Suspension control method and device based on mode decoupling, vehicle and medium

Abstract

The embodiment of the invention relates to the technical field of suspension control, and discloses a suspension control method and device based on mode decoupling, a vehicle and a medium, and the method comprises the steps that according to a suspension system signal of the vehicle and a vehicle state signal, the target pressure difference between a shock absorber upper cavity and a shock absorber lower cavity is determined; inputting the pressure data of the upper and lower cavities of the shock absorber and the target pressure difference into a flow model; determining the target flow of the suspension system according to the output data of the flow model; based on the first target flow distributed to the hydraulic pump and the second target flow distributed to the hydraulic pipeline valve in the target flow, the target rotating speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valve are obtained through decoupling solving; and the opening degree of a hydraulic pipeline valve is controlled to be adjusted to the target opening degree, and the rotating speed of a hydraulic pump is controlled to be adjusted to the target rotating speed. According to the technical scheme, the pressure control precision of the suspension system can be improved.

Description

Technical Field

[0001] This invention relates to the field of suspension control technology, specifically to a suspension control method, device, vehicle, and medium based on mode decoupling. Background Technology

[0002] Currently, electro-hydraulic fully active suspensions equipped with CDC (Continuous Damping Control) technology can significantly improve ride comfort and handling stability under different road conditions and driving scenarios by precisely controlling the damping force of the shock absorbers. However, when controlling the pressure difference between the upper and lower chambers of the shock absorber, there is a coupling between the hydraulic pump speed's control of flow rate and the CDC valve opening adjustment. That is, when adjusting the hydraulic pump speed to change the flow rate to meet pressure requirements, changes in the CDC valve opening will interfere with the pressure distribution in the hydraulic circuit; conversely, when adjusting the CDC valve opening to control the damping force, changes in the CDC valve opening will affect the load and flow output of the hydraulic pump. Therefore, this mutual interference makes it difficult to accurately achieve the target pressure difference between the upper and lower chambers of the shock absorber. Summary of the Invention

[0003] In view of the above problems, embodiments of the present invention provide a suspension control method, device, vehicle and medium based on mode decoupling, which is used to solve the technical problem in the prior art that there is coupling interference between the control of flow rate by hydraulic pump speed and the adjustment of CDC valve opening, making it difficult for the upper and lower chambers of the shock absorber to accurately achieve the target pressure difference.

[0004] According to one aspect of the present invention, a suspension control method based on mode decoupling is provided, the method comprising:

[0005] Based on the vehicle's suspension system signals and vehicle status signals, determine the target pressure difference between the upper and lower chambers of the shock absorber; Input the pressure data of the upper and lower chambers of the shock absorber and the target pressure difference into the flow model; The target flow rate of the suspension system is determined based on the output data of the flow model. Based on the first target flow rate allocated to the hydraulic pump and the second target flow rate allocated to the hydraulic pipeline valves, the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valves are decoupled and obtained. The opening degree of the hydraulic pipeline valves is adjusted to the target opening degree, and the speed of the hydraulic pump is adjusted to the target speed.

[0006] In one alternative approach, the step of decoupling the target speed of the hydraulic pump and the target opening of the hydraulic valve based on the first target flow allocated to the hydraulic pump and the second target flow allocated to the hydraulic line valve in the target flow includes: Based on the load pressure of the hydraulic pump and the target flow rate, the first target flow rate of the hydraulic pump is calculated in a decoupled manner, and based on the target flow rate and the target pressure difference, the second target flow rate of the hydraulic pipeline valve is calculated in a decoupled manner. Based on the load pressure of the hydraulic pump, the target speed of the hydraulic pump is determined according to the first target flow rate; Based on the vehicle status signal and the second target flow rate, the target opening degree of the hydraulic pipeline valve is determined.

[0007] In one alternative approach, the step of determining the target rotational speed of the hydraulic pump based on the first target flow rate, in conjunction with the load pressure of the hydraulic pump, includes: Based on the hydraulic pump's load pressure, volumetric efficiency, and first target flow rate, the inverse model of the hydraulic pump flow rate model is determined, and the target speed of the hydraulic pump is obtained.

[0008] In one alternative approach, the step of determining the target opening degree of the hydraulic line valve based on the second target flow rate in conjunction with the vehicle status signal includes: The correction coefficients are obtained by processing the suspension system signals and vehicle status signals using a fuzzy control algorithm. The inverse model of the valve flow model is determined based on the target pressure difference, the second target flow rate, and the correction coefficient, and the target opening degree of the hydraulic pipeline valve is obtained.

[0009] In one optional embodiment, the suspension system signals include at least one of vehicle roll attitude, vehicle pitch attitude, vehicle braking state, vehicle acceleration state, vehicle cornering state, and suspension travel vector; the vehicle state signals include at least one of vehicle speed, road surface roughness level, road anticipation state, driving events, comfort parameters, and handling parameters; the step of determining the target pressure difference between the upper and lower chambers of the shock absorber based on the vehicle's suspension system signals and vehicle state signals includes: The vertical vibration damping force, road impact compensation force, roll damping force, and pitch damping force are calculated based on the parameters in the suspension system signal and the vehicle status signal, respectively. The target active force is obtained by superimposing the components of vertical vibration suppression force, road impact compensation force, roll suppression force, and pitch suppression force. The target active force is input into the shock absorber piston model, and the target pressure difference between the upper chamber and the lower chamber of the shock absorber is determined by the model output. The shock absorber piston model is constructed based on the principle of piston force balance.

[0010] In one alternative approach, the flow model includes a shock absorber hydraulic cylinder model, a valve flow model, and a damping orifice flow model.

[0011] In one alternative approach, after the steps of adjusting the opening of the control hydraulic line valve to the target opening and adjusting the speed of the control hydraulic pump to the target speed, the method further includes: Collect pressure data from the upper and lower chambers of the shock absorber to determine the actual pressure difference; The deviation between the actual pressure difference and the target pressure difference is input into the flow model and the inverse model of the flow model, and the opening adjustment value and the speed adjustment value are determined according to the model output. The opening degree of the hydraulic pipeline valve is adjusted according to the opening degree adjustment value, and the speed of the hydraulic pump is adjusted according to the speed adjustment value.

[0012] According to another aspect of the present invention, a suspension control device based on mode decoupling is provided, the device comprising: The differential pressure calculation module is used to determine the target pressure difference between the upper and lower chambers of the shock absorber based on the vehicle's suspension system signals and vehicle status signals. The flow calculation module is used to input the pressure data of the upper and lower chambers of the shock absorber and the target pressure difference into the flow model, and determine the target flow of the suspension system based on the model output. The decoupling algorithm module is used to decouple the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valve based on the first target flow allocated to the hydraulic pump and the second target flow allocated to the hydraulic pipeline valve in the target flow. The adjustment module is used to control the opening degree of the hydraulic pipeline valves to the target opening degree, and to control the speed of the hydraulic pump to the target speed.

[0013] According to another aspect of the present invention, a vehicle is provided, including: a suspension system, a processor, a memory, a communication interface, and a communication bus, wherein the suspension system, the processor, the memory, and the communication interface communicate with each other through the communication bus; The suspension system includes shock absorbers and a hydraulic control assembly. The shock absorber has independent upper and lower chambers. The hydraulic control assembly includes a hydraulic pump, hydraulic line valves, and hydraulic lines. The hydraulic pump is connected to the upper and lower chambers of the shock absorber through the hydraulic lines. The hydraulic line valves are located in the hydraulic lines to dynamically adjust the damping force of the shock absorber. The memory is used to store at least one executable instruction that causes the processor to perform the operation of the suspension control method based on mode decoupling as described above.

[0014] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing at least one executable instruction, which, when executed on a mode-decoupling-based suspension control device / vehicle, causes the mode-decoupling-based suspension control device / vehicle to perform the operation of the mode-decoupling-based suspension control method as described in any of the preceding embodiments.

[0015] This invention, based on suspension system signals reflecting vehicle dynamics and vehicle status signals encompassing driving conditions and the external environment, comprehensively and accurately captures real-time driving conditions and complex road disturbances. Through multi-dimensional signal fusion, it determines the target pressure difference between the upper and lower chambers of the shock absorber, ensuring real-time adaptation between pressure difference requirements and vehicle attitude adjustment and road impact compensation. This lays a target benchmark that aligns with actual operating conditions for subsequent precise control, avoiding adjustment deviations caused by the disconnect between traditional fixed target pressure differences and dynamic conditions. Furthermore, the real-time pressure data from the upper and lower chambers of the shock absorber, along with the target pressure difference, are input into a flow model integrating the full-domain characteristics of the shock absorber's hydraulic cylinders, valves, and hydraulic pumps. This model fully correlates the inherent logic of dynamic pressure changes and system flow requirements, accurately outputting the total target flow of the suspension system that adapts to the current pressure state and target requirements. This solves the problem of blind adjustment caused by the weak correlation between pressure and flow in traditional control. The problem is that, more importantly, by allocating the total target flow rate to the first target flow rate corresponding to the hydraulic pump and the second target flow rate corresponding to the hydraulic pipeline valve, a decoupling algorithm is used to independently solve the target speed and target opening of both. This completely breaks the coupling interference between the hydraulic pump speed control and the valve opening adjustment, eliminates the flow output deviation and pressure fluctuation caused by the mutual influence between the two in traditional control, and realizes independent and accurate calculation of the control channels of the pump and valve. Finally, by synchronously executing the precise control of the hydraulic pump speed and valve opening, it is ensured that the two work together and cooperate with each other to quickly respond to the target pressure difference demand, effectively offset the pressure deviation caused by coupling interference, avoid the system pressure mismatch caused by the adjustment of a single component, and finally achieve accurate and rapid convergence of the pressure difference between the upper and lower chambers of the shock absorber, significantly improving the pressure control accuracy of the suspension system, and solving the core technical problem of the difficulty in accurately achieving the pressure target caused by coupling interference in the existing technology.

[0016] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0017] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1A flowchart illustrating an embodiment of the suspension control method based on mode decoupling provided by the present invention is shown. Figure 2 A flowchart illustrating a third embodiment of the suspension control method based on mode decoupling provided by the present invention is shown. Figure 3 The diagram shows an example flow chart of the dual closed-loop decoupling control architecture in Embodiment 4 of the suspension control method based on mode decoupling provided by the present invention. Figure 4 The diagram shows the topology of the suspension control system based on mode decoupling in Embodiment 4 of the suspension control method based on mode decoupling provided by the present invention. Figure 5 The control flow timing diagram of Embodiment 4 of the suspension control method based on mode decoupling provided by the present invention is shown; Figure 6 A schematic diagram of the suspension control device based on mode decoupling provided by the present invention is shown; Figure 7 A structural schematic diagram of an embodiment of the vehicle provided by the present invention is shown. Detailed Implementation

[0018] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0019] Figure 1 A flowchart of an embodiment of the suspension control method based on mode decoupling of the present invention is shown, which is executed by the vehicle. Figure 1 As shown, the method includes the following steps: Step S10: Determine the target pressure difference between the upper and lower chambers of the shock absorber based on the vehicle's suspension system signals and vehicle status signals.

[0020] In this embodiment, the suspension system signals are signals directly collected and processed by sensors mounted on the vehicle suspension itself, used to reflect the real-time operating status of the suspension, including at least one of the following: vehicle roll attitude, vehicle pitch attitude, vehicle braking status, vehicle acceleration status, vehicle cornering status, and suspension travel vector. Vehicle status signals are signals from other vehicle systems or user-defined signals, used to reflect the overall vehicle operating conditions and user experience requirements, including at least one of the following: vehicle speed, road surface roughness level, road anticipation status, driving events, comfort parameters, and handling parameters. The upper chamber of the shock absorber is the chamber above the piston inside the shock absorber, and the lower chamber is the chamber below the piston inside the shock absorber. The target pressure difference is the pressure difference that needs to be achieved between the upper and lower chambers of the shock absorber to meet the current operating conditions and user needs, directly determining the magnitude of the suspension damping force.

[0021] As an alternative implementation, the suspension system signals and vehicle status signals are standardized to eliminate the dimensional differences between different signals. Then, they are input into a pre-trained full active force model, which is generated based on a large amount of working condition data and can output a target active force that matches the current input. The target active force is then input into the shock absorber piston model, and the target pressure difference between the upper and lower chambers of the shock absorber is calculated by combining parameters such as the shock absorber piston area and stroke.

[0022] As another optional implementation, the suspension system signals and vehicle status signals are weighted and assigned. The weight of the suspension system signals is set according to the signal response priority, and the weight of the vehicle status signals is set according to the user's mode preference. Then, the comprehensive operating condition parameters are obtained by weighted summation. The corresponding target pressure difference is directly obtained by consulting the preset operating condition parameter and target pressure difference mapping table. The mapping table is pre-calibrated through real vehicle tests and simulation analysis.

[0023] Step S20: Input the pressure data of the upper and lower chambers of the shock absorber and the target pressure difference into the flow model.

[0024] Step S30: Determine the target flow rate of the suspension system based on the output data of the flow rate model.

[0025] In this embodiment, the pressure data of the upper and lower chambers of the shock absorber are the current chamber pressure values ​​collected in real time by pressure sensors installed in the upper and lower chambers of the shock absorber. The flow model is a multi-parameter calculation model integrating the shock absorber hydraulic cylinder model, valve flow model, and hydraulic pump flow model, which can reflect the dynamic correlation between pressure and flow. The target flow rate is the total flow rate value required by the suspension system to make the pressure in the upper and lower chambers of the shock absorber reach the target pressure difference.

[0026] As an optional implementation, the pressure deviation value is obtained by calculating the difference between the real-time pressure data of the upper and lower chambers of the shock absorber and the target pressure difference. The pressure deviation value is then input into the flow model. Based on the preset pressure-flow conversion coefficient and system dynamic characteristic parameters, the model outputs the target flow required by the suspension system through linear calculation, and at the same time outputs flow distribution suggestion parameters for use in subsequent steps.

[0027] As another optional implementation method, the pressure data of the upper and lower chambers of the shock absorber are first input into the shock absorber hydraulic cylinder model in the flow model to calculate the basic value of the current hydraulic cylinder flow demand. Then, the target pressure difference is combined with the valve flow model and the hydraulic pump flow model. The basic value of the flow demand is corrected through multi-model coupling operation, and finally the target flow of the suspension system considering the dynamic response characteristics of the system is output.

[0028] For example, the specific process of inputting the pressure data of the upper and lower chambers of the shock absorber and the target pressure difference into the flow model to determine the target flow of the suspension system is as follows: First, data acquisition and preprocessing are performed. High-precision pressure sensors installed in the upper and lower chambers of the shock absorber are used to collect the current chamber pressure data in real time, denoted as Pupper and Plower, respectively. Simultaneously, the target pressure difference ΔP_target between the upper and lower chambers of the shock absorber, determined in step S13, is retrieved and combined with the vehicle speed v and suspension travel vector s from the vehicle state signal to form the flow model input dataset. The collected pressure data is preprocessed, using a first-order low-pass filter algorithm to remove high-frequency interference signals (the filter cutoff frequency is set to 10Hz). Data smoothing is then used to eliminate instantaneous pressure fluctuations, ensuring the stability and accuracy of the input data.

[0029] The flow model calculation is then initiated. This flow model integrates the shock absorber hydraulic cylinder model, the valve flow model, and the damping orifice flow model. The various sub-models work together to complete the flow calculation. Shock absorber hydraulic cylinder model calculation: The pre-processed P_upper, P_lower and suspension dynamic stroke vector s are input into the hydraulic cylinder model. This model is built based on the working principle of the hydraulic cylinder and has built-in parameters such as the effective working area of ​​the piston A_p (calibrated to 0.012m²) and the piston movement speed v_p (obtained by differentiating the suspension dynamic stroke vector with respect to time). The basic value of the real-time flow requirement of the hydraulic cylinder is calculated by the formula Q_cylinder = A_p × v_p. At the same time, combined with the target pressure difference ΔP_target, the hydraulic cylinder flow correction coefficient k1 is output (range 0.8-1.2, dynamically adjusted by the pressure deviation ΔP = ΔP_target - (P_upper - P_lower). The larger the pressure deviation, the closer k1 is to 1.2).

[0030] Valve flow model calculation: The target pressure difference ΔP_target, the current vehicle speed v, and the pre-processed pressure data are input into the valve flow model. The model presets the maximum flow area A_v of the valve (calibrated to 0.0005m²), the flow coefficient C_d (taken as 0.65), and the hydraulic oil density ρ (taken as 850kg / m³). The theoretical flow regulation value of the valve is calculated using the formula Q_valve = C_d × A_v × √[2 × |ΔP_target - (P_upper - P_lower)| / ρ]. At the same time, it is dynamically corrected according to the road surface roughness level R_q. When R_q ≥ 0.7 (bumpy road surface), it is multiplied by the correction coefficient k2 = 1.15 to enhance the flow regulation redundancy; when R_q ≤ 0.3 (smooth road surface), it is multiplied by the correction coefficient k2 = 0.95 to optimize the flow output efficiency.

[0031] Damping orifice flow rate model calculation: Input the actual pressure difference ΔP_actual = P_upper - P_lower and the target pressure difference ΔP_target of the upper and lower chambers of the shock absorber into the damping orifice flow rate model. This model is built based on the fluid dynamics orifice flow rate formula and includes parameters such as the damping orifice diameter d (calibrated to 3mm), the damping orifice length L (calibrated to 10mm), and the hydraulic oil dynamic viscosity μ (taken as 0.03Pa·s). The flow rate is calculated using the formula Q_orifice = (π × d) / ( ... 4 The flow compensation value of the damping orifice is calculated as (×|ΔP_target-ΔP_actual|) / (128×μ×L), which is used to offset the effect of the damping orifice throttling effect on the system flow and ensure the integrity of the flow calculation.

[0032] Finally, the overall target flow is integrated. Based on the output results of each sub-model, the flow model calculates the target flow of the suspension system, Q_total, using a weighted summation algorithm. The specific formula is Q_total = k1 × Q_cylinder + k2 × Q_valve + Q_orifice. The weight coefficients of the output flow of each sub-model are dynamically allocated based on the real-time vehicle speed: when the vehicle speed v ≤ 60 km / h, the weight of Q_cylinder is 0.4, Q_valve is 0.35, and Q_orifice is 0.25; when 60 km / h < v ≤ 100 km / h, the weights are adjusted to Q_cylinder 0.35, Q_valve 0.4, and Q_orifice 0.25; when v > 100 km / h, the weights are set to Q_cylinder 0.3, Q_valve 0.45, and Q_orifice 0.25, to adapt to the flow demand characteristics of the suspension system at different vehicle speeds. After calculation, the flow model outputs Q_total as the target flow of the suspension system, and also outputs a suggested flow distribution ratio, i.e., the baseline ratio for flow distribution between the hydraulic pump and valves.

[0033] Step S40: Based on the first target flow rate allocated to the hydraulic pump and the second target flow rate allocated to the hydraulic pipeline valve in the target flow rate, the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valve are decoupled to obtain.

[0034] In this embodiment, the first target flow rate is the flow output task value allocated to the hydraulic pump based on the target flow rate of the suspension system, combined with the load characteristics and working efficiency of the hydraulic pump. The second target flow rate is the flow regulation task value allocated to the hydraulic pipeline valves within the target flow rate, used to achieve dynamic control of the damping force. Decoupling solution is a process of eliminating mutual interference between the hydraulic pump flow control and the hydraulic pipeline valve flow control through a preset algorithm, achieving independent and accurate calculation. The target speed is the speed standard required for the hydraulic pump to output the first target flow rate, and the target opening degree is the degree of opening required for the hydraulic pipeline valves to achieve the second target flow rate regulation.

[0035] As an optional implementation, based on a preset flow allocation algorithm, the target flow is allocated into a first target flow and a second target flow according to the working characteristics ratio of the hydraulic pump and the hydraulic pipeline valve. A fuzzy decoupling algorithm is used to establish an inverse model of hydraulic pump flow-speed and an inverse model of valve flow-opening, respectively. The first target flow is input into the inverse model of hydraulic pump flow-speed to obtain the target speed of the hydraulic pump, and the second target flow is input into the inverse model of valve flow-opening to obtain the target opening of the hydraulic pipeline valve.

[0036] As another optional implementation, the target flow rate is first processed by the decoupling algorithm module to eliminate the coupling effect between the hydraulic pump and the valve. Then, the first target flow rate and the second target flow rate are allocated. The target speed of the hydraulic pump is solved by the PID control algorithm, combined with the load pressure and volumetric efficiency of the hydraulic pump. At the same time, the correction coefficient is calculated based on the vehicle status signal. The target opening degree of the hydraulic pipeline valve is solved by the model predictive control algorithm, combined with the correction coefficient and the second target flow rate.

[0037] Step S50: Adjust the opening degree of the hydraulic pipeline valve to the target opening degree, and adjust the speed of the hydraulic pump to the target speed.

[0038] In this embodiment, control execution refers to the process by which the controller sends control commands to the hydraulic pipeline valves and hydraulic pumps based on the target opening degree and target rotation speed obtained from the solution, thereby driving the corresponding actuators to complete the adjustment action.

[0039] As an optional implementation, the controller converts the target opening degree into a corresponding electrical signal, which is then output to the electromagnetic actuator of the hydraulic pipeline valve through the drive circuit. The electromagnetic actuator adjusts the valve core position according to the electrical signal strength so that the valve opening degree reaches the target opening degree. At the same time, the controller adjusts the power supply frequency of the hydraulic pump drive motor through the PWM signal to control the motor speed and drive the hydraulic pump to reach the target speed.

[0040] As another optional implementation, a hierarchical control strategy is adopted. First, the speed of the hydraulic pump is quickly adjusted to a preset range close to the target speed, and then fine-tuned to the target speed. For hydraulic pipeline valves, coarse adjustment is first made based on the difference between the current opening and the target opening, and then fine adjustment is made through closed-loop feedback control to ensure that the valve opening accurately reaches the target opening. At the same time, the coordination status of the two during the adjustment process is monitored in real time to avoid action conflicts.

[0041] For example, when a vehicle is driving on an urban road, it first passes through a bumpy section of road. At this time, the vehicle speed sensor collects a vehicle speed of 30 km / h, the road roughness sensor detects a road roughness level of 0.8, the acceleration sensor collects a large vertical acceleration, and the suspension system signals show a drastic change in the suspension dynamic travel vector. The comfort parameter weight in the vehicle status signal is automatically adjusted to 0.7. Based on these signals, the target active force is calculated through the all-active force model, and then input into the shock absorber piston model to determine the target pressure difference between the upper and lower chambers of the shock absorber as 0.8 MPa. The pressure sensor collects the current upper chamber pressure of the shock absorber as 0.3 MPa and the lower chamber pressure as 0.1 MPa. These pressure data and the target pressure difference are input into the flow model to calculate the target flow rate of the suspension system as 5 L / min. The target flow rate is allocated as follows using a decoupling algorithm: a first target flow rate of 4 L / min for the hydraulic pump and a second target flow rate of 1 L / min for the hydraulic pipeline valves. Considering the current load pressure of the hydraulic pump is 2 MPa, the target speed is calculated as 1500 r / min using the hydraulic pump flow-speed inverse model. Simultaneously, a correction coefficient of 1.3 is obtained by processing the vehicle status signal using a fuzzy control algorithm. Combining the target pressure difference and the second target flow rate, the target opening is calculated as 60% using the valve flow-opening inverse model. Finally, the controller drives the hydraulic pipeline valves to adjust the opening to 60%, controlling the hydraulic pump drive motor speed to reach 1500 r / min. This allows the pressure in the upper and lower chambers of the shock absorber to quickly approach the target pressure difference, effectively absorbing the impact of road bumps. The vehicle then entered the highway and increased its speed to 100 km / h. The steering angle sensor detected that the vehicle was making a slight turn. At this time, the weight of the handling parameter in the vehicle status signal was adjusted to 0.6. The suspension system signal showed that the vehicle's roll attitude had changed. The target pressure difference was recalculated to be 1.2 MPa. The above flow calculation, decoupling solution and control execution steps were repeated. The target speed of the hydraulic pump was adjusted to 1800 r / min and the target opening of the hydraulic pipeline valve was adjusted to 40% to ensure that the suspension provides sufficient roll support force when the vehicle turns, thereby improving handling stability.

[0042] This embodiment determines the target pressure difference by combining suspension system signals and vehicle status signals, ensuring that the pressure difference requirement is accurately matched with real-time driving conditions, providing a reasonable benchmark for subsequent control. It associates pressure data with the target flow rate through a flow model, achieving dynamic adaptation of pressure and flow, avoiding blind adjustments. A decoupling algorithm independently solves for the target speed of the hydraulic pump and the target opening of the valve, completely eliminating coupling interference between the two and solving the pressure deviation problem caused by mutual influence in traditional control. Precise control ensures that the coordinated action quickly approaches the target pressure difference, effectively offsetting interference from complex road conditions and changes in vehicle posture, ultimately significantly improving the adjustment accuracy of the pressure difference between the upper and lower chambers of the shock absorber, and fully leveraging the performance advantages of the fully active suspension.

[0043] Based on any of the above embodiments, in Embodiment 2 of this application, step S10 includes: Step S11: Calculate the vertical vibration suppression force, road impact compensation force, roll suppression force, and pitch suppression force based on the parameters in the suspension system signal and the vehicle status signal.

[0044] In this embodiment, the vertical vibration suppression force is a force parameter used to counteract vertical vibrations during vehicle operation, ensuring ride comfort. The road impact compensation force is a force parameter used to compensate for the impact of road impacts on the suspension system, addressing different levels of road bumps. The roll suppression force is a force parameter used to suppress vehicle body roll during cornering, improving handling stability. The pitch suppression force is a force parameter used to mitigate vehicle body pitch during acceleration or braking. The suspension system signals include at least one of the following: vehicle roll attitude, vehicle pitch attitude, vehicle braking state, vehicle acceleration state, vehicle cornering state, and suspension travel vector. The vehicle state signals include at least one of the following: vehicle speed, road surface roughness level, road anticipation state, driving events, comfort parameters, and handling parameters.

[0045] As an optional implementation, the suspension dynamic travel vector in the suspension system signal and the vehicle speed and vertical acceleration parameters in the vehicle state signal are extracted, and the vertical vibration suppression force is calculated by a PID control algorithm; combined with the road surface roughness level and road pre-aiming state, the road impact compensation force is output in advance by a model predictive control algorithm; based on the steering angle, turning radius and roll attitude parameters in the vehicle turning state, the roll suppression force is calculated by multiplying the roll stiffness coefficient and the roll angle deviation; based on the vehicle acceleration / braking state and pitch attitude, the pitch suppression force is obtained by multiplying the pitch stiffness coefficient and the pitch angle deviation.

[0046] As another optional implementation, a multi-parameter component force calculation model is established. The suspension system signal and vehicle state signal are standardized and then input into the model. The component force calculation coefficients corresponding to different parameters are preset in the model. The vertical vibration suppression force, road impact compensation force, roll suppression force and pitch suppression force are calculated by multiple linear regression algorithm. At the same time, the calculation weight of each component force is dynamically adjusted according to the driving event type.

[0047] Step S12: The target active force is calculated by superimposing the components of vertical vibration suppression force, road impact compensation force, roll suppression force, and pitch suppression force.

[0048] In this embodiment, the component force superposition calculation is a process of combining four independent damping / compensating forces according to preset rules to obtain a comprehensive reflection of the overall force requirements of the suspension system. The target active force is the total active force value required by the suspension system to achieve preset comfort and handling targets.

[0049] As an optional implementation method, a weighted superposition algorithm is adopted. The weight coefficients of each component force are set according to the real-time driving conditions of the vehicle. When driving at high speed or turning, the weights of roll suppression force and pitch suppression force are increased. When driving on bumpy roads, the weights of vertical vibration suppression force and road impact compensation force are increased. The target active force is obtained by multiplying each component force by its corresponding weight and then summing them.

[0050] As another alternative implementation method, the four component forces are first screened for effectiveness, and abnormal component force values ​​that exceed the preset reasonable range are eliminated. Then, an adaptive superposition algorithm is used to dynamically adjust the superposition ratio of each component force according to the real-time requirements of comfort parameters and controllability parameters, and the optimal target active force is obtained through iterative calculation.

[0051] Step S13: Input the target active force into the shock absorber piston model, and use the model output to determine the target pressure difference between the upper chamber and the lower chamber of the shock absorber. The shock absorber piston model is constructed based on the principle of piston force balance.

[0052] In this embodiment, the shock absorber piston model is a mathematical model that simulates the force and pressure relationship during the piston's movement. Its core principle is based on the piston force balance principle, meaning the total force acting on the piston is equal to the force generated by the pressure difference between the upper and lower chambers of the shock absorber. The target pressure difference is the pressure difference between the upper and lower chambers of the shock absorber required for the piston to generate the target driving force.

[0053] As an optional implementation, the shock absorber piston model presets the effective working area parameter of the piston. This parameter is obtained by calibrating the hardware structure of the shock absorber. After the target active force is input into the model, the target pressure difference is directly calculated by the formula ΔP=F_target / A_p (where ΔP is the target pressure difference, F_target is the target active force, and A_p is the effective working area of ​​the piston), and the dynamic adjustment range of the pressure difference is output.

[0054] As another optional implementation, a refined shock absorber piston model is constructed, which includes parameters such as piston friction coefficient and hydraulic oil viscous damping. After inputting the target active force into the model, the target pressure difference is obtained by iteratively solving the force balance equation, combined with the suspension dynamic stroke vector and piston movement speed. At the same time, the influence of temperature on hydraulic oil characteristics is considered for dynamic correction to ensure the accuracy of pressure difference calculation.

[0055] For example, when a vehicle is driving on a mountain road, it first encounters a section of continuous curves. At this time, the steering angle sensor collects a steering angle of 30 degrees and a turning radius of 50 meters. The roll attitude sensor detects a deviation of 2 degrees between the actual roll angle and the target roll angle. Based on the roll stiffness coefficient C_roll = 15000 N / rad, the roll suppression force F_roll = 15000 × 2 = 30000 N is calculated. At the same time, the vehicle braking status signal shows light braking, and the pitch attitude deviation is 1 degree. The pitch stiffness coefficient C_pitch = 12000 N / rad, and the corresponding pitch suppression force F_pitch = 12000 × 1 = 12000 N. The vertical acceleration sensor collects a vertical acceleration of 0.8g. Combined with the suspension dynamic travel deviation, the vertical vibration suppression force F_vert = 8000 N is calculated using a PID algorithm. The road surface roughness level is 0.6, and the road impact compensation force F_road = 5000 N is obtained through a model predictive control algorithm. Based on the current cornering driving conditions, the weights for roll suppression force (0.4), pitch suppression force (0.3), vertical vibration suppression force (0.2), and road impact compensation force (0.1) are set. The target active force is calculated as F_target = 30000×0.4 + 12000×0.3 + 8000×0.2 + 5000×0.1 = 12000 + 3600 + 1600 + 500 = 17700 N. This target active force is then input into a shock absorber piston model constructed based on the piston force balance principle. Given the effective piston area A_p = 0.01 m², the target pressure difference ΔP = 17700 / 0.01 = 1770000 Pa = 1.77 MPa is calculated using the formula, providing a precise target benchmark for subsequent suspension system pressure control.

[0056] As an optional implementation, the specific process for determining the target pressure difference between the upper and lower chambers of the shock absorber is as follows: First, signal acquisition and preprocessing are performed. Vehicle roll and pitch attitude data are collected in real-time from the suspension system signals using vehicle-mounted attitude sensors. Suspension travel vectors are acquired using travel sensors. Vehicle braking, acceleration, and turning status information are obtained using brake pedal, accelerator pedal, and steering angle sensors, respectively. Simultaneously, vehicle speed is acquired using a vehicle speed sensor, road surface roughness levels are obtained using a road surface perception sensor, and road pre-aiming status is acquired using an environmental perception camera. These data, combined with preset comfort and handling parameters from the vehicle control system and real-time identified driving events (such as cornering, straight-line bumps, and emergency braking), form a complete signal set. The acquired signals are then standardized. A Kalman filter algorithm is used to eliminate sensor noise in the roll and pitch attitude signals. The suspension travel vector is smoothed using a sliding window filter. The road surface roughness level is converted into a quantization coefficient in the 0-1 range, completing the signal preprocessing. Next, force calculations are performed. For the vertical vibration suppression force, the pre-processed suspension dynamic travel vector and vertical acceleration data are extracted and input into the PID control algorithm. The proportional coefficient Kp = 5000, integral coefficient Ki = 100, and derivative coefficient Kd = 500 are set. The vertical vibration suppression force is calculated using the formula F_vert = Kp × Δx + Ki × ∫Δxdt + Kd × Δv (where Δx is the suspension dynamic travel deviation and Δv is the vertical velocity deviation). For the road impact compensation force, combining the road roughness level quantization coefficient and road pre-aiming state data, a model predictive control algorithm is used to predict the road impact location and intensity in advance, and output the corresponding road impact compensation force. For the roll suppression force… Based on the steering angle, turning radius, and roll attitude data during vehicle turning, the deviation θ_roll between the actual roll angle and the target roll angle is calculated. The roll suppression force is obtained using the formula F_roll=C_roll×θ_roll (where C_roll is the roll stiffness coefficient, calibrated to 18000N / rad). For pitch suppression force, based on the vehicle acceleration / braking status signal and pitch attitude data, the deviation θ_pitch between the actual pitch angle and the target pitch angle is calculated. The pitch suppression force is obtained using the formula F_pitch=C_pitch×θ_pitch (where C_pitch is the pitch stiffness coefficient, calibrated to 15000N / rad).

[0057] The target active force is then calculated, and the weight coefficients of each component force are dynamically adjusted according to real-time driving events: when the driving event is cornering, the weights for roll suppression force, pitch suppression force, vertical vibration suppression force, and road impact compensation force are set to 0.4, 0.2, 0.2, and 0.2 respectively; when the driving event is bumpy road driving, the weights for vertical vibration suppression force, road impact compensation force, roll suppression force, and pitch suppression force are adjusted to 0.4, 0.3, 0.15, and 0.15 respectively; when the driving event is emergency braking, the pitch suppression force weight is increased to 0.5, and the weights of the remaining components are evenly distributed at 0.167. Based on the set weight coefficients, the four components are multiplied by their corresponding weights and then summed to obtain the target active force F_target.

[0058] Finally, the target pressure difference is calculated by inputting the target active force into a shock absorber piston model built based on the piston force balance principle. This model presets the effective working area of ​​the shock absorber piston to A_p = 0.012 m² (obtained from hardware parameter calibration). The target pressure difference between the upper and lower chambers of the shock absorber is directly output using the built-in formula ΔP_target = F_target / A_p. Simultaneously, the model combines the current vehicle speed and suspension travel vector to perform boundary checks on the calculated target pressure difference. If the target pressure difference exceeds the preset safety range (0.2 MPa - 2.5 MPa), it is automatically corrected to the nearest boundary value to ensure that the pressure difference meets the physical load-bearing limit of the suspension system.

[0059] This embodiment calculates the components of the suspension independently to accurately match the stress requirements under different driving conditions, avoiding the one-sided control caused by single force value calculation; it obtains the target active force through dynamic weighted superposition to achieve an adaptive balance between comfort and handling; and it uses a shock absorber piston model based on the piston force balance principle to ensure accurate mapping between the target pressure difference and the target active force, solving the problem of the disconnect between traditional pressure difference calculation and actual suspension stress requirements, and significantly improving the calculation accuracy of the target pressure difference.

[0060] Based on any of the above embodiments, in Embodiment 3 of this application, referring to Figure 2 , Figure 2 Steps S31-S32 and step S30 are shown, including: Step S31: Based on the load pressure of the hydraulic pump and the target flow rate, the first target flow rate of the hydraulic pump is calculated in a decoupled manner, and based on the target flow rate and the target pressure difference, the second target flow rate of the hydraulic pipeline valve is calculated in a decoupled manner.

[0061] In this embodiment, the first target flow rate is the flow rate value independently allocated by the decoupling algorithm module for the hydraulic pump, and the second target flow rate is the flow rate value separately allocated by the decoupling algorithm module for the hydraulic pipeline valve. The two are decoupled to eliminate mutual interference, and their sum is consistent with the target flow rate of the suspension system.

[0062] As an optional implementation, the hydraulic pump load pressure and target flow rate are input into the pump flow calculation unit of the decoupling algorithm module. The unit has a built-in load-flow mapping table. Based on the load pressure, the corresponding flow allocation benchmark ratio is queried. Then, the potential interference of valve flow is eliminated through the interference compensation algorithm, and the first target flow rate is output. At the same time, the target flow rate and target pressure difference are input into the valve flow calculation unit of the module. The flow allocation weight is dynamically adjusted according to the pressure difference deviation. Combined with the feedforward decoupling algorithm, the influence of pump flow fluctuation is offset to obtain the second target flow rate.

[0063] As another optional implementation, a model prediction decoupling algorithm is used to construct a pump-valve flow coupling interference model. The target flow rate, hydraulic pump load pressure and target pressure difference are input into the model. The first target flow rate and the second target flow rate without coupling interference are obtained through rolling optimization calculation. At the same time, the dynamic adjustment threshold of flow distribution is output to ensure the stability of subsequent control.

[0064] Step S32: Combine the load pressure of the hydraulic pump and determine the target speed of the hydraulic pump based on the first target flow rate.

[0065] Step S33: Combine the vehicle status signal and calculate the target opening degree of the hydraulic pipeline valve based on the second target flow rate.

[0066] In this embodiment, the target rotational speed is the rotational speed that the hydraulic pump needs to reach in order to stably output the first target flow rate, and the target opening degree is the degree to which the hydraulic pipeline valve needs to be adjusted to accurately control the second target flow rate.

[0067] As an optional implementation, the first target flow rate and hydraulic pump load pressure are input into the hydraulic pump flow-speed inverse model. The model combines the preset pump displacement and real-time volumetric efficiency (obtained by load pressure calibration) to directly calculate the target speed through a formula, and then corrects it with a PID algorithm to obtain the final value. Vehicle speed and road surface roughness data are extracted from the vehicle status signal, and an opening correction coefficient is generated through a fuzzy control algorithm. The second target flow rate and the correction coefficient are input into the valve flow-opening inverse model to solve for the target opening.

[0068] As another optional implementation, a hierarchical solution strategy is adopted. The initial speed of the hydraulic pump is first obtained by coarse calculation formula for the first target flow rate, and then fine iterative correction is performed in combination with the load pressure to output the target speed. The initial opening of the valve is first obtained by matching the valve flow rate-opening basic mapping relationship, and then dynamically fine-tuned according to the vehicle steering angle and acceleration status to finally determine the target opening, so as to ensure that it is adapted to the real-time driving conditions.

[0069] This embodiment achieves independent and precise allocation of pump and valve flow through a decoupling algorithm, completely eliminating coupling interference in traditional control and ensuring that the first and second target flow rates are precisely matched with actual needs. By combining load pressure and vehicle status signals to solve for target speed and opening, the accuracy of parameter control is further improved, laying the foundation for subsequent pump and valve coordinated action, effectively avoiding flow and pressure mismatch problems, and significantly enhancing the stability and response speed of suspension system pressure control.

[0070] Optionally, the step of determining the target speed of the hydraulic pump based on the first target flow rate, in conjunction with the load pressure of the hydraulic pump, includes: solving the inverse model of the hydraulic pump flow rate model based on the load pressure of the hydraulic pump, the volumetric efficiency of the hydraulic pump, and the first target flow rate to obtain the target speed of the hydraulic pump.

[0071] Step S321: Based on the load pressure of the hydraulic pump, the volumetric efficiency of the hydraulic pump, and the first target flow rate, solve the inverse model of the hydraulic pump flow rate model to obtain the target speed of the hydraulic pump.

[0072] In this embodiment, the inverse model of the hydraulic pump flow model is a calculation model built by reverse derivation based on the forward model of hydraulic pump flow-speed. It is used to solve the target speed of the hydraulic pump required by the first target flow rate in reverse, and the core is related to the dynamic relationship between load pressure, volumetric efficiency and flow rate and speed.

[0073] As an optional implementation, the volumetric efficiency parameters of the hydraulic pump under different load pressures are first calibrated through bench tests, and a load pressure-volumetric efficiency mapping table is established. The corresponding volumetric efficiency value is obtained by querying the real-time load pressure of the current hydraulic pump. The first target flow rate, the queried volumetric efficiency, and the preset hydraulic pump displacement parameters are substituted into the built-in formula n_target=(Q1_target×10^6) / (V_p×η_v) of the inverse model of the hydraulic pump flow model (where n_target is the target speed, Q1_target is the first target flow rate, V_p is the hydraulic pump displacement, and η_v is the volumetric efficiency) to directly calculate the preliminary target speed. Then, through a closed-loop verification algorithm, the preliminary target speed is substituted into the positive model of the hydraulic pump flow to calculate the theoretical output flow rate. It is compared with the first target flow rate. If the deviation is greater than 0.5%, the volumetric efficiency value is iteratively corrected until the deviation meets the requirements, and the final target speed is output.

[0074] As another optional implementation, a hydraulic pump flow inverse model including a load pressure compensation term is constructed. The first target flow rate and real-time load pressure are input into the model, and the model automatically calls the preset volumetric efficiency calculation formula (η_v=a×P_L+b, where a and b are calibration coefficients and P_L is the load pressure) to calculate the volumetric efficiency. The inverse model is solved through multi-parameter coupling operation to output the initial target speed. At the same time, the initial target speed is corrected for aging by combining the historical operating data of the hydraulic pump to compensate for the performance degradation caused by long-term use and ensure the accuracy of the target speed.

[0075] For example, a vehicle is driving in a congested urban area. The real-time load pressure of the hydraulic pump is 1.8 MPa, the first target flow rate is 4 L / min, and the hydraulic pump displacement is calibrated to 10 mL / r. Firstly, using the first implementation method, the load pressure-volume efficiency mapping table is consulted. 1.8 MPa corresponds to a volume efficiency of 90%. Substituting the parameters into the inverse model formula, the initial target speed is calculated as (4 × 10^6) / (10 × 90%) ≈ 4444.44 r / min. Substituting this speed into the forward model to calculate the theoretical flow rate, the theoretical flow rate is obtained as (10 × 4444.44 × 90%) / 10^6 ≈ 4.0 L / min, which deviates from the first target flow rate by 0. The target speed of 4444 r / min is directly output.

[0076] This embodiment solves for the target speed by using the inverse model of the hydraulic pump flow model. Combined with the dynamic correlation between load pressure and volumetric efficiency, it ensures that the calculated speed is accurately matched with the actual working state of the hydraulic pump, avoiding the flow output deviation caused by traditional fixed speed control. Through optimization methods such as closed-loop verification or aging correction, the calculation accuracy of the target speed is further improved, providing a guarantee for the hydraulic pump to stably output the first target flow, and effectively enhancing the reliability of the suspension system pressure control.

[0077] Optionally, the step of determining the target opening degree of the hydraulic pipeline valve based on the second target flow rate, in conjunction with the vehicle status signal, includes: Step S3221: The suspension system signal and vehicle state signal are processed by a fuzzy control algorithm to obtain the correction coefficient.

[0078] In this embodiment, the correction coefficient is a dynamic adjustment parameter adapted to different driving conditions and used to optimize the accuracy of valve opening calculation. Its value ranges from 0.8 to 1.2, and its value is positively correlated with the complexity of the driving conditions.

[0079] As an optional implementation, the roll attitude and suspension travel vector in the suspension system signal, as well as the vehicle speed and road surface roughness level in the vehicle status signal, are extracted, standardized, and then input into the fuzzy control module. The module has a built-in fuzzy rule library, which divides the input signal into three levels of fuzzy subsets: "small / medium / large". Through fuzzy inference and defuzzification, the corresponding correction coefficients are output.

[0080] As another optional implementation, a two-layer fuzzy control strategy is adopted. The first layer uses vehicle speed and driving events as inputs and outputs basic correction coefficients. The second layer uses lateral tilt attitude and road surface roughness as inputs to fine-tune the basic coefficients and obtain the final correction coefficients.

[0081] Step S3222: Solve the inverse model of the valve flow model based on the target pressure difference, the second target flow rate, and the correction coefficient to obtain the target opening degree of the hydraulic pipeline valve.

[0082] In this embodiment, the inverse model of the valve flow model is derived by reversing the valve flow-opening model. The calculation model of the target opening can be solved by reversing the flow rate, pressure difference and correction coefficient.

[0083] As an optional implementation method, the target pressure difference, the second target flow rate, and the correction coefficient are substituted into the preset formula of the inverse model, and the target opening degree is directly calculated by combining the calibration parameters such as the valve's maximum flow area, flow coefficient, and hydraulic oil density.

[0084] As another optional implementation, after inputting the input parameters into the inverse model, the initial opening degree is solved through multi-parameter iterative calculation. Combined with the historical opening degree data of the valve, the system pressure fluctuation caused by sudden opening changes is avoided, and the final target opening degree is output.

[0085] Next, the decoupling solution scheme for obtaining the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valve based on the first target flow allocated to the hydraulic pump and the second target flow allocated to the hydraulic pipeline valve will be explained.

[0086] Specifically, based on a multi-parameter decoupled mathematical model, by constructing and solving the inverse model of hydraulic pump flow and CDC valve flow, the decoupled and accurate solution of target flow to target hydraulic pump speed and target CDC valve opening is achieved, eliminating the control coupling interference between the two. First, a multi-parameter positive model including the dynamic pressure characteristics of the hydraulic pump, CDC valve, and shock absorber is established. Hydraulic pump flow-speed positive model: Qp=fp(n,PL,ηv), where Qp is the hydraulic pump output flow, n is the pump speed, PL is the system load pressure, and ηv is the pump volumetric efficiency, which is positively correlated with speed and load, and is obtained through bench testing. CDC valve flow-opening positive model: Qv=fv(k,Pdiff,ρ), where Qv is the CDC valve flow, k is the valve opening (0-100%), Pdiff is the pressure difference between the upper and lower chambers of the shock absorber, and ρ is the hydraulic oil density (constant). This model is obtained by fitting the valve orifice flow formula with experimental data. The dynamic response model of the shock absorber pressure is: ΔP=fd(Qp,Qv,vp,A), where ΔP is the target pressure difference between the upper and lower chambers, vp is the piston speed of the shock absorber, and A is the effective area of ​​the piston.

[0087] The inverse model of hydraulic pump flow rate is the reverse mapping of the forward model, that is, the target speed ntarget is derived from the target flow rate Qp_target, and the expression is: ntarget = fp - ¹(Qp_target,PL,ηv). The volumetric efficiency ηv under different loads PL and different speeds n is calibrated through bench tests. A fitting formula for ηv=g(n,PL) is established, such as a quadratic polynomial fitting: ηv=a0+a1n+a2PL+a3nPL, where a0-a3 are calibration coefficients. Substituting these coefficients into the forward model gives the basis for the derivation of the inverse model.

[0088] Based on the total target flow rate Qtotal of the suspension system and the current load pressure PL, the target flow rate Qp_target to be handled by the hydraulic pump is allocated. Using a decoupling algorithm, it is ensured that there is no coupling interference with the target flow rate Qv_target of the CDC valve. Therefore, Qtotal = Qp_target + Qv_target. Based on the current load PL and the preset initial speed n0, the initial volumetric efficiency ηv0 is calculated using ηv = g(n0, PL). Substituting Qp_target, PL, and ηv0 into the inverse model formula: ntarget = (Qp_target × 10) / (n0, PL). 6 The initial target speed n1 is obtained by calculating (Vp × ηv0) / (Vp × ηv0) (where Vp is the hydraulic pump displacement in mL / r, a constant). Substituting n1 into ηv = g(n1, PL) updates the volumetric efficiency ηv1. Substituting it again into the inverse model calculates n2. This process is repeated until |nk+1-nk| < 0.1 r / min, finally outputting a stable target hydraulic pump speed ntarget.

[0089] The inverse model of the CDC valve flow rate is the reverse mapping of the forward model, that is, the target opening ktarget is derived from the target flow rate Qv_target, and the expression is: ktarget = fv - ¹(Qv_target,Pdiff,ρ,S), where S is the correction coefficient for external environmental data, integrating information such as road surface bumpiness, vehicle speed, and steering angle. The flow rate Qv under different opening degrees k and different pressure differences Pdiff is obtained through experiments. The positive model Qv=k×Cd×Av×√(2ΔP / ρ) is fitted, where Cd is the flow coefficient and Av is the maximum flow area of ​​the valve orifice, both constants. The inverse model's basic formula is derived by reverse derivation.

[0090] Real-time data, including vehicle speed v, vertical acceleration az, and road roughness Rq, is collected by vehicle speed sensors, acceleration sensors, and road roughness sensors. A correction coefficient S is calculated using a fuzzy control algorithm. Based on the system's total target flow rate Qtotal and the current target pressure difference Pdiff_target between the upper and lower chambers of the shock absorber, the target flow rate Qv_target to be handled by the CDC valve is allocated. Substituting Qv_target, Pdiff_target, ρ, and S into the inverse model formula: kinitial=(Qv_target×√ρ) / (S×Cd×Av×√(2Pdiff_target)), the initial target opening kinitial is obtained. Kinitial is then substituted into the CDC valve flow forward model to calculate the actual flow rate Qv_actual, which is compared with Qv_target to obtain the deviation ΔQv. The opening value ktarget=kinitial+Kp×ΔQv is corrected using a model predictive control algorithm, where Kp is a proportional correction coefficient calibrated on a test bench to ensure that opening adjustment does not affect the hydraulic pump load, achieving decoupled control.

[0091] The decoupled ntarget is transmitted to the hydraulic pump control module, where the pump drive motor speed is adjusted via a PWM signal, and the pump output flow is monitored in real time to ensure consistency with Qp_target. ktarget is transmitted to the CDC valve control module, where an electromagnetic actuator is driven by an electrical signal to adjust the valve opening. The damping force adjustment accuracy is verified by combining the differential pressure data from the pressure sensor. The decoupling algorithm module monitors the mutual interference between the two control signals in real time. If deviations occur, the inverse model is used to iterate and solve the problem again, ensuring independent and coordinated control under all operating conditions.

[0092] This embodiment uses a step-by-step process: first, a fuzzy control algorithm is used to accurately adapt to the working conditions and generate correction coefficients; then, the opening degree is solved through an inverse model. This dual approach ensures the valve adjustment accuracy and avoids deviations caused by single calculations, effectively improving the stability of the suspension system pressure control.

[0093] Based on any of the above embodiments, in Embodiment 4 of this application, after step S40, the following is included: Step S51: Collect pressure data of the upper and lower chambers of the shock absorber to determine the actual pressure difference.

[0094] In this embodiment, the actual pressure difference is the difference between the current real-time pressure of the upper and lower chambers of the shock absorber, which is calculated by real-time collected chamber pressure data and is used to reflect the difference between the current pressure state and the target state of the suspension system.

[0095] As an optional implementation, high-precision pressure sensors installed in the upper and lower chambers of the shock absorber acquire chamber pressure data in real time at a sampling frequency of 100Hz. The acquired data is then subjected to first-order low-pass filtering to remove high-frequency interference signals. Finally, the actual pressure difference is obtained by subtracting the lower chamber pressure data from the upper chamber pressure data.

[0096] As another optional implementation, a dual-sensor redundant acquisition strategy is adopted, in which two pressure sensors are installed in each chamber, and the average value of the pressure data is taken as the final pressure data of the chamber after synchronous acquisition. The difference between the two values ​​is then calculated to obtain the actual pressure difference, thereby improving the reliability of data acquisition.

[0097] Step S52: Input the deviation between the actual pressure difference and the target pressure difference into the flow model and the inverse model of the flow model, and determine the opening adjustment value and the speed adjustment value based on the model output.

[0098] In this embodiment, the deviation is the difference between the actual pressure difference and the target pressure difference, used to quantify the degree of deviation between the current pressure state and the target state; the opening adjustment value is the magnitude of adjustment required to the current opening of the hydraulic pipeline valve to eliminate the pressure deviation; and the speed adjustment value is the magnitude of adjustment required to the current speed of the hydraulic pump to offset the pressure deviation.

[0099] As an optional implementation method, the deviation ΔP between the actual pressure difference and the target pressure difference is first calculated as ΔP = actual pressure difference - target pressure difference. The deviation ΔP is then input into the flow model. Based on the correlation between the pressure deviation and the flow demand, the model outputs the corrected target flow adjustment amount. This adjustment amount is then input into the hydraulic pump flow inverse model and the valve flow inverse model, respectively. The inverse models output the corresponding speed adjustment value and opening adjustment value, respectively.

[0100] As another optional implementation, a deviation-adjustment mapping model is constructed. The pressure deviation ΔP, the current hydraulic pump load pressure, and the vehicle status signal are input into the model. The model combines the dynamic characteristics of the flow model and the solution logic of the inverse model. The speed adjustment value and opening adjustment value are calculated by the PID algorithm. At the same time, the boundary limit value of the adjustment amount is output to avoid the system instability caused by excessive adjustment.

[0101] Step S53: Adjust the opening of the hydraulic pipeline valve according to the opening adjustment value, and adjust the speed of the hydraulic pump according to the speed adjustment value.

[0102] In this embodiment, the adjustment execution refers to the process by which the controller sends dynamic correction commands to the hydraulic pipeline valves and hydraulic pumps based on the opening adjustment value and the speed adjustment value, thereby realizing closed-loop compensation for pressure deviation.

[0103] As an optional implementation, the controller adds the current valve opening to the opening adjustment value to obtain the corrected target opening, and drives the valve actuator to adjust to the target opening through an electrical signal; at the same time, it superimposes the current hydraulic pump speed to the speed adjustment value to obtain the corrected target speed, and adjusts the power supply frequency of the pump drive motor through a PWM signal to achieve precise speed adjustment.

[0104] As another optional implementation, a gradual adjustment strategy is adopted, in which the opening adjustment value and the speed adjustment value are divided into multiple adjustment steps. The controller sends step adjustment commands sequentially at preset time intervals. After each step adjustment is completed, the actual pressure difference is collected. If the pressure deviation is less than the preset threshold, the adjustment is stopped to ensure a smooth adjustment process and avoid sudden changes in system pressure.

[0105] For example, during high-speed vehicle operation, the target pressure difference is 1.5 MPa. Pressure sensors collect data showing an upper chamber pressure of 1.4 MPa and a lower chamber pressure of 0.1 MPa in the shock absorber, resulting in an actual pressure difference of 1.3 MPa. The pressure deviation ΔP = 1.3 MPa - 1.5 MPa = -0.2 MPa. This deviation is input into the flow model, which outputs a target flow adjustment of 0.8 L / min. This is then input into the hydraulic pump flow inverse model to obtain a speed adjustment value of +300 r / min, and into the valve flow inverse model to obtain an opening adjustment value of +5%. Upon receiving the adjustment value, the controller adds the current hydraulic pump speed of 1800 r / min to the adjustment value of 300 r / min to obtain a corrected target speed of 2100 r / min. The motor speed is then adjusted to this value via a PWM signal. Simultaneously, the current valve opening of 40% is added to the adjustment value of 5%, resulting in a target opening of 45%, which is then used to adjust the valve actuator to this opening. After the adjustment was completed, pressure data was collected again. The actual pressure difference reached 1.48 MPa, and the pressure deviation was reduced to -0.02 MPa, which met the control accuracy requirements.

[0106] This embodiment establishes a dynamic monitoring mechanism for pressure deviation by collecting pressure data in real time and calculating the actual pressure difference, solving the problem that traditional open-loop control cannot compensate for pressure offset in a timely manner. By inputting the deviation into the flow model and solving the adjustment value using the inverse model, a precise mapping between pressure deviation and pump and valve control parameters is achieved. Through closed-loop dynamic adjustment of pump and valve parameters, pressure deviation caused by factors such as system coupling interference and road surface fluctuations is effectively offset, ensuring that the pressure difference between the upper and lower chambers of the shock absorber stably approaches the target value. This significantly improves the accuracy and stability of the suspension system pressure control, further optimizing the vehicle's comfort and handling.

[0107] Furthermore, combined Figure 3 This paper describes the dual-closed-loop decoupled control architecture. Through in-depth research on the dynamic characteristics of the suspension hydraulic system, a multi-parameter mathematical model is established, including the hydraulic pump flow-speed characteristics, CDC valve flow-opening characteristics, and the dynamic response of the shock absorber pressure. Based on this model, a dual-closed-loop decoupled control architecture is designed: the outer loop uses the target pressure difference between the upper and lower chambers of the shock absorber as the control object, and calculates the total pressure and flow required by the suspension system through feedback data collected in real time by pressure sensors; the inner loop constructs independent control channels for the hydraulic pump and CDC valve respectively. For hydraulic pump speed control, based on the total pressure and flow requirements and combined with the volumetric efficiency and load characteristics of the hydraulic pump, a speed control algorithm is designed to precisely adjust the output flow of the hydraulic pump, providing a stable pressure foundation for the system. For CDC valve opening control, based on real-time vehicle acceleration, speed, steering angle, and other driving state information, as well as external environmental data such as road bumpiness, the CDC valve opening is independently adjusted through fuzzy control or model predictive control algorithms to achieve dynamic and precise adjustment of the damping force. The two control channels work in parallel, and the mutual interference is eliminated through a decoupling algorithm, ensuring that the hydraulic pump and CDC valve can work together to quickly and accurately control the damping chamber pressure at the target value under any operating condition, which significantly improves the response speed and control accuracy of the suspension system.

[0108] For example, at time T1, suspension system signals and vehicle status signals are acquired and input into the all-active force target value calculation model to calculate the all-active force representing the demand at time T1. Then, the all-active force is input into the shock absorber piston model to calculate the target pressure difference. Simultaneously or before inputting the target pressure difference into the flow model at time T1, upper and lower chamber pressure data of the shock absorber are collected. These data, along with the target pressure difference, are input into the flow model. The target flow rate is then calculated using the shock absorber hydraulic cylinder model, valve flow model, and damping orifice flow model within the flow model. The target flow rate is used as input to the decoupling algorithm module. The first target flow rate allocated to the CDC valve and the second target flow rate allocated to the hydraulic pump are calculated using the hydraulic pump / CDC valve decoupling model. Then, the inverse model of the CDC valve flow rate is solved based on the first target flow rate to obtain the target opening of the hydraulic pipeline valve; and the inverse model of the hydraulic pump flow rate is solved based on the second target flow rate to obtain the target speed of the hydraulic pump. All the above actions are completed within the time period from time T1 to time T2. Optionally, the time period for each time point is a value within 1-100ms, such as 1ms, 2ms, etc. For example, 1ms, 2ms, 20ms, 100ms. This embodiment does not specifically limit the length of the time period.

[0109] Furthermore, referring to Figure 4 The mode-decoupling based suspension control system consists of two parts: a hardware layer and a control layer. The hardware layer mainly includes a hydraulic pump, a continuously adjustable damping (CDC) valve, shock absorbers, a pressure sensor array, a vehicle speed sensor, an acceleration sensor, a steering angle sensor, and a controller. The system topology diagram is shown below. Figure 4 As shown in the diagram, pressure sensor groups are installed in the upper and lower chambers of the shock absorber to collect pressure data in real time; sensors for vehicle speed, acceleration, and steering angle are responsible for acquiring vehicle driving status information; the controller, as the core of the system, integrates a hydraulic pump control module, a CDC valve control module, and a decoupling algorithm module, receives sensor data, executes the decoupling control algorithm, and outputs control commands to adjust the hydraulic pump speed and CDC valve opening.

[0110] First, pressure sensors collect real-time pressure data from the upper and lower chambers of the shock absorber, while vehicle speed, acceleration, and steering angle sensors simultaneously acquire vehicle driving status information. All data is transmitted to the controller via the CAN bus. Second, the controller calculates the target pressure difference between the upper and lower chambers of the shock absorber based on preset comfort and handling control strategies and real-time driving status data. Simultaneously, the decoupling algorithm module, based on the system's mathematical model and current operating conditions, including road surface roughness, vehicle speed, current suspension motion state (compression / rebound), vertical velocity, vertical displacement, vehicle steering, and acceleration / deceleration status, calculates and simultaneously outputs hydraulic pump speed control parameters and CDC valve opening control parameters after mode decoupling. Then, the hydraulic pump control module, based on the calculated speed control parameters, adjusts the speed of the hydraulic pump drive motor via a PWM signal to precisely control the hydraulic pump's flow output. The CDC valve control module, based on the opening control parameters, drives the electromagnetic actuator inside the CDC valve via an electrical signal to adjust the valve opening in real-time.

[0111] Finally, the pressure sensor continuously monitors the pressure changes in the upper and lower chambers of the shock absorber and feeds the real-time data back to the controller. The decoupling algorithm module dynamically adjusts the control parameters of the hydraulic pump speed and CDC valve opening based on the pressure deviation. Through feedforward compensation and feedback correction mechanisms, it eliminates the coupling effect between the two, forming a closed-loop optimized control.

[0112] Furthermore, referring to Figure 5 , Figure 5 The control flow timing diagram for Embodiment 4 of this application shows that, firstly, pressure data is collected by high-precision pressure sensors in the upper and lower chambers of the shock absorber. Combined with parameters such as real-time vehicle speed in the vehicle status signal, the actual pressure difference is calculated after first-order low-pass filtering or averaging by dual-sensor redundancy. Then, the deviation ΔP between the actual pressure difference and the target pressure difference is immediately quantified. This deviation and the real-time vehicle speed are input into the flow model, and the target flow is output. Then, the flow is input into the hydraulic pump flow inverse model and the valve flow inverse model, respectively. Alternatively, the speed control command and opening control command are solved by a PID algorithm by combining the vehicle status signals such as hydraulic pump load pressure, real-time vehicle speed, and road surface roughness. Next, the controller controls the hydraulic pump and CDC valve to perform adjustment actions. After each adjustment, the actual pressure difference and real-time vehicle speed are collected synchronously. Then, the decoupling algorithm optimizes the parameters by the deviation between the actual pressure difference and the target pressure difference, generates updated speed control commands and updated opening control commands, and controls the hydraulic pump to adjust according to the updated speed control commands, and controls the CDC valve to adjust according to the updated opening control commands.

[0113] This embodiment effectively solves the coupling problem of traditional electro-hydraulic fully active suspension through the above system architecture and control process, realizes high-precision and fast-response control of damping chamber pressure, realizes full-domain pressure trajectory following control, greatly increases the operating boundary of the control system, and achieves more precise pressure following control with higher control accuracy and faster response.

[0114] Secondly, Figure 6 A schematic diagram of an embodiment of the suspension control device based on mode decoupling of the present invention is shown. Figure 6 As shown, the device 300 includes: a differential pressure calculation module 310, a flow rate calculation module 320, a decoupling algorithm module 330, and an adjustment module 340.

[0115] The differential pressure calculation module 310 is used to determine the target pressure difference between the upper chamber and the lower chamber of the shock absorber based on the vehicle's suspension system signals and vehicle status signals. The flow calculation module 320 is used to input the pressure data of the upper and lower chambers of the shock absorber and the target pressure difference into the flow model; and to determine the target flow of the suspension system based on the output data of the flow model. The decoupling algorithm module 330 is used to decouple the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valve based on the first target flow allocated to the hydraulic pump and the second target flow allocated to the hydraulic pipeline valve in the target flow. The adjustment module 340 is used to control the opening degree of the hydraulic pipeline valve to the target opening degree and to control the speed of the hydraulic pump to the target speed.

[0116] In one optional approach, the suspension system signals include at least one of vehicle roll attitude, vehicle pitch attitude, vehicle braking state, vehicle acceleration state, vehicle cornering state, and suspension dynamic travel vector. The vehicle state signals include at least one of vehicle speed, road surface roughness level, road anticipation state, driving events, comfort parameters, and handling parameters. The pressure difference calculation module 310 is further configured to calculate the vertical vibration damping force, road impact compensation force, roll damping force, and pitch damping force based on the parameters in the suspension system signals and the vehicle state signals, respectively; to calculate the target active force by superimposing the components of the vertical vibration damping force, road impact compensation force, roll damping force, and pitch damping force; and to input the target active force into the shock absorber piston model, using the model output to determine the target pressure difference between the upper and lower chambers of the shock absorber, wherein the shock absorber piston model is constructed based on the principle of piston force balance.

[0117] In one alternative approach, the flow model includes a shock absorber hydraulic cylinder model, a valve flow model, and a damping orifice flow model.

[0118] In an alternative embodiment, the decoupling algorithm module 330 is further configured to: decouple and calculate a first target flow rate of the hydraulic pump based on the load pressure of the hydraulic pump and the target flow rate; decouple and calculate a second target flow rate of the hydraulic pipeline valve based on the target flow rate and the target pressure difference; determine the target speed of the hydraulic pump based on the first target flow rate in conjunction with the load pressure of the hydraulic pump; and solve for the target opening degree of the hydraulic pipeline valve based on the second target flow rate in conjunction with the vehicle status signal.

[0119] In an alternative approach, the decoupling algorithm module 330 is further configured to determine the inverse model of the hydraulic pump flow model based on the load pressure of the hydraulic pump, the volumetric efficiency of the hydraulic pump, and the first target flow rate, so as to obtain the target speed of the hydraulic pump.

[0120] In an alternative embodiment, the decoupling algorithm module 330 is further configured to process the suspension system signal and the vehicle status signal through a fuzzy control algorithm to obtain a correction coefficient; and to determine the inverse model of the valve flow model based on the target pressure difference, the second target flow rate, and the correction coefficient to obtain the target opening degree of the hydraulic pipeline valve.

[0121] In an alternative approach, the mode-decoupling-based suspension control device also includes a data acquisition module 350 for acquiring pressure data from the upper and lower chambers of the shock absorber. The flow calculation module 320 is also used to determine the actual pressure difference; input the deviation between the actual pressure difference and the target pressure difference into the flow model and the inverse model of the flow model, and determine the opening adjustment value and the speed adjustment value according to the model output; the adjustment module 340 is also used to adjust the opening of the hydraulic pipeline valve according to the opening adjustment value, and adjust the speed of the hydraulic pump according to the speed adjustment value.

[0122] Thirdly, Figure 7 The diagram shows a structural schematic of an embodiment of the vehicle of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the vehicle.

[0123] like Figure 7 As shown, the vehicle may include: a suspension system, a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0124] The suspension system, processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408. Communication interface 404 is used to communicate with other network elements such as clients or other servers. Processor 402 executes program 410, specifically performing the relevant steps described in the above embodiment of the suspension control method based on pattern decoupling. The suspension system includes shock absorbers and a hydraulic control assembly. The shock absorber has independent upper and lower chambers. The hydraulic control assembly includes a hydraulic pump, hydraulic pipeline valves, and hydraulic pipelines. The hydraulic pump is connected to the upper and lower chambers of the shock absorber via hydraulic pipelines. The hydraulic pipeline valves are located within the hydraulic pipelines to dynamically adjust the damping force of the shock absorber.

[0125] Specifically, program 410 may include program code, which includes computer-executable instructions. Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The vehicle may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0126] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0127] Specifically, program 410 can be called by processor 402 to enable the vehicle to implement the method provided in the first aspect.

[0128] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing at least one executable instruction that, when executed on a mode-decoupling-based suspension control device / vehicle, causes the mode-decoupling-based suspension control device / vehicle to perform the mode-decoupling-based suspension control method in any of the above method embodiments.

[0129] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Furthermore, the embodiments of this invention are not directed to any particular programming language.

[0130] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. Similarly, for the sake of brevity and to aid in understanding one or more aspects of the invention, in the description of exemplary embodiments of the invention above, various features of the embodiments are sometimes grouped together in a single embodiment, figure, or description thereof. The claims, which follow the detailed description, are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0131] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components, except that at least some of such features and / or processes or units are mutually exclusive.

[0132] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A suspension control method based on mode decoupling, characterized in that, The method includes: Based on the vehicle's suspension system signals and vehicle status signals, determine the target pressure difference between the upper and lower chambers of the shock absorber; Input the pressure data of the upper and lower chambers of the shock absorber and the target pressure difference into the flow model; The target flow rate of the suspension system is determined based on the output data of the flow model. Based on the first target flow rate allocated to the hydraulic pump and the second target flow rate allocated to the hydraulic pipeline valves, the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valves are decoupled and obtained. The opening degree of the hydraulic pipeline valves is adjusted to the target opening degree, and the speed of the hydraulic pump is adjusted to the target speed.

2. The suspension control method based on mode decoupling as described in claim 1, characterized in that, The step of decoupling the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valve based on the first target flow allocated to the hydraulic pump and the second target flow allocated to the hydraulic pipeline valve from the target flow includes: Based on the load pressure of the hydraulic pump and the target flow rate, the first target flow rate of the hydraulic pump is calculated in a decoupled manner, and based on the target flow rate and the target pressure difference, the second target flow rate of the hydraulic pipeline valve is calculated in a decoupled manner. Based on the load pressure of the hydraulic pump, the target speed of the hydraulic pump is determined according to the first target flow rate; Based on the vehicle status signal and the second target flow rate, the target opening degree of the hydraulic pipeline valve is determined.

3. The suspension control method based on mode decoupling as described in claim 2, characterized in that, The step of determining the target speed of the hydraulic pump based on the load pressure of the hydraulic pump and the first target flow rate includes: Based on the hydraulic pump's load pressure, volumetric efficiency, and first target flow rate, the inverse model of the hydraulic pump flow rate model is determined, and the target speed of the hydraulic pump is obtained.

4. The suspension control method based on mode decoupling as described in claim 2, characterized in that, The step of determining the target opening degree of the hydraulic pipeline valve based on the second target flow rate, in conjunction with the vehicle status signal, includes: The correction coefficients are obtained by processing the suspension system signals and vehicle status signals using a fuzzy control algorithm. The inverse model of the valve flow model is determined based on the target pressure difference, the second target flow rate, and the correction coefficient, and the target opening degree of the hydraulic pipeline valve is obtained.

5. The suspension control method based on mode decoupling as described in claim 1, characterized in that, The suspension system signals include at least one of vehicle roll attitude, vehicle pitch attitude, vehicle braking state, vehicle acceleration state, vehicle cornering state, and suspension travel vector. The vehicle state signals include at least one of vehicle speed, road surface roughness level, road anticipation state, driving events, comfort parameters, and handling parameters. The step of determining the target pressure difference between the upper and lower chambers of the shock absorber based on the vehicle's suspension system signals and vehicle state signals includes: The vertical vibration damping force, road impact compensation force, roll damping force, and pitch damping force are calculated based on the parameters in the suspension system signal and the vehicle status signal, respectively. The target active force is obtained by superimposing the components of vertical vibration suppression force, road impact compensation force, roll suppression force, and pitch suppression force. The target active force is input into the shock absorber piston model, and the target pressure difference between the upper chamber and the lower chamber of the shock absorber is determined by the model output. The shock absorber piston model is constructed based on the principle of piston force balance.

6. The suspension control method based on mode decoupling as described in claim 1, characterized in that, The flow models include the shock absorber hydraulic cylinder model, the valve flow model, and the damping orifice flow model.

7. The suspension control method based on mode decoupling as described in claim 1, characterized in that, After the steps of adjusting the opening degree of the control hydraulic pipeline valve to the target opening degree and adjusting the speed of the control hydraulic pump to the target speed, the following steps are included: Collect pressure data from the upper and lower chambers of the shock absorber to determine the actual pressure difference; The deviation between the actual pressure difference and the target pressure difference is input into the flow model and the inverse model of the flow model, and the opening adjustment value and the speed adjustment value are determined according to the model output. The opening degree of the hydraulic pipeline valve is adjusted according to the opening degree adjustment value, and the speed of the hydraulic pump is adjusted according to the speed adjustment value.

8. A suspension control device based on mode decoupling, characterized in that, The device includes: The differential pressure calculation module is used to determine the target pressure difference between the upper and lower chambers of the shock absorber based on the vehicle's suspension system signals and vehicle status signals. The flow calculation module is used to input the pressure data of the upper and lower chambers of the shock absorber and the target pressure difference into the flow model; and to determine the target flow of the suspension system based on the output data of the flow model. The decoupling algorithm module is used to decouple the target speed of the hydraulic pump and the target opening degree of the hydraulic pipeline valve based on the first target flow allocated to the hydraulic pump and the second target flow allocated to the hydraulic pipeline valve in the target flow. The adjustment module is used to control the opening degree of the hydraulic pipeline valves to the target opening degree, and to control the speed of the hydraulic pump to the target speed.

9. A vehicle, characterized in that, include: The system includes a suspension system, a processor, a memory, a communication interface, and a communication bus, wherein the suspension system, the processor, the memory, and the communication interface communicate with each other via the communication bus. The suspension system includes shock absorbers and a hydraulic control assembly. The shock absorber has independent upper and lower chambers. The hydraulic control assembly includes a hydraulic pump, hydraulic line valves, and hydraulic lines. The hydraulic pump is connected to the upper and lower chambers of the shock absorber through the hydraulic lines. The hydraulic line valves are located in the hydraulic lines to dynamically adjust the damping force of the shock absorber. The memory is used to store at least one executable instruction that causes the processor to perform the operation of the suspension control method based on mode decoupling as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores at least one executable instruction, which, when executed on a mode-decoupled suspension control device / vehicle, causes the mode-decoupled suspension control device / vehicle to perform the operation of the mode-decoupled suspension control method as described in any one of claims 1-7.

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