Parameter optimization method of hybrid powertrain based on time-frequency analysis

Abstract

The present invention proposes a hybrid powertrain parameter optimization method based on time-frequency analysis, comprising: step 1, establishing a dynamic model of the hybrid powertrain; step 2, establishing a total transient torque model T of the engine. e ; Step 3, establish the transmission torque model T of the torsional vibration damper d ; Step 4, calculate the total moment of inertia J3 of the gears on the input shaft of the gearbox and the total moment of inertia J4 of the gears on the output shaft; Step 5, calculate the moment of inertia J of the vehicle body body , the output torque T of the drive motor MG2 mg2 , resistance torque T1; Step 6: Establish a system of differential equations of motion for hybrid powertrain mode; Step 7: Perform time-frequency analysis based on the system of differential equations of motion; Step 8: Select several key parameters as optimization variables; Step 9: Set constraints and objective function; Step 10: Execute a genetic algorithm to obtain the optimal solution. This invention establishes a hybrid powertrain model and combines time-frequency analysis with a multi-objective genetic algorithm to achieve optimal design of the powertrain.

Description

Technical Field

[0001] The present invention belongs to the technical field of vibration control of new energy vehicles and relates to a method for optimizing parameters of a hybrid power transmission system based on time-frequency analysis. Background Art

[0002] The complex coupling characteristics of power sources in hybrid electric vehicles (HEVs) can easily lead to torsional vibrations. These issues not only impact the vehicle's NVH performance but can also negatively impact the reliability and lifespan of the drivetrain. Therefore, conducting torsional vibration analysis and parameter optimization of the drivetrain is crucial for improving HEV performance.

[0003] Traditional research has focused on analyzing the inherent characteristics of powertrains, using simplified modeling methods to analyze the system's natural frequencies and vibration modes. However, hybrid powertrains are subject to a variety of nonlinear excitations in actual operation, and their torsional vibration responses exhibit significant time- and frequency-varying characteristics. Research based solely on static analysis cannot fully reflect the system's dynamic behavior.

[0004] Time-frequency analysis, a tool that can simultaneously describe signal characteristics in both the time and frequency domains, has significant application value in analyzing the dynamic response of transmission systems. Time-frequency analysis can capture the vibration characteristics of a system under different operating conditions and reveal the influence of key parameters on torsional vibration response. However, existing research on transmission system parameter optimization has been limited to single-objective optimization and has not fully integrated time-frequency analysis techniques, resulting in limited applicability and effectiveness of the optimization results under actual operating conditions.

[0005] Therefore, combining time-frequency analysis technology to study the dynamic response characteristics of the hybrid powertrain system and conducting multi-objective parameter optimization based on this will provide an effective technical approach to improving the torsional vibration resistance of the powertrain system and the operational adaptability of the vehicle. Summary of the Invention

[0006] The purpose of the present invention is to provide a hybrid powertrain parameter optimization method based on time-frequency analysis. By establishing a hybrid powertrain model covering components such as the engine, motor, gearbox, and power coupling device, and combining time-frequency analysis with a multi-objective genetic algorithm, the optimal design of the powertrain is achieved.

[0007] A hybrid powertrain parameter optimization method based on time-frequency analysis comprises the following steps:

[0008] Step 1: Establish a dynamic model of the hybrid powertrain system, which includes:

[0009] an engine and a flywheel, wherein the flywheel is connected to an output shaft of the engine;

[0010] A torsional vibration damper, wherein the primary mass is fixedly connected to the flywheel and the secondary mass is connected to the input shaft of the gearbox; a vibration damping spring is provided between the secondary mass and the primary mass;

[0011] The gearbox comprises an output shaft and an input shaft;

[0012] The final reducer-differential includes two output shafts, each connected to an axle, on which drive wheels are mounted; the final reducer-differential is connected to the gearbox and drive motor MG2 through a gear set;

[0013] Step 2: Establish the total transient torque model T of the engine e ;

[0014] Step 3: Establish the transmission torque model T of the torsional vibration damper d ;

[0015] Step 4: Calculate the total moment of inertia J3 of the gears on the input shaft and the total moment of inertia J4 of the gears on the output shaft of the gearbox;

[0016] Step 5: Calculate the moment of inertia J of the vehicle body body , the output torque T of the drive motor MG2 mg2 , resistance torque T1;

[0017] Step 6: Create a file containing T e , J3, J4, J body 、T mg2 , the differential equations of motion of the powertrain in hybrid mode of T1;

[0018] Step 7: Perform time-frequency analysis based on the differential equations of motion;

[0019] Step 8: Select several key parameters as optimization variables;

[0020] Step 9: Set constraints and objective function;

[0021] Step 10: Execute the genetic algorithm to obtain the optimal solution.

[0022] Preferably, the expressions of J3 and J4 in step 4 are specifically:

[0023]

[0024] J a1 is the moment of inertia of the ML gear driving gear (1);

[0025] J a2 is the moment of inertia of the ML gear driven gear (2);

[0026] J a3is the moment of inertia of the MH gear driving gear (3);

[0027] J a4 is the moment of inertia of the MH gear driven gear (4);

[0028] J a5 is the moment of inertia of the MG1 motor driving gear (5);

[0029] J a6 is the moment of inertia of the driven gear (6) of the MG1 motor;

[0030] i ml ML gear ratio;

[0031] i mh is the MH gear transmission ratio;

[0032] i mg1 is the gear ratio of the generator MG1.

[0033] Preferably, in step 5, J body 、T mg2 The specific expressions of and T1 are:

[0034]

[0035] T l =(F f +F w )·r w

[0036]

[0037] F f =fmg

[0038] m is the vehicle mass, which is the set value;

[0039] r w is the radius of the driving wheel, which is the set value;

[0040] i g and i0 are the transmission ratios of the gearbox and the final reducer respectively;

[0041] T tar is the motor target torque, is the set value;

[0042] τ is the motor torque response time;

[0043] T max is the maximum torque output by the drive motor MG2;

[0044] t is the simulation time, is the set value;

[0045] F fis the rolling resistance;

[0046] F w is the air resistance;

[0047] f is the rolling resistance coefficient between the driving wheel and the road surface;

[0048] m is the vehicle mass;

[0049] C D is the air resistance coefficient;

[0050] A is the frontal area of ​​the vehicle;

[0051] u is the vehicle speed.

[0052] Preferably, the differential equations of motion in step 6 are:

[0053]

[0054] J i is the equivalent moment of inertia of the i-th component;

[0055] θ i is the rotation angle of the i-th component;

[0056] k ij is the equivalent torsional stiffness between the i-th component and the j-th component; c ij is the equivalent viscous damping between the i-th component and the j-th component;

[0057] Among them, the value set of i and j includes the engine torsional reducer, the transmission input shaft, the transmission output shaft, the main reducer, the left driving force, the right driving wheel, the generator MG1 rotor, and the drive motor MG2 rotor.

[0058] Preferably, the optimization variables in step 8 are:

[0059] x=[J2,k 12 ,c 12 ,k 23 ,k 34 ,k 56 ,k 57 ,J 10 ]

[0060] J2-equivalent moment of inertia of the engine;

[0061] k 12 -Equivalent torsional stiffness between the engine and the torsional vibrator;

[0062] c 12 -Equivalent viscous stiffness between the engine and the torsional vibrator;

[0063] k 23-Equivalent torsional stiffness between the torsional vibrator and the gearbox input shaft;

[0064] k 34 -Equivalent torsional stiffness between the gearbox input shaft and the gearbox output shaft;

[0065] k 56 -Equivalent torsional stiffness between the final reducer and the left drive wheel;

[0066] k 57 -Equivalent torsional stiffness between the final reducer and the right drive wheel;

[0067] J 10 -Equivalent moment of inertia of the rotor of the generator MG1.

[0068] Preferably, the objective function in step 9 is: minimizing the root mean square value of the second-order angular acceleration of the transmission input shaft, the left drive wheel, and the right drive wheel.

[0069] Compared with the prior art, the advantages of the present invention are:

[0070] A multi-objective genetic algorithm optimization based on time-frequency analysis has significantly improved the torsional vibration resistance and vibration control performance of a hybrid electric vehicle drivetrain. By accurately modeling the dynamic characteristics of key components, this method effectively reduces the second-order angular acceleration of the transmission input shaft and the left and right drive wheels, reducing vibration amplitude and noise, and improving the vehicle's NVH performance. Compared with traditional optimization methods, this method ensures that optimization parameters remain within a reasonable range, has strong versatility and application value, and can provide strong support for the design of hybrid electric drivetrains. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 Schematic diagram of the hybrid powertrain system;

[0072] Figure 2 Kinematic and dynamic analysis diagrams for the engine crank-connecting rod mechanism;

[0073] Figure 3 is the torsional characteristic curve;

[0074] Figure 4 It is the torsional vibration model of the hybrid vehicle;

[0075] Figure 5(a) to Figure 5(c) It is the system time-frequency analysis process;

[0076] Figure 6 Flowchart of the multi-objective optimization algorithm.

[0077] Among them, 1-ML gear driving gear, 2-ML gear driven gear, 3-MH gear driving gear, 4-MH gear driven gear, 5-MG1 motor driving gear, 6-MG1 motor driven gear. DETAILED DESCRIPTION

[0078] The following is a more detailed description of the hybrid powertrain parameter optimization method based on time-frequency analysis, with reference to a schematic diagram. This diagram illustrates a preferred embodiment of the present invention. It should be understood that those skilled in the art may modify the present invention described herein while still achieving the beneficial effects of the present invention. Therefore, the following description should be understood as a general guide for those skilled in the art and not as a limitation of the present invention.

[0079] 1. Establish a dynamic model of the hybrid powertrain system.

[0080] The hybrid powertrain system includes:

[0081] an engine and a flywheel, the flywheel being connected to an output shaft of the engine;

[0082] The primary mass of the torsional vibration damper is fixed to the flywheel, and together they serve as the power input end, transmitting the engine torque to the secondary mass.

[0083] The secondary mass of the torsional vibration damper is connected to the primary mass through a damping spring and is directly connected to the gearbox input shaft to complete the power output.

[0084] The gearbox has an input shaft connected to the output end of the torsional vibration damper, and a plurality of gears are arranged on the output shaft and the input shaft.

[0085] The gearbox is a two-shaft, two-speed gearbox, which achieves gear switching by adjusting the inner and outer gear hub coupling state of the MH (high gear) and ML (low gear) driven gears.

[0086] When the gearbox is in ML gear, the shift actuator pushes the outer gear hub of the ML driven gear 2 to engage with the inner gear hub. At this time, the power transmission path is that the ML gear driving gear 1 on the input shaft is engaged with the ML gear driven gear 2 on the output shaft to complete the power transmission. Although the MH gear driving gear 3 and the MH gear driven gear 4 are engaged, the MH gear driven gear 4, MG1 motor driving gear 5 and MG1 motor driven gear 6 on its branch road are all in idling state.

[0087] When the gearbox switches to MH gear, the shift actuator pushes the outer gear hub of the MH driven gear 4 to combine with the inner gear hub. At this time, the power is transmitted from the MH gear driving gear 3 on the input shaft to the output shaft through the MH gear driven gear 4. The MH gear driven gear 4 is fixedly connected to the MG1 motor driving gear 5. The MG1 motor driving gear 5 drives the MG1 motor driven gear 6 through a fixed transmission ratio. The branch where the ML gear driving gear 1 and the ML gear driven gear 2 are located is in idling in this state.

[0088] The main reducer-differential includes two output shafts, each of which is connected to a half-shaft, and the drive wheels are installed on the half-shafts; the main reducer-differential is engaged with the ML gear driven gear 2 and the drive motor MG2 through a gear set.

[0089] Among them, the connection relationship between the main reducer-differential and the ML gear driven gear 2 and the drive motor MG2 is the existing technology.

[0090] The drive motor MG2 and the engine transmit torque to the final reducer-differential respectively.

[0091] In summary, a comprehensive model of the hybrid powertrain system, encompassing the engine, motor, gearbox, and power coupling, should be constructed. The model should include the engine, generator, drive motor, gearbox, final reducer, and power coupling, using the lumped mass method and simplified models to describe the dynamic characteristics of each major component.

[0092] 2. Establish the total transient torque model of the engine.

[0093] The engine transient torque model is based on the kinematics and dynamics of the crank-connecting rod mechanism. It comprehensively considers the forces acting on the in-cylinder gas pressure and the equivalent reciprocating mass. It can accurately describe the periodic fluctuation characteristics of the engine output torque and provide an important excitation source for the torsional vibration analysis of the vehicle powertrain system.

[0094] like Figure 2 As shown, first, according to the kinematic relationship of the crank-connecting rod mechanism, the crankshaft angle α, the connecting rod swing angle β, and the piston displacement s are defined. k The relationship between them is:

[0095] lsinβ=rsinα (1)

[0096]

[0097] Where r is the crank radius, which is the set value;

[0098] l is the connecting rod length, which is the set value;

[0099] λ p is the ratio of crank radius to connecting rod length, which is the set value;

[0100] The piston force F includes the equivalent reciprocating mass inertia force F of the piston, piston ring, piston pin and part of the connecting rod m and the in-cylinder gas pressure F g Two parts:

[0101]

[0102] in:

[0103]

[0104] Among them, P g (ωt) is the in-cylinder gas pressure that changes with the crankshaft angle and is a lookup table value determined based on the instantaneous crankshaft angle;

[0105] J1 is the equivalent moment of inertia of the engine, which is the set value;

[0106] ω is the crankshaft angular velocity, which is obtained by formula (3);

[0107] d p is the piston diameter, is the set value;

[0108] m p is the equivalent reciprocating mass, is the set value.

[0109] The transient torque of a single cylinder is obtained from the piston force, which is composed of the reciprocating inertia torque and the gas pressure torque:

[0110] T e =T m +T g (6)

[0111]

[0112]

[0113] 3. Establish the transmission torque model between flywheel and torsional vibration damper.

[0114] A torsional vibration damper is a key component for attenuating torsional vibrations transmitted from the engine to the drivetrain. Its basic structure consists of a flywheel, a primary mass, a secondary mass, and a vibration damping spring and damping assembly.

[0115] Specifically, the primary and secondary masses refer to the mass of the flywheel's fixed connection to the damper and the mass connected to the transmission input shaft, respectively. The primary mass of the flywheel and torsional vibration damper is fixed together, simplifying it to represent the system's first inertia. The secondary mass represents the mass of the other portion of the torsional vibration damper (i.e., the portion connected to the transmission input shaft), simplifying it to represent the second inertia. Using this model, the total inertia of the flywheel and torsional vibration damper can be considered the sum of the inertias of these two components.

[0116] Furthermore, the shock absorber adopts a two-stage stiffness design. The first and second stiffness levels of the torsional vibration damper correspond to the stiffness provided by the two damping springs, respectively. The first-stage torsional stiffness, provided by the primary damping spring, primarily affects torsional vibration suppression on the driving side; the second-stage torsional stiffness, provided by the secondary damping spring, primarily affects torsional vibration suppression on the trailing side.

[0117] Among them, "primary spring" refers to the vibration damping spring located between the secondary mass and the primary mass, when it is in the first torsional compression state; "first-stage torsional stiffness" refers to the stiffness of the primary spring.

[0118] "Secondary spring" refers to the vibration damping spring located between the secondary mass and the primary mass, when it is in the second torsional compression state; "secondary torsional stiffness" refers to the stiffness of the secondary spring.

[0119] like Figure 3 As shown, the transmission torque T of the torsional vibration damper d Divided into elastic torque T s and hysteresis damping torque T h There are two parts. The elastic torque is determined by the stiffness characteristics of the shock absorber, while the hysteresis damping torque is related to the dynamic response of the shock absorber. The specific expression is as follows:

[0120] T d =T s +T h (10)

[0121] in:

[0122]

[0123] Among them, θ r is the relative rotation angle between the primary mass and the secondary mass of the torsional vibration damper, which is the set value;

[0124] T d is the transmission torque of the torsional vibration damper, is the simulation output value;

[0125] φ 23 、φ 23 'The limit turning angles of the driving side and the dragging side are set values ​​respectively;

[0126] φ 12 is the switching angle between the first-stage torsional stiffness and the second-stage torsional stiffness on the drive side of the torsional vibration damper, which is the set value;

[0127] k1 is the first-stage torsional stiffness of the drive side of the torsional vibration damper, which is the set value;

[0128] k2 is the second-stage torsional stiffness of the drive side of the torsional vibration damper, which is the set value;

[0129] H1 is the hysteresis damping torque on the driving side of the torsional vibration damper, which is the set value;

[0130] φ 12 ′ is the switching angle between the first-stage torsional stiffness and the second-stage torsional stiffness on the drag side of the torsional vibration damper, which is the set value;

[0131] k1′ is the first-stage torsional stiffness of the dragging side of the torsional vibration damper, which is the set value;

[0132] k2′ is the second-stage torsional stiffness of the dragging side of the torsional vibration damper, which is the set value;

[0133] H1′ is the hysteresis damping torque on the drag side of the torsional vibration damper, which is the set value.

[0134] Among them, "driving side" refers to the primary mass side; "drag side" refers to the secondary mass side.

[0135] "Drive-side" refers to the section of the shock-absorbing spring that is connected to the primary mass.

[0136] The "trailing side" refers to the section of the shock absorber spring that connects to the secondary mass.

[0137] 4. Calculate the total moment of inertia J3 of the gears on the input shaft and the total moment of inertia J4 of the gears on the output shaft of the gearbox.

[0138] The transmission model primarily describes the power transfer and torque regulation characteristics of the transmission in a hybrid powertrain. This vehicle utilizes a two-shaft, two-speed transmission with two operating ranges: ML and MH. The transmission's structure enables gear selection and shifting through an internal shift mechanism and the meshing of an external hub gear with gears. The differences in power transfer between ML and MH also need to be considered separately during the modeling process.

[0139] The gearbox can be simplified into two inertial elements, two elastic elements and two damping elements.

[0140] The inertial elements include gears on the input and output shafts of the transmission;

[0141] The elastic element represents the torsional stiffness of the transmission input shaft and output shaft.

[0142] The damping element represents the damping of the transmission input shaft and output shaft.

[0143] Since the gear meshing relationship of the transmission is different in different gears, it is necessary to calculate the transmission system in ML gear and MH gear separately.

[0144] In ML or MH gear, the total moment of inertia of the gears on the input and output shafts of the transmission is calculated as follows:

[0145]

[0146] Among them, J a1 is the moment of inertia of the ML gear driving gear 1, which is the set value;

[0147] J a2 is the moment of inertia of the driven gear 2 in ML gear, which is the set value;

[0148] J a3 is the moment of inertia of the MH gear driving gear 3, which is the set value;

[0149] J a4 is the moment of inertia of the driven gear 4 of MH gear, which is the set value;

[0150] J a5 is the moment of inertia of the driving gear of the MG1 motor, which is the set value;

[0151] J a6 is the moment of inertia of the driven gear 6 of the MG1 motor, which is the set value;

[0152] i ml ML gear ratio;

[0153] i mh is the MH gear transmission ratio;

[0154] i mg1 is the gear ratio of the generator MG1.

[0155] i ml is the ML gear transmission ratio, is the set value; i ml = Speed ​​of driving gear 1 / speed of driven gear 2;

[0156] i mh is the MH gear transmission ratio, is the set value; i mh = MH gear driving gear 3 speed / MH gear driven gear 4 speed;

[0157] i mg1 is the gear ratio of the generator MG1, which is a set value.

[0158] 5. Calculate the moment of inertia J of the vehicle body body , the output torque T of the drive motor MG2 mg2 , resistance torque T1.

[0159] (1) Main reducer-differential model

[0160] The final drive-differential model integrates the final drive and differential.

[0161] The final drive uses gear transmission to reduce speed and increase torque, while the differential distributes torque when wheel speeds are inconsistent. Under conditions that exclude cornering, the differential evenly distributes the transmission's torque to the left and right wheels. Due to the high gear stiffness and concentrated moment of inertia of the final drive and differential, these components can be simplified to inertial elements.

[0162] (2) Semi-axis model

[0163] The inertia of the half-axles is relatively small and they are usually simplified as elastic elements. Taking into account the asymmetry of the left and right half-axles, their inertia is evenly distributed between the final drive and differential at both ends and the wheels.

[0164] (3) Body model

[0165] The drive wheels have a large moment of inertia, so the tires can be considered inertial elements and are connected to the vehicle body via elastic elements. The moment of inertia of the vehicle body is equivalently converted to the moment of inertia at the engine crankshaft base speed using the principle of conservation of kinetic energy. The calculation formula is as follows:

[0166]

[0167]

[0168] Where m is the vehicle body mass and is the set value;

[0169] r w is the radius of the driving wheel, which is the set value;

[0170] i g i0 and i10 are the transmission ratios of the gearbox and the final reducer in the final reducer-differential model, respectively, and ω is the set value; w is the angular velocity of the driving wheel, which is an intermediate quantity;

[0171] v is the speed of the driving wheel, which is an intermediate quantity;

[0172] (4) Drive motor MG2

[0173] The output torque of the drive motor does not consider the harmonic effect, and uses the first-order transfer function to simulate the hysteresis effect of the motor torque. The output torque calculation formula is:

[0174]

[0175] Among them, T tar is the motor target torque, is the set value;

[0176] t is the simulation time, is the set value;

[0177] τ is the motor torque response time, which is the set value;

[0178] Tmax The maximum torque output by the drive motor MG2 is determined by the motor's external characteristic curve and is a function of the motor's speed.

[0179] (5) Driving resistance model

[0180] The resistance encountered by a vehicle during driving mainly includes rolling resistance and air resistance. The formula is as follows:

[0181] F f =fmg (19)

[0182]

[0183] T l =(F f +F w )·r w (twenty one)

[0184] Among them, F f is the rolling resistance, which is the calculated median value;

[0185] F w is the air resistance, which is the calculated intermediate value;

[0186] f is the rolling resistance coefficient between the driving wheel and the road surface, which is a set value;

[0187] m is the vehicle mass, which is the set value;

[0188] C D is the air resistance coefficient, which is the set value;

[0189] A is the frontal area of ​​the vehicle, which is the set value;

[0190] u is the vehicle speed, which is the simulation output value;

[0191] 6. Typical working mode

[0192] The system optimizes the powertrain's response in the more complex hybrid mode. In ML or MH gears, the engine and drive motor (MG2) work together, with the power output of the engine and motor optimized and matched through the torque coupling system.

[0193] like Figure 4 As shown in Figure 2, in this mode, the dynamic response of the powertrain becomes more complex. The model has been expanded from ten degrees of freedom to eleven, fully accounting for the impact of the motor's moment of inertia and torque output on the overall system. The torque and speed between the engine and motor interact according to a specific coupling relationship to achieve optimal power distribution. The differential equations of motion are shown below:

[0194]

[0195] Where, J i is the equivalent moment of inertia of the i-th component, except J3, J4 and J body The rest are set values; i is the rotation angle of the i-th component, which is the set value;

[0196] k ij is the equivalent torsional stiffness between the i-th component and the j-th component, which is a set value;

[0197] c ij is the equivalent viscous damping between the i-th component and the j-th component, which is the set value;

[0198] The specific meanings of the values ​​of i and j can be found in Table 1 below:

[0199] Table 1 Specific meanings of the values ​​of i and j

[0200] The values ​​of i and j meaning 1 engine 2 Torsional vibration damper 3 Transmission input shaft 4 gearbox output shaft 5 Final reducer 6 Left drive wheel 7 Right drive wheel 8 Half of the vehicle's mass is equivalent to the left drive shaft 9 Half of the vehicle's mass is equivalent to the right drive shaft 10 Generator MG1 rotor 11 Drive motor MG2 rotor

[0201] Among them, formula (22) is a whole, which is used to solve the engine speed Angular acceleration of the transmission input shaft and the angular acceleration of the left and right driving wheels

[0202] In summary, the dynamic response of the engine and motor working together in hybrid mode is considered. By expanding the model's degrees of freedom, the influence of the motor's moment of inertia and torque output on the entire system is fully considered, and the torque and speed coupling relationship between the engine and motor is established to simulate the power transmission characteristics under actual working conditions.

[0203] 7. Time-Frequency Analysis

[0204] Time-frequency analysis evaluates the vibration characteristics of the vehicle in hybrid drive mode by calculating the second-order angular acceleration of the powertrain.

[0205] (1) As shown in Figure 5(a), the vehicle dynamics simulation is performed based on formula (22) to obtain the engine speed Angular acceleration of the transmission input shaft and the angular acceleration of the left and right driving wheels And extract the time domain signal within the corresponding simulation time. Among them, the horizontal axis is time and the vertical axis is speed or angular acceleration.

[0206] (2) As shown in Figure 5(b), the time domain signals of the engine speed and the three angular accelerations are subjected to a fast Fourier transform (FFT) to obtain the corresponding frequency domain signals, revealing the distribution characteristics of the angular acceleration and speed at different frequencies. The horizontal axis is the frequency, and the vertical axis is the engine speed.

[0207] (3) Further order tracking analysis is performed on the spectrum to extract the main vibration frequencies of the system and their relationship with the engine speed. As shown in Figure 5(c), the order is set to 2 and the frequency band is set to 15 Hz. Feature analysis and extraction of the second-order angular acceleration of the transmission input shaft and the left and right drive wheels are performed to identify the key characteristics of the system vibration. The horizontal axis is the engine speed, and the vertical axis is the second-order angular acceleration.

[0208] The amplitudes (maximum values) of the three second-order angular accelerations can be obtained from Figure 5(c).

[0209] 8. Select key parameters for multi-objective optimization

[0210] Based on Figure 5(c), the amplitudes of the three second-order angular accelerations can be obtained. The parameters in formula (22) are then varied and multiple simulations are performed to identify the parameters that have a significant impact on the amplitudes of the three second-order angular accelerations. These parameters, such as flywheel inertia, torsional vibration damper stiffness, and motor inertia, are identified as key parameters that significantly affect the system's dynamic response and are used as optimization variables. A multi-objective optimization of the key parameters of the hybrid powertrain is performed using a genetic algorithm, aiming to simultaneously reduce the amplitudes of the second-order angular accelerations of the transmission input shaft and the left and right drive wheels, thereby improving the system's vibration performance.

[0211] (1) Optimization objectives and objective functions

[0212] The optimization goal is to minimize the RMS value of the second-order angular acceleration of the transmission input shaft and the left and right drive wheels within the engine speed range of 1000 rpm to 6000 rpm. The objective function is specifically expressed as follows:

[0213]

[0214] Where RMS is the calculated root mean square value;

[0215] Among them, there is a situation where the three objective functions are minimized at the same time, which corresponds to one solution.

[0216] When the three objective functions do not have the same minimum at the same time, there are multiple solutions.

[0217] (2) Optimization variables and constraints

[0218] Based on the above analysis, the following eight key parameters are selected as optimization variables:

[0219] x=[J2,k 12 ,c 12 ,k 23 ,k 34 ,k 56 ,k 57 ,J10 ]

[0220] The constraints of each optimization variable are shown in the following table:

[0221] Table 2 Constraints of optimization variables

[0222] variable name Lower limit Upper limit unit <![CDATA[J2]]> -5％ +5％ kg·m2 <![CDATA[k 12 ]]> -20％ +20％ Nm / rad <![CDATA[c 12 ]]> -20％ +20％ Nm <![CDATA[k 23 ]]> -15％ +15％ Nm / rad <![CDATA[k 34 ]]> -15％ +15％ Nm / rad <![CDATA[k 56 ]]> -15％ +15％ Nm / rad <![CDATA[k 57 ]]> -15％ +15％ Nm / rad <![CDATA[J 10 ]]> -5％ +5％ kg·m2

[0223] (3) Genetic algorithm optimization process

[0224] like Figure 6 As shown in Figure 1, a genetic algorithm is used to solve this multi-objective optimization problem. First, individuals are represented using real-number encoding, and the fitness function is used to evaluate the quality of each solution. The main steps of a genetic algorithm include selection, crossover, and mutation. The optimization process continuously generates new generations of individuals until it converges to a Pareto optimal solution. A Pareto optimal solution is one where one objective cannot be further optimized without compromising any other objectives.

[0225] Combining time-frequency analysis with the aforementioned multi-objective genetic algorithm, the hybrid vehicle drivetrain parameters were optimized, significantly improving the system's vibration characteristics. By optimizing key parameters such as flywheel inertia, torsional damper stiffness, and motor inertia, the second-order angular acceleration of the transmission input shaft and drive wheels was effectively reduced, thereby reducing vibration amplitude and noise, improving the vehicle's NVH performance and driving comfort. The optimization process also ensured that all parameters remained within reasonable ranges and constraints, ultimately achieving a Pareto optimal solution that met the multi-objective optimization requirements. This provides effective technical support for hybrid drivetrain design, and the optimization results can be used as design parameters to achieve a more efficient, low-vibration, and low-noise drivetrain.

[0226] Furthermore, after the optimization process is complete, simulation verification is performed to examine the effects of the optimized parameters on system vibration behavior, torsional vibration reduction, and overall dynamic performance. This ensures that the optimization results meet performance requirements under different operating conditions, achieving the goal of reducing vibration and noise and improving system reliability.

[0227] Step A: First, adjust the values ​​of key parameters within the constraints and generate a new parameter array containing 8 values.

[0228] Step B: Then, substitute the array into formula (22) to perform system dynamics simulation, and finally perform time-frequency analysis, and extract the relationship curve between the engine speed and the second-order angular acceleration corresponding to each simulation.

[0229] According to the engine speed-second-order angular acceleration curve of each simulation, its root mean square value is calculated to quantify the dynamic characteristics of the system vibration.

[0230] Step C: After traversing the root mean square values ​​of all simulation results, select the parameter array that minimizes both objective functions and takes it as the optimal solution for multi-objective optimization.

[0231] Among them, steps A and C are completed by genetic algorithms.

[0232] The above description is merely a preferred embodiment of the present invention and does not limit the present invention in any way. Any person skilled in the art who, without departing from the scope of the present invention, makes any equivalent substitution, modification, or other changes to the technical solution and technical content disclosed in the present invention shall be deemed to be within the scope of the present invention and still fall within the scope of protection of the present invention.

Claims

1. A hybrid powertrain parameter optimization method based on time-frequency analysis, characterized in that: The following steps are involved: Step 1: Establish a dynamic model of the hybrid powertrain system, which includes: an engine and a flywheel, wherein the flywheel is connected to an output shaft of the engine; A torsional vibration damper, wherein the primary mass is fixedly connected to the flywheel and the secondary mass is connected to the input shaft of the gearbox; a vibration damping spring is provided between the secondary mass and the primary mass; The gearbox comprises an output shaft and an input shaft; The final reducer-differential includes two output shafts, each connected to an axle, on which drive wheels are mounted; the final reducer-differential is connected to the gearbox and drive motor MG2 through a gear set; Step 2: Establish the total transient torque model T of the engine e ; Step 3: Establish the transmission torque model T of the torsional vibration damper d ; Step 4: Calculate the total moment of inertia J3 of the gears on the input shaft and the total moment of inertia J4 of the gears on the output shaft of the gearbox; Step 5: Calculate the moment of inertia J of the vehicle body body , the output torque T of the drive motor MG2 mg2 , resistance torque T1; Step 6: Create a file containing T e 、T d , J3, J4, J body 、T mg2 , the differential equations of motion of the powertrain in hybrid mode of T1; Step 7: Perform time-frequency analysis based on the differential equations of motion; Step 8: Select several key parameters as optimization variables; Step 9: Set constraints and objective function; Step 10: Execute the genetic algorithm to obtain the optimal solution; J in step 5 body 、T mg2 The specific expressions of and T1 are: T l =(F f +F w )·r w F f =fmg m is the vehicle mass, which is the set value; r w is the radius of the driving wheel, which is the set value; i g and i0 are the transmission ratios of the gearbox and the final reducer respectively; t is the simulation time, and is the set value; T tar is the target torque of the motor, is the set value; τ is the motor torque response time; T max is the maximum torque output by the drive motor MG2; F f is the rolling resistance; F w is the air resistance; f is the rolling resistance coefficient between the driving wheel and the road surface; m is the vehicle mass; C D is the air resistance coefficient; A is the frontal area of ​​the vehicle; u is the vehicle speed; The differential equations of motion in step 6 are: J i is the equivalent moment of inertia of the i-th component; θ i is the rotation angle of the i-th component; k ij is the equivalent torsional stiffness between the i-th component and the j-th component; c ij is the equivalent viscous damping between the i-th component and the j-th component; Among them, the value set of i and j includes the engine torsional reducer, the transmission input shaft, the transmission output shaft, the main reducer, the left driving force, the right driving wheel, the generator MG1 rotor, and the drive motor MG2 rotor.

2. The hybrid powertrain system parameter optimization method based on time-frequency analysis according to claim 1, characterized in that: The specific expressions of J3 and J4 in step 4 are: J a1 is the moment of inertia of the ML gear driving gear (1); J a2 is the moment of inertia of the ML gear driven gear (2); J a3 is the moment of inertia of the MH gear driving gear (3); J a4 is the moment of inertia of the MH gear driven gear (4); J a5 is the moment of inertia of the MG1 motor driving gear (5); J a6 is the moment of inertia of the driven gear (6) of the MG1 motor; i ml ML gear ratio; i mh is the MH gear transmission ratio; i mg1 is the gear ratio of the generator MG1.

3. The hybrid powertrain system parameter optimization method based on time-frequency analysis according to claim 1, characterized in that: The optimization variables in step 8 are: x=[J2,k 12 ,c 12 ,k 23 ,k 34 ,k 56 ,k 57 ,J 10 ] J2-equivalent moment of inertia of the engine; k 12 -Equivalent torsional stiffness between the engine and the torsional vibrator; c 12 -Equivalent viscous stiffness between the engine and the torsional vibrator; k 23 -Equivalent torsional stiffness between the torsional vibrator and the gearbox input shaft; k 34 -Equivalent torsional stiffness between the gearbox input shaft and the gearbox output shaft; k 56 -Equivalent torsional stiffness between the final reducer and the left drive wheel; k 57 -Equivalent torsional stiffness between the final reducer and the right drive wheel; J 10 -Equivalent moment of inertia of the rotor of the generator MG1.

4. The hybrid powertrain system parameter optimization method based on time-frequency analysis according to claim 1, characterized in that: The objective function in step 9 is to minimize the root mean square value of the second-order angular acceleration of the transmission input shaft, the left drive wheel, and the right drive wheel.

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