Hybrid drive system drive control method combining energy management and torsional vibration suppression

Abstract

The present application relates to a kind of hybrid power transmission system drive control method combined energy management and torsional vibration suppression, belong to hybrid electric vehicle technical field, comprising the following steps: S1: energy management controller distributes the drive power of engine motor according to driver's intention and vehicle driving state, and determines vehicle driving mode;S2: hybrid controller selects corresponding torsional vibration controller according to the driving mode and switching state of vehicle, and additional motor active control torque command is based on the output of energy management controller;S3: motor controller, engine controller and transmission controller receive command, and carry out speed torque control to power source;S4: the torque speed command of controller is executed to each component of transmission system;S5: sensor of each component of transmission system detects current vehicle driving state, and feedback to upper controller.

Description

Technical Field

[0001] This invention belongs to the field of hybrid electric vehicle technology and relates to a drive control method for a hybrid powertrain that combines energy management and torsional vibration suppression. Background Technology

[0002] Under the overall technological trend of "high integration," "high power density," "lightweight," and "intelligent power" in next-generation hybrid power systems, the rapid response and good controllability of electric motors have made it possible for transmission system vibration reduction to move beyond passive damping, thus enabling hybrid vehicles to eliminate the dual-mass flywheel. Through energy management and power coordination control of hybrid power systems, vehicle fuel economy can be significantly improved, and harmful emissions reduced. However, when energy management and coordination control of the hybrid vehicle's power system are inadequate, NVH (noise, vibration, and harshness) problems can arise under various operating conditions due to torque and speed vibrations of the engine and electric motor, and shocks generated during mode transitions, thereby affecting the vehicle's comfort, economy, and emissions. Therefore, adaptive active vibration suppression methods that eliminate the dual-mass flywheel have become a hot topic in hybrid vehicle research and development, attracting significant attention from domestic scholars and industry.

[0003] In recent years, scholars have focused on active vibration reduction through feedback control and frequency correction, and dynamic coordinated control for torque disturbance compensation. Both of these active vibration suppression methods can effectively attenuate torsional vibration problems in hybrid drive transmission systems. However, since torsional vibration controllers are not integrated with energy management strategies, motor control, engine control, and transmission control, and specific torsional vibration controllers are required for torsional vibration problems in hybrid drive transmission systems under different drive modes and switching states, it is necessary to design a control method that combines energy management strategies and torsional vibration suppression to specifically suppress torsional vibration problems under different drive modes. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a drive control method for a hybrid powertrain that combines energy management and torsional vibration suppression.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A drive control method for a hybrid powertrain that combines energy management and torsional vibration suppression includes the following steps:

[0007] S1: The energy management controller allocates the drive power of the engine motor according to the driver's intention and the vehicle's driving status, and determines the vehicle's driving mode;

[0008] S2: The hybrid controller selects the corresponding torsional vibration controller based on the vehicle's drive mode and switching state, and adds the motor active control torque command to the output of the energy management controller;

[0009] S3: The motor controller, engine controller, and transmission controller receive commands and perform speed and torque control on the power source;

[0010] S4: Each component of the transmission system executes the torque and speed commands issued by the controller;

[0011] S5: Sensors in each component of the transmission system detect the current driving status of the vehicle and feed it back to the upper controller.

[0012] Furthermore, step S1 specifically includes:

[0013] The energy management controller calculates the total torque demand T based on the driver's intention and the current driving status of the vehicle. r Based on the battery's SOC value, an energy management strategy is formulated according to the required torque, SOC range, engine torque range, and motor torque range. The required torque is allocated and transmitted to the hybrid controller, engine controller, and motor controller. The vehicle drive mode is determined and transmitted to the hybrid controller and transmission controller.

[0014] T r =T e_ref +T m_ref

[0015] In the formula, T e_ref For the engine target torque, T m_ref This represents the target torque for the motor.

[0016] Furthermore, step S2 specifically includes:

[0017] The hybrid controller divides the driving modes of hybrid electric vehicles into pure electric drive, engine-only drive, and hybrid drive. Based on whether the clutch state changes during the mode switching process, the driving mode switching is divided into 6 forms.

[0018] First, pure electric drive, hybrid drive, and pure electric-hybrid drive mode switching are listed as typical driving conditions, and corresponding torsional vibration controllers are designed for each. For pure electric drive mode, a hybrid adaptive control algorithm is used to suppress torsional vibration; for hybrid drive mode, a model predictive control algorithm is used to suppress torsional vibration; and for pure electric-hybrid drive mode switching, a model reference adaptive algorithm is used to suppress torsional vibration.

[0019] Furthermore, for the pure electric mode, based on the dynamic model of the transmission system in the pure electric mode, a torsional vibration controller under acceleration is built based on a hybrid adaptive algorithm, and the system transfer function is obtained as follows:

[0020]

[0021] Where Tm * ω represents the target torque of the motor and is the system input. m ζ represents the motor speed, s represents the system output; s represents the transfer function variable, a represents the pole equation coefficients, b0~b3 represents the zero equation coefficients, p represents the control system, and ζ represents the control system. p ω represents the system damping ratio. p Indicates the system poles;

[0022] The ideal model response function is defined as follows:

[0023]

[0024] The feedforward controller is represented as:

[0025]

[0026] Where r represents feedforward control, ζ r ω represents the ideal damping ratio. r Represents the poles of an ideal system;

[0027] The bandpass filter H(s) is expressed as:

[0028]

[0029] Where k represents the filter coefficient;

[0030] Assuming input torque T m * =0, then ω m The response relative to the input disturbance d is:

[0031] ω m =(1-H(s))G p (s)d

[0032] Let k = (1-ζ) p ), ω m Expressed as:

[0033]

[0034] Where d represents the system input disturbance.

[0035] Furthermore, for the hybrid power mode, based on the powertrain dynamics model of the hybrid power mode, a torsional vibration controller under acceleration is constructed using a model prediction algorithm. The system's state-space equation is:

[0036]

[0037] The state variable x consists of the following variables: engine angular velocity, engine-motor angle difference, motor angular velocity, motor-wheel angle difference, and wheel angular velocity; the system control variable is the motor torque T. m The interference quantity is the engine output torque T. e It is the system's disturbance quantity. The system output consists of the angular velocity of the motor, the angular acceleration of the motor, the angular velocity of the wheel and body, and the difference between the angular velocities of the motor and the wheel.

[0038] The state equations of the continuous system are discretized, and the coefficients of each term in the state-space equations are discretized according to the sampling period t. An approximate discretization formula is used to discretize the coefficient matrix. The discretization equations are as follows:

[0039]

[0040] A f =AT s +I

[0041] B f =T s B

[0042] C f =C

[0043] Where I is a 4×4 identity matrix, T s =0.001 represents the sampling period time;

[0044] Change the discrete model to an incremental model:

[0045]

[0046] Among them, Δx(k)=x(k)-x(k-1), Δu(k)=u(k)-u(k-1)

[0047] Construct a predictive model: The state variables of the predictive system are:

[0048]

[0049] Where Δx(k+i|k) represents time point k after the predicted state of the system at time point i; A f Let B represent the coefficients of the predicted state variables, Δx(k) represent the predicted state variables, and B represent the coefficients of the predicted state variables. f Δu(k) represents the coefficient of the predictor control variable;

[0050] The system output prediction is:

[0051]

[0052] Where y(k+1|k) represents the predicted output variable, Cf y(k) represents the coefficients of the predicted output variable, and y(k) represents the output variable.

[0053] Actuator dynamic compensation: When the total delay time of the motor is T d At that time, the linear dynamic system equation can be rewritten as:

[0054]

[0055] Among them, T de For the ideal delay time, T de Numerically, it is T s Integer multiples of;

[0056] An explicit delay time compensation scheme is adopted; x(k+T) de |k) serves as the starting point for the prediction model, and its expression is as follows:

[0057]

[0058] The starting point of the prediction model is defined as:

[0059]

[0060] The discretized system is represented as:

[0061]

[0062] To achieve the desired control objective, a relevant system optimization problem is established, and optimal control is achieved by solving the predictive model of the control system; the cost function is expressed as:

[0063]

[0064] R c (k+1)=[r(k+1) r(k+2)…r(k+N P )] T

[0065] In the formula, R is the reference sequence; Q and R are weight matrices; ||Q(YR) c )|| 2 The goal is to minimize torsional vibration fluctuations at the generator shaft; ||RΔU|| 2 This is achieved by adjusting the rate of change of the power supply during operation;

[0066] To control the motor torque increment within a reasonable range, the following constraints are added to the original optimization problem:

[0067] y min (k)≤y(k)≤y max (k)

[0068] Umin (k)≤U(k)≤U max (k)

[0069] -ΔU min (k)≤ΔU(k)≤ΔU max (k)

[0070] Taking into account the constraints, the objective function can be rewritten in the standard form of a quadratic programming problem as follows:

[0071]

[0072] in,

[0073]

[0074]

[0075] Solve the quadratic programming problem for finding the optimal value.

[0076] Furthermore, the "pure electric to hybrid" mode switching process is divided into five stages: clutch free displacement stage, clutch slippage stage 1, clutch slippage stage 2, speed synchronization stage, and full participation stage. The dynamic equations for each stage are as follows:

[0077]

[0078] Among them, J e and J m These are the moments of inertia of the engine section and the motor section, respectively; ω e and ω m T represents the engine speed and the electric motor speed, respectively. e and T m T represents engine torque and motor torque, respectively; r The equivalent load torque of the motor output shaft is distributed by the energy management system according to the driver's needs; T c This is the maximum frictional torque that the clutch can provide, expressed as follows: Equation Chapter (Next) Section 1

[0079] T c =μ c R c F b N c sign(ω m -ω e )

[0080] In the formula, μ c R c Fc N c These are the friction coefficient of the clutch disc, the effective radius of the clutch disc, the number of clutch discs, and the pressure on the clutch disc;

[0081] If the dynamic model of the clutch free displacement stage is set as the reference model of this controller, then the dynamic equation of the reference model is:

[0082]

[0083] Where, ω m The required rotational speed is calculated using the reference model; T m This is the equivalent torque required by the driver;

[0084] Let the state variable x d =ω m Input variable u d =T m Output variable y d =ω m The disturbance variable d1 = -T r Then the state-space equation of the reference model is:

[0085]

[0086] Given the actual state x and the ideal state x of the system d The tracking error of the system and its reciprocal are obtained as follows:

[0087]

[0088] Substituting the state-space equation of the control system into the above equation, we obtain the dynamic error equation of the system as follows:

[0089]

[0090] Define matrix H m ∈R 2×2 For any Hurwitz matrix, the above equation transforms into:

[0091]

[0092] In the formula, K * ∈R 2×2 L * ∈R 2×2 Their relationship is shown in the following formula:

[0093]

[0094] In the formula, I∈R 2×2 It is the identity matrix;

[0095] The control law and dynamic error of the control system are as follows:

[0096]

[0097] Estimate the unknown parameters of the system control law, and let the estimation error be:

[0098]

[0099] In the formula, and K * and L * The estimated value;

[0100] Replacing the unknown system parameters in the control law with their estimated values, we obtain the adaptive control law as follows:

[0101]

[0102] For the switching process between the two modes of "engine-only - pure electric drive" and "hybrid - pure electric drive", the power switching is done by disconnecting the clutch between the engine and the motor to cut off the engine's output torque. The resulting torsional vibration problem is suppressed by the hybrid adaptive torsional vibration controller in pure electric mode.

[0103] For the process of switching between the two modes of "engine-only drive" and "engine-only-hybrid drive" and "hybrid-engine-only", the power switching is determined by whether the motor outputs effective torque. A model predictive controller in hybrid mode is used to suppress torsional vibration.

[0104] For the switching process between "pure electric-hybrid drive" and "pure electric-engine-only drive" modes, the power switching is achieved by the motor driving the clutch to engage and start the engine to participate in power output. A model reference controller in the pure electric-hybrid drive mode is used to suppress torsional vibration.

[0105] Furthermore, in step S3, the motor controller and engine controller receive the target speed and target torque commands transmitted by the energy management system via CAN; the transmission controller receives the mode selection and switching commands transmitted by the energy management system via CAN.

[0106] Furthermore, in step S4, the motor executes the torque and speed commands issued by the motor controller; the engine executes the torque and speed commands issued by the engine controller; the clutch executes the engagement, disengagement, or switching commands issued by the transmission mechanism; and the transmission executes the gear selection and switching commands issued by the transmission mechanism.

[0107] Furthermore, in step S5, the speed sensors and acceleration sensors distributed on various components of the transmission system record the current driving status of the vehicle and transmit them to the motor controller, engine controller, transmission controller and hybrid controller, and simultaneously transmit them to the energy management controller via CAN.

[0108] The beneficial effects of this invention are: this method combines energy management and torsional vibration control of the transmission system, thereby improving the applicability of torsional vibration control.

[0109] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0110] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0111] Figure 1 For the control method flowchart;

[0112] Figure 2 This is a structural diagram of the control method;

[0113] Figure 3 This is a schematic diagram of the driving mode;

[0114] Figure 4 A schematic diagram for selecting a torsional vibration controller. Detailed Implementation

[0115] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0116] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0117] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0118] This invention addresses the torsional vibration problem in the transmission system of P2 hybrid electric vehicles by proposing a hybrid powertrain drive control method that combines energy management and torsional vibration suppression. First, the energy management controller allocates the drive power of the engine and motor based on the driver's intention and the vehicle's driving state, and determines the vehicle's driving mode. Next, a torsional vibration controller for typical operating conditions is designed. The hybrid controller selects the corresponding torsional vibration controller based on the vehicle's driving mode and switching state, and adds an active motor control torque command to the output of the energy management controller. Then, the motor controller, engine controller, and transmission controller perform speed and torque control on the power source according to the received commands. Finally, sensors in each component of the transmission system detect the current vehicle driving state and feed it back to the upper-level controller.

[0119] Specific steps of this invention:

[0120] I. Energy Management and Distribution Power

[0121] like Figure 2 As shown, the energy management controller can obtain the total required torque T based on the driver's intention and the current driving status of the vehicle. r Based on the battery's SOC value, an energy management strategy is formulated according to the required torque, SOC value range, engine torque range, and motor torque range. The required torque is rationally allocated and transmitted to the hybrid controller, engine controller, and motor controller. The vehicle drive mode is determined and transmitted to the hybrid controller and transmission controller.

[0122] T r =T e_ref +T m_ref

[0123] In the formula, T e_ref For the engine target torque, T m_ref This represents the target torque for the motor.

[0124] II. Design of Torsional Vibration Controller for Typical Operating Conditions

[0125] The hybrid controller classifies the driving modes of a P2 hybrid electric vehicle into pure electric drive, engine-only drive, and hybrid drive. For example... Figure 3 As shown, based on whether the clutch state changes during mode switching, drive mode switching can be divided into six types. First, pure electric drive, hybrid drive, and pure electric-hybrid drive mode switching are listed as typical drive conditions, and corresponding torsional vibration controllers are designed for each. For pure electric drive mode, a hybrid adaptive control algorithm is used to suppress torsional vibration; for hybrid drive mode, a model predictive control algorithm is used to suppress torsional vibration; and for pure electric-hybrid drive mode switching, a model reference adaptive algorithm is used to suppress torsional vibration. The specific controller details are as follows:

[0126] (1) Pure electric mode

[0127] Based on the dynamic model of the transmission system in pure electric mode, a torsional vibration controller under acceleration conditions is constructed using a hybrid adaptive algorithm. Let the system input be the target torque T of the motor. m * The system output is the motor speed ω. m The transfer function of the system can be derived as follows:

[0128]

[0129] The ideal model response function is defined as follows:

[0130]

[0131] The feedforward controller can then be expressed as:

[0132]

[0133] The control model includes feedforward and feedback components. To achieve better control, different problems are analyzed. After the feedforward controller takes effect, the ideal damping ratio is generally used instead of the actual damping ratio. The feedback controller can reduce disturbances, making the control action closer to the ideal state. Therefore, H(s) can be expressed as:

[0134]

[0135] Assuming input torque T m * =0, then ω m The response relative to the input disturbance d is:

[0136] ω m =(1-H(s))G p (s)d

[0137] Let k = (1-ζ) p ), ω mThis can be expressed as:

[0138]

[0139] (2) Hybrid mode

[0140] Based on the dynamic model of the transmission system in hybrid power mode, a torsional vibration controller under acceleration conditions is constructed using a model prediction algorithm. The state-space equation of the system is:

[0141]

[0142] The state variable x consists of the following variables: engine angular velocity, engine-motor angle difference, motor angular velocity, motor-wheel angle difference, and wheel angular velocity; the system control variable is the motor torque T. m The interference quantity is the engine output torque T. e It is the system's disturbance quantity. The system output consists of the angular velocity of the motor, the angular acceleration of the motor, the angular velocity of the wheel and body, and the difference between the angular velocities of the motor and the wheel.

[0143] 1) Discretization

[0144] To design a vibration controller for model simulation, it is necessary to discretize the state equations of the continuous system and, based on the sampling period t, discretize the coefficients of each term in the state-space equations. An approximate discretization formula is used to discretize the coefficient matrix, and the discretization equations are as follows:

[0145]

[0146] A f =AT s +I

[0147] B f =T s B

[0148] C f =C

[0149] Where I is a 4×4 identity matrix, T s =0.001 represents the sampling period time.

[0150] To stabilize the system and reduce static errors, the discrete model described above can be further modified into an incremental model:

[0151]

[0152] Among them, Δx(k)=x(k)-x(k-1), Δu(k)=u(k)-u(k-1).

[0153] 2) Model prediction

[0154] The construction of the predictive model is the core of the model predictive vibration reduction controller. The main function of the predictive model is to calculate the optimal control sequence at each time step, ensuring that the input-output trajectory of the predictive model closely approximates the given reference output. Therefore, the accuracy of the predictive model has a significant impact on the control results. The state variables of the predictive system are:

[0155]

[0156] Where Δx(k+i|k) represents the state of the system after time point k, i after the prediction time point.

[0157] The system output prediction is:

[0158]

[0159] 3) Actuator dynamic compensation

[0160] When the total delay time of the motor is T d At that time, the linear dynamic system equation can be rewritten as:

[0161]

[0162] Among them, T de For the ideal delay time, T de Numerically, it is T s Integer multiples of.

[0163] An explicit delay time compensation scheme is adopted. x(k+T) de |k) serves as the starting point for the prediction model, and its expression is as follows:

[0164]

[0165] The starting point of the prediction model is defined as:

[0166]

[0167] A discretized system can be represented as:

[0168]

[0169] 4) Solve

[0170] After constructing the predictive model of the control system, a relevant system optimization problem can be established for the required control objective. Optimal control can then be achieved by solving the predictive model. By adjusting the motor torque, the oscillation amplitude on the motor shaft can be minimized, thereby reducing the speed difference between the motor and the tire. This achieves the goal of active vibration reduction in the control system. The cost function can be expressed as:

[0171]

[0172] R c (k+1)=[r(k+1) r(k+2)…r(k+N P )] T

[0173] In the formula, R is the reference sequence; Q and R are weight matrices; ||Q(YR) c )|| 2 The goal is to minimize torsional vibration fluctuations at the generator shaft; ||RΔU|| 2 In order to prevent excessive changes in motor torque from creating new excitation sources and thus generating new current resonance, the rate of change of the power supply during operation is adjusted.

[0174] To control the motor torque increment within a reasonable range, the following constraints are added to the original optimization problem:

[0175] y min (k)≤y(k)≤y max (k)

[0176] U min (k)≤U(k)≤U max (k)

[0177] -ΔU min (k)≤ΔU(k)≤ΔU max (k)

[0178] Taking into account the constraints, the objective function can be rewritten in the standard form of a quadratic programming problem as follows:

[0179]

[0180] in,

[0181]

[0182]

[0183] The above quadratic programming problem for finding the optimal value is solved using the quadratic prog function built into MATLAB software.

[0184] (3) Switching process between "pure electric" and "hybrid" modes

[0185] The mode switching process is divided into five stages: clutch free displacement stage, clutch slippage first stage, clutch slippage second stage, speed synchronization stage, and full participation stage. The dynamic equations for each stage are as follows:

[0186]

[0187] Among them, J e and J m These are the moments of inertia of the engine section and the motor section, respectively; ω e and ω m T represents the engine speed and the electric motor speed, respectively. e and T m T represents engine torque and motor torque, respectively; r The equivalent load torque of the motor output shaft is distributed by the energy management system according to the driver's needs; T c This is the maximum frictional torque that the clutch can provide, which can be expressed as follows: Equation Chapter (Next) Section 1

[0188] T c =μ c R c F b N c sign(ω m -ω e )

[0189] In the formula, μ c R c F c N c These are the friction coefficient of the clutch disc, the effective radius of the clutch disc, the number of clutch discs, and the pressure on the clutch disc.

[0190] If the dynamic model of the clutch free displacement stage is set as the reference model of this controller, then the dynamic equation of the reference model is:

[0191]

[0192] Where, ω m The required rotational speed is calculated using the reference model; T m This is the equivalent torque required by the driver.

[0193] Let the state variable x d =ω m Input variable u d =T m Output variable y d =ω m The disturbance variable d1 = -T r Then the state-space equation of the reference model is:

[0194]

[0195] Given the actual state x and the ideal state x of the system d The tracking error of the system and its reciprocal can be obtained as follows:

[0196]

[0197] Substituting the state-space equation of the control system into the above equation, we obtain the dynamic error equation of the system as follows:

[0198]

[0199] Define matrix H m ∈R 2×2 For any Hurwitz matrix, the above equation can be transformed into:

[0200]

[0201] In the formula, K * ∈R 2×2 L * ∈R 2×2 Their relationship is shown in the following formula:

[0202]

[0203] In the formula, I∈R 2×2 It is an identity matrix.

[0204] The control law and dynamic error of the control system are as follows:

[0205]

[0206] In the control law, K * and L * Since these parameters cannot be obtained directly through calculation, it is necessary to estimate the unknown parameters of the system control law. Let the estimation error be:

[0207]

[0208] In the formula, and K * and L * The estimated value.

[0209] Replacing the unknown system parameters in the control law with their estimated values ​​yields the adaptive control law:

[0210]

[0211] III. Selection Rules for Torsional Vibration Controllers

[0212] like Figure 4 As shown, different torsional vibration controllers can be selected to control the transmission system according to the torsional vibration response characteristics under different driving modes.

[0213] For the switching process between "engine-only - pure electric drive" and "hybrid - pure electric drive" modes, the power switching is achieved by disengaging the clutch between the engine and the motor to cut off the engine's output torque. Because the vehicle's driving torque decreases sharply at the moment of disengagement, the motor's torque demand suddenly increases at the instant of switching. This is equivalent to applying a step signal to the motor's torque demand, similar to the effect of a sudden increase in torque on the transmission system in pure electric mode. Therefore, the torsional vibration problem generated during this process can be suppressed using a hybrid adaptive torsional vibration controller in pure electric mode.

[0214] Regarding the switching process between the two modes of "engine-only drive" and "engine-only-hybrid drive" and "hybrid-engine-only", the power switching is determined by whether the motor outputs effective torque. During the switching process between these two modes, the clutch remains engaged. The torsional vibration of the transmission system mainly comes from the fluctuation of the engine's output torque, which is the same as the torsional vibration problem in the hybrid drive mode. Therefore, a model predictive controller in hybrid mode can be used to suppress torsional vibration.

[0215] For the switching process between "pure electric-hybrid drive" and "pure electric-engine-only drive" modes, the power switching is achieved by the motor driving the clutch to engage and start the engine to participate in power output. During the switching process between these two modes, the torsional vibration of the transmission system comes from the clutch slippage stage and the output torque fluctuation of the engine. Therefore, the model reference controller in the pure electric-hybrid drive mode can be used to suppress torsional vibration.

[0216] IV. Implementation and Feedback

[0217] The motor controller and engine controller receive target speed and target torque commands from the energy management system via CAN; the transmission controller receives mode selection and switching commands from the energy management system via CAN. The motor executes torque and speed commands from the motor controller; the engine executes torque and speed commands from the engine controller; the clutch executes engagement, disengagement, or switching commands from the transmission mechanism; and the transmission executes gear selection and switching commands from the transmission mechanism. Speed ​​and acceleration sensors distributed across various components of the transmission system record the current vehicle's driving status and transmit this data to the motor controller, engine controller, transmission controller, and hybrid controller, as well as to the energy management controller via CAN.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A drive control method for a hybrid powertrain system combining energy management and torsional vibration suppression, characterized in that: Includes the following steps: S1: The energy management controller allocates the drive power of the engine motor according to the driver's intention and the vehicle's driving status, and determines the vehicle's driving mode; S2: The hybrid controller selects the corresponding torsional vibration controller based on the vehicle's drive mode and switching state, and adds the motor active control torque command to the output of the energy management controller; S3: The motor controller, engine controller, and transmission controller receive commands and perform speed and torque control on the power source; S4: Each component of the transmission system executes the torque and speed commands issued by the controller; S5: Sensors in each component of the transmission system detect the current driving status of the vehicle and feed it back to the upper controller; Step S2 specifically includes: The hybrid controller divides the driving modes of hybrid electric vehicles into pure electric drive, engine-only drive, and hybrid drive. Based on whether the clutch state changes during the mode switching process, the driving mode switching is divided into 6 forms. First, pure electric drive, hybrid drive, and pure electric-hybrid drive mode switching are listed as typical driving conditions, and corresponding torsional vibration controllers are designed for each. For pure electric drive mode, a hybrid adaptive control algorithm is used to suppress torsional vibration; for hybrid drive mode, a model predictive control algorithm is used to suppress torsional vibration; and for pure electric-hybrid drive mode switching, a model reference adaptive algorithm is used to suppress torsional vibration. For the pure electric mode, based on the dynamic model of the transmission system in the pure electric mode, a torsional vibration controller under acceleration is built based on a hybrid adaptive algorithm, and the transfer function of the system is obtained as follows: Where T m * ω represents the target torque of the motor and is the system input. m ζ represents the motor speed, s represents the system output; s represents the transfer function variable, a represents the pole equation coefficients, b0~b3 all represent the zero equation coefficients, p represents the control system, and ζ represents the control system. p ω represents the system damping ratio. p Indicates the system poles; The ideal model response function is defined as follows: The feedforward controller is represented as: Where r represents feedforward control, ζ r ω represents the ideal damping ratio. r Represents the poles of an ideal system; The bandpass filter H(s) is expressed as: Where k represents the filter coefficient; Assuming input torque T m * =0, then ω m The response relative to the input disturbance d is: ω m =(1-H(s))G p (s)d Let k = (1-ζ) p ), ω m Expressed as: Where d represents the system input disturbance; For the hybrid mode, based on the dynamic model of the transmission system in the hybrid mode, a torsional vibration controller under acceleration is built based on the model prediction algorithm. The state-space equation of the system is: The state variable x consists of the following variables: engine angular velocity, engine-motor angle difference, motor angular velocity, motor-wheel angle difference, and wheel angular velocity; the system control variable is the motor torque T. m The interference quantity is the engine output torque T. e It is the system's disturbance quantity. The system output consists of the angular velocity of the motor, the angular acceleration of the motor, the angular velocity of the wheel and body, and the difference between the angular velocities of the motor and the wheel. The state equations of the continuous system are discretized, and the coefficients of each term in the state-space equations are discretized according to the sampling period t. An approximate discretization formula is used to discretize the coefficient matrix. The discretization equations are as follows: A f =AT s +I B f =T s B C f =C Where I is a 4×4 identity matrix, T s =0.001 represents the sampling period time; Change the discrete model to an incremental model: Among them, Δx(k)=x(k)-x(k-1), Δu(k)=u(k)-u(k-1) Construct a predictive model: The state variables of the predictive system are: Where Δx(k+i|k) represents time point k after the predicted state of the system at time point i; A f Let B represent the coefficients of the predicted state variables, Δx(k) represent the predicted state variables, and B represent the coefficients of the predicted state variables. f Δu(k) represents the coefficient of the predictor control variable; The system output prediction is: Where y(k+1|k) represents the predicted output variable, C f y(k) represents the coefficients of the predicted output variable, and y(k) represents the output variable. Actuator dynamic compensation: When the total delay time of the motor is T d At that time, the linear dynamic system equation can be rewritten as: Among them, T de For the ideal delay time, T de Numerically, it is T s Integer multiples of; An explicit delay time compensation scheme is adopted; x(k+T) de |k) serves as the starting point for the prediction model, and its expression is as follows: The starting point of the prediction model is defined as: The discretized system is represented as: To achieve the desired control objective, a relevant system optimization problem is established, and optimal control is achieved by solving the predictive model of the control system; the cost function is expressed as: R c (k+1)=[r(k+1) r(k+2) … r(k+N P )] T In the formula, R is the reference sequence; Q and R are weight matrices; ||Q(YR) c )|| 2 The goal is to minimize torsional vibration fluctuations at the generator shaft; ||RΔU|| 2 This is achieved by adjusting the rate of change of the power supply during operation; To control the motor torque increment within a reasonable range, the following constraints are added to the original optimization problem: y min (k)≤y(k)≤y max (k) YOU min (k)≤U(k)≤U max (k) -ΔU min (k)≤ΔU(k)≤ΔU max (k) Taking into account the constraints, the objective function can be rewritten in the standard form of a quadratic programming problem as follows: in, Solve the quadratic programming problem for finding the optimal value; The "pure electric to hybrid" mode switching process is divided into five stages: clutch free displacement stage, clutch slippage stage 1, clutch slippage stage 2, speed synchronization stage, and full participation stage. The dynamic equations for each stage are as follows: Among them, J e and J m These are the moments of inertia of the engine section and the motor section, respectively; ω e and ω m T represents the engine speed and the electric motor speed, respectively. e and T m T represents engine torque and motor torque, respectively; r The equivalent load torque of the motor output shaft is distributed by the energy management system according to the driver's needs; T c This is the maximum frictional torque that the clutch can provide, expressed as follows: T c =μ c R c F b N c sign(ω m -oh e ) In the formula, μ c R c F c N c These are the friction coefficient of the clutch disc, the effective radius of the clutch disc, the number of clutch discs, and the pressure on the clutch disc; If the dynamic model of the clutch free displacement stage is set as the reference model of this controller, then the dynamic equation of the reference model is: Where, ω m The required rotational speed is calculated using the reference model; T m This is the equivalent torque required by the driver; Let the state variable x d =ω m Input variable u d =T m Output variable y d =ω m The disturbance variable d1 = -T r Then the state-space equation of the reference model is: Given the actual state x and the ideal state x of the system d The tracking error of the system and its reciprocal are obtained as follows: Substituting the state-space equation of the control system into the above equation, we obtain the dynamic error equation of the system as follows: Define matrix H m ∈R 2×2 For any Hurwitz matrix, the above equation transforms into: In the formula, K * ∈R 2×2 L * ∈R 2×2 Their relationship is shown in the following formula: In the formula, I∈R 2×2 It is the identity matrix; The control law and dynamic error of the control system are as follows: Estimate the unknown parameters of the system control law, and let the estimation error be: In the formula, and K * and L * The estimated value; Replacing the unknown system parameters in the control law with their estimated values, we obtain the adaptive control law as follows: For the switching process between the two modes of "engine-only - pure electric drive" and "hybrid - pure electric drive", the power switching is done by disconnecting the clutch between the engine and the motor to cut off the engine's output torque. The resulting torsional vibration problem is suppressed by the hybrid adaptive torsional vibration controller in pure electric mode. For the process of switching between the two modes of "engine-only drive" and "engine-only-hybrid drive" and "hybrid-engine-only", the power switching is determined by whether the motor outputs effective torque. A model predictive controller in hybrid mode is used to suppress torsional vibration. For the switching process between "pure electric-hybrid drive" and "pure electric-engine-only drive" modes, the power switching is achieved by the motor driving the clutch to engage and start the engine to participate in power output. A model reference controller in the pure electric-hybrid drive mode is used to suppress torsional vibration.

2. The hybrid powertrain drive control method combining energy management and torsional vibration suppression according to claim 1, characterized in that: Step S1 specifically includes: The energy management controller calculates the total torque demand T based on the driver's intention and the current driving status of the vehicle. r Based on the battery's SOC value, an energy management strategy is formulated according to the required torque, SOC range, engine torque range, and motor torque range. The required torque is allocated and transmitted to the hybrid controller, engine controller, and motor controller. The vehicle drive mode is determined and transmitted to the hybrid controller and transmission controller. T r =T e_ref +T m_ref In the formula, T e_ref For the engine target torque, T m_ref This represents the target torque for the motor.

3. The hybrid powertrain drive control method combining energy management and torsional vibration suppression according to claim 1, characterized in that: In step S3, the motor controller and engine controller receive the target speed and target torque commands transmitted by the energy management system via CAN; the transmission controller receives the mode selection and switching commands transmitted by the energy management system via CAN.

4. The hybrid powertrain drive control method combining energy management and torsional vibration suppression according to claim 1, characterized in that: In step S4, the motor executes the torque and speed commands issued by the motor controller; the engine executes the torque and speed commands issued by the engine controller; the clutch executes the engagement, disengagement, or switching commands issued by the transmission mechanism; and the transmission executes the gear selection and switching commands issued by the transmission mechanism.

5. The hybrid powertrain drive control method combining energy management and torsional vibration suppression according to claim 1, characterized in that: In step S5, the speed sensors and acceleration sensors distributed on various components of the transmission system record the current driving status of the vehicle and transmit them to the motor controller, engine controller, transmission controller and hybrid controller, and at the same time transmit them to the energy management controller via CAN.

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