Intelligent control method and system for hybrid engine

Abstract

The application discloses an intelligent control method and system of a hybrid engine, and relates to the technical field of intelligent control of new energy vehicles.Under the time window before the mechanical action of a clutch or an engine is completed after a power mode switching instruction is issued, an impact torque acting on a driving shaft and a change amount of equivalent mass are predicted, are converted into feedforward compensation forces of four suspension actuators, and are superposed with feedback control forces to drive the suspension to complete active power preset in advance, the equivalent sprung mass of a suspension dynamics model is reconstructed online according to a current power working mode, and suspension feed energy power is brought into an engine, a motor, a battery and a suspension four-source power balance equation for collaborative optimization.The application can inhibit mode switching impact, improve ride comfort and reduce vehicle energy consumption, and is suitable for intelligent chassis control of hybrid electric vehicles.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for new energy vehicles, specifically to an intelligent control method and system for hybrid power engines. Background Technology

[0002] Hybrid electric vehicles utilize the combined operation of an internal combustion engine and a drive motor. In pure electric mode, the drive motor drives the wheels alone. In series mode, the engine drives a generator to charge the battery, which in turn drives the wheels. In parallel mode, the engine and drive motor work together to drive the vehicle. Some models also have a mode where the engine directly drives the wheels. The vehicle controller dynamically determines the current operating mode based on information such as vehicle speed, throttle opening, and battery state of charge, and issues corresponding instructions to the engine management system, motor controller, and clutch actuator to complete the switching of operating modes. At the same time, modern vehicles are generally equipped with active or semi-active suspension systems. These systems collect road excitation and vehicle attitude information through vehicle height sensors, inertial measurement units, and wheel speed sensors, and the chassis domain controller adjusts the suspension damping force or active driving force in real time to improve the vehicle's ride comfort and handling stability.

[0003] Current solutions for mitigating the impact of hybrid mode switching primarily focus on compensation within the power domain. A typical process involves: the vehicle controller determining the target operating mode based on driver torque requirements and battery status, issuing a switching command; the engine management system adjusting start-stop or fuel injection strategies; the clutch actuator engaging or disengaging according to a preset sequence; and the motor controller adjusting the motor output torque in real-time based on engine torque variations to fill or offset torque gaps, thereby reducing fluctuations in the combined torque of the drive shaft. Regarding the suspension system, existing active or semi-active suspension control schemes typically operate independently. A typical structure involves: vehicle posture and road excitation information being collected by sensors and input to the suspension domain controller; the controller, based on a two-degree-of-freedom (two-degrees of freedom) or quarter-degree-of-freedom vehicle dynamics model (either sprung or unsprung), and combining feedback control algorithms such as ceiling damping and linear quadratic adjustment, solving for and outputting suspension damping force or active force commands in real-time to drive actuators. The entire process relies solely on the suspension's own state variables for closed-loop feedback adjustment, without receiving any feedforward information from the power domain.

[0004] The aforementioned existing technical solutions have the following technical defects: First, because the existing solutions only compensate for engine-side torque fluctuations within the power domain through motor torque compensation, and motor torque compensation has limitations in response bandwidth and execution accuracy, it cannot completely eliminate the mechanical impact components that have been transmitted to the vehicle body through the engine mounts and transmission system. Therefore, the vehicle body will still experience perceptible pitch and longitudinal vibration, resulting in a decrease in ride comfort. Second, because the suspension system operates independently and only adjusts based on road excitation and vehicle posture, it fails to detect upcoming mode switching events in the power domain. The suspension controller is always in a passive state, responding only after the event occurs, missing the time window to pre-adjust suspension power and achieve active buffering before the impact reaches the vehicle body. Third, the classic suspension dynamics model treats sprung and unsprung mass as constants or slow variables, without considering the significant abrupt changes in the equivalent unsprung mass of the front compartment and the torque distribution of the whole vehicle caused by engine intervention or withdrawal. At the moment of power mode switching, a mismatch will occur between the dynamics model on which the suspension controller is based and the actual dynamic characteristics of the vehicle, resulting in deviations in the calculation of control quantities. Fourth, the existing hybrid energy management algorithm only makes power allocation decisions among the engine, motor and battery, without including the damping energy consumption or vibration energy feed state of the suspension system in the unified allocation range of energy flow. Under conditions with high suspension energy consumption, such as bumpy roads, the energy utilization efficiency of the whole vehicle needs to be improved, and the engine may be forced to intervene more frequently to make up for the power gap.

[0005] Those skilled in the art generally believe that the suspension domain controller only needs to perform closed-loop feedback adjustment based on the road excitation and vehicle posture information collected by its own sensors to meet the ride comfort requirements. Introducing the mode switching event that has not yet been completed in the power domain into the suspension feedforward control in advance will be difficult to achieve effective compensation due to the mismatch between the response bandwidth and timing of the power domain and the suspension domain, and may even introduce new disturbances due to prediction errors. Based on this technical understanding, the existing technology has long failed to attempt to build a cross-domain feedforward coordination mechanism between the power domain and the suspension domain. This invention breaks through the above technical understanding by constructing a transient impact prediction model within a deterministic time window after the power mode switching command is issued and before the mechanical action is completed, thereby realizing reliable feedforward transmission of power domain information to the suspension domain. To this end, we propose an intelligent control method and system for hybrid engines. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent control method and system for hybrid power engines.

[0007] The technical problem this invention aims to solve is that during the power mode switching process of hybrid electric vehicles, due to the independent control of the power domain and suspension domain and the lack of joint modeling and feedforward coordination mechanisms, the torque fluctuations and inertia changes generated by the powertrain cannot be detected and actively suppressed by the suspension system in advance, which in turn causes impacts such as vehicle pitch and longitudinal vibration, affecting ride comfort. At the same time, the existing suspension control model does not adaptively update with changes in power operating mode, resulting in model mismatch problems when the power state changes abruptly. In addition, the existing hybrid energy management algorithm does not incorporate the energy consumption and energy recharge states of the suspension system, resulting in the lack of coordinated optimization between the power system and the chassis system in the energy dimension, and the overall vehicle energy efficiency needs to be improved.

[0008] To address the aforementioned technical problems, this invention provides an intelligent control method for a hybrid engine, comprising: acquiring a power mode switching command issued by the vehicle controller, a current engine speed signal, a current motor speed and torque signal, and a clutch engagement state signal; recording the moment the switching command is issued as the prediction start moment; constructing a transient impact prediction model corresponding to the current switching event based on the target operating mode corresponding to the switching command; calculating a predicted impact torque using the transient impact prediction model, combined with the current engine speed change rate, clutch torque transmission progress, and real-time motor output torque; and based on the predicted impact torque, combined with... The vehicle's center of gravity position parameters and wheelbase parameters are used to calculate the equivalent mass change of the front compartment. The predicted impact torque and the equivalent mass change are then allocated and converted into feedforward compensation forces that should be applied to the four suspension actuators (left front, right front, left rear, and right rear). These feedforward compensation forces are then sent to the suspension domain controller, which superimposes them with the feedback control force calculated based on road excitation and vehicle attitude to form control commands for the suspension actuators. Before the actual completion of the mechanical actions corresponding to clutch engagement, clutch disengagement, and engine start / stop, the suspension actuators are controlled to complete the preset output of active force according to the control commands.

[0009] Based on the above methods, this invention further provides an adaptive reconstruction method for the suspension dynamics model using the current operating mode of the hybrid powertrain as a parameter. The method involves obtaining the operating mode, acquiring the corresponding equivalent mass increment from a pre-calibrated mode-mass correction correspondence, adding the reference sprung mass to the equivalent mass increment to obtain the reconstructed equivalent sprung mass, and updating the mass parameters of the suspension dynamics model. During the transition period of power mode switching, the equivalent sprung mass undergoes a smooth transition process. This invention also provides the incorporation of suspension damping energy consumption and energy recharge states into the relationship between the engine, motor, battery, and suspension. The present invention provides a collaborative energy management method based on the four-source power balance equation. This method periodically collects the available power of each energy source and determines whether the road excitation is under bumpy conditions. Under bumpy conditions, the predicted energy feed power of the suspension is incorporated into the power balance equation, and the power distribution ratio between the engine and the motor is resolved to reduce the engine intervention power. Accordingly, the present invention provides an intelligent control system for implementing the above method. A cross-domain collaborative control module is added between the power domain controller and the suspension domain controller. This module integrates three functional sub-modules: a transient impact prediction unit, a suspension dynamics model adaptive reconstruction unit, and a four-source energy collaborative distribution unit.

[0010] Compared with the prior art, the beneficial effects of the present invention by adopting the above technical solution are as follows:

[0011] 1. This invention applies a reverse feedforward compensation force to the suspension system before the power impact is transmitted to the vehicle body, which can further absorb the impact on the second line of defense in addition to the motor torque compensation, effectively suppressing the vehicle pitch and vertical impact during the power mode switching process and improving ride comfort.

[0012] 2. This invention uses the power operating mode as the underlying parameter to perform online adaptive reconstruction of the equivalent sprung mass of the suspension dynamics model, eliminating the model mismatch problem at the moment of mode switching and improving the suspension control accuracy;

[0013] 3. This invention incorporates suspension damping energy consumption and power recharge into the four-source power balance equation for synergistic optimization. Under bumpy conditions, the suspension power recharge can be used to fill part of the drive power gap, reduce the frequency of engine intervention, and improve the overall vehicle energy utilization efficiency. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the suspension feedforward impact compensation process for hybrid mode switching in an embodiment of the present invention;

[0015] Figure 2 This is a schematic diagram of the adaptive reconstruction process of the suspension dynamics model in an embodiment of the present invention;

[0016] Figure 3 This is a schematic diagram of the four-source collaborative energy management process in an embodiment of the present invention. Detailed Implementation

[0017] The following is in conjunction with the appendix Figure 1-3 The specific embodiments of the present invention will be further described below. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0018] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0019] I. System Overall Architecture:

[0020] The system described in this invention comprises two major functional domains: a power domain and a chassis domain. The power domain includes a vehicle controller, an engine management system, a motor controller, and a clutch actuator. The modules are connected via an internal bus within the power domain. The vehicle controller determines the current operating mode based on information such as vehicle speed, throttle opening, and battery state of charge, and issues corresponding commands to the engine management system, motor controller, and clutch actuator. The chassis domain includes a suspension domain controller, four suspension actuators corresponding to the positions of the left front, right front, left rear, and right rear wheels, a vehicle body inertial measurement unit, and a suspension height sensor. The suspension domain controller calculates and outputs the feedback control force of the suspension actuators based on the road excitation and vehicle attitude information collected by the sensors.

[0021] Between the power domain and the chassis domain, this invention adds a cross-domain collaborative control module. This module is bidirectionally connected to the vehicle controller in the power domain and the suspension domain controller in the chassis domain via an in-vehicle gigabit Ethernet or a controller area network extension bus. It is used to receive mode switching commands, engine speed and torque signals, and motor speed and torque signals issued by the power domain, and to send the predicted feedforward compensation signal to the suspension domain controller in real time. It also receives the suspension status signal and energy feeding power signal fed back by the suspension domain controller. The cross-domain collaborative control module integrates three functional sub-modules: a transient impact prediction unit, a suspension dynamics model adaptive reconstruction unit, and a four-source energy collaborative distribution unit. These correspond to the three innovations of this invention, and their detailed implementation methods are described below.

[0022] II. Transient attitude control method with cross-domain feedforward compensation:

[0023] The core of this technical solution is to complete the impact prediction and feedforward signal transmission within the time window after the power switching command is issued and before the clutch or engine has completed its mechanical action. The detailed implementation steps are as follows:

[0024] The cross-domain collaborative control module acquires the mode switching command, current engine speed signal, current motor speed and torque signal, and clutch engagement status signal issued by the vehicle controller in real time through the power domain internal bus, and records the time when the switching command is issued as the prediction start time.

[0025] Based on the target working mode corresponding to the switching command, the equivalent moment of inertia parameter, clutch torque transmission characteristic curve and motor torque response characteristic of this type of switching event are read from the pre-calibrated mode switching characteristic database to construct a transient impact prediction model for the current switching event.

[0026] Using the constructed prediction model, combined with the current engine speed change rate, clutch torque transmission progress, and real-time motor output torque, the predicted impact torque is calculated. The calculation formula is as follows:

[0027] ;

[0028] in, express The impact torque acting on the drive shaft is predicted at all times. This represents the equivalent moment of inertia of the engine side and the clutch side referred to the drive shaft. express The engine crankshaft angular velocity at all times, This represents the rate of change of the engine's angular velocity, i.e., angular acceleration. express The actual torque transmitted by the clutch at any given moment. express The driving torque output by the motor controller at any time is shown in the above formula, which reflects that the impact torque on the drive shaft is composed of the sum of the engine side inertial torque and the clutch transmitted torque, minus the motor compensation torque. This remaining component is the impact component that cannot be eliminated by motor torque compensation and needs to be further absorbed by the suspension system.

[0029] Based on the predicted impact torque, combined with the vehicle's center of gravity position parameters and wheelbase parameters, the equivalent mass change is calculated, and the predicted impact torque and equivalent mass change are converted into the feedforward compensation force that each of the four suspension actuators should apply using the following formula:

[0030] ;

[0031] in, express Time of the first The feedforward compensation force that each suspension actuator should output Take the four positions in sequence: left front, right front, left back, and right back. Indicates the first The pitch force distribution coefficient of each suspension actuator is pre-calibrated based on the ratio of the longitudinal distance from the vehicle's center of gravity to each wheel. Indicates the wheelbase of the entire vehicle. express The amount of change in the equivalent mass of the front cabin caused by the switching of power modes at all times. Indicates the first The load distribution coefficient of each suspension actuator is obtained by pre-calibrating the static axle load distribution of the entire vehicle. The first term of the above formula represents the distribution of the vehicle pitch tendency caused by the impact torque at each wheel position, and the second term represents the distribution of the static load change caused by the equivalent mass change at each wheel position. The sum of the two is the feedforward compensation force that the suspension actuator should finally output.

[0032] The cross-domain collaborative control module determines whether the absolute value of the predicted impact torque is greater than the preset impact torque threshold. If it is greater than the threshold, the calculated four-way feedforward compensation force is sent to the suspension domain controller in real time. If it is not greater than the threshold, the original feedback control strategy of the suspension system is maintained and the feedforward action is not triggered, thereby avoiding frequent triggering of feedforward compensation under the condition that the impact intensity is low and insufficient to cause a perceptible body response.

[0033] After receiving the feedforward compensation force command, the suspension domain controller superimposes it with the feedback control force calculated based on road excitation and vehicle posture to form the control command of the suspension actuator. Before the actual completion of mechanical actions such as clutch engagement, clutch disengagement, or engine start-stop, the controller controls the suspension actuator to complete the preset output of the active force in advance, thereby forming a reverse cancellation effect before the impact torque is actually transmitted to the vehicle body.

[0034] After the mechanical action is completed, the system collects the actual pitch angular velocity and vertical acceleration fed back by the vehicle body inertial measurement unit, compares them with the aforementioned predicted values, calculates the prediction error, and uses the error feedback to correct the equivalent moment of inertia parameter and distribution coefficient in the prediction model, realizing online self-learning and continuous optimization of the feedforward model. After iterative correction through multiple mode switching events, the prediction accuracy of the transient impact prediction model can be gradually improved with vehicle use, adapting to long-term operating conditions such as engine mount aging and changes in clutch friction characteristics.

[0035] III. Adaptive Reconstruction Method for Suspension Dynamics Model Based on Dynamic State:

[0036] The quarter-vehicle suspension dynamics model includes a sprung mass module, a suspension spring and damper module, an unsprung mass module, and a tire module. This invention adds a power mode sensing and mass correction input terminal next to the sprung mass module. This input terminal receives the current operating mode signal from the power domain and outputs the corrected equivalent sprung mass value in real time through a lookup table. The corrected value is fed back to update the mass parameter terminal of the suspension dynamics model. The operating modes include pure electric mode, series mode, parallel mode, and direct drive mode.

[0037] The corresponding equation for the quarter-vehicle suspension dynamics of this innovation is:

[0038] ;

[0039] in, express The equivalent sprung mass after adaptive reconstruction at any given moment. Represents the vertical displacement of the mass on the spring. The vertical acceleration representing the mass on the spring. Represents the vertical velocity of the mass on the spring. This represents the vertical displacement of the unsprung mass. Represents the vertical velocity of the unsprung mass. Indicates the suspension damping coefficient. This indicates the suspension spring stiffness coefficient. This represents the feedforward compensation force calculated from the aforementioned innovation points. This indicates the active control force calculated by the suspension controller based on feedback.

[0040] The adaptive correction rule for the equivalent spring mass is as follows:

[0041] ;

[0042] in, This represents the reference sprung mass of the vehicle calibrated under a reference operating condition, which is a pure electric mode with the engine completely disengaged. express The operating mode of the hybrid powertrain at all times. This represents the equivalent mass increment correction function corresponding to the current operating mode, caused by engine intervention or withdrawal. This function is pre-calibrated into a lookup table form according to different operating modes.

[0043] The detailed implementation steps of this method are as follows: The cross-domain collaborative control module receives the current working mode identification signal from the power domain feedback in real time. This signal is obtained by the vehicle controller based on the engine speed, clutch engagement state, and motor working state. According to the received working mode identification, the corresponding equivalent mass increment is retrieved from the pre-calibrated mode and mass correction lookup table, and the equivalent sprung mass at the current moment is calculated according to the aforementioned formula. The calculated equivalent sprung mass is written into the suspension dynamics model parameter register maintained by the suspension domain controller in real time, replacing the original static or gradually changing mass parameters, and completing the online reconstruction of the model parameters. Based on the reconstructed suspension dynamics model, the suspension domain controller, combined with the current vehicle acceleration, suspension relative displacement, and other feedback quantities, re-solves the feedback control force, and outputs it to the suspension actuator after superimposing it with the feedforward compensation force. During the transition period when the power mode is switched, the system performs smooth transition processing on the equivalent sprung mass according to the preset time constant, so that it changes continuously with time, avoiding discontinuous jumps in the control force output due to step changes in mass parameters, thereby ensuring the stability of suspension control.

[0044] IV. A global energy management approach that combines suspension energy replenishment with multi-source power coordination:

[0045] The energy management module periodically collects four inputs: available engine power, available motor power, available battery charging and discharging power, and current suspension damping energy consumption and energy recharge power. It determines whether the current road excitation level is under the preset bumpy condition. If it is under the bumpy condition, it calculates the expected energy recharge power of the suspension and incorporates it into the power balance equation. It then re-solves the power distribution ratio between the engine and the motor, prioritizing the reduction of engine intervention power. If it is not under the bumpy condition, it distributes power according to the conventional strategy. The energy management module sends the final distribution results to the engine management system, the motor controller, and the suspension domain controller. The suspension domain controller adjusts the damping coefficient accordingly to match the energy recharge target. The system continuously monitors the battery state of charge and the actual power execution of each component, forming a closed-loop feedback correction.

[0046] The formula for calculating the suspension energy recharge power is:

[0047] ;

[0048] in, express The actual energy recovery power of the suspension system at all times. This represents the energy conversion efficiency coefficient of the suspension energy supply device, and its value ranges from greater than zero to no greater than one. Indicates the suspension actuator is in The damping force output at all times, This indicates the relative speed of motion between the two ends of the suspension actuator;

[0049] The global optimization objective function for four-source coordinated energy management is:

[0050] ;

[0051] in, In the prediction time domain Total energy consumption cost within, express The equivalent power output corresponding to the fuel consumed by the engine at any given time. express The charge and discharge power of the battery is measured at constant speeds, and the square of this term is used to suppress high-current charging and discharging of the battery to extend its lifespan. This indicates that the aforementioned suspension energy supply power, expressed as a negative term, offsets the overall cost. , , These represent the weighting coefficients for fuel consumption, battery loss, and suspension energy depletion, respectively, and their values ​​are preset to specific values ​​based on the vehicle calibration requirements.

[0052] The detailed implementation steps of this method are as follows: The energy management module collects the current available power range of the engine, the current available power range of the motor, the current allowable charge and discharge power range of the battery, and the current measured damping force and relative speed of the suspension at fixed intervals. Based on the collected suspension damping force and relative speed, the actual energy feeding power of the suspension at the current moment is calculated according to the aforementioned energy feeding power formula. Combined with the recent road excitation statistical characteristics, the average available energy feeding power of the suspension in the future prediction time domain is predicted. Based on the hierarchical model predictive control architecture, in the upper control layer, the vehicle drive power demand, battery state of charge constraints, and the predicted energy feeding power of the suspension are used as inputs. The engine power and relative speed are solved in the prediction time domain according to the aforementioned global optimization objective function. The power allocation ratio of the motor ensures that the total energy consumption meets the preset optimization conditions. Under the premise of meeting the driving demand, the suspension power is used first to fill part of the driving power gap, reducing the frequency and power of engine intervention. In the lower control layer, the target suspension power obtained from the upper layer is converted into the target damping coefficient of the suspension actuator. Combined with the aforementioned feedforward compensation force and the adaptively reconstructed dynamic model, the comprehensive control command of the suspension actuator is solved. The energy management module sends the final power allocation result to the engine management system, motor controller and suspension domain controller respectively, and re-executes the above steps at the beginning of the next control cycle to form a rolling optimization closed-loop control process.

[0053] V. System Hardware Implementation Description:

[0054] The method described in this invention can be implemented based on the centralized domain controller architecture commonly used in intelligent connected new energy vehicles. It does not require additional sensor hardware, but only needs to reuse existing engine speed sensors, motor resolver sensors, vehicle body inertial measurement units and suspension height sensors. High-speed data interaction between the power domain and chassis domain is achieved through onboard gigabit Ethernet or controller area network extension bus. The function of the cross-domain collaborative control module can be deployed in the existing domain controller or vehicle central computing platform through software, and the function can be implemented through remote upgrade.

[0055] VI. Alternative Implementation Methods:

[0056] On vehicle platforms that do not have high-speed in-vehicle Ethernet or controller area network extension bus, the transient impact prediction function of the cross-domain collaborative control module can be directly integrated into the vehicle controller. The vehicle controller can directly calculate the predicted impact torque while generating the mode switching command, and send the feedforward compensation force command to the suspension domain controller in the form of a high-priority message through the existing controller area network bus. Thus, without adding independent collaborative control module hardware, a cross-domain feedforward compensation effect similar to the above-mentioned implementation method can be achieved, with the only difference that the communication real-time performance is slightly lower than that of the gigabit Ethernet solution.

[0057] For the adaptive reconstruction of the suspension dynamics model, instead of using a lookup table based on the working mode, a real-time estimation function for the equivalent mass can be constructed based on continuous variables such as engine speed and clutch engagement. By weighted fusion of the engine speed change rate and clutch engagement, the equivalent sprung mass correction can be continuously estimated, thus achieving a smoother model parameter transition than discrete mode lookup. This is suitable for application scenarios with high requirements for the smoothness of the mode switching transition process.

[0058] The above embodiments are only some examples of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions and improvements made within the concept and principles of the present invention should be included within the scope of protection of the present invention.

[0059] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, any modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for intelligent control of a hybrid engine, characterized in that, include: The system acquires the power mode switching command issued by the vehicle controller, the current engine speed signal, the current motor speed and torque signal, and the clutch engagement status signal. It records the moment the switching command is issued as the prediction start time. Based on the target operating mode corresponding to the switching command, a transient impact prediction model corresponding to this switching event is constructed. Using this transient impact prediction model, combined with the current engine speed change rate, clutch torque transmission progress, and real-time motor output torque, the predicted impact torque is calculated. Based on the predicted impact torque, combined with the vehicle's center of gravity position parameters and wheelbase parameters, the front compartment, etc., are calculated. The effective mass change is calculated, and the predicted impact torque and the equivalent mass change are allocated and converted into feedforward compensation forces that should be applied by the four suspension actuators (left front, right front, left rear, and right rear). The feedforward compensation forces are sent to the suspension domain controller, which superimposes the feedforward compensation forces with the feedback control forces calculated based on road excitation and vehicle posture to form control commands for the suspension actuators. Before any corresponding mechanical action in clutch engagement, clutch disengagement, or engine start / stop is actually completed, the suspension actuators are controlled to complete the preset output of active force according to the control commands.

2. The intelligent control method for a hybrid engine according to claim 1, characterized in that: The steps for calculating the predicted impact torque include: obtaining the equivalent moment of inertia of the engine side and the clutch side referred to the drive shaft, the rate of change of the engine crankshaft angular velocity, the actual torque transmitted by the clutch, and the driving torque output by the motor controller; adding the product of the equivalent moment of inertia and the rate of change of the angular velocity to the actual torque transmitted by the clutch; and then subtracting the driving torque output by the motor to obtain the predicted impact torque.

3. The intelligent control method for a hybrid engine according to claim 1, characterized in that: The step of converting the predicted impact torque and the equivalent mass change into the feedforward compensation force that each of the four suspension actuators should apply includes: for each of the four suspension actuators (left front, right front, left rear, and right rear), multiplying the pre-calibrated corresponding pitch force distribution coefficient by the quotient obtained by dividing the predicted impact torque by the vehicle wheelbase, and adding the product of the pre-calibrated corresponding load distribution coefficient, the equivalent mass change, and the gravitational acceleration constant to obtain the feedforward compensation force corresponding to that suspension actuator.

4. The intelligent control method for a hybrid engine according to claim 1, characterized in that, Also includes: The system determines whether the absolute value of the predicted impact torque is greater than a preset impact torque threshold. If the absolute value of the predicted impact torque is greater than the preset impact torque threshold, the system executes the step of issuing the feedforward compensation force. If the absolute value of the predicted impact torque is not greater than the preset impact torque threshold, the original feedback control strategy of the suspension system is maintained. After the mechanical action is completed, the actual pitch angular velocity and vertical acceleration fed back by the vehicle body inertial measurement unit are collected and compared with the predicted values ​​corresponding to the transient impact prediction model to obtain the prediction error. The equivalent moment of inertia parameter and distribution coefficient in the transient impact prediction model are corrected according to the prediction error.

5. The intelligent control method for a hybrid engine according to claim 1, characterized in that, Also includes: The current operating mode of the hybrid powertrain is obtained. Based on the operating mode, the equivalent mass increment corresponding to the operating mode is obtained from the pre-calibrated mode-mass correction correspondence. The reference sprung mass is added to the equivalent mass increment to obtain the adaptively reconstructed equivalent sprung mass. The equivalent sprung mass is updated to the mass parameters of the suspension dynamics model. Based on the updated suspension dynamics model, combined with the vehicle acceleration and relative suspension displacement, the feedback control force of the suspension controller is calculated. The feedback control force is superimposed with the feedforward compensation force to obtain the control command of the suspension actuator.

6. The intelligent control method for a hybrid engine according to claim 5, characterized in that: During the transition period when the power mode is switched, the equivalent sprung mass is smoothly processed according to a preset time constant, so that the equivalent sprung mass changes continuously with time, avoiding discontinuous jumps in the control force output caused by step changes in mass parameters.

7. The intelligent control method for a hybrid engine according to claim 1, characterized in that, It also includes: periodically collecting the available power of the engine, the available power of the motor, the allowable charging and discharging power range of the battery, and the current damping force and relative motion speed of the suspension actuator; calculating the current energy supply power of the suspension system based on the damping force and the relative motion speed; determining whether the current road excitation is under a preset bumpy condition; when under the bumpy condition, incorporating the energy supply power into the power balance equation of the engine, motor, battery and suspension; resolving the power distribution ratio of the engine and motor; reducing the engine's intervention power; and when not under the bumpy condition, distributing power according to a preset conventional strategy.

8. The intelligent control method for a hybrid engine according to claim 1, characterized in that, The current power supply of the suspension system is calculated as follows: the power supply power is obtained by multiplying the energy conversion efficiency coefficient of the suspension power supply device, the damping force, and the relative motion speed. The power balance equation is constructed with the equivalent power of the engine fuel consumption, the square of the battery charging and discharging power, and the power supply power as variables in the prediction time domain to construct the total energy consumption cost. By rolling the solution in the prediction time domain, the value of the total energy consumption cost is made to meet the preset optimization conditions, and the power distribution ratio between the engine and the motor is obtained.

9. An intelligent control system for a hybrid engine, characterized in that, The system includes a power domain and a chassis domain. The power domain includes a vehicle controller, an engine management system, a motor controller, and a clutch actuator. The chassis domain includes a suspension domain controller, four suspension actuators corresponding to the left front, right front, left rear, and right rear wheel positions, a vehicle body inertial measurement unit, and a suspension height sensor. It also includes a cross-domain collaborative control module, which is communicatively connected to both the vehicle controller and the suspension domain controller. This module receives power mode switching commands, engine speed signals, motor speed and torque signals, and clutch engagement status signals from the vehicle controller. It predicts the impact torque and equivalent mass change, and sends the predicted feedforward compensation force to the suspension domain controller. The suspension domain controller then controls the four suspension actuators to output the preset active force before the corresponding mechanical action is actually completed.

10. The intelligent control system for a hybrid engine according to claim 9, characterized in that: The cross-domain collaborative control module includes a transient impact prediction unit, a suspension dynamics model adaptive reconstruction unit, and a four-source energy collaborative allocation unit. The transient impact prediction unit is used to perform the steps of predicting the impact torque and calculating the feedforward compensation force. The suspension dynamics model adaptive reconstruction unit is used to perform the equivalent sprung mass adaptive reconstruction step. The four-source energy collaborative allocation unit is used to perform the power allocation step.

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