Commercial vehicle hybrid power system efficiency optimal energy management method based on longitudinal road adhesion coefficient real-time estimation

Abstract

The invention relates to a commercial vehicle hybrid power system efficiency optimal energy management method based on longitudinal road adhesion coefficient real-time estimation, and belongs to the technical field of hybrid power commercial vehicle energy management. The commercial vehicle hybrid power system efficiency optimal energy management method comprises the following steps: establishing a three-axis commercial vehicle longitudinal dynamics model and a Dugoff tire model; carrying out real-time estimation on a longitudinal road adhesion coefficient in the driving process by adopting a UKF (Unscented Kalman Filter); the method comprises the following steps: aiming at various working modes of a vehicle, in a full working condition range, by taking optimal total efficiency of a hybrid power system as a target, constructing an optimal efficiency MAP; during real-time running of the vehicle, calculating a safety torque limit value corresponding to the maximum adhesion force of the wheel end based on the minimum longitudinal road adhesion coefficient obtained through estimation; the torque required by the driver is restrained through the safe torque limit value; and in the safe torque range, the optimal efficiency MAP is inquired according to the current wheel end rotating speed and the required torque, and the working mode and the power distribution instruction with the optimal efficiency of the current system are decided.

Description

Technical Field

[0001] This invention belongs to the field of energy management technology for hybrid commercial vehicles, and relates to an optimal energy management method for hybrid commercial vehicle systems based on real-time estimation of longitudinal road adhesion coefficient. Background Technology

[0002] Hybrid commercial vehicles have two power sources: an engine and an electric motor. However, the high-efficiency range and operating characteristics of the engine and electric motor differ significantly. To improve the performance of the hybrid system, the engine and electric motor must work together and complement each other's strengths. Therefore, energy management strategies are one of the key technologies for hybrid commercial vehicles.

[0003] Estimating the road surface adhesion coefficient is a key factor in realizing active vehicle safety technologies, which require accurate road surface adhesion coefficients as data input for precise control. For commercial vehicles, the road surface adhesion coefficient varies with road conditions (e.g., dry, wet, slippery), and combined with their large mass, this leads to significant variations in the vehicle's maximum adhesion force. Therefore, energy management strategies must consider road surface adhesion conditions when coordinating power source output to avoid safety issues such as wheel slippage, ensuring both efficient and safe power distribution. However, existing research on commercial vehicle energy management strategies has not fully considered the limitations of longitudinal road surface adhesion coefficient variations on power distribution, making it difficult to achieve a balance between optimal system efficiency and driving safety under different road conditions. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide an optimal energy management method for commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient.

[0005] To achieve the above objectives, the present invention provides the following technical solution: An optimal energy management method for commercial vehicle hybrid power systems based on real-time estimation of longitudinal road adhesion coefficient includes the following steps: S1: Online estimation of longitudinal road adhesion coefficient: A longitudinal dynamics model and a Dugoff tire model of a three-axle commercial vehicle are established; the longitudinal road adhesion coefficient of the six wheels is used as the state variable and the longitudinal acceleration of the whole vehicle is used as the observation variable. The unscented Kalman filter algorithm UKF is used to estimate the longitudinal road adhesion coefficient in real time during the driving process. S2: Optimal system efficiency MAP Offline calibration: For various vehicle operating modes, across the entire operating range, with the goal of optimizing the overall efficiency of the hybrid system, offline calculation and storage are performed for the optimal operating mode, engine and motor torque distribution scheme, and transmission gear position corresponding to the optimal system efficiency at each operating point, forming a global optimal efficiency lookup table. MAP ; S3: Online Energy Management Constrained by Longitudinal Adhesion Coefficient: During real-time vehicle operation, based on the estimated minimum longitudinal road adhesion coefficient, the safe torque limit corresponding to the maximum wheel-end adhesion force is calculated; the driver's required torque is constrained by the safe torque limit; within the safe torque range, the optimal efficiency is queried based on the current wheel-end speed and the required torque. MAP It determines the most efficient working mode and power allocation instructions for the current system.

[0006] Furthermore, the establishment of the longitudinal dynamics model for the three-axle commercial vehicle specifically includes: A three-axle vehicle dynamics model is established considering the longitudinal motion of the vehicle, with the following assumptions: the origin of the coordinate system fixed on the vehicle coincides with the center of mass of the three-axle heavy vehicle; it is assumed that the vehicle only moves longitudinally in a plane, and the effects of pitch, roll, and vertical motion on the vehicle's dynamic characteristics are ignored; the effects of air resistance on vehicle dynamics are ignored; it is assumed that all tires have the same motion characteristics; the road surface is flat, and the effects of slope resistance are ignored. The longitudinal force balance equations for the entire vehicle are as follows:

[0007] The rotational dynamics of a wheel are described by the following equations:

[0008] In the formula, m For the overall vehicle quality, a x For longitudinal acceleration, F xfr , F xfl , F xmr , F xml , F xrr , F xrl The longitudinal force is the force exerted on the left and right tires of the front, middle, and rear axles. J w For the moment of inertia of the wheel, oh i Let be the angular velocity of the i-th wheel. F di , F bi 、F xi For each wheel's driving torque, braking torque, and longitudinal force, r The radius of the wheel; Considering the effect of longitudinal acceleration, the vertical load on each tire is expressed as:

[0009] In the formula, F zfr , F zfl , F zmr , F zml , F zrr , F zrl The vertical load on the left and right tires of the front, middle, and rear axles. a 1. a 2. a 3 represents the distance from the front, middle, and rear axles to the vehicle's center of gravity. h g For the height of the vehicle's center of gravity, L This is the distance between the center of the front axle and the center of the rear axle.

[0010] Furthermore, the establishment of the Dugoff tire model specifically includes: The force relationship of the tire is as follows:

[0011]

[0012] In the formula, F x , F z For the longitudinal and vertical forces of the tire, f The adhesion coefficient, C x These are the longitudinal stiffness of the tire. l For slip ratio, v x The longitudinal speed of the entire vehicle; Introducing boundary values L Describes the nonlinear characteristics of tire forces caused by tire slippage:

[0013] In the formula, e As a speed-affecting factor; The Dugoff tire model is simplified to the following normalized model, written as:

[0014] In the formula, It is the longitudinal normalized force.

[0015] Furthermore, the real-time estimation of the longitudinal road adhesion coefficient during the driving process using the Unscented Kalman Filter (UKF) algorithm specifically includes: Construct and discretize process equations and observation equations: Define state variables x= [ f fl , f fr, f ml, f mr, f rl, f rr ] T ,in f i Define the observed variables for the road adhesion coefficients of the six wheels. z = [ a x ]; Based on the vehicle dynamics model, the dynamic evolution of the adhesion coefficient is described. The continuous-time equation is discretized to obtain the discrete state equation. x ( k +1) = Φx ( k ) + w ( k )for:

[0016] In the formula, F Here is the state transition matrix. w ( k ) represents process noise; Based on the Dugoff tire model, the mapping between observed variables and state variables is established through the relationship between tire force and acceleration, and the observation equations are listed. z ( k ) = Hx ( k ) + v ( k )for:

[0017] In the formula, H For the observation matrix, v ( k (This refers to the measurement of noise.) UKF initialization: Provides initial conditions for the UKF recursive process and sets initial state estimates. (0), initial covariance matrix P (0); Setting process noise covariance Q and measurement noise covariance R ; Generate Sigma points: Estimate based on the current state ( k ) and covariance P ( k), generated by Unscented(UT) transformation 2 n +1 Sigma point, n For the state dimension, the calculation formula is:

[0018] In the formula, s As a scaling factor, The i-th column is the square root of the matrix; Assign mean weights to each Sigma point Covariance weights ,satisfy ; Time update: Substitute the generated Sigma point into the state equation to obtain the Sigma point at the predicted time:

[0019] The mean of the predicted state is calculated by weighted summation:

[0020] Calculate the covariance of the predicted state:

[0021] Based on the current state and the dynamic characteristics of the system, predict the state and uncertainties at the next moment; Measurement Update: Substitute the predicted Sigma points into the observation equation to obtain the Sigma points in the observation space:

[0022] Calculate the predicted mean of the observations:

[0023] Calculate the observation covariance, the cross-covariance between state and observation, and the Kalman gain:

[0024] Corrected state and covariance:

[0025] The predicted values ​​are corrected using actual observations to reduce estimation errors and obtain a posterior estimate; Output adhesion coefficient estimate: from the corrected state The longitudinal road adhesion coefficients of the six wheels are extracted, and the minimum value is taken as a constraint condition for the subsequent calculation of the torque demand for energy management strategies. f est : .

[0026] Furthermore, the multiple operating modes of the vehicle mentioned in step S2 include: by controlling the operating states of the engine, motor M1, motor M2 and clutch C, the vehicle driving mode is divided into nine different operating modes: pure engine mode m1, pure electric mode m21 motor M1 driving and motor M2 not working, pure electric mode m22 motor M1 not working and motor M2 driving, pure electric mode m23 motor M1 driving and motor M2 driving, hybrid mode m31 motor M1 not working and motor M2 driving, hybrid mode m32 motor M1 driving and motor M2 not working, hybrid mode m33 motor M1 charging and motor M2 not working, hybrid mode m34 motor M1 driving and motor M2 driving, hybrid mode m35 motor M1 charging and motor M2 driving.

[0027] Furthermore, in step S2, based on the established vehicle model and mode division, the independent variable for calculating system efficiency is the engine torque. T Eng With rotational speed n Eng The torque of motor M1 T M1 With rotational speed n M1 The torque of motor M2 T M2 With rotational speed n M2 and the AMT1 gearbox for the middle axle and the AMT2 gearbox for the rear axle. N AMT1 , N AMT2 ; Given wheel end torque T wheel Wheel end speed n wheel And under the condition of battery SOC, the engine fuel heat release power can be calculated separately. P fuel Battery chemical power P chem and wheel drive power P wheel ; System efficiency is the ratio of total system output power to total input power. During drive operation, all charging modes involve the engine charging the battery via motor M1. System efficiency... or sys Calculate using the following formula:

[0028] In the formula, l coef This is the oil-electric equivalence coefficient between the engine fuel exothermic power and the battery chemical power. For a specific working point under a specific mode ( T wheel , n wheel For each gear combination of the transmission that meets the independent variable constraint conditions, N AMT1 , N AMT2 All power source torque distribution combinations () T M1 , T M2 , T Eng The system efficiency is calculated accordingly, and the optimal efficiency for that operating point under that mode, along with its corresponding gearbox gear combination and power source torque distribution combination, is determined by comparing the calculation results. Then, the optimal efficiency for each operating point under each mode, along with its corresponding power source torque distribution combination and gearbox gear combination, is calculated using the same method.

[0029] In the formula, or mij It is the working point under the mode mij ( T wheel , n wheel The optimal efficiency of the system. EfficiencyMAP mij , TrqENGMAP mij , TrqM1MAP mij , TrqM2MAP mij , N AMT1 MAP mij , N AMT2 MAP mij These are the efficiencies corresponding to the optimal system efficiency at each operating point under mode mij. MAP Engine torque distribution MAP Torque distribution of motor M1 MAP Torque distribution of motor M2 MAP AMT1 gearbox MAP AMT 2 gear MAP ; When calculating the efficiency of each system mode, the constraints for selecting the independent variables are as follows:

[0030] In the formula, T Engmax This indicates the engine's maximum torque.n Engmax This indicates the engine's maximum speed. T M1max This indicates the peak torque of motor M1. n M1max This indicates the maximum speed of motor M1. T M2max This indicates the peak torque of motor M2. n M2max This indicates the maximum speed of motor M2. N AMT1 , N AMT2 This indicates the gear number of the transmission.

[0031] Furthermore, the online energy management of the longitudinal adhesion coefficient constraint described in step S3 specifically includes: S31: Determine the current vehicle operating status; S32: Determines the energy management strategy for driving, braking, and parking states based on the current vehicle operating status, and calculates the required torque after entering the driving state. S33: Construct a mode selection strategy based on optimal system efficiency; S34: Construct a system mode switching coordination strategy.

[0032] Furthermore, in step S31, the vehicle operating state is divided into parking state, running empty state, driving state, driving state and braking state, wherein the vehicle driving state includes driving state and braking state. After the vehicle key is powered on, the train enters the no-load operation state; based on the current driver's pedal opening signal... Acc Brake pedal opening signal Brk and the current wheel end speed signal n wheel Determine the current vehicle operating status: If the vehicle speed is zero and the drive pedal opening is zero, the vehicle enters the parking state; if the vehicle speed is zero and the drive pedal opening is greater than zero, the vehicle enters the driving state; if the drive pedal opening is greater than zero while the vehicle is in the driving state, the vehicle enters the driving state; if the brake pedal opening is greater than zero while the vehicle is in the driving state, the vehicle enters the braking state; when the vehicle speed is zero, the vehicle exits the driving state and enters the running empty state.

[0033] Furthermore, step S32 specifically includes: based on the current wheel end speed signal n wheel The maximum wheel-end torque required at this speed can be obtained by referring to the table. T reqwheelmax Combined with pedal opening signal Acc ( Brk The required torque corresponding to the pedal opening degree is calculated. T reqpedal :

[0034] Based on the currently estimated longitudinal road adhesion coefficient f est Combined with the overall vehicle weight m Calculate the maximum adhesion at the wheel end F φ :

[0035] Combined with the tire radius r tire Further calculation of the torque corresponding to the maximum adhesion force at the wheel end T φ :

[0036] The torque condition for preventing wheel slippage is:

[0037] The required torque corresponding to the pedal opening T reqpedal Torque corresponding to the maximum adhesion at the wheel end T φ In comparison, the smaller value is taken as the final wheel-end torque requirement: .

[0038] Furthermore, in step S33, during vehicle operation, the current vehicle operating status and wheel end speed are used to determine the speed. n wheel and the calculated wheel-end torque requirements T req Based on the system efficiency of each mode obtained in S31 MAP Look up the table to obtain the system efficiency under different operating modes under the current conditions:

[0039] If the vehicle is in driving mode, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which characterizes the battery's SOC status, the optimal system efficiency under this condition is determined. or veh With pattern M veh Determined as:

[0040] In the formula, DisCharAndCharFig = -1 indicates that the vehicle needs to be forcibly discharged, and the optimal efficiency mode is in m 34 m 23 Choose from all modes; DisCharAndCharFig = 0 indicates that the vehicle does not require forced charging and discharging, and the optimal efficiency mode is selected from all modes; DisCharAndCharFig = 1 indicates that the vehicle requires forced charging, and the optimal efficiency mode is selected from all modes. 33 m 35 Choose from; If the vehicle is under braking, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which represents the battery's SOC status, if the forced charge / discharge signal DisCharAndCharFig = -1, meaning the vehicle needs forced discharge, then the resistance torque of both motors is zero, and the braking torque demand is entirely provided by mechanical braking; if the forced charge / discharge signal DisCharAndCharFig ≠ -1, then the motor currently in operation provides the maximum resistance torque that it can provide at the current speed, and the insufficient part is made up by mechanical braking; if neither motor is currently in operation, then both motors provide the maximum resistance torque that they can provide at the current speed, and the insufficient part is made up by mechanical braking. If the vehicle is parked, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which characterizes the battery's SOC, if DisCharAndCharFig = 1, indicating that the vehicle requires forced charging, then parking charging is necessary: ​​shift the transmission to neutral and engage clutch C1 to use the engine drive motor M1 to charge the battery, thus determining the system's optimal efficiency. or veh = or m33 With pattern M veh M33 motor M1 is in charging mode while motor M2 is not operating; Finally, based on the optimal system efficiency obtained in S31, the corresponding engine, motor, and transmission gears are determined. MAP Look up the table to obtain the corresponding transmission gear and power source torque distribution that optimizes system efficiency under the current operating conditions.

[0041] Furthermore, step S34 specifically includes: At the present moment k The efficiency of the optimal target mode selected under the wheel-end speed and wheel-end torque requirements is compared with the previous step length ( kIf the absolute value of the efficiency difference between the optimal modes of -1) is less than 5% of the efficiency of the optimal mode of the previous step, or if the waiting time after the last gear shift is less than a specified time, or the waiting time after the last mode switch is less than a specified time, then the mode selected in the previous step remains unchanged.

[0042] In the formula, It is the current moment. k The efficiency of the optimal target mode selected under the wheel-end speed and wheel-end torque requirements. It is the length of the previous step ( k The efficiency of the optimal mode of -1). t AMT This is the waiting time after the last gear shift. t model This is the waiting time after the last mode switch was completed. T ruleAMT It is the specified waiting time between two gear shifts. T rulemodel This refers to the waiting time specified for two mode switching cycles.

[0043] The beneficial effects of this invention are as follows: (1) Establish a model for estimating the longitudinal road surface adhesion coefficient of commercial vehicles based on the Unmarked Kalman Filter (UKF) algorithm. The real-time estimation result of the longitudinal road surface adhesion coefficient by UKF is introduced as a hard constraint into the energy management strategy of the hybrid power system of commercial vehicles, which solves the safety hazard of traditional strategies that only consider efficiency and ignore driving anti-skid.

[0044] (2) An energy management strategy was established by combining “offline global optimization” and “online safety constraints”. Under the premise of ensuring the vehicle’s longitudinal adhesion, the energy-saving potential of the hybrid power system was fully utilized, taking into account both economy and safety.

[0045] 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

[0046] 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: Figure 1 This is the three-axle vehicle dynamics model described in this invention; Figure 2This is a schematic diagram of the longitudinal road surface adhesion coefficient estimation process based on unscented Kalman filtering as described in this invention; Figure 3 This is a configuration diagram of the hybrid commercial vehicle described in this invention; Figure 4 This is a flowchart illustrating the overall implementation process of the energy management strategy described in this invention. Figure 5 This is a schematic diagram illustrating the principle of safety constraint for wheel-end required torque. Detailed Implementation

[0047] 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.

[0048] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0049] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0050] Example 1: This invention provides a method for optimal energy management of a commercial vehicle hybrid power system based on real-time estimation of longitudinal road surface adhesion coefficient, comprising: 1. Establish a longitudinal dynamics model and a Dugoff tire model for a three-axle commercial vehicle; using the longitudinal road adhesion coefficient of the six wheels as the state variable and the longitudinal acceleration of the whole vehicle as the observation variable, the unscented Kalman filter algorithm UKF is used to estimate the longitudinal road adhesion coefficient in real time during the driving process.

[0051] (1) Vehicle dynamics model like Figure 1As shown, a three-axle vehicle dynamics model is established considering the longitudinal motion of the vehicle, and the following assumptions are made: the origin of the coordinate system fixed on the vehicle coincides with the center of mass of the three-axle heavy vehicle; it is assumed that the vehicle only moves longitudinally in the plane, and the effects of pitch, roll and vertical motion on the vehicle dynamics are ignored; the effects of air resistance on vehicle dynamics are ignored; it is assumed that all tires have the same motion characteristics; the road surface is flat, and the effects of slope resistance are ignored.

[0052] The longitudinal force balance equations for the entire vehicle are as follows:

[0053] Meanwhile, the rotational dynamics of the wheel is described by the following equation:

[0054] In the formula, m For the overall vehicle quality, a x For longitudinal acceleration, F xfr , F xfl , F xmr , F xml , F xrr , F xrl The longitudinal force is the force exerted on the left and right tires of the front, middle, and rear axles. J w For the moment of inertia of the wheel, oh i This is the wheel angular velocity (the subscript i indicates the specific wheel). F di , F bi 、F xi For each wheel's driving torque, braking torque, and longitudinal force, r The radius is the wheel radius.

[0055] Considering the effect of longitudinal acceleration, the vertical load on each tire can be expressed as:

[0056] In the formula, F zfr , F zfl , F zmr , F zml , F zrr , F zrlThe vertical load on the left and right tires of the front, middle, and rear axles. a 1. a 2. a 3 represents the distance from the front, middle, and rear axles to the vehicle's center of gravity. h g For the height of the vehicle's center of gravity, L This is the distance between the center of the front axle and the center of the rear axle.

[0057] (2) Dugoff tire model All forces and torques acting on a vehicle are generated through the interaction between the moving tires and the ground. Accurately representing the relationship between these forces and torques and vehicle parameters such as slip ratio, vertical force, and road adhesion coefficient requires establishing a suitable tire model for simulation analysis. This paper adopts an empirical or semi-empirical formula modeling method, namely the Dugoff tire model. Its force relationships are as follows:

[0058]

[0059] In the formula, F x , F z For the longitudinal and vertical forces of the tire, f The adhesion coefficient, C x These are the longitudinal stiffness of the tire. l For slip ratio, v x This represents the longitudinal speed of the entire vehicle.

[0060] To characterize the nonlinear characteristics of tire forces caused by tire slippage, boundary values ​​were introduced. L These quantities are independent of the adhesion coefficient.

[0061]

[0062] In the formula, e This is the speed influence factor.

[0063] To facilitate the estimation of the road adhesion coefficient, the Dugoff tire model is simplified to the following normalized model, which can be written as:

[0064] In the formula, This is a longitudinally normalized force, independent of the road surface adhesion coefficient. This greatly facilitates the determination of the coefficient matrix and the implementation of the adhesion coefficient estimation algorithm based on UKF filtering during the implementation process.

[0065] (3) Estimation of longitudinal road adhesion coefficient based on UKF like Figure 2 Road surface adhesion coefficient estimation based on UKF (Unscented Kalman Filter) is a process that combines vehicle dynamics models, tire models, and the UKF algorithm to estimate the longitudinal adhesion coefficient between the tire and the road surface in real time using information from onboard sensors. Its core principle is to leverage the advantages of UKF in handling nonlinear systems, treating the longitudinal road surface adhesion coefficient as a state variable, and achieving high-precision estimation through a "prediction-correction" recursive process. The specific process is as follows: ① Construct process equations and observation equations and discretize them. Define state variables x = [ f fl , f fr, f ml, f mr, f rl, f rr ] T ,in f i Define the observed variables for the road adhesion coefficients of the six wheels. z = [ a x ].

[0066] Based on the vehicle dynamics model in (1), the dynamic evolution of the adhesion coefficient is described. The continuous-time equation is discretized to obtain the discrete state equation. x ( k +1) = Φx ( k ) + w ( k )for:

[0067] In the formula, F Here is the state transition matrix. w ( k () represents process noise.

[0068] Based on the tire model in (2), the mapping between observed variables and state variables is established through the relationship between tire force and acceleration, and the observation equations are listed. z ( k ) = Hx ( k ) + v ( k )for:

[0069] In the formula, H For the observation matrix, v ( k () is for measuring noise.

[0070] ②UKF initialization Provide initial conditions for the UKF recursive process and set initial state estimates. (0), initial covariance matrix P (0), the rationality of the initial value directly affects the convergence speed of the algorithm; setting the noise covariance during the process. Q and measurement noise covariance R Noise covariance Q and R The selection of values ​​balances the weights of "predicted values" and "observed values," thus determining the estimation accuracy.

[0071] ③ Generate Sigma points Based on the current state estimate ( k ) and covariance P ( k ), generated by Unscented(UT) transformation 2 n +1 Sigma point ( n For the state dimension, here n =6, therefore 13 points are generated), the calculation formula is:

[0072] In the formula, s For the scaling factor ( β (Control Sigma point distribution) The i-th column is the square root of the matrix.

[0073] Assign weights to each Sigma point (mean weight) and (Covariance weights), satisfying .

[0074] ④ Time Update (Prediction Step) Substituting the generated Sigma point into the state equation, we obtain the Sigma point at the predicted time:

[0075] The mean of the predicted state is calculated by weighted summation:

[0076] Calculate the covariance of the predicted state:

[0077] Based on the current state and the dynamic characteristics of the system, the state and uncertainties at the next moment are predicted, providing a "prior estimate" for subsequent corrections.

[0078] ⑤ Measurement update (calibration steps) Substituting the predicted Sigma points into the observation equation, we obtain the Sigma points in the observation space:

[0079] Calculate the predicted mean of the observations:

[0080] Calculate the observation covariance, the cross-covariance between state and observation, and the Kalman gain:

[0081] Corrected state and covariance:

[0082] The predicted value is corrected using the actual observed value (sensor data) to reduce the estimation error and obtain the "posterior estimate".

[0083] ⑥ Output adhesion coefficient estimate From the corrected state The longitudinal road adhesion coefficients of the six wheels are extracted, and the minimum value is taken as a constraint condition for the subsequent calculation of the torque demand for energy management strategies. f est .

[0084]

[0085] 2. For various vehicle operating modes, across the entire operating range, with the goal of optimizing the overall efficiency of the hybrid power system, offline calculations are performed and the optimal operating mode, engine and motor torque distribution scheme, and transmission gear position corresponding to the optimal system efficiency at each operating point are stored, forming a global optimal efficiency lookup table. MAP ; The heavy-duty hybrid commercial vehicle used in this embodiment is a series-parallel hybrid configuration with a coaxial middle axle and a pure electric rear axle, such as... Figure 3As shown, the connection relationships between components such as the engine and the axle are clearly defined. By controlling the working states of the engine, motor M1, motor M2, and clutch C, the vehicle's driving modes can be divided into nine different working modes: pure engine mode m1, pure electric mode m21 (motor M1 drives, motor M2 does not work), pure electric mode m22 (motor M1 does not work, motor M2 drives), pure electric mode m23 (motor M1 drives, motor M2 drives), hybrid mode m31 (motor M1 does not work, motor M2 drives), hybrid mode m32 (motor M1 drives, motor M2 does not work), hybrid mode m33 (motor M1 charges, motor M2 does not work), hybrid mode m34 (motor M1 drives, motor M2 drives), and hybrid mode m35 (motor M1 charges, motor M2 drives).

[0086] Based on the vehicle model and mode division established above, the independent variable for calculating system efficiency is the engine torque. T Eng With rotational speed n Eng The torque of motor M1 T M1 With rotational speed n M1 The torque of motor M2 T M2 With rotational speed n M2 and the AMT1 gearbox for the middle axle and the AMT2 gearbox for the rear axle. N AMT1 , N AMT2 Given the wheel-end torque T wheel Wheel end speed n wheel And under the condition of battery SOC, the engine fuel heat release power under this operating condition can be calculated separately. P fuel Battery chemical power P chem and wheel drive power P wheel System efficiency is the ratio of total system output power to total system input power. Since this hybrid commercial vehicle operates without external charging, all charging modes during drive are performed by the engine charging the battery via motor M1. Therefore, the system efficiency is... or sys Calculate using the following formula:

[0087] In the formula, l coef It is the oil-electric equivalence coefficient between the engine fuel exothermic power and the battery chemical power.

[0088] To obtain the optimal system efficiency under different operating conditions in various modes, and to obtain the optimal efficiency and the corresponding power source torque distribution and transmission gear combination. MAP For a specific working point under a specific mode ( T wheel , n wheel ), it is necessary to consider each gear combination of the transmission that meets the independent variable constraints ( N AMT1 , N AMT2 All power source torque distribution combinations () T M1 , T M2 , T Eng The system efficiency is calculated accordingly, and the optimal efficiency for that operating point under that mode, along with its corresponding gearbox gear combination and power source torque distribution combination, is determined by comparing the calculation results. Then, the optimal efficiency for each operating point under each mode, along with its corresponding power source torque distribution combination and gearbox gear combination, is calculated using the same method.

[0089] In the formula, or mij It is the working point under the mode mij ( T wheel , n wheel The optimal efficiency of the system. EfficiencyMAP mij , TrqENGMAP mij , TrqM1MAP mij , TrqM2MAP mij , N AMT1 MAP mij , N AMT2 MAP mij These are the efficiencies corresponding to the optimal system efficiency at each operating point under mode mij. MAP Engine torque distribution MAP Torque distribution of motor M1 MAP Torque distribution of motor M2 MAP AMT1 gearbox MAP AMT 2 gear MAP .

[0090] When calculating the efficiency of each system mode, the constraints for selecting the independent variables are as follows:

[0091] In the formula, T Engmax This indicates the engine's maximum torque. n Engmax This indicates the engine's maximum speed. T M1max This indicates the peak torque of motor M1. n M1max This indicates the maximum speed of motor M1. T M2max This indicates the peak torque of motor M2. n M2max This indicates the maximum speed of motor M2. N AMT1 , N AMT2 This indicates the gear number of the transmission.

[0092] 3. During real-time vehicle operation, based on the estimated minimum longitudinal road surface adhesion coefficient, calculate the safe torque limit corresponding to the maximum wheel-end adhesion force; constrain the driver's required torque using the safe torque limit; within the safe torque range, query the optimal efficiency based on the current wheel-end speed and required torque. MAP It determines the most efficient working mode and power allocation instructions for the current system.

[0093] like Figure 4 The diagram illustrates the online energy management strategy for hybrid heavy-duty trucks, clearly describing the decision-making logic throughout the entire process, from state assessment and demand torque calculation to mode selection and torque distribution. This strategy, combined with the previously estimated adhesion coefficient, battery SOC state, and vehicle operating status, coordinates and controls the operation of various components of the powertrain system to ensure efficient, energy-saving, and safe operation of the hybrid heavy-duty truck. The strategy mainly covers the following four parts: ①Current operating status determined The vehicle's operating status is mainly divided into parking status, idle operating status, in-process operating status, driving status, and braking status. The in-process operating status includes both driving and braking. When the vehicle key is powered on, the train enters the idle operating status. This is based on the current driver's pedal opening signal. Acc Brake pedal opening signal Brk and the current wheel end speed signal n wheelThe current vehicle operating state is determined as follows: If the vehicle speed is zero and the drive pedal opening is zero, the vehicle enters the parking state; if the vehicle speed is zero and the drive pedal opening is greater than zero, the vehicle enters the driving state; if the drive pedal opening is greater than zero while the vehicle is in the driving state, the vehicle enters the driving state; if the brake pedal opening is greater than zero while the vehicle is in the driving state, the vehicle enters the braking state. When the vehicle speed is zero, the vehicle exits the driving state and enters the idle state.

[0094] ② Calculation of wheel-end torque requirements The energy management strategy for driving, braking, and parking is determined based on the current vehicle operating status. Upon entering the driving operating state, the required torque is first calculated based on the current wheel-end speed signal. n wheel The maximum wheel-end torque required at this speed can be obtained by referring to the table. T reqwheelmax Combined with pedal opening signal Acc ( Brk The required torque corresponding to the pedal opening degree is calculated. T reqpedal :

[0095] During vehicle operation, the longitudinal adhesion coefficient at the wheel end f This varies depending on road conditions, and is to prevent the wheel's required torque from exceeding the maximum traction at the wheel end. F φ The corresponding torque causes wheel slippage, which needs to be determined based on the currently estimated longitudinal road adhesion coefficient. f est Combined with the overall vehicle weight m Calculate the maximum adhesion at the wheel end F φ :

[0096] Combined with the tire radius r tire Further calculation of the torque corresponding to the maximum adhesion force at the wheel end T φ :

[0097] Therefore, the torque condition for the wheel to not slip is:

[0098] The required torque corresponding to the pedal opening mentioned above T reqpedal Torque corresponding to the maximum adhesion at the wheel end T φIn comparison, the smaller value is taken as the final wheel-end torque requirement:

[0099] like Figure 5 This visually demonstrates how to calculate the safe torque limit based on the estimated longitudinal adhesion coefficient and how to adjust the driver's required torque to ensure that driving remains within the adhesion limits. T reqpedal and T φ The comparison limits the required torque at the wheel ends. T req ∈[0, T φ To ensure the rotational speed at the wheel end. n wheel When selecting the mode with optimal system efficiency, the torque corresponding to the maximum adhesion at the wheel end is... T φ The system uses a lookup table based on the required torque at the wheel ends to find the optimal efficiency mode, the corresponding power source torque distribution combination, and the transmission gear combination to avoid slippage.

[0100] ③ Mode selection strategy based on optimal system efficiency During vehicle operation, the current vehicle operating status and wheel end speed are used to determine the vehicle's speed. n wheel and the calculated wheel-end torque requirements T req Based on the system efficiency of each model obtained in ① MAP Look up the table to obtain the system efficiency under different operating modes under the current conditions:

[0101] If the vehicle is in driving mode, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which characterizes the battery's SOC status, the optimal system efficiency under this condition is determined. or veh With pattern M veh Determined as:

[0102] In the formula, DisCharAndCharFig = -1 indicates that the vehicle needs to be forcibly discharged, and the optimal efficiency mode is in m 34 m 23 Choose from all modes; DisCharAndCharFig = 0 indicates that the vehicle does not require forced charging and discharging, and the optimal efficiency mode is selected from all modes; DisCharAndCharFig = 1 indicates that the vehicle requires forced charging, and the optimal efficiency mode is selected from all modes. 33m 35 Choose from the options provided.

[0103] If the vehicle is under braking, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which represents the battery's SOC status, if the forced charge / discharge signal DisCharAndCharFig = -1, meaning the vehicle needs forced discharge, then the resistance torque of both motors is zero, and the braking torque demand is entirely provided by mechanical braking. If the forced charge / discharge signal DisCharAndCharFig ≠ -1, then the motor currently in operation provides the maximum resistance torque it can provide at the current speed, with any shortfall made up by mechanical braking. If neither motor is currently in operation, then both motors provide the maximum resistance torque they can provide at the current speed, with any shortfall made up by mechanical braking.

[0104] If the vehicle is parked, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which characterizes the battery's SOC, if DisCharAndCharFig = 1, indicating that the vehicle requires forced charging, then parking charging is necessary: ​​shift the transmission to neutral and engage clutch C1 to use the engine drive motor M1 to charge the battery, thus determining the system's optimal efficiency. or veh = or m33 With pattern M veh This is the charging mode for motor M1 (m33) and the non-operating mode for motor M2.

[0105] Finally, based on the optimal system efficiency obtained in ①, the corresponding engine, motor, and transmission gears are determined. MAP Look up the table to obtain the corresponding transmission gear and power source torque distribution that optimizes system efficiency under the current operating conditions.

[0106] ④ System mode switching coordination strategy If the optimal target mode differs from the optimal mode used in the previous moment, it means that switching modes is required to adopt the current target mode. To avoid the shock caused by switching driving modes back and forth and frequent gear shifts during driving, at the current moment... k The efficiency of the optimal target mode selected under the wheel-end speed and wheel-end torque requirements is compared with the previous step length ( k If the absolute value of the efficiency difference between the optimal modes of -1) is less than 5% of the efficiency of the optimal mode of the previous step, or if the waiting time after the last gear shift is less than the specified time, or if the waiting time after the last mode switch is less than the specified time, then the mode will remain the mode selected in the previous step.

[0107]

[0108] In the formula, It is the current moment. k The efficiency of the optimal target mode selected under the wheel-end speed and wheel-end torque requirements. It is the length of the previous step ( k The efficiency of the optimal mode of -1). t AMT This is the waiting time after the last gear shift. t model This is the waiting time after the last mode switch was completed. T ruleAMT It is the specified waiting time between two gear shifts. T rulemodel This refers to the waiting time specified for two mode switching cycles.

[0109] Example 2: An electronic device, comprising a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the method described in Embodiment 1 when executing the computer program.

[0110] Example 3: A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0111] Example 4: A computer program product includes a computer program that, when executed by a processor, implements the method described in Example 1.

[0112] In the above embodiments, the reference to "this embodiment" in the specification indicates that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple appearances of "this embodiment" do not necessarily refer to the same embodiment.

[0113] In the above embodiments, although the invention has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory structures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed. The embodiments of the invention are intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims.

[0114] As will be understood by those skilled in the art, the computer-readable storage medium described in this embodiment allows for the implementation of all or part of the steps in the above method embodiments by computer program-related hardware. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0115] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver, and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication between them. The memory is used to store computer programs, the communication interface is used to perform communication, and the processor and the transceiver are used to run the computer programs, so that the electronic terminal performs the steps of the above method.

[0116] In this embodiment, the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0117] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0118] This invention can be used in a wide range of general-purpose or special-purpose computing system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0119] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0120] 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 method for optimal energy management of a commercial vehicle hybrid power system based on real-time estimation of longitudinal road surface adhesion coefficient, characterized in that: Includes the following steps: S1: Online estimation of longitudinal road adhesion coefficient: A longitudinal dynamics model and a Dugoff tire model of a three-axle commercial vehicle are established; the longitudinal road adhesion coefficient of the six wheels is used as the state variable and the longitudinal acceleration of the whole vehicle is used as the observation variable. The unscented Kalman filter algorithm UKF is used to estimate the longitudinal road adhesion coefficient in real time during the driving process. S2: Optimal system efficiency MAP Offline calibration: For various vehicle operating modes, across the entire operating range, with the goal of optimizing the overall efficiency of the hybrid system, offline calculation and storage are performed for the optimal operating mode, engine and motor torque distribution scheme, and transmission gear position corresponding to the optimal system efficiency at each operating point, forming a global optimal efficiency lookup table. MAP ; S3: Online energy management constrained by longitudinal adhesion coefficient: During real-time vehicle operation, the safe torque limit corresponding to the maximum adhesion force at the wheel end is calculated based on the estimated minimum longitudinal road adhesion coefficient. The driver's required torque is constrained by the aforementioned safe torque limit; within the safe torque range, the optimal efficiency is queried based on the current wheel-end speed and the required torque. MAP It determines the most efficient working mode and power allocation instructions for the current system.

2. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 1, characterized in that: The establishment of the longitudinal dynamics model for the three-axle commercial vehicle specifically includes: A three-axle vehicle dynamics model is established considering the longitudinal motion of the vehicle, with the following assumptions: the origin of the coordinate system fixed on the vehicle coincides with the center of mass of the three-axle heavy vehicle; it is assumed that the vehicle only moves longitudinally in a plane, and the effects of pitch, roll, and vertical motion on the vehicle's dynamic characteristics are ignored; the effects of air resistance on vehicle dynamics are ignored; it is assumed that all tires have the same motion characteristics; the road surface is flat, and the effects of slope resistance are ignored. The longitudinal force balance equations for the entire vehicle are as follows: The rotational dynamics of a wheel are described by the following equations: In the formula, m For the overall vehicle quality, a x For longitudinal acceleration, F xfr , F xfl , F xmr , F xml , F xrr , F xrl The longitudinal force is the force exerted on the left and right tires of the front, middle, and rear axles. J w For the moment of inertia of the wheel, ω i Let be the angular velocity of the i-th wheel. F di , F bi 、F xi For each wheel's driving torque, braking torque, and longitudinal force, r The radius of the wheel; Considering the effect of longitudinal acceleration, the vertical load on each tire is expressed as: In the formula, F zfr , F zfl , F zmr , F zml , F zrr , F zrl The vertical load on the left and right tires of the front, middle, and rear axles. a 1. a 2. a 3 represents the distance from the front, middle, and rear axles to the vehicle's center of gravity. h g For the height of the vehicle's center of gravity, L This is the distance between the center of the front axle and the center of the rear axle.

3. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 2, characterized in that: The establishment of the Dugoff tire model specifically includes: The force relationship of the tire is as follows: In the formula, F x , F z For the longitudinal and vertical forces of the tire, φ The adhesion coefficient, C x These are the longitudinal stiffness of the tire. λ For slip ratio, v x The longitudinal speed of the entire vehicle; Introducing boundary values L Describes the nonlinear characteristics of tire forces caused by tire slippage: In the formula, ε As a speed-affecting factor; The Dugoff tire model is simplified to the following normalized model, written as: In the formula, It is the longitudinal normalized force.

4. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 3, characterized in that: The method of using the Unscented Kalman Filter (UKF) algorithm to estimate the longitudinal road adhesion coefficient during driving in real time includes: Construct and discretize process equations and observation equations: Define state variables x = [ φ fl , φ fr, φ ml, φ mr, φ rl, φ rr ] T ,in φ i Define the observed variables for the road adhesion coefficients of the six wheels. z = [ a x ]; Based on the vehicle dynamics model, the dynamic evolution of the adhesion coefficient is described. The continuous-time equation is discretized to obtain the discrete state equation. x ( k +1) = Φx ( k ) + w ( k )for: In the formula, Φ Here is the state transition matrix. w ( k ) represents process noise; Based on the Dugoff tire model, the mapping between observed variables and state variables is established through the relationship between tire force and acceleration, and the observation equations are listed. z ( k ) = Hx ( k ) + v ( k )for: In the formula, H For the observation matrix, v ( k (This refers to the measurement of noise.) UKF initialization: Provides initial conditions for the UKF recursive process and sets initial state estimates. (0), initial covariance matrix P (0); Setting process noise covariance Q and measurement noise covariance R ; Generate Sigma points: Estimate based on the current state ( k ) and covariance P ( k ), generated by Unscented(UT) transformation 2 n +1 Sigma point, n For the state dimension, the calculation formula is: In the formula, s As a scaling factor, The i-th column is the square root of the matrix; Assign mean weights to each Sigma point Covariance weights ,satisfy ; Time update: Substitute the generated Sigma point into the state equation to obtain the Sigma point at the predicted time: The mean of the predicted state is calculated by weighted summation: Calculate the covariance of the predicted state: Based on the current state and the dynamic characteristics of the system, predict the state and uncertainties at the next moment; Measurement Update: Substitute the predicted Sigma points into the observation equation to obtain the Sigma points in the observation space: Calculate the predicted mean of the observations: Calculate the observation covariance, the cross-covariance between state and observation, and the Kalman gain: Corrected state and covariance: The predicted values ​​are corrected using actual observations to reduce estimation errors and obtain a posterior estimate; Output adhesion coefficient estimate: from the corrected state The longitudinal road adhesion coefficients of the six wheels are extracted, and the minimum value is taken as a constraint condition for the subsequent calculation of the torque demand for energy management strategies. φ est : 。 5. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 1, characterized in that: The multiple operating modes of the vehicle mentioned in step S2 include: by controlling the working states of the engine, motor M1, motor M2 and clutch C, the vehicle driving mode is divided into nine different operating modes: pure engine mode m1, pure electric mode m21 motor M1 driving and motor M2 not working, pure electric mode m22 motor M1 not working and motor M2 driving, pure electric mode m23 motor M1 driving and motor M2 driving, hybrid mode m31 motor M1 not working and motor M2 driving, hybrid mode m32 motor M1 driving and motor M2 not working, hybrid mode m33 motor M1 charging and motor M2 not working, hybrid mode m34 motor M1 driving and motor M2 driving, hybrid mode m35 motor M1 charging and motor M2 driving; In step S2, based on the established vehicle model and mode division, the independent variable for calculating system efficiency is the engine torque. T Eng With rotational speed n Eng The torque of motor M1 T M1 With rotational speed n M1 The torque of motor M2 T M2 With rotational speed n M2 and the AMT1 gearbox for the middle axle and the AMT2 gearbox for the rear axle. N AMT1 , N AMT2 ; Given wheel end torque T wheel Wheel end speed n wheel And under the condition of battery SOC, the engine fuel heat release power can be calculated separately. P fuel Battery chemical power P chem and wheel drive power P wheel ; System efficiency is the ratio of total system output power to total input power. During drive operation, all charging modes involve the engine charging the battery via motor M1. System efficiency... η sys Calculate using the following formula: In the formula, λ coef This is the oil-electric equivalence coefficient between the engine fuel exothermic power and the battery chemical power. For a specific working point under a specific mode ( T wheel , n wheel For each gear combination of the transmission that meets the independent variable constraint conditions, N AMT1 , N AMT2 All power source torque distribution combinations () T M1 , T M2 , T Eng The system efficiency is calculated accordingly, and the optimal efficiency for that operating point under that mode, along with its corresponding gearbox gear combination and power source torque distribution combination, is determined by comparing the calculation results. Then, the optimal efficiency for each operating point under each mode, along with its corresponding power source torque distribution combination and gearbox gear combination, is calculated using the same method. In the formula, η mij It is the working point under the mode mij ( T wheel , n wheel The optimal efficiency of the system. EfficiencyMAP mij , TrqENGMAP mij , TrqM1MAP mij , TrqM2MAP mij , N AMT1 MAP mij , N AMT2 MAP mij These are the efficiencies corresponding to the optimal system efficiency at each operating point under mode mij. MAP Engine torque distribution MAP Torque distribution of motor M1 MAP Torque distribution of motor M2 MAP AMT1 gearbox MAP AMT 2 gear MAP ; When calculating the efficiency of each system mode, the constraints for selecting the independent variables are as follows: In the formula, T Engmax This indicates the engine's maximum torque. n Engmax This indicates the engine's maximum speed. T M1max This indicates the peak torque of motor M1. n M1max This indicates the maximum speed of motor M1. T M2max This indicates the peak torque of motor M2. n M2max This indicates the maximum speed of motor M2. N AMT1 , N AMT2 This indicates the gear number of the transmission.

6. The method for optimal energy management of a commercial vehicle hybrid power system based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 1, characterized in that: The online energy management of the longitudinal adhesion coefficient constraint mentioned in step S3 specifically includes: S31: Determine the current vehicle operating status; S32: Determines the energy management strategy for driving, braking, and parking states based on the current vehicle operating status, and calculates the required torque after entering the driving state. S33: Construct a mode selection strategy based on optimal system efficiency; S34: Construct a system mode switching coordination strategy.

7. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 6, characterized in that: In step S31, the vehicle operating state is divided into parking state, running empty state, moving operating state, driving state and braking state, wherein the moving operating state includes driving state and braking state. After the vehicle key is powered on, the train enters the no-load operation state; based on the current driver's pedal opening signal... Acc Brake pedal opening signal Brk and the current wheel end speed signal n wheel Determine the current vehicle operating status: If the vehicle speed is zero and the drive pedal opening is zero, the vehicle enters the parking state; if the vehicle speed is zero and the drive pedal opening is greater than zero, the vehicle enters the driving running state. If the opening of the drive pedal is greater than zero while the vehicle is in motion, the vehicle enters the driving state. If the brake pedal opening is greater than zero while the vehicle is in motion, the vehicle will enter a braking state. When the vehicle speed is zero, the vehicle exits the driving state and enters the running empty state.

8. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 6, characterized in that: Step S32 specifically includes: based on the current wheel end speed signal n wheel The maximum wheel-end torque required at this speed can be obtained by referring to the table. T reqwheelmax Combined with pedal opening signal Acc ( Brk The required torque corresponding to the pedal opening degree is calculated. T reqpedal : Based on the currently estimated longitudinal road adhesion coefficient φ est Combined with the overall vehicle weight m Calculate the maximum adhesion at the wheel end F φ : Combined with the tire radius r tire Further calculation of the torque corresponding to the maximum adhesion force at the wheel end T φ : The torque condition for preventing wheel slippage is: The required torque corresponding to the pedal opening T reqpedal Torque corresponding to the maximum adhesion at the wheel end T φ In comparison, the smaller value is taken as the final wheel-end torque requirement: 。 9. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 6, characterized in that: In step S33, during vehicle operation, the current vehicle operating status and wheel end speed are used to determine the speed. n wheel and the calculated wheel-end torque requirements T req Based on the system efficiency of each mode obtained in S31 MAP Look up the table to obtain the system efficiency under different operating modes under the current conditions: If the vehicle is in driving mode, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which characterizes the battery's SOC status, the optimal system efficiency under this condition is determined. η veh With pattern M veh Determined as: In the formula, DisCharAndCharFig = -1 indicates that the vehicle needs to be forcibly discharged, and the optimal efficiency mode is in m 34 m 23 Choose from all modes; DisCharAndCharFig = 0 indicates that the vehicle does not require forced charging and discharging, and the optimal efficiency mode is selected from all modes; DisCharAndCharFig = 1 indicates that the vehicle requires forced charging, and the optimal efficiency mode is selected from all modes. 33 m 35 Choose from; If the vehicle is under braking, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which represents the battery's SOC status, if the forced charge / discharge signal DisCharAndCharFig = -1, meaning the vehicle needs forced discharge, then the resistance torque of both motors is zero, and the braking torque demand is entirely provided by mechanical braking; if the forced charge / discharge signal DisCharAndCharFig ≠ -1, then the motor currently in operation provides the maximum resistance torque that it can provide at the current speed, and the insufficient part is made up by mechanical braking; if neither motor is currently in operation, then both motors provide the maximum resistance torque that they can provide at the current speed, and the insufficient part is made up by mechanical braking. If the vehicle is parked, and considering the vehicle's forced charge / discharge signal DisCharAndCharFig, which characterizes the battery's SOC, if DisCharAndCharFig = 1, indicating that the vehicle requires forced charging, then parking charging is necessary: ​​shift the transmission to neutral and engage clutch C1 to use the engine drive motor M1 to charge the battery, thus determining the system's optimal efficiency. η veh = η m33 With pattern M veh M33 motor M1 is in charging mode while motor M2 is not operating; Finally, based on the optimal system efficiency obtained in S31, the corresponding engine, motor, and transmission gears are determined. MAP Look up the table to obtain the corresponding transmission gear and power source torque distribution that optimizes system efficiency under the current operating conditions.

10. The method for optimal energy management of commercial vehicle hybrid power systems based on real-time estimation of longitudinal road surface adhesion coefficient according to claim 6, characterized in that: Step S34 specifically includes: At the present moment k The efficiency of the optimal target mode selected under the wheel-end speed and wheel-end torque requirements is compared with the previous step length ( k If the absolute value of the efficiency difference between the optimal modes of -1) is less than 5% of the efficiency of the optimal mode of the previous step, or if the waiting time after the last gear shift is less than a specified time, or the waiting time after the last mode switch is less than a specified time, then the mode selected in the previous step remains unchanged. In the formula, It is the current moment. k The efficiency of the optimal target mode selected under the wheel-end speed and wheel-end torque requirements. It is the length of the previous step ( k The efficiency of the optimal mode of -1). t AMT This is the waiting time after the last gear shift. t model This is the waiting time after the last mode switch was completed. T ruleAMT It is the specified waiting time between two gear shifts. T rulemodel This refers to the waiting time specified for two mode switching cycles.

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