Electromagnetic suspension multi-layer loop control method and system for vehicle performance coordination and vehicle

Abstract

The invention relates to the technical field of electromagnetic suspensions, and provides an electromagnetic suspension multi-layer loop control method and system for vehicle performance coordination and a vehicle. Comprising the steps that vehicle and motor state information is obtained through a preset sensing unit, and a suspension controller calculates and outputs target control force through a control model based on a whole vehicle performance target and generates a control instruction; after an electromagnetic execution unit driving layer receives an instruction, FOC three-closed-loop control is combined with an algorithm of a state observer, target current is controlled and tracked through current loop proportional-integral, a speed loop and a position loop construct a sliding mode surface design control law based on state deviation through sliding mode control, and the target current is obtained. And the motor is driven to output corresponding electromagnetic acting force through coordinate inverse transformation and space vector pulse width modulation. And meanwhile, interference of electromagnetic characteristics of the motor, vehicle posture changes and external disturbance on motor output is compensated, suspension actuation control is accurately achieved through multi-layer loop coordination control, and vehicle running smoothness and safety are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electromagnetic suspension, in particular to a multi-layer loop control method and system for vehicle performance coordination and a vehicle. BACKGROUND

[0002] The content of this part only provides background information related to the present application, which may not constitute prior art.

[0003] With the rapid development of automobile technology, modern vehicles have increasingly high requirements for comfort, safety and energy efficiency. During vehicle driving, the driving state changes greatly in terms of load, speed, road conditions, etc. The requirements for smoothness, maneuverability and stability of the vehicle under different working conditions are different. The suspension system, as a key component connecting the vehicle body and the wheels, has a decisive influence on the dynamic performance of the vehicle. The traditional passive suspension cannot adapt to complex and changeable road conditions and driving conditions due to fixed parameters, and it is difficult to simultaneously consider comfort and control stability. Under this demand, various active suspension technologies have emerged, among which the electromagnetic active suspension has become a research hotspot due to its fast adjustment speed and high control precision. The electromagnetic actuator, as the core component, is one of the key research contents of the electromagnetic active suspension. Whether the actuator can accurately and effectively track the instructions output by the upper suspension controller still needs further consideration and verification.

[0004] In the prior art, a Chinese patent with the application number 201710127192.6 discloses an electromagnetic suspension system based on a wheel drive electric vehicle and a control method thereof. A three-degree-of-freedom electromagnetic suspension model is established based on a wheel drive electric vehicle. An ECU collects the sprung mass acceleration signal through an acceleration sensor and collects the displacement signals of the sprung mass and the unsprung mass through a displacement sensor. Real-time suspension dynamic parameters of the vehicle are obtained by analysis and processing. An LQG algorithm is used to control the output active force of the linear motor. The control method switches the comfort mode, safety mode and comprehensive mode of the electromagnetic suspension through the real-time values of the vehicle body acceleration and the tire dynamic load. The system includes outer loop control and inner loop control. The outer loop generates target control force according to the real-time dynamic parameters of the suspension through the LQG algorithm and inputs the inner loop. The inner loop tracks the target control force through PI control and acts on the suspension model. At the same time, the suspension model outputs the real-time suspension dynamic parameters as the inner loop, forming a double-loop control of inner and outer loops. The patent only establishes a three-degree-of-freedom electromagnetic suspension model and controls the motor actuator through inner and outer loop control. The mathematical model of the motor actuator is not established. The influence of the electromagnetic characteristics of the motor itself and external disturbances is ignored when controlling the motor output actuator. In actual application, there is a large fluctuation between the actual output value and the target value of the motor. In addition, another Chinese patent with application number 202410211256.0 discloses an active suspension control strategy based on fuzzy theory. By establishing a road excitation model, a seven-degree-of-freedom suspension model and an actuator model, a fuzzy control-PID controller for active suspension is designed using fuzzy theory, the difference between the first derivative of the suspension deflection and the ideal reference input and its rate of change are used as the fuzzy control input signal, the PID controller parameters are used as the output signal, and the PID controller parameters are adjusted according to the road conditions. The actuator is composed of a linear motor and a ball screw, the actuator output actuating force is in a proportional relationship with the motor current, and the ideal active force is converted into the actual active force by controlling the motor current. However, although the patent establishes a complete seven-degree-of-freedom suspension model and an actuator model, it still regards the motor output active force and current as a linear relationship, ignores the external environment and the disturbance source of the motor itself, and the actuator adopts a mechanical combination of a DC motor and a ball screw, which is worse than a linear motor in response and control accuracy. SUMMARY

[0005] To solve the above technical problems, the purpose of the present application is to provide a whole vehicle performance coordinated electromagnetic suspension multi-loop control method, system and vehicle. The suspension controller generates target control force instructions based on the whole vehicle performance target, and the electromagnetic actuator driving layer adopts FOC three closed loop control combined with state observer, and the corresponding electromagnetic force is output by coordinate inverse transformation and space vector pulse width modulation driving motor. Through compensating the motor electromagnetic characteristics, vehicle attitude changes and external disturbance, the suspension actuation precise control is realized by multi-loop coordination, which significantly improves the vehicle ride comfort and safety.

[0006] The purpose of the present application is realized by the following technical solutions: In a first aspect, the present application provides a whole vehicle performance coordinated electromagnetic suspension multi-loop control method, comprising: The current vehicle state information is obtained by a preset sensing unit; The vehicle state information is input to the suspension controller, and the suspension controller obtains the target control force based on the whole vehicle performance target through a preset control model, and generates the corresponding control instructions input to the electromagnetic actuator driving layer; In response to the control instructions, the electromagnetic actuator driving layer controls the high-voltage driver to output corresponding voltage and current to drive the target motor through the preset algorithm of FOC three closed loop control combined with state observer; at the same time, the current state information of the motor is obtained by the corresponding sensing unit; The preset algorithm comprises a three-closed-loop control structure of a current loop, a speed loop and a position loop arranged from inside to outside; the current loop adopts proportional integral control to track a target current to quickly output a current control quantity; the speed loop and the position loop adopt sliding mode control, a sliding mode surface is constructed based on a deviation between an actual state and a target state, a control law is designed through a reaching law, and a speed loop control output and a position loop control output are obtained respectively; according to the speed loop control output and the position loop control output, in combination with the current loop control output, corresponding pulse width modulation waveforms are generated through coordinate inverse transformation and space vector pulse width modulation processing in sequence, and the waveforms are controlled through an inverter to drive the target motor to output electromagnetic forces corresponding to the target control force.

[0007] Further, the preset control model adopts one of a multi-agent consensus algorithm, an H2 / H∞ algorithm or an LQG optimal control algorithm.

[0008] Further, the preset control model comprises: each electromagnetic actuator in the electromagnetic suspension is taken as a single independent agent; a mechanical transmission model between each motion state of the sprung mass and the vertical motion of the unsprung mass is constructed; a multi-agent consensus control protocol is set based on the mechanical transmission model, the protocol comprises position parameters, speed parameters, gain coefficients of each agent and weight coefficients in a multi-agent communication graph, vehicle state information is substituted into the control protocol, and a consensus active control force of each agent is calculated and a target control force is output.

[0009] Further, an expression of the target control force is: wherein, is an electromagnetic thrust; is a pole pair number; is a pole pitch; is a permanent magnet flux linkage; is a q-axis stator current.

[0010] Further, the step of constructing the mechanical transmission model between each motion state of the sprung mass and the vertical motion of the unsprung mass comprises: the vehicle sprung mass is regarded as a rigid body, a correlation between vertical motion, pitch motion and roll motion of the sprung mass and vertical motion of the unsprung mass is constructed, and a transmission law of spring force and damping force in each motion process is obtained; a mechanical transmission model between each motion state of the sprung mass and the vertical motion of the unsprung mass is constructed by establishing a corresponding relationship and a transmission law between vertical displacement of the sprung mass mass center and displacement of front and rear suspension support points, and an influence relationship between pitch motion, roll motion and displacement of each suspension support point.

[0011] Furthermore, the output target control force also includes: Active acceleration damping control is introduced, and an inertial capacity coefficient is set. Based on the rate of change of vertical vibration acceleration of the vehicle body associated with each intelligent agent in the vehicle state information, the active acceleration damping control force corresponding to each intelligent agent is calculated in combination with the inertial capacity coefficient. The consistent active control force and the acceleration damping active control force are weighted and fused according to a preset adjustment coefficient to obtain the final target control force of each agent.

[0012] Furthermore, while obtaining the speed loop control output and the position loop control output respectively, it also includes: By using an extended state observer, external disturbances and internal uncertainties are regarded as extended state terms. By designing the observer parameters, the actual state and extended state terms are estimated in real time to obtain the estimated value of the total disturbance and convert it into a compensation quantity. The compensation quantity is then fed forward to the given control quantities of the velocity loop and position loop to complete the compensation.

[0013] Furthermore, the target motor is a permanent magnet synchronous linear motor.

[0014] Secondly, the present invention provides an electromagnetic suspension multi-loop control system for coordinating overall vehicle performance, comprising: The data acquisition module is used to acquire current vehicle status information through preset sensing units; The control force calculation module is used to input vehicle status information to the suspension controller. The suspension controller derives the target control force based on the overall vehicle performance target through a preset control model and generates corresponding control commands to be input to the electromagnetic actuator drive layer. The execution module, upon receiving a control command, uses the electromagnetic execution unit drive layer to control the high-voltage driver to output the corresponding voltage and current to drive the target motor through the FOC three-closed-loop control combined with the preset algorithm of the state observer; at the same time, it obtains the current state information of the motor through the corresponding sensing unit. The preset algorithm includes a three-loop control structure consisting of a current loop, a speed loop, and a position loop arranged sequentially from the inside out. The current loop employs proportional-integral control to track the target current and quickly output the current control quantity. The speed and position loops use sliding mode control, constructing a sliding surface based on the deviation between the actual and target states. A control law is designed using a reaching law to obtain the speed loop control output and the position loop control output, respectively. Based on the speed loop control output and the position loop control output, combined with the current loop control output, the system sequentially undergoes inverse coordinate transformation and space vector pulse width modulation (PWM) processing to generate corresponding PWM waveforms. The inverter controls these waveforms, driving the target motor to output an electromagnetic force corresponding to the target control force.

[0015] Thirdly, the present invention provides a vehicle, including a vehicle body, a suspension and a controller disposed on the vehicle body, the controller including a memory, a processor and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement the steps corresponding to the method in the first aspect.

[0016] In summary, the technical solutions of the embodiments of the present invention have at least the following advantages and beneficial effects: This invention collects current vehicle state information through a preset sensing unit. The suspension controller, based on the overall vehicle performance target, calculates the target control force using a preset control model and generates corresponding control commands, which are then transmitted to the electromagnetic execution unit drive layer. After responding to the commands, the drive layer uses a preset algorithm combining FOC three-loop control and a state observer to control the high-voltage driver to output the corresponding voltage and current to drive the target motor. The three closed loops, from the inside out, are a current loop that uses proportional-integral control to quickly track the target current, and a speed loop and a position loop that construct a sliding mode surface based on the deviation between the actual and target states and design a control law using a reaching law. The control outputs of the three loops are processed by inverse coordinate transformation and space vector pulse width modulation to generate a pulse width modulation waveform, which is then used by the inverter to drive the motor to output the corresponding electromagnetic force. At the same time, the current motor state is obtained through the sensing unit. This method fully considers the electromagnetic characteristics of the motor, changes in vehicle attitude, and interference from external disturbances on the motor output, avoiding their impact on the overall vehicle driving smoothness and performing targeted interference compensation. Through the coordinated operation of multiple loops, more precise control of the suspension action is achieved, ultimately ensuring that the vehicle achieves better driving smoothness and safety. Attached Figure Description

[0017] Figure 1 A flowchart of a multi-loop control method for electromagnetic suspension to coordinate overall vehicle performance, provided by the present invention; Figure 2 This is a schematic diagram of the electromagnetic suspension control architecture in this invention; Figure 3 This is a schematic diagram of the control loop of the electromagnetic execution unit drive layer in this invention; Figure 4 This is a schematic diagram showing the comparison results of thrust fluctuation between the control method in this application and the ordinary control method under no-load operation of the motor. Figure 5 The diagram shows the position error waveforms of the control method in this application and the ordinary control method when the motor is suddenly loaded. Figure 6 This is a schematic diagram showing the ratio of the root mean square values ​​of various suspension performance indicators between the control method in this application and the ordinary control method under different operating conditions. Figure 7 This is a block diagram of the H2H∞ control structure in this invention; Figure 8This invention provides a structural schematic diagram of an electromagnetic suspension multi-loop control system for coordinating overall vehicle performance. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0019] like Figure 1 and Figure 2 As shown in the embodiment of the present invention, a multi-loop control method for electromagnetic suspension with coordinated vehicle performance is proposed, comprising: S101, obtains the current vehicle status information through a preset sensing unit.

[0020] Specifically, the preset sensing unit includes sensing components for acquiring dynamic parameters related to the sprung mass, sensing components for capturing the motion state of the unsprung mass, and sensing components for detecting changes in vehicle body attitude. The signal acquisition frequency and detection accuracy of each sensing unit are matched with the vehicle's dynamic response characteristics to ensure comprehensive coverage of key state detection needs during vehicle operation. Vehicle state information includes the vertical motion parameters of the sprung mass center of gravity, the pitch and roll motion parameters of the vehicle body, the vertical motion parameters of the unsprung mass corresponding to the four wheels, and related parameters such as acceleration, displacement, and rate of change corresponding to the above motion states. These parameters directly reflect the vehicle body attitude and suspension working state under the current road excitation, vehicle speed conditions, and load state, converting the vehicle's physical motion state into an electrical signal form that can be recognized and processed by the suspension controller.

[0021] Its working principle is based on the needs of vehicle dynamic characteristic detection. It uses adaptive components such as acceleration sensors and displacement sensors to sense the mechanical and kinematic changes caused by factors such as road surface undulations, load changes, and steering operations during vehicle operation. Among them, the sensing components for sprung mass focus on detecting the vertical displacement and acceleration of the center of gravity, the sensing components for unsprung mass focus on capturing the displacement and speed of the wheel center of gravity, and the sensing components for vehicle attitude focus on identifying pitch angle, roll angle and their rate of change. The collaborative work of each sensing unit ensures the comprehensiveness and real-time nature of the status information acquisition.

[0022] S102, the vehicle status information is input to the suspension controller. The suspension controller obtains the target control force based on the overall vehicle performance target through a preset control model, and generates the corresponding control command to be input to the electromagnetic actuator drive layer.

[0023] Specifically, the suspension controller, as the core decision-making unit of the electromagnetic suspension multi-loop control, receives vehicle state information collected by preset sensing units. Guided by performance goals such as vehicle ride comfort, handling stability, and safety, it transforms the vehicle's physical motion state into control commands executable by the electromagnetic actuators through the computational logic of a preset control model. This achieves command transmission and control connection between the suspension control layer and the electromagnetic actuator drive layer, ensuring that the generation of control commands always revolves around the vehicle's performance requirements and providing a clear basis for the precise actions of the electromagnetic actuators. The preset control model employs one of the following algorithms: multi-agent consensus collaborative algorithm, H2 / H∞ algorithm, or LQG optimal control algorithm. The principle is to combine the dynamic characteristics of the electromagnetic suspension system with the overall vehicle performance coordination requirements. It can flexibly select the appropriate algorithm based on the priority of vehicle performance goals under different driving conditions, thereby enriching the adaptability scenarios of the control model and ensuring that appropriate control logic is output under complex and varied road conditions, loads, and vehicle speeds, guaranteeing the universality and effectiveness of the control strategy.

[0024] Taking the multi-agent consensus and cooperation algorithm as an example, the preset control model includes: Each electromagnetic actuator in the electromagnetic suspension is treated as a single, independent intelligent agent. The principle is based on the distributed control characteristics of multi-agent systems. By defining each electromagnetic actuator as an independent intelligent agent, each actuator can independently respond to its corresponding vehicle state information, while also possessing the foundation for collaborative work with other intelligent agents. This achieves distributed allocation of control tasks, avoids load concentration on a single control node, and improves the specificity and flexibility of control response.

[0025] A mechanical transmission model is constructed between the various motion states of the sprung mass and the vertical motion of the unsprung mass. Specifically, this involves treating the sprung mass as a rigid body and establishing the correlation between its vertical motion, pitch motion, and roll motion and the vertical motion of the unsprung mass, thus obtaining the transmission laws of spring force and damping force during each motion. By establishing the correspondence and transmission laws between the vertical displacement of the sprung mass's center of mass and the displacements of the front and rear suspension pivots, as well as the influence relationships between pitch motion and roll motion and the displacements of each suspension pivot, a complete mechanical transmission model is constructed. The principle is to combine the core characteristics of vehicle dynamics, ignore unnecessary interference factors, focus on the key motion coupling relationship between the sprung and unsprung masses, and clarify the mechanical transmission path and laws. This allows the model to accurately reflect the mechanical action mechanism during vehicle motion, providing a precise dynamic basis for subsequent control algorithm calculations, ensuring that the control output matches the actual mechanical state of the vehicle, and improving the accuracy of the target control force calculation. The specific calculation process is as follows: Assume the sprung mass is a rigid body; wind resistance is negligible; tire damping is ignored, and the stiffness of the tires and suspension springs is linear; changes in the vehicle's moment of inertia, center of mass, and mass are negligible. (According to the appendix...) Figure 2Based on relevant mechanics knowledge, the dynamic differential equation of the vehicle suspension system can be obtained as follows: The vertical dynamic equation at the center of mass of the spring-loaded mass is: (1) The dynamic equation for the vehicle body pitch motion is: (2) The dynamic equation for the vehicle body roll motion is: (3) The vertical dynamic equations for the four unsprung masses are as follows: (4) In equations (1) to (4), For the sprung mass; The vertical acceleration of the center of mass of the sprung mass; , These are spring stiffness and damping, respectively; For the first Displacement of the center of mass of each wheel; For the sprung mass in the first Displacement at each suspension pivot point; This corresponds to the active electromagnetic force output by the electromagnetic actuator; The moment of inertia of the sprung mass during pitching; Angular acceleration is the pitch angle; The moment of inertia of the sprung mass during tilting; The roll angle is the angular acceleration. The mass of the wheel; Input the road surface for the wheels; For index ( =1, 2, 3, 4,).

[0026] Due to the vehicle's pitch angle and vehicle body roll angle The values ​​are all very small, at this time and Approximately equal to and Then the displacements at the four suspension pivots can be expressed as: (5) in, and These are the distances from the center of mass to the front and rear axes, respectively. and These are the front and rear wheel tracks, respectively.

[0027] A multi-agent consensus control protocol is established based on a mechanics transfer model. The protocol includes position parameters, velocity parameters, gain coefficients, and weight coefficients in the multi-agent communication graph for each agent. Vehicle state information is substituted into the control protocol to calculate the consistent active control force for each agent. The principle is based on the precise mechanical relationships of the mechanics transfer model, incorporating multi-agent collaborative control logic. The state parameters in the protocol reflect the actual motion state of the agents, the gain coefficients adjust the control intensity, and the communication weight coefficients coordinate the work of each agent. After incorporating vehicle state information, the protocol calculations achieve coordinated consistency in the motion states of each agent. Its beneficial effect is ensuring that the control outputs of multiple electromagnetic actuators are coordinated, avoiding instability in vehicle posture caused by imbalance in the action of a single actuator, and improving the overall coordination of vehicle attitude control.

[0028] An active acceleration damping control strategy is introduced, and an inertial capacity coefficient is set. Based on the rate of change of vertical vibration acceleration of the vehicle body associated with each agent in the vehicle state information, the active acceleration damping control force corresponding to each agent is calculated in combination with the inertial capacity coefficient. The principle is to address the performance shortcomings of multi-agent consensus control protocols in controlling vertical vibration acceleration of the vehicle body by supplementing the active acceleration damping control strategy. By adapting the inertial capacity coefficient to the vehicle's dynamic characteristics, and using the rate of change of vertical vibration acceleration of the vehicle body to specifically calculate the control force, precise suppression of vertical vibration is achieved. Its beneficial effects are to compensate for the deficiencies of a single control protocol, enhance the effect of suppressing vertical vibration of the vehicle body, and further improve the ride comfort of the vehicle.

[0029] The consistent active control force and the acceleration damping active control force are weighted and fused according to a preset adjustment coefficient to obtain the final target control force for each agent. The principle is to set a preset adjustment coefficient based on the priority of the overall vehicle performance target, and then rationally allocate the weights of the two control forces through this coefficient. This ensures that the final target control force simultaneously considers the needs of multi-agent collaborative stability and vertical vibration suppression. Its beneficial effect is that the target control force possesses multi-dimensional performance optimization characteristics, ensuring both the collaborative stability of the vehicle's attitude and effectively suppressing vertical vibration, thus comprehensively improving the vehicle's ride comfort and handling stability. The specific calculation process is as follows: The suspension controller employs a vehicle control algorithm that combines a multi-agent consensus and cooperative algorithm with acceleration and damping control. It treats the fully active suspension vehicle as a multi-agent system and the electromagnetic actuators of the suspension system as single agents. For a single agent, we have: (6) In the formula, For damping force; This is the spring force.

[0030] The specific control protocol for the multi-agent consensus algorithm is as follows: (7) In the formula, , This is the gain coefficient; For the first Location; For the first Location; For the first Speed; For the first Speed; These are the weight coefficients in the multi-agent communication graph.

[0031] To address the issue of poor performance in controlling the vertical vibration acceleration of the vehicle body in the consistency control algorithm, it was decided to introduce active acceleration damping control into the consistency control to take into account the vertical vibration acceleration control of the vehicle body. A hybrid control law was designed as follows: (8) (9) In the formula, For the ultimate goal of control; For consistent proactive control; For acceleration damping active control force; The inertia coefficient; The control force adjustment coefficient in the hybrid control law, 0 < 1.

[0032] S103, in response to the control command, the electromagnetic actuator drive layer controls the high-voltage driver to output the corresponding voltage and current to drive the target motor through the FOC three-closed-loop control combined with the preset algorithm of the state observer; at the same time, the current state information of the motor is obtained through the corresponding sensing unit.

[0033] Specifically, the control logic of the electromagnetic actuator drive layer is dominated by the high-voltage driver. Through a pre-defined FOC three-loop control algorithm combined with a state observer, it converts control commands into motor drive signals, ultimately outputting the corresponding voltage and current to drive the target motor. Simultaneously, the motor sensing unit configured in the electromagnetic actuator drive layer synchronously collects the current motor state information, providing data support for feedback adjustment of the closed-loop control. The principle is that the electromagnetic actuator drive layer, through the coordinated work of the high-voltage driver, electromagnetic actuator, and corresponding sensing units, constructs a complete execution chain from command reception and signal processing to motor drive. Real-time acquisition of motor state information reflects the current operating state of the motor, ensuring that the control algorithm can dynamically adjust the output according to the actual operating conditions, forming closed-loop control to guarantee control accuracy. This achieves precise execution and dynamic correction of control commands, preventing the motor operating state from deviating from the target value, and providing execution-level assurance for the stable performance of the entire vehicle. The target motor is a permanent magnet linear synchronous motor (PMLSM), which, compared to traditional servo linear motors, eliminates problems such as backlash, dead zone, and inflexibility caused by mechanical transmission links. It has linear motion characteristics with high speed, high precision, high rigidity, and high dynamic response, and can adapt to the high-performance requirements of electromagnetic suspension for actuators. This avoids performance loss and control deviation caused by mechanical transmission links, and improves the motion performance and control accuracy of electromagnetic actuators.

[0034] In addition, such as Figure 3 As shown, the core architecture of the preset algorithm is a three-loop control structure. This structure consists of a current loop, a speed loop, and a position loop, arranged sequentially from the inside out. Each loop level has a clear division of labor and works in concert. Its principle is based on the priority and response characteristics of the control target. The inner loop focuses on rapid response and stability of basic control quantities, while the outer loop focuses on precise tracking and anti-interference capabilities. This hierarchical control achieves multi-dimensional optimization of control performance. Compared to single-loop control, the three-loop structure can balance response speed, control accuracy, and robustness, avoiding the performance limitations of a single control dimension and improving the overall control quality of the electromagnetic actuator.

[0035] The current loop employs proportional-integral (PI) control to track the target current in real time and rapidly output the current control quantity. The principle behind this is that PI control is simple in structure, has a fast response, and no steady-state error. It can quickly eliminate current deviations, meet the motor's requirement for rapid current establishment, and adapt to the high dynamic response requirements of the electromagnetic actuator. It ensures that the current control quantity can quickly follow the target current, providing a stable current basis for the rapid generation of the motor's electromagnetic force, while avoiding the impact of current fluctuations on the motor's output performance.

[0036] The speed and position loops employ sliding mode control. The algorithm's implementation process is as follows: First, a sliding surface is constructed based on the deviation between the motor's actual motion state and the target motion state, clarifying the system's desired motion trajectory. Then, a corresponding control law is designed using a reaching law to rapidly approach and maintain the system state on the sliding surface, thereby obtaining the control outputs of the speed and position loops respectively. The principle is that sliding mode control, as a highly robust nonlinear control method, can effectively overcome the influence of actuator nonlinearity, model uncertainty, and external disturbances. It adapts to the robustness requirements of the speed and position loops, resisting external disturbances such as load changes and thrust fluctuations; thus improving the anti-interference capability of speed and position control, ensuring that the motor's speed and position closely follow the target command, avoiding control deviations caused by external disturbances, and guaranteeing the motion accuracy of the electromagnetic actuator.

[0037] After obtaining the control outputs of each closed loop, the control flow sequentially performs coordinate inverse transformation and space vector pulse width modulation (SVM) processing according to preset logic: coordinate inverse transformation converts the control quantity in the rotating coordinate system into the control quantity in the stationary coordinate system, achieving signal adaptation between different coordinate systems; space vector pulse width modulation (SVM) processing generates a corresponding pulse width modulation waveform based on the converted control quantity, which accurately reflects the voltage requirements of the control command; subsequently, the inverter controls this pulse width modulation waveform, converting it into the voltage signal required for motor drive, driving the target motor to output an electromagnetic force corresponding to the target control force. The principle is that coordinate inverse transformation solves the adaptation problem of control quantities in different coordinate systems, space vector pulse width modulation ensures the accurate generation of voltage signals, and the inverter realizes the conversion of electrical signals into motor driving force. These three form a coherent signal processing and drive link; achieving accurate conversion of control outputs into motor electromagnetic force, ensuring that the electromagnetic force output by the motor is consistent with the target control force set by the suspension control layer.

[0038] Based on the content in S103, the calculation process is as follows: Considering the impact of electromagnetic suspension thrust fluctuation on the whole vehicle, a mathematical model of the electromagnetic suspension actuator (permanent magnet synchronous linear motor) is established to increase the coordination control accuracy. The following assumptions are made for the establishment of its mathematical model: (1) The influence of magnetic circuit saturation in the motor is ignored, and the hysteresis phenomenon and eddy current loss of the stator core and mover core in the motor are not considered; (2) The three-phase windings of the motor are ideally symmetrically distributed, and the angle between each axis is 120°; (3) The stator electromotive force of the motor changes according to a sinusoidal law, and the influence of high-order harmonics in the magnetic field of the motor is not considered. The vector control of the FOC three-loop control is carried out in the dq rotating coordinate system. The coordinate system needs to be transformed. The transformation matrices of the Clarke transformation and the inverse Clarke transformation with unchanged amplitude before and after the vector transformation are as follows: (10) The transformation matrices of the Park transform and the Park inverse ring are as follows: (11) In the formula, The electric angle is the motor angle.

[0039] In a two-phase rotating coordinate system, the equation of the permanent magnet synchronous linear motor dq in the synchronous rotating coordinate system can be expressed as follows: The stator voltage equation is: (12) The stator flux linkage equation is: (13) In equations (12) and (13), , and , These are the stator voltage and flux linkage vectors along the d and q axes, respectively; , For the stator currents along the d and q axes; This refers to the stator resistance of the motor. The electric angular velocity of synchronous rotation in the magnetic field. ; This represents the equivalent linear velocity of the linear motor. ; The moving speed of the linear motor's rotor. , This represents the displacement of the moving part of the linear motor. , Inductance components along the d and q axes, respectively; For permanent magnet flux linkage; It is a differential operator.

[0040] Therefore, the expression for the electromagnetic thrust of the linear motor can be obtained as follows: (14) use With the PMSLM control strategy where =0, the electromagnetic thrust Fe can be expressed as: (15) In the formula, Electromagnetic thrust; It is the extreme logarithm; This represents the polar distance.

[0041] Its corresponding equation of motion is: (16) In the formula, Mass of the mover; For total disturbance; is the coefficient of friction.

[0042] In the three-loop vector control of FOC, the velocity loop and position loop adopt sliding mode controllers, and the sliding mode function is defined as follows: (17) in For integral sliding mode gain, satisfying >0, λ determines the rate of asymptotic convergence of the system after reaching the sliding surface. The larger the value, the faster the convergence speed. Taking the position loop as an example, the state variables of a permanent magnet synchronous linear motor are defined as follows: (18) In the formula, The target speed value; For speed error; This is the integral of the speed error.

[0043] The reaching law of the sliding mode controller is: (19) For signal symbol functions; for All are constants greater than zero. Based on this reaching law, the sliding mode control law for the above-mentioned nonlinear motor system is designed as follows: (20) in: (twenty one) (twenty two) In the formula, The total disturbance. Based on the output of the sliding mode controller. for: (twenty three) Furthermore, in the process of obtaining the speed loop control output and position loop control output respectively, an Extended State Observer (ESO) is introduced to achieve accurate compensation for system disturbances. Specifically, the application logic of the Extended State Observer is to treat the external disturbances and internal uncertainties faced by the electromagnetic actuator during operation as extended state terms. External disturbances include disturbances caused by load changes during vehicle operation and disturbances transmitted from the road surface to the motor. Internal uncertainties include motor parameter fluctuations, friction of the linear guide rail, and thrust fluctuations caused by uneven magnetic field distribution. All of these factors will interfere with the control accuracy of the speed loop and position loop. Including them in the extended state terms can achieve comprehensive coverage of system disturbances. The design of the observer parameters needs to be based on the dynamic characteristics of the permanent magnet synchronous linear motor, the working conditions of the electromagnetic suspension, and the control accuracy requirements. By reasonably setting the parameters, it is ensured that the observer can make real-time and accurate estimates of the actual operating state of the motor (including speed, position, etc.) and the extended state terms, avoiding estimation lag or deviation caused by parameter mismatch. The estimated total disturbance obtained through this observation process needs to be further transformed into a compensation quantity of the same dimension as the given control quantities of the velocity and position loops. This transformation process must adhere to the physical characteristics and signal adaptation requirements of the control quantities to ensure that the compensation quantity can be directly superimposed on the given control quantities. Subsequently, the aforementioned compensation quantity is fed forward to the given control quantities of the velocity and position loops, respectively, to complete the active compensation for the disturbance. The feedforward compensation method can offset the effect of the disturbance before it actually affects the system control output, rather than providing post-event correction. The principle is that while sliding mode control has strong robustness, it fails to fully consider the combined influence of multiple disturbance factors in the system. The extended state observer, through real-time estimation and compensation of disturbances, can compensate for the shortcomings of sliding mode control in disturbance suppression, ensuring that the control processes of the velocity and position loops are not significantly affected by external disturbances and internal uncertainties. The specific calculation process is as follows: In the ESO design based on a permanent magnet synchronous linear motor, taking the position loop as an example, the unknown disturbance terms in the system state equation are expanded into state variables. The system state equations can be obtained as follows: (twenty four) In the formula, This represents the position of the mover in a permanent magnet synchronous linear motor. This represents an unknown disturbance term in the system. ; Let be the derivative of the extended state term. The designed extended state function is as follows: (25) In the formula, This refers to the positional error; To estimate the location; This is the estimated total system disturbance; , All are observer parameters and are all greater than zero; It is a nonlinear factor; It is the filter factor; ;like Figure 3 As shown, the extended state term is converted into a current form and fed forward to the q-axis current setpoint, and real-time compensation is performed according to the disturbance change, resulting in: (26) In the formula, This is the updated q-axis current setpoint; Given the q-axis value before updating; ; .

[0044] Experiments were conducted based on the technical solution in Example 1 and compared with common methods in the prior art, resulting in... Figure 4 , Figure 5 and Figure 6 The comparison chart; among them, Figure 4 This paper compares the thrust fluctuation of the control method of this application with that of a conventional control method under no-load operation of the motor. Curve a represents the control method of this application, and curve b represents the conventional method. According to the figure, the control method of this application can effectively suppress thrust fluctuation. (See attached diagram) Figure 5 The figure shows the position error waveforms of the control method of this application and the ordinary control method when the motor is suddenly loaded. Curve c represents the control method of this application, and curve d represents the ordinary method. According to the figure, the control method of this application can effectively improve the system response and anti-interference level compared with the ordinary method. Figure 6 As shown, the ratio of the root mean square values ​​of various suspension performance indicators of the control method of this application and the ordinary control method under different working conditions is given. The performance indicators are vertical acceleration, pitch acceleration, and roll acceleration. According to the figure, the root mean square values ​​of vertical, pitch, and roll acceleration of the control method of this application are reduced to a certain extent compared with those of the ordinary control method, which significantly improves the ride comfort and handling stability of the vehicle.

[0045] Example 2: like Figure 7 As shown, based on the technical solution in Embodiment 1, when the preset control model adopts the H2H∞ algorithm, let (27) (28) (29) (30) (31) The system state variables are selected as follows: (32) The sprung mass acceleration, roll angle acceleration, pitch angle acceleration, and suspension dynamic travel are selected as the measurement outputs, namely: (33) The sprung mass acceleration, roll angle acceleration, pitch angle acceleration, suspension dynamic travel, tire dynamic deformation, and active electromagnetic actuation force are selected as the H2 performance indicators, namely: (33) The following performance indicators were selected: suspension dynamic travel, tire dynamic deformation, and active electromagnetic actuation force H∞. (34) It should be noted that, in combination Figure 7 The formulas in Example 2 are defined with the following parameters: G is the electromagnetic suspension system; K is the controller; This is the active control force input for the suspension, calculated by the controller; Input for road surface; and The output is the performance index for H∞ and H2 norm constraints; y is the measurement output, and n is the noise input mixed in during the measurement. Weight the H2 / H∞ performance indices as a matrix; design the feedback control law. ,make arrive Closed-loop transfer function H∞ norm Less than a given constant Under the premise of arrive closed-loop function H2 norm To reach the minimum.

[0046] Example 3: Based on the same inventive concept, such as Figure 8 As shown, the present invention provides an electromagnetic suspension multi-loop control system for coordinating overall vehicle performance, comprising: Data acquisition module 201 is used to acquire current vehicle status information through preset sensing units; The control force calculation module 202 is used to input vehicle status information to the suspension controller. The suspension controller obtains the target control force based on the overall vehicle performance target through a preset control model and generates corresponding control commands to be input to the electromagnetic execution unit drive layer. The execution module 203 is used to control the high-voltage driver through the electromagnetic execution unit drive layer after receiving the control command, and output the corresponding voltage and current to drive the target motor by combining the FOC three-closed-loop control with the preset algorithm of the state observer; at the same time, it obtains the current state information of the motor through the corresponding sensing unit. The preset algorithm includes a three-loop control structure consisting of a current loop, a speed loop, and a position loop arranged sequentially from the inside out. The current loop employs proportional-integral control to track the target current and quickly output the current control quantity. The speed and position loops use sliding mode control, constructing a sliding surface based on the deviation between the actual and target states. A control law is designed using a reaching law to obtain the speed loop control output and the position loop control output, respectively. Based on the speed loop control output and the position loop control output, combined with the current loop control output, the system sequentially undergoes inverse coordinate transformation and space vector pulse width modulation (PWM) processing to generate corresponding PWM waveforms. The inverter controls these waveforms, driving the target motor to output an electromagnetic force corresponding to the target control force.

[0047] Example 4: Based on the same inventive concept, the present invention provides a vehicle, including a vehicle body, a suspension and a controller mounted on the vehicle body, the controller including a memory, a processor and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement an electromagnetic suspension multi-loop control method for overall vehicle performance coordination.

[0048] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A multi-loop control method for electromagnetic suspension to coordinate overall vehicle performance, characterized in that, include: The current vehicle status information is obtained through a preset sensing unit; The vehicle status information is input to the suspension controller, which derives the target control force based on the overall vehicle performance target through a preset control model and generates corresponding control commands, which are then input to the electromagnetic actuator drive layer. In response to the control command, the electromagnetic actuator drive layer controls the high-voltage driver to output the corresponding voltage and current to drive the target motor through the FOC three-closed-loop control combined with the preset algorithm of the state observer; at the same time, the current state information of the motor is obtained through the corresponding sensing unit. The preset algorithm includes a three-loop control structure consisting of a current loop, a speed loop, and a position loop arranged sequentially from the inside out. The current loop employs proportional-integral control to track the target current and quickly output the current control quantity. The speed loop and position loop employ sliding mode control, constructing a sliding surface based on the deviation between the actual state and the target state. A control law is designed using a reaching law to obtain the speed loop control output and the position loop control output, respectively. Based on the speed loop control output and the position loop control output, combined with the current loop control output, the data undergoes inverse coordinate transformation and space vector pulse width modulation processing to generate a corresponding pulse width modulation waveform. The inverter controls this waveform to drive the target motor to output an electromagnetic force corresponding to the target control force.

2. The electromagnetic suspension multi-loop control method for overall vehicle performance coordination according to claim 1, characterized in that, The preset control model adopts one of the following: multi-agent consensus cooperative algorithm, H2 / H∞ algorithm, or LQG optimal control algorithm.

3. The electromagnetic suspension multi-loop control method for overall vehicle performance coordination according to claim 1, characterized in that, The preset control model includes: Each electromagnetic actuator in the electromagnetic suspension is treated as a single, independent intelligent agent. Construct a mechanical transmission model between the various motion states of the sprung mass and the vertical motion of the unsprung mass; Based on the aforementioned mechanical transmission model, a multi-agent consensus control protocol is set up. The protocol includes the position parameters, velocity parameters, gain coefficients, and weight coefficients in the multi-agent communication graph corresponding to each agent. The vehicle state information is substituted into the control protocol to calculate the consensus active control force of each agent and output the target control force.

4. The electromagnetic suspension multi-loop control method for overall vehicle performance coordination according to claim 3, characterized in that, The expression for the target control force is: in, Electromagnetic thrust; It is the extreme logarithm; The polar distance; For permanent magnet flux linkage; This represents the q-axis stator current.

5. The electromagnetic suspension multi-loop control method for overall vehicle performance coordination according to claim 3, characterized in that, The steps for constructing the mechanical transmission model between the various motion states of the sprung mass and the vertical motion of the unsprung mass specifically include: Treating the sprung mass of the vehicle as a rigid body, we construct the correlation between the vertical motion, pitching motion, and roll motion of the sprung mass and the vertical motion of the unsprung mass, and obtain the transmission law of spring force and damping force during each motion process. By establishing the correspondence between the vertical displacement of the sprung mass center of mass and the displacement of the front and rear suspension pivots, the transmission law, and the influence relationship between pitch and roll motions and the displacement of each suspension pivot, a mechanical transmission model between the various motion states of the sprung mass and the vertical motion of the unsprung mass is constructed.

6. The electromagnetic suspension multi-loop control method for overall vehicle performance coordination according to claim 3, characterized in that, The output target control force also includes: Active acceleration damping control is introduced, and an inertia capacity coefficient is set. Based on the rate of change of vertical vibration acceleration of the vehicle body associated with each intelligent agent in the vehicle state information, the active acceleration damping control force corresponding to each intelligent agent is calculated in combination with the inertia capacity coefficient. The consistency active control force and the acceleration damping active control force are weighted and fused according to a preset adjustment coefficient to obtain the final target control force for each agent.

7. The electromagnetic suspension multi-loop control method for overall vehicle performance coordination according to claim 1, characterized in that, In addition to obtaining the speed loop control output and the position loop control output respectively, it also includes: An extended state observer is used to treat external disturbances and internal uncertainties as extended state terms. By designing the observer parameters, the actual state and the extended state terms are estimated in real time to obtain the estimated value of the total disturbance and convert it into a compensation amount. The compensation amount is then fed forward to the given control values ​​of the velocity loop and the position loop to complete the compensation.

8. The electromagnetic suspension multi-loop control method for overall vehicle performance coordination according to claim 1, characterized in that, The target motor is a permanent magnet synchronous linear motor.

9. A multi-loop electromagnetic suspension control system for coordinating overall vehicle performance, characterized in that, include: The data acquisition module is used to acquire current vehicle status information through preset sensing units; The control force calculation module is used to input the vehicle state information to the suspension controller. The suspension controller derives the target control force based on the overall vehicle performance target through a preset control model and generates corresponding control commands, which are then input to the electromagnetic actuator drive layer. The execution module, upon receiving the control command, controls the high-voltage driver through the electromagnetic execution unit drive layer to output the corresponding voltage and current to drive the target motor via the FOC three-closed-loop control combined with the preset algorithm of the state observer; simultaneously, it acquires the current state information of the motor through the corresponding sensing unit. The preset algorithm includes a three-loop control structure consisting of a current loop, a speed loop, and a position loop arranged sequentially from the inside out. The current loop employs proportional-integral control to track the target current and quickly output the current control quantity. The speed loop and position loop employ sliding mode control, constructing a sliding surface based on the deviation between the actual state and the target state. A control law is designed using a reaching law to obtain the speed loop control output and the position loop control output, respectively. Based on the speed loop control output and the position loop control output, combined with the current loop control output, the data undergoes inverse coordinate transformation and space vector pulse width modulation processing to generate a corresponding pulse width modulation waveform. The inverter controls this waveform to drive the target motor to output an electromagnetic force corresponding to the target control force.

10. A vehicle, characterized in that, The system includes a vehicle body, a suspension mounted on the vehicle body, and a controller. The controller includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the electromagnetic suspension multi-loop control method for overall vehicle performance coordination as described in any one of claims 1 to 8.

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