined effect in the suspension system is also influenced by factors such as road surface excitation, mechanical friction, and the sprung / unsprung mass motion relationship. Using only a single linear model, empirical model, or independent local models often fails to accurately reflect the true dynamic characteristics of the composite active suspension system under different frequency bands, control inputs, and external disturbances, leading to insufficient model accuracy and consequently affecting the reliability of subsequent control strategy development, system performance prediction, and simulation analysis results. Summary of the Invention

[0006] This disclosure provides at least one method and apparatus for modeling a composite active suspension system using a linear motor and magnetorheological fluid. This allows for a unified characterization of the dynamic characteristics of the linear motor, the nonlinear hysteresis characteristics of the magnetorheological fluid damper, and the multiphysics coupling relationships of the suspension system. This improves the accuracy and completeness of the composite active suspension system model, providing a reliable model foundation for suspension control algorithm design, dynamic performance analysis, and energy consumption assessment. Consequently, it enables a more accurate description of the dynamic response and energy consumption characteristics of the composite active suspension system under different operating conditions, improves the model's accuracy in representing the actual system behavior, and provides support for the development and optimization of high-performance suspension control strategies.

[0007] This disclosure provides a model characterization method for a composite active suspension system combining a linear motor and magnetorheological fluid, including: Obtain the system composition and interaction information of the linear motor and magnetorheological fluid composite active suspension system, and construct the corresponding system architecture model; Based on the system architecture model, a damping characteristic model is established for the magnetorheological fluid damper in the composite active suspension system. Based on the system architecture model, a motor dynamics model is established for the linear motor in the composite active suspension system. Based on the damping characteristic model and the motor dynamics model, a corresponding control model is constructed; Based on the damping characteristic model, the motor dynamics model, and the external excitation information, a coupled dynamics model of the composite active suspension system is constructed to characterize the dynamic response characteristics of the composite active suspension system.

[0008] In one optional implementation, the system composition and interaction information of the linear motor and magnetorheological fluid composite active suspension system are obtained, and a corresponding system architecture model is constructed, specifically including: The composite active suspension system is defined as including a linear motor actuator module, a magnetorheological fluid damper module, a suspension mechanical coupling module, and an electronic control unit module. Determine the mechanical connections, signal transmission relationships, and energy interaction relationships between the modules; The system architecture model of the composite active suspension system is constructed based on the relationships between the modules.

[0009] In one optional implementation, a damping characteristic model is established for the magnetorheological fluid damper in the composite active suspension system, specifically including: Acquire relative displacement, relative velocity, and excitation current information of the magnetorheological fluid vibration damper; Based on the rheological and hysteretic properties of magnetorheological fluids, a damping force output model is established by introducing hysteresis characterization variables. The internal hysteresis variables in the Bouc-Wen model are used to characterize the nonlinear hysteresis behavior of the magnetorheological fluid damper. Based on the relative displacement information, relative velocity information and the internal hysteresis variables, the functional relationship between the damping force and the displacement, velocity and hysteresis terms is established. Based on the evolution law of the internal hysteresis variables, the corresponding first-order nonlinear differential equation is established. Establish the mapping relationship between excitation current and model parameters to characterize the output damping force of magnetorheological fluid vibration damper under different excitation conditions; In this model, the viscous damping parameters, stiffness parameters, and hysteresis shape parameters in the magnetorheological fluid vibration damper are set as functions of the excitation current. Polynomial fitting is used to determine the correspondence between each model parameter and the excitation current, and the parameter set under different excitation current conditions is obtained based on the fitting results.

[0010] In one optional implementation, the method further includes: Obtain measured damping force data for magnetorheological fluid vibration dampers; An objective function is constructed based on the error between the model output damping force and the measured damping force. Intelligent optimization algorithms are used to identify the parameters to be identified in the magnetorheological fluid vibration damper model in order to obtain the target parameter combination.

[0011] In one optional implementation, a motor dynamics model is established for the linear motor in the composite active suspension system, specifically including: Obtain the structural, operational, and electrical parameters of the linear motor; Based on the correspondence between linear motors and rotating permanent magnet synchronous motors, the coordinate transformation relationship of linear motors is established; Specifically, the current quantity in the three-phase stationary coordinate system is converted into the current quantity in the two-phase stationary coordinate system, and then the current quantity in the two-phase stationary coordinate system is converted into the current quantity in the synchronous rotating coordinate system. The state variable expression relationship in the synchronous rotating coordinate system is established based on the position or electrical angle information of the mover. Based on the coordinate transformation relationship, voltage equation, flux linkage equation and electromagnetic thrust equation are established in the synchronous rotating coordinate system to characterize the output characteristics of the linear motor. Specifically, the voltage balance relationship between the d-axis and q-axis is established based on the winding resistance, inductance parameters, and permanent magnet flux linkage parameters of the linear motor. The coupling relationship between the current component and the flux linkage component is determined based on the voltage balance relationship between the d-axis and q-axis. The electromagnetic thrust characterization relationship is established based on the flux linkage component and the current component.

[0012] In one optional implementation, a corresponding control model is constructed based on the damping characteristic model and the motor dynamics model, specifically including: A closed-loop control structure with cascaded position, speed, and current loops is established for linear motors. Determine the reference velocity based on the target displacement information and the actual displacement information; The reference thrust is determined based on the reference speed and the actual speed, and the reference current is determined based on the reference thrust. The reference voltage is determined based on the reference current and the actual current to drive the linear motor. Feedforward decoupling compensation is introduced in the current loop to weaken the coupling effect between different axial components and to compensate for back EMF interference, thereby obtaining the d-axis reference voltage and the q-axis reference voltage. A multiphase drive voltage signal for driving the linear motor is generated based on the d-axis reference voltage and the q-axis reference voltage. A current-driven model is established for the magnetorheological fluid vibration damper to adjust the excitation current according to the control command.

[0013] In one optional implementation, a coupled dynamics model of the composite active suspension system is constructed based on the damping characteristic model, the motor dynamics model, and the external excitation information, specifically including: Acquire external road surface excitation information and suspension mechanical structure parameters; The electromagnetic thrust output by the linear motor, the damping force output by the magnetorheological fluid damper, and the external excitation load are coupled together, and a mechanical friction term is introduced during the coupling process to characterize the frictional influence between the linear motor and the inside of the magnetorheological fluid damper. The vertical motion equations of the composite active suspension system are established based on the mechanical motion relationship; The dynamic response process of the composite active suspension system is characterized by the vertical motion equation.

[0014] In one optional implementation, a mechanical friction term is introduced to characterize the frictional effects between the linear motor and the magnetorheological fluid damper, specifically including: The mechanical friction force is characterized as a combination of Coulomb friction terms and viscous friction terms; The frictional changes near the zero-crossing point of velocity are smoothly characterized using the hyperbolic tangent function. The smoothed friction model is used in the construction of the coupled dynamics model.

[0015] This disclosure also provides a model characterization device for a composite active suspension system of a linear motor and magnetorheological fluid, comprising: The system architecture model construction module is used to obtain the system composition information and interaction information of the linear motor and magnetorheological fluid composite active suspension system, and to construct the corresponding system architecture model. The damping characteristic model construction module is used to establish a damping characteristic model for the magnetorheological fluid damper in the composite active suspension system based on the system architecture model. The motor dynamics model construction module is used to establish a motor dynamics model for the linear motor in the composite active suspension system based on the system architecture model. The control model construction module is used to construct the corresponding control model based on the damping characteristic model and the motor dynamics model; The coupled dynamics model construction module is used to construct the coupled dynamics model of the composite active suspension system based on the damping characteristic model, the motor dynamics model, and external excitation information, so as to characterize the dynamic response characteristics of the composite active suspension system. This disclosure also provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they execute the steps of any possible implementation of the above-described model characterization method for the linear motor and magnetorheological fluid composite active suspension, or the above-described model characterization method for the linear motor and magnetorheological fluid composite active suspension.

[0016] This disclosure also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs steps in any of the possible implementations of the above-described model characterization method for a linear motor and magnetorheological fluid composite active suspension, or the above-described model characterization method for a linear motor and magnetorheological fluid composite active suspension.

[0017] This disclosure also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implements the model characterization method of the above-described linear motor and magnetorheological fluid composite active suspension, or any possible implementation of the model characterization method of the above-described linear motor and magnetorheological fluid composite active suspension.

[0018] This disclosure provides a model characterization method and apparatus for a linear motor and magnetorheological fluid composite active suspension. This method enables a unified characterization of the dynamic characteristics of the linear motor, the nonlinear hysteresis characteristics of the magnetorheological fluid damper, and the multiphysics coupling relationships of the suspension system. This improves the accuracy and completeness of the composite active suspension system model, providing a reliable model foundation for suspension control algorithm design, dynamic performance analysis, and energy consumption assessment. Consequently, it can more accurately describe the dynamic response and energy consumption characteristics of the composite active suspension system under different operating conditions, improving the model's accuracy in representing the actual system behavior and providing support for the development and optimization of high-performance suspension control strategies.

[0019] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments will be briefly described below. These drawings are incorporated in and constitute a part of this specification. They illustrate embodiments conforming to this disclosure and, together with the specification, serve to explain the technical solutions of this disclosure. It should be understood that the following drawings only show some embodiments of this disclosure and should not be considered as limiting the scope. Those skilled in the art can obtain other related drawings based on these drawings without creative effort.

[0021] Figure 1 A flowchart is shown below illustrating a model characterization method for a composite active suspension system of a linear motor and magnetorheological fluid provided in an embodiment of this disclosure. Figure 2 A schematic diagram of a model characterization device for a linear motor and magnetorheological fluid composite active suspension provided in an embodiment of this disclosure is shown. Figure 3 A schematic diagram of an electronic device provided in an embodiment of the present disclosure is shown. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. The components of the embodiments of this disclosure described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this disclosure provided in the accompanying drawings is not intended to limit the scope of the claimed disclosure, but merely represents selected embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0023] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0024] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0025] Research has revealed that the composite active suspension system combining linear motors and magnetorheological fluid involves multiple physical processes, including electromagnetic drive, rheological damping, mechanical vibration, and control coupling. Magnetorheological fluid dampers typically exhibit significant nonlinear and hysteretic characteristics, while linear motors display complex behaviors such as electrical dynamics, magnetic flux coupling, and closed-loop control response. The combined effect of these two components in the suspension system is also influenced by factors such as road surface excitation, mechanical friction, and the sprung / unsprung mass motion relationship. Using only a single linear model, empirical model, or independent local models often fails to accurately reflect the true dynamic characteristics of the composite active suspension system under different frequency bands, control inputs, and external disturbances, leading to insufficient model accuracy and consequently affecting the reliability of subsequent control strategy development, system performance prediction, and simulation analysis results.

[0026] Based on the above research, this disclosure provides a model characterization method and apparatus for a linear motor and magnetorheological fluid composite active suspension. This method enables a unified characterization of the dynamic characteristics of the linear motor, the nonlinear hysteresis characteristics of the magnetorheological fluid damper, and the multi-physics coupling relationships of the suspension system. This improves the accuracy and completeness of the composite active suspension system model, providing a reliable model foundation for suspension control algorithm design, dynamic performance analysis, and energy consumption assessment. Consequently, it can more accurately describe the dynamic response and energy consumption characteristics of the composite active suspension system under different operating conditions, improve the model's accuracy in representing the behavior of the actual system, and provide support for the development and optimization of high-performance suspension control strategies.

[0027] To facilitate understanding of this embodiment, a detailed description of the model characterization method for a linear motor and magnetorheological fluid composite active suspension disclosed in this disclosure embodiment will be provided first. The execution entity of the model characterization method for the linear motor and magnetorheological fluid composite active suspension provided in this disclosure embodiment is generally a computer device with certain computing capabilities. This computer device may include, for example, a terminal device, a server, or other processing devices. The terminal device may be a user equipment (UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA), handheld device, computing device, vehicle-mounted device, wearable device, etc. In some possible implementations, the model characterization method for the linear motor and magnetorheological fluid composite active suspension can be implemented by a processor calling computer-readable instructions stored in memory.

[0028] See Figure 1 The diagram shows a flowchart of a model characterization method for a composite active suspension system using a linear motor and magnetorheological fluid, provided in an embodiment of this disclosure. The method includes steps S101 to S105, wherein: S101. Obtain the system composition information and interaction information of the linear motor and magnetorheological fluid composite active suspension system, and construct the corresponding system architecture model.

[0029] In specific implementation, the object to be characterized is determined to be a composite active suspension system of linear motor and magnetorheological fluid. The composite active suspension system can be composed of a linear motor actuator module, a magnetorheological fluid damper module, a suspension mechanical coupling module, and an electronic control unit module.

[0030] Here, the linear motor actuator module is used to output active driving force in the vertical direction of the suspension to actively adjust the relative motion between the vehicle body and the wheels; the magnetorheological fluid damper module is used to output adjustable damping force according to the change of excitation current to dissipate energy during suspension vibration and help improve system stability; the suspension mechanical coupling module is used to establish the mechanical connection between the linear motor actuator module, the magnetorheological fluid damper module and the vehicle body side and wheel side, so that the electromagnetic thrust output by the linear motor and the damping force output by the magnetorheological fluid damper can work together on the suspension system; the electronic control unit module is used to receive external control commands, run control algorithms and output corresponding control signals to the linear motor actuator module and the magnetorheological fluid damper module.

[0031] The acquisition of system composition information may include acquiring category information, functional information, input / output information, and parameter information for each component module. The category information characterizes whether each module is an actuator, damping mechanism, mechanical connection mechanism, or control mechanism; the functional information characterizes the specific role of each module in the composite active suspension system; the input / output information characterizes the signal input, signal output, mechanical input, and mechanical output terminals of each module; and the parameter information characterizes at least one of the structural, electrical, rheological, mass, stiffness, damping, or control parameters involved in the modeling process of each module.

[0032] In specific implementation, acquiring the interaction information may include acquiring the mechanical connection relationships, signal transmission relationships, and energy interaction relationships between the modules. The mechanical connection relationships are mainly used to characterize the installation position, connection method, and force transmission relationship between the linear motor actuator module and the magnetorheological fluid damper module in the suspension system and the sprung mass and unsprung mass.

[0033] For example, a linear motor actuator module can be connected to moving parts in the suspension to apply electromagnetic thrust directly to the vertical motion link of the suspension; a magnetorheological fluid damper module can be arranged in parallel or in conjunction with the mechanical support structure of the suspension to output adjustable damping force during the relative motion of the suspension.

[0034] Here, the signal transmission relationship is mainly used to characterize the control signal transmission relationship between the electronic control unit module and the linear motor actuator module and the magnetorheological fluid damper module, as well as the feedback path of each sensor information to the electronic control unit module. The energy interaction relationship is mainly used to characterize the conversion relationship of electrical energy to electromagnetic driving force in the system, the adjustment relationship of excitation control on damping characteristics, and the interaction relationship of external road excitation transmitted to each module through the suspension mechanical structure.

[0035] Furthermore, based on the acquired system composition and interaction information, a corresponding system architecture model is constructed. This system architecture model can be constructed using a modular hierarchical structure, dividing the entire composite active suspension system into an execution layer, a damping layer, a mechanical coupling layer, and a control layer.

[0036] The system architecture model is divided into three layers: the execution layer corresponds to the linear motor actuator module, the damping layer corresponds to the magnetorheological fluid vibration damper module, the mechanical coupling layer corresponds to the suspension mechanical coupling module, and the control layer corresponds to the electronic control unit module. For each module, not only are its own inputs, outputs, and state variables recorded, but connection edges or action links between modules are also established to reflect the coupling relationships between them. Preferably, the system architecture model can also define boundary conditions and interface variables for each module, so that the corresponding sub-models can be called separately and unified.

[0037] Furthermore, when constructing the system architecture model, the output of the linear motor actuator module can be defined as electromagnetic thrust, the output of the magnetorheological fluid damper module can be defined as damping force, the state quantity of the suspension mechanical coupling module can be defined as at least one of displacement, velocity, acceleration and load force, and the output of the electronic control unit module can be defined as the drive control quantity for the linear motor and the excitation control quantity for the magnetorheological fluid damper.

[0038] In this way, the input-output correspondence between modules can be initially determined at the system architecture level. For example, the control commands output by the electronic control unit module act on the linear motor actuator module and the magnetorheological fluid damper module; the electromagnetic thrust output by the linear motor actuator module and the damping force output by the magnetorheological fluid damper module act together on the suspension mechanical coupling module; the motion state information generated by the suspension mechanical coupling module under the excitation of the external road surface can be fed back to the electronic control unit module as the basis for subsequent control and modeling correction.

[0039] Optionally, after constructing the system architecture model, each module can be uniformly numbered, a set of state variables can be defined, and parameter index relationships can be established to integrate the magnetorheological fluid vibration damper model, the linear motor dynamics model, the control model, and the system coupled dynamics model under a unified framework.

[0040] S102. Based on the system architecture model, establish a damping characteristic model for the magnetorheological fluid damper in the composite active suspension system.

[0041] In practical implementation, based on the functional positioning, input-output relationship, and interaction with the suspension mechanical coupling module of the magnetorheological fluid damper module in the system architecture model, it is determined that the magnetorheological fluid damper in the composite active suspension system is mainly used to provide adjustable damping force. Its inputs can include excitation current, relative displacement, and relative velocity, and its outputs can include the corresponding damping force. Since magnetorheological fluids exhibit significant rheological changes under an applied magnetic field, and magnetorheological fluid dampers typically exhibit strong nonlinear and hysteretic characteristics during reciprocating motion, this embodiment does not use a simple linear damping relationship to characterize it. Instead, a damping characteristic model is established based on the rheological properties and nonlinear hysteresis effect of the magnetorheological fluid, thereby improving the model's accuracy in describing the actual damping output behavior.

[0042] Specifically, relative motion information and control input information at both ends of the magnetorheological fluid damper can be acquired. The relative motion information may include at least the relative displacement and relative velocity information of the magnetorheological fluid damper, and the control input information may include at least the excitation current information applied to the excitation coil of the magnetorheological fluid damper. The relative displacement information reflects the stroke change of the damper during the vertical vibration of the suspension; the relative velocity information reflects the changes in the shear and throttling states of the fluid inside the damper; and the excitation current information reflects the regulating effect of the magnetic field strength on the yield stress and damping capacity of the magnetorheological fluid.

[0043] Based on the above input information, a nonlinear mapping relationship between the excitation current and the damping output can be further established, so that the damping characteristics of the magnetorheological fluid damper can change dynamically with the change of the control current.

[0044] Furthermore, when establishing the damping characteristic model, an internal hysteresis variable can be introduced to characterize the nonlinear hysteresis behavior of the magnetorheological fluid damper. Here, the internal hysteresis variable is used to describe the path dependence of the magnetorheological fluid damper during loading and unloading, that is, under the same displacement or the same velocity conditions, the damping output may differ due to different historical motion states.

[0045] Based on this internal hysteresis variable, the correlation between damping force and relative displacement, relative velocity, and hysteresis state can be constructed. This allows the resulting model to reflect not only the viscous damping component and the elastic recovery component, but also the hysteresis component caused by the material properties and internal structural reconstruction of the magnetorheological fluid, thus more realistically depicting the mechanical output characteristics of the magnetorheological fluid damper.

[0046] In this embodiment, the Bouc-Wen model is preferably used to describe the evolution of the internal hysteresis variable. That is, by establishing a first-order nonlinear differential relationship, the evolution of the internal hysteresis variable with time, displacement, and velocity can be characterized to describe the hysteresis loop shape, smoothness, and nonlinearity of the magnetorheological fluid vibration damper under different motion states.

[0047] Furthermore, considering that the viscous damping parameters, stiffness parameters, and hysteresis shape parameters of the magnetorheological fluid damper usually change with the excitation current, when establishing the damping characteristic model, the parameters of each model to be calibrated can also be set as functions of the excitation current.

[0048] Preferably, a polynomial fitting method can be used to establish the correspondence between each model parameter and the excitation current. In this way, when the excitation current changes, the corresponding parameter values ​​can be directly updated according to the preset fitting relationship to obtain the damping characteristic model of the magnetorheological fluid vibration damper under different excitation conditions.

[0049] In some implementations, to improve the accuracy of the damping characteristic model, parameter identification can be performed on the model parameters. Specifically, measured damping force data of the magnetorheological fluid vibration damper under different excitation currents and different motion conditions can be obtained, and the error between the model output damping force and the measured damping force can be used as an evaluation criterion to construct an objective function. The objective function can be the root mean square error or other error functions that can characterize the fitting deviation. Subsequently, an intelligent optimization algorithm is used to search and optimize the parameters to be identified in the Bouc-Wen model to obtain the optimal parameter set under different excitation current conditions.

[0050] Specifically, the measured damping force data of the magnetorheological fluid vibration damper is obtained; an objective function is constructed based on the error between the model output damping force and the measured damping force; and an intelligent optimization algorithm is used to identify the parameters to be identified in the magnetorheological fluid vibration damper model to obtain the target parameter combination.

[0051] In one specific implementation, an internal hysteresis variable is introduced. Characterizing the nonlinear hysteresis properties of magnetorheological fluids and establishing damping forces. Mathematical model:

[0052] in, For relative velocity, This is relative displacement. The viscous damping coefficient is... This is the stiffness coefficient.

[0053] Hysteresis variables The evolution follows a first-order nonlinear differential equation (Bouc-Wen model):

[0054] In the formula, To control the shape and smoothness of the hysteresis loop, and the above parameters and , All were characterized as excitation current. The function is represented by a polynomial fitting method, and its expression is:

[0055] In the formula, This represents any parameter to be calibrated in the Bouc-Wen model, including the viscous damping coefficient. Stiffness coefficient and hysteresis loop shape parameters ; These are the polynomial fitting coefficients for the corresponding parameters. Let be the order of the polynomial.

[0056] The construction of the magnetorheological fluid vibration damper model also includes a step of using an intelligent optimization algorithm to identify the parameters of the Bouc-Wen model; based on the measured damping force. With model output damping force The root mean square error between them is used as the objective function. :

[0057] In the formula, The number of sampling points; by minimizing the objective function To obtain the optimal set of model parameters under different excitation currents.

[0058] The damping characteristic model established in the above manner can be integrated into the system architecture model as a sub-model of the magnetorheological fluid damper module. Specifically, the damping characteristic model can receive relative displacement and relative velocity state quantities from the suspension mechanical coupling module, as well as excitation current control quantities from the electronic control unit module, and output the corresponding damping force. The output damping force can further serve as one of the important forces in the system coupled dynamics model, acting together with the electromagnetic thrust output by the linear motor on the suspension mechanical system. Thus, the correlation modeling between the damping characteristics of the magnetorheological fluid damper and the overall dynamic behavior of the system can be realized under a unified system architecture.

[0059] S103. Based on the system architecture model, establish a motor dynamics model for the linear motor in the composite active suspension system.

[0060] In practical implementation, based on the structural and functional positioning of the linear motor actuator module in the system architecture model, as well as its interaction with the suspension mechanical coupling module and the electronic control unit module, the linear motor is determined to be the active actuation unit in the composite active suspension system. It is used to convert electrical energy into electromagnetic thrust output along the vertical direction of the suspension to actively adjust the relative motion between the vehicle body and the wheels.

[0061] Here, since the linear motor involves multiple state variables such as voltage, current, flux linkage, thrust, and mechanical motion during operation, and its output characteristics are coupled with the position of the mover, the running speed, and the control input, in this embodiment, a corresponding motor dynamics model is established based on the motor body parameters and motion state information to accurately characterize the force output law and dynamic response process of the linear motor in the composite active suspension system.

[0062] Specifically, the structural parameters, operating parameters, and electrical parameters of the linear motor can be obtained. The structural parameters may include information such as pole pitch, number of pole pairs, winding structural parameters, and the relative structural relationship between the stator and the mover; the operating parameters may include at least one of the mover displacement, mover velocity, electrical angle, and electrical angular velocity; the electrical parameters may include at least one of the winding resistance, inductance parameters, permanent magnet flux linkage parameters, and three-phase voltage and current signals.

[0063] By obtaining the above parameters, the electrical and mechanical states of the linear motor under the current operating conditions can be determined, providing a foundation for the subsequent establishment of coordinate transformation relationships, voltage equations, flux linkage equations, and electromagnetic thrust equations.

[0064] Furthermore, when establishing the motor dynamics model, the linear motor can be regarded as an expanded form of a rotating permanent magnet synchronous motor, and a corresponding coordinate transformation model can be established based on this equivalence relationship. That is, the current quantity in the three-phase stationary coordinate system can be converted into the current quantity in the two-phase stationary coordinate system, and then further converted into the current quantity in the synchronous rotating coordinate system, thereby converting the AC quantity that originally varied with position into a DC component that is easy to model and control.

[0065] Preferably, the coordinate transformation includes Clark transformation and Park transformation. Clark transformation is used to convert from a three-phase stationary coordinate system to a two-phase stationary coordinate system, and Park transformation is used to convert from a two-phase stationary coordinate system to a synchronous rotating coordinate system. When performing Park transformation, a corresponding transformation matrix can be established based on the electrical angles of the linear motor's mover.

[0066] In this way, the three-phase electromagnetic relationship of the linear motor can be uniformly expressed in the d-axis and q-axis coordinate system, thus creating conditions for the subsequent establishment of a decoupled motor model.

[0067] In a preferred embodiment, a voltage balance equation in a synchronously rotating coordinate system is established based on the Clark and Park transformation results. This voltage balance equation can be used to characterize the relationship between the d-axis and q-axis voltage components and their corresponding current, inductance, winding resistance, and back electromotive force.

[0068] Furthermore, flux linkage equations can be established based on the state variables in the synchronous rotating coordinate system to describe the coupling relationship between the current component and the flux linkage component. By constructing the voltage balance equation and flux linkage equation, the internal dynamic characteristics of the linear motor during the electromagnetic conversion process can be characterized more completely, and a mathematical basis can be provided for decoupling control, current control, and thrust control in the subsequent control model.

[0069] Furthermore, when establishing the motor dynamics model, an electromagnetic thrust characterization equation can also be established. This equation describes the correspondence between the linear motor's output thrust and the d-axis and q-axis current components, the permanent magnet flux linkage, and the motor's structural parameters. By establishing this electromagnetic thrust equation, the electrical state of the motor can be linked to the mechanical force state of the suspension, meaning the voltage or current control quantity output by the electronic control unit can be converted into an electromagnetic thrust output acting on the suspension mechanical system via the motor dynamics model.

[0070] In this way, the established motor dynamics model can not only reflect the electromagnetic process inside the linear motor, but also serve as an important bridge connecting the control layer and the mechanical layer, participating in the construction of the subsequent system coupled dynamics model.

[0071] In practical implementation, the motor dynamics model can receive drive voltage signals or reference current signals from the electronic control unit module, and combine them with mechanical state information such as displacement and velocity from the suspension mechanical coupling module to output corresponding current state quantities, flux linkage state quantities, and electromagnetic thrust. Therefore, the linear motor dynamics model can be integrated into the unified modeling framework as an actuator sub-model in the system architecture model, and work together with the magnetorheological fluid damper damping characteristic model on the suspension mechanical coupling module.

[0072] Optionally, after establishing the motor dynamics model, input interfaces, output interfaces, and intermediate state interfaces can be defined based on the state variables in the model. The input interfaces may include three-phase drive voltage, reference current, mover displacement, and mover velocity; the output interfaces may include d-axis current, q-axis current, electromagnetic thrust, and other variables characterizing the motor's operating state; and the intermediate state interfaces may include at least one of electrical angle, electrical angular velocity, and flux linkage state variables.

[0073] In one specific implementation, the pole pitch of the linear motor is defined as... The velocity of the mover is The electric angular velocity is .

[0074] Current in a three-phase stationary coordinate system Converted to current in a two-phase stationary coordinate system using the constant amplitude Clark transform. Then, the current is converted into a synchronous rotating coordinate system using the Park transformation. Its transformation matrix satisfy:

[0075] In the formula, Let be the electrical angle of the linear motor's rotor, and .

[0076] Based on Clark and Park transformations, voltage balance equations are established in a synchronously rotating coordinate system (dq axis):

[0077] Establish electromagnetic thrust Characterization equation:

[0078] In the formula, For stator voltage components, For stator current components, For inductive components, It is a permanent magnet flux linkage. This represents the winding resistance.

[0079] S104. Based on the damping characteristic model and the motor dynamics model, construct the corresponding control model.

[0080] In practical implementation, based on the control relationship between the electronic control unit module, the linear motor actuator module, and the magnetorheological fluid damper module in the system architecture model, the control model is determined to be used to uniformly characterize the active output process of the linear motor and the damping adjustment process of the magnetorheological fluid damper.

[0081] In this system, the control objective on the linear motor side can be to track and control the target displacement, target velocity, or target thrust. The control objective on the magnetorheological fluid damper side can be to output the corresponding excitation current according to the control command, thereby adjusting the damping output corresponding to the damping characteristic model. Since the composite active suspension system includes both active power output and adjustable damping output, by incorporating the damping characteristic model and the motor dynamics model into the same control framework, the coordinated adjustment relationship between the two types of actuators under a unified control logic can be characterized.

[0082] Specifically, when constructing the control model, a three-loop control model based on vector control—position, velocity, and current—can be established for the linear motor. That is, the control model can adopt a cascaded closed-loop structure, including an outermost displacement loop, a middle velocity loop, and an innermost current loop.

[0083] The displacement loop generates a reference speed based on the deviation between the target displacement and the actual displacement, the speed loop generates a reference thrust based on the deviation between the reference speed and the actual speed, and the current loop determines the reference current based on the reference thrust and further generates a reference voltage to drive the linear motor.

[0084] Furthermore, in the displacement loop, the commanded displacement can be compared with the measured displacement, and a reference speed can be output through proportional-integral control. Here, the commanded displacement can originate from the upper-level control strategy, the target suspension attitude requirements, or a preset vibration suppression target, while the measured displacement can originate from displacement sensor feedback or be obtained from system state estimation.

[0085] Subsequently, in the speed loop, the reference speed can be compared with the measured speed, and the reference thrust can be output through proportional-integral control. Then, according to the thrust coefficient relationship of the linear motor, the reference thrust is converted into the q-axis reference current.

[0086] In a preferred embodiment, the current loop is used to control the d-axis and q-axis currents of the linear motor. Considering that there is usually cross-coupling between the d-axis and q-axis, and that the linear motor is also subject to back EMF interference during operation, feedforward decoupling compensation can be introduced into the current loop when constructing the control model.

[0087] Specifically, based on the voltage equation and flux linkage equation in the motor dynamics model, the coupling terms between the d-axis and q-axis can be compensated, and the back electromotive force term can be fed forward to output the d-axis reference voltage and the q-axis reference voltage.

[0088] Furthermore, after obtaining the d-axis and q-axis reference voltages, the reference voltages can be converted into three-phase voltage signals to drive the linear motor via a space vector pulse width modulation module. These three-phase voltage signals can be used as one of the input quantities to the motor dynamics model to drive the linear motor's actual operation and output corresponding current state quantities and electromagnetic thrust.

[0089] Therefore, the control model and the motor dynamics model can form a closed-loop relationship. That is, the control model generates drive commands based on the feedback state, the motor dynamics model outputs the actual operating results based on the drive commands and the mechanical state, and the output results are then fed back to the control model for the next cycle adjustment.

[0090] On the other hand, a corresponding current-driven model can be established for the magnetorheological fluid vibration damper. This current-driven model can receive damping adjustment commands from the electronic control unit module and output excitation current control quantities according to the damping adjustment commands to drive the excitation coil of the magnetorheological fluid vibration damper.

[0091] Here, since the aforementioned damping characteristic model has established a mapping relationship between the excitation current and the damping output, the excitation current output by the current-driven model can dynamically change the parameter values ​​in the magnetorheological fluid vibration damper model or directly change its damping output characteristics. In other words, the control model on the magnetorheological fluid vibration damper side essentially converts control commands into excitation current and adjusts the damping characteristic model through the excitation current to enable the magnetorheological fluid vibration damper to output appropriate damping force under different operating conditions.

[0092] In some implementations, the control model can further unify the definition of input interfaces, output interfaces, and feedback interfaces. The input interface may include target displacement information, target damping adjustment information, actual displacement information, actual velocity information, actual current information, and other state information fed back from the system coupled dynamics model. The output interface may include the d-axis reference voltage, q-axis reference voltage, or three-phase drive voltage from the linear motor side, and the excitation current control quantity from the magnetorheological fluid damper side. The feedback interface is used to receive state feedback output from the linear motor dynamics model and the damping characteristic model.

[0093] Through this interface-based definition, the control model can be integrated into the unified modeling framework as an independent sub-model in the system architecture model, and can be analyzed in conjunction with the linear motor dynamics model, the magnetorheological fluid damper damping characteristic model, and the subsequent system coupled dynamics model.

[0094] The control model constructed based on the above method can characterize the position control, speed control, and current control processes on the linear motor side, and the excitation adjustment process on the magnetorheological fluid damper side, thereby achieving coordinated control of the active driving force and adjustable damping force in the composite active suspension system. Furthermore, the control model can be used to describe the mathematical relationships and signal transmission relationships of the controller, and can also be used for subsequent system simulation, control strategy verification, and dynamic response analysis, thus providing support for the performance evaluation of the composite active suspension system under different operating conditions.

[0095] In one specific implementation, a cascaded three-closed-loop control architecture is used to drive the linear motor: Outermost loop (displacement loop): Compares command displacements Compared with the measured displacement The reference speed is output through the PI controller. ; Intermediate loop (speed loop): Compares to reference speed Compared with the measured speed The reference thrust is output through the PI controller. And based on the thrust coefficient Converted to q-axis reference current ; Innermost loop (current loop): Compares to the reference current To eliminate the interference of cross-coupling voltage and back EMF between the d-axis and q-axis, and in conjunction with the measured current, a feedforward decoupling compensation voltage is designed. and :

[0096]

[0097] Combined with back EMF feedforward decoupling, the output dq-axis reference voltage is obtained. .

[0098] Finally, the reference voltage is converted into the three-phase voltage for driving the motor through the space vector pulse width modulation (SVPWM) module.

[0099] S105. Based on the damping characteristic model, the motor dynamics model, and the external excitation information, construct a coupled dynamics model of the composite active suspension system to characterize the dynamic response characteristics of the composite active suspension system.

[0100] In specific implementation, based on the connection and interaction relationships between the modules in the aforementioned system architecture model, the coupled dynamics model is used to integrate the magnetorheological fluid damper module, the linear motor actuator module, the suspension mechanical coupling module, and the external road excitation into the same dynamics analysis framework.

[0101] Among them, the magnetorheological fluid damper module outputs damping force through the damping characteristic model, the linear motor actuator module outputs electromagnetic thrust through the motor dynamics model, and the external excitation information is used to characterize the disturbance effect of road surface roughness, impact input or periodic vibration input on the suspension system.

[0102] By incorporating the aforementioned multiple sources of action into the dynamic equilibrium relationship of the suspension mechanical system, a system-level coupled dynamic model of the composite active suspension system can be established. This allows the model to reflect not only the local characteristics of a single subsystem but also the overall dynamic behavior under the interaction of each subsystem.

[0103] Specifically, external excitation information and suspension mechanical structure parameters can be obtained. The external excitation information may include road surface displacement input, road surface velocity input, equivalent road surface load input, or other parameter information that can characterize road surface disturbance characteristics; the suspension mechanical structure parameters may include at least one of the following: sprung mass, unsprung mass, elastic element stiffness, connection structure parameters, and mechanical transmission relationship parameters.

[0104] Here, the external excitation information is used to characterize the external disturbance source of the suspension system, and the mechanical structural parameters are used to characterize the internal force transmission and motion conversion basis of the suspension system. By obtaining the above information, the necessary conditions can be provided for constructing the dynamic equations of the composite active suspension system in the vertical direction.

[0105] Furthermore, when constructing the coupled dynamics model, the electromagnetic thrust output by the linear motor, the damping force output by the magnetorheological fluid damper, and the external excitation load can be uniformly coupled. That is, the electromagnetic thrust output by the motor dynamics model is used as the active control force, the damping force output by the damping characteristic model is used as the adjustable damping force, and the load or displacement input corresponding to the external excitation information is used as the disturbance force. These are combined with the inertial force and elastic restoring force in the suspension mechanical structure to establish the system's force balance relationship.

[0106] This approach allows the coupling effects between the active driving force of the linear motor, the damping adjustment effect of the magnetorheological fluid, and road disturbances to be reflected in the unified equation, thus enabling the obtained model to describe the actual stress state of the composite active suspension system under complex working conditions.

[0107] In a preferred embodiment, the vertical motion equation of the composite active suspension system can be established based on Newton's second law. Specifically, a dynamic equilibrium relationship can be established for the target moving component in the suspension, synthesizing the electromagnetic thrust, damping force, elastic force, external excitation force, and friction force acting on the target moving component, and establishing a correspondence between them and the mass and acceleration of the target moving component.

[0108] Preferably, a dynamic equilibrium equation can be established for the mover or an equivalent combination of the mover and unsprung mass to characterize the transient motion process of the composite active suspension system in the vertical direction. Through this dynamic equilibrium equation, the outputs of the aforementioned magnetorheological damper model and linear motor model can be uniformly mapped into the mechanical motion equation, thus forming a complete coupled dynamic description.

[0109] Furthermore, a mechanical friction term can be introduced into the coupled dynamics model to improve the model's accuracy in describing the actual system's motion. Since the linear motor and magnetorheological fluid damper typically experience friction effects due to guiding mechanism friction, sealing friction, and internal mechanical contact during actual operation, the mechanical friction force can be treated as an independent term in the system's force balance when establishing the system-level dynamics model.

[0110] Preferably, the mechanical friction force may include a Coulomb friction term and a viscous friction term. The Coulomb friction term characterizes an approximately constant frictional force related to the direction of motion, while the viscous friction term characterizes a drag force related to relative velocity. By simultaneously introducing these two types of friction terms, the coupled dynamics model can more closely approximate the actual operating state of the device.

[0111] In a more preferred embodiment, to avoid model discontinuities caused by abrupt changes in friction near the zero-crossing point of velocity, a hyperbolic tangent function can be used to smooth the friction force. That is, the Coulomb friction term can be made continuous using the hyperbolic tangent function, so that the friction force changes smoothly in the zero-crossing region where the velocity changes from positive to negative or from negative to positive, and together with the viscous friction term, it constitutes the total mechanical friction force model.

[0112] The coupled dynamics model established in the above manner can receive the damping force output from the damping characteristic model, the electromagnetic thrust output from the motor dynamics model, and the road excitation input from the external environment, and output at least one of the displacement response, velocity response, acceleration response, damping force response, electromagnetic thrust response, or energy consumption response of the composite active suspension system under the target working condition.

[0113] In other words, the coupled dynamics model is not only used to characterize the coupling relationship of multiple force sources within the system, but can also be used to generate the dynamic response characteristics of the system, so as to analyze the working state of the composite active suspension system under different frequency bands, different control inputs and different external disturbances.

[0114] Furthermore, the dynamic response characteristics may include at least vibration response characteristics and energy consumption characteristics at different frequency bands. Vibration response characteristics may be reflected in indicators such as suspension displacement, velocity, acceleration, or vehicle body vibration suppression effect, while energy consumption characteristics may be reflected in the energy consumption, energy recovery, or overall system operating power changes of the linear motor during active output.

[0115] Optionally, after constructing the coupled dynamics model, it can be combined with the aforementioned control model to form a closed-loop system-level representation model. In this closed-loop system-level representation model, the control model generates control commands for the linear motor and the magnetorheological fluid damper based on the system response state. The motor dynamics model and the damping characteristic model output electromagnetic thrust and damping force respectively based on the control commands. The coupled dynamics model then solves for the system motion response based on the above outputs and external excitation information, and feeds the motion response back to the control model.

[0116] In one specific implementation, the dynamic equilibrium equations of the mover (primary) are established:

[0117] In the formula, The sum of the mass of the mover and the unsprung mass. The load force generated by the road surface excitation and elastic elements, This refers to the mechanical friction force between the motor and the inside of the vibration damper.

[0118] The friction force It includes Coulomb friction and viscous friction terms. A hyperbolic tangent friction model is used for characterization to smoothly describe the abrupt change in frictional force near the zero-crossing point of the mover; the expression for the hyperbolic tangent model is:

[0119] In the formula, The amplitude of the Coulomb friction force. To adjust the shape parameters of the curve slope at the zero point, The coefficient of viscous friction is... Let be the relative velocity of the moving part.

[0120] This disclosure provides a model characterization method for a composite active suspension system using a linear motor and magnetorheological fluid. This method enables a unified characterization of the dynamic characteristics of the linear motor, the nonlinear hysteresis characteristics of the magnetorheological fluid damper, and the multiphysics coupling relationships of the suspension system. This improves the accuracy and completeness of the composite active suspension system model, providing a reliable model foundation for suspension control algorithm design, dynamic performance analysis, and energy consumption assessment. Consequently, it can more accurately describe the dynamic response and energy consumption characteristics of the composite active suspension system under different operating conditions, improving the model's accuracy in representing the actual system behavior and providing support for the development and optimization of high-performance suspension control strategies.

[0121] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0122] Based on the same inventive concept, this disclosure also provides a model characterization device for a linear motor and magnetorheological fluid composite active suspension, corresponding to the model characterization method for a linear motor and magnetorheological fluid composite active suspension. Since the principle of the device in this disclosure for solving the problem is similar to the model characterization method for a linear motor and magnetorheological fluid composite active suspension described above, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0123] Please see Figure 2 , Figure 2 This is a schematic diagram of a model characterization device for a composite active suspension system combining a linear motor and magnetorheological fluid, provided as an embodiment of this disclosure. Figure 2 As shown in the figure, the model characterization device 200 for a linear motor and magnetorheological fluid composite active suspension provided in this embodiment includes: The system architecture model construction module 210 is used to obtain the system composition information and the interaction information of the linear motor and magnetorheological fluid composite active suspension system, and to construct the corresponding system architecture model.

[0124] The damping characteristic model construction module 220 is used to establish a damping characteristic model for the magnetorheological fluid damper in the composite active suspension system based on the system architecture model.

[0125] The motor dynamics model construction module 230 is used to establish a motor dynamics model for the linear motor in the composite active suspension system based on the system architecture model.

[0126] The control model construction module 240 is used to construct a corresponding control model based on the damping characteristic model and the motor dynamics model.

[0127] The coupled dynamics model construction module 250 is used to construct the coupled dynamics model of the composite active suspension system based on the damping characteristic model, the motor dynamics model and external excitation information, so as to characterize the dynamic response characteristics of the composite active suspension system.

[0128] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0129] This disclosure provides a model characterization device for a linear motor and magnetorheological fluid composite active suspension. This device enables a unified characterization of the dynamic characteristics of the linear motor, the nonlinear hysteresis characteristics of the magnetorheological fluid damper, and the multiphysics coupling relationships of the suspension system. This improves the accuracy and completeness of the composite active suspension system model, providing a reliable model foundation for suspension control algorithm design, dynamic performance analysis, and energy consumption assessment. Consequently, it can more accurately describe the dynamic response and energy consumption characteristics of the composite active suspension system under different operating conditions, improving the model's representation accuracy of actual system behavior and providing support for the development and optimization of high-performance suspension control strategies.

[0130] Corresponding to Figure 1 The present disclosure also provides an electronic device 300, such as a model characterization method for a composite active suspension system of linear motor and magnetorheological fluid. Figure 3 The diagram shown is a structural schematic of an electronic device 300 provided in an embodiment of this disclosure, including: Processor 31, memory 32, and bus 33; memory 32 is used to store execution instructions, including main memory 321 and external memory 322; the main memory 321, also called internal memory, is used to temporarily store the computational data in processor 31, as well as the data exchanged with external memory 322 such as hard disk. Processor 31 exchanges data with external memory 322 through main memory 321. When the electronic device 300 is running, processor 31 and memory 32 communicate through bus 33, enabling processor 31 to execute... Figure 1 The steps of the model characterization method for the composite active suspension of linear motor and magnetorheological fluid.

[0131] This disclosure also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs the steps of the model characterization method for the linear motor and magnetorheological fluid composite active suspension described in the above-described method embodiments. The storage medium can be volatile or non-volatile computer-readable storage.

[0132] This disclosure also provides a computer program product, which includes computer instructions. When the computer instructions are executed by a processor, they can perform the steps of the model characterization method for the linear motor and magnetorheological fluid composite active suspension described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0133] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied in a computer storage medium; in another optional embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0134] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here. In the several embodiments provided in this disclosure, it should be understood that the disclosed device and method 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. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0135] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0136] In addition, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0137] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or a portion of the technical solution, 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 steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0138] Finally, it should be noted that the above-described embodiments are merely specific implementations of this disclosure, used to illustrate the technical solutions of this disclosure, and not to limit it. The protection scope of this disclosure is not limited thereto. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this disclosure. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be covered within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the protection scope of the claims.

Claims

1. A model characterization method for a composite active suspension system using a linear motor and magnetorheological fluid, characterized in that, include: Obtain the system composition and interaction information of the linear motor and magnetorheological fluid composite active suspension system, and construct the corresponding system architecture model; Based on the system architecture model, a damping characteristic model is established for the magnetorheological fluid damper in the composite active suspension system. Based on the system architecture model, a motor dynamics model is established for the linear motor in the composite active suspension system. Based on the damping characteristic model and the motor dynamics model, a corresponding control model is constructed; Based on the damping characteristic model, the motor dynamics model, and the external excitation information, a coupled dynamics model of the composite active suspension system is constructed to characterize the dynamic response characteristics of the composite active suspension system.

2. The method according to claim 1, characterized in that, Obtain the system composition and interaction information of the linear motor and magnetorheological fluid composite active suspension system, and construct the corresponding system architecture model, specifically including: The composite active suspension system is defined as including a linear motor actuator module, a magnetorheological fluid damper module, a suspension mechanical coupling module, and an electronic control unit module. Determine the mechanical connections, signal transmission relationships, and energy interaction relationships between the modules; The system architecture model of the composite active suspension system is constructed based on the relationships between the modules.

3. The method according to claim 1, characterized in that, A damping characteristic model for the magnetorheological fluid damper in the composite active suspension system is established, specifically including: Acquire relative displacement, relative velocity, and excitation current information of the magnetorheological fluid vibration damper; Based on the rheological and hysteretic properties of magnetorheological fluids, a damping force output model is established by introducing hysteresis characterization variables. The internal hysteresis variables in the Bouc-Wen model are used to characterize the nonlinear hysteresis behavior of the magnetorheological fluid damper. Based on the relative displacement information, relative velocity information and the internal hysteresis variables, the functional relationship between the damping force and the displacement, velocity and hysteresis terms is established. Based on the evolution law of the internal hysteresis variables, the corresponding first-order nonlinear differential equation is established. Establish the mapping relationship between excitation current and model parameters to characterize the output damping force of magnetorheological fluid vibration damper under different excitation conditions; In this model, the viscous damping parameters, stiffness parameters, and hysteresis shape parameters in the magnetorheological fluid vibration damper are set as functions of the excitation current. Polynomial fitting is used to determine the correspondence between each model parameter and the excitation current, and the parameter set under different excitation current conditions is obtained based on the fitting results.

4. The method according to claim 3, characterized in that, The method further includes: Obtain measured damping force data for magnetorheological fluid vibration dampers; An objective function is constructed based on the error between the model output damping force and the measured damping force. Intelligent optimization algorithms are used to identify the parameters to be identified in the magnetorheological fluid vibration damper model in order to obtain the target parameter combination.

5. The method according to claim 1, characterized in that, A motor dynamics model is established for the linear motor in the composite active suspension system, specifically including: Obtain the structural, operational, and electrical parameters of the linear motor; Based on the correspondence between linear motors and rotating permanent magnet synchronous motors, the coordinate transformation relationship of linear motors is established; Specifically, the current quantity in the three-phase stationary coordinate system is converted into the current quantity in the two-phase stationary coordinate system, and then the current quantity in the two-phase stationary coordinate system is converted into the current quantity in the synchronous rotating coordinate system. The state variable expression relationship in the synchronous rotating coordinate system is established based on the position or electrical angle information of the mover. Based on the coordinate transformation relationship, voltage equation, flux linkage equation and electromagnetic thrust equation are established in the synchronous rotating coordinate system to characterize the output characteristics of the linear motor. Specifically, the voltage balance relationship between the d-axis and q-axis is established based on the winding resistance, inductance parameters, and permanent magnet flux linkage parameters of the linear motor. The coupling relationship between the current component and the flux linkage component is determined based on the voltage balance relationship between the d-axis and q-axis. The electromagnetic thrust characterization relationship is established based on the flux linkage component and the current component.

6. The method according to claim 1, characterized in that, Based on the damping characteristic model and the motor dynamics model, a corresponding control model is constructed, specifically including: A closed-loop control structure with cascaded position, speed, and current loops is established for linear motors. Determine the reference velocity based on the target displacement information and the actual displacement information; The reference thrust is determined based on the reference speed and the actual speed, and the reference current is determined based on the reference thrust. The reference voltage is determined based on the reference current and the actual current to drive the linear motor. Feedforward decoupling compensation is introduced in the current loop to weaken the coupling effect between different axial components and to compensate for back EMF interference, thereby obtaining the d-axis reference voltage and the q-axis reference voltage. A multiphase drive voltage signal for driving the linear motor is generated based on the d-axis reference voltage and the q-axis reference voltage. A current-driven model is established for the magnetorheological fluid vibration damper to adjust the excitation current according to the control command.

7. The method according to claim 1, characterized in that, Based on the damping characteristic model, the motor dynamics model, and the external excitation information, a coupled dynamics model of the composite active suspension system is constructed, specifically including: Acquire external road surface excitation information and suspension mechanical structure parameters; The electromagnetic thrust output by the linear motor, the damping force output by the magnetorheological fluid damper, and the external excitation load are coupled together, and a mechanical friction term is introduced during the coupling process to characterize the frictional influence between the linear motor and the inside of the magnetorheological fluid damper. The vertical motion equations of the composite active suspension system are established based on the mechanical motion relationship; The dynamic response process of the composite active suspension system is characterized by the vertical motion equation.

8. The method according to claim 7, characterized in that, A mechanical friction term is introduced to characterize the frictional effects within the linear motor and the magnetorheological fluid damper, specifically including: The mechanical friction force is characterized as a combination of Coulomb friction terms and viscous friction terms; The frictional changes near the zero-crossing point of velocity are smoothly characterized using the hyperbolic tangent function. The smoothed friction model is used in the construction of the coupled dynamics model.

9. A model characterization device for a composite active suspension system of a linear motor and magnetorheological fluid, characterized in that, include: The system architecture model construction module is used to obtain the system composition information and interaction information of the linear motor and magnetorheological fluid composite active suspension system, and to construct the corresponding system architecture model. The damping characteristic model construction module is used to establish a damping characteristic model for the magnetorheological fluid damper in the composite active suspension system based on the system architecture model. The motor dynamics model construction module is used to establish a motor dynamics model for the linear motor in the composite active suspension system based on the system architecture model. The control model construction module is used to construct the corresponding control model based on the damping characteristic model and the motor dynamics model; The coupled dynamics model construction module is used to construct the coupled dynamics model of the composite active suspension system based on the damping characteristic model, the motor dynamics model, and external excitation information, so as to characterize the dynamic response characteristics of the composite active suspension system.

10. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the model characterization method for the linear motor and magnetorheological fluid composite active suspension as described in any one of claims 1 to 8.

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