Electric four-wheel drive torque distribution method based on climbing working condition

Abstract

The invention relates to the field of power control, and particularly discloses an electric four-wheel drive torque distribution method based on a climbing working condition, which comprises the following steps: defining vehicle state parameters, power system parameters, vehicle real-time driving state parameters and road condition parameters; carrying out torque calculation by utilizing Julia, considering shaft load, friction coefficient, motor efficiency and yaw velocity correction, obtaining a comprehensive weight of a front shaft and a rear shaft, and carrying out normalized torque distribution; and establishing model simulation through Modelica, and verifying the effectiveness of the distribution scheme. According to the invention, the climbing performance of the vehicle can be improved, the control flexibility and driving stability of the vehicle are improved, the energy consumption is reduced, the dynamic stability is enhanced, and the method is suitable for power control of the electric four-wheel-drive vehicle under the climbing working condition.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power control, and in particular to a method for distributing torque of an electric four-wheel drive vehicle based on a climbing working condition. BACKGROUND

[0002] In the field of power control of electric four-wheel drive vehicles, a reasonable torque distribution strategy has a significant impact on the performance, energy consumption, and driving stability of the vehicle. It directly determines the core performance of the vehicle, the energy utilization efficiency, and the stability and safety of driving. Traditional power distribution methods often only consider motor torque limitations or a single vehicle driving parameter, such as simply distributing front and rear axle torque in a fixed ratio, or adjusting total torque output based solely on accelerator pedal opening, without considering changes in real-time vehicle state and road conditions. This mode, although simple in control logic and low in cost, is difficult to achieve optimal power output in complex conditions.

[0003] In different slope scenarios: when the vehicle is driving on a steep slope, whether uphill or downhill, the vehicle's center of gravity shifts dramatically. When going uphill, the rear axle load increases, requiring more rear axle torque to prevent slipping and provide driving power; when going downhill, the front axle motor may be used for stronger energy recovery and stability. Fixed distribution cannot adapt to such dynamic changes in load, which may result in insufficient driving force (when going uphill) or unbalanced braking force (when going downhill). At this time, the proportion of torque of the rear axle (or front axle) needs to be dynamically increased based on the information fed back by the slope sensor to improve the climbing ability or enhance the braking stability; on flat roads, a more balanced distribution method is needed to reduce energy consumption.

[0004] When facing different road friction coefficients, traditional strategies cannot perceive or quickly respond to such microscopic friction differences. On wet or icy roads, the road adhesion coefficient is low, and if the front and rear axle torque distribution is improper, it is easy to cause slipping of one axle. For example, if the front axle torque is too large, it may cause the front wheels to slip, resulting in loss of control; if the rear axle torque is too high, it may cause the vehicle to spin. At this time, the wheel slip rate detected by the wheel speed sensor needs to be combined to adjust the torque distribution ratio in real time, distributing more torque to the wheel with a higher adhesion coefficient to avoid slipping and ensure the driving efficiency and stability of the vehicle.

[0005] When the vehicle is in a turning condition, significant lateral acceleration and load transfer (increased load on the outer wheel, decreased load on the inner wheel) will occur when the vehicle is turning at high speed or changing lanes in an emergency. At this time, if the torque distribution is still linear, especially if it is distributed too much to the inner low adhesion wheel or the understeer axle (usually the front axle), the vehicle turning radius will be larger than expected due to insufficient front wheel grip, which will easily cause understeer. Or because of insufficient rear wheel grip, the vehicle tail slides outward, causing oversteer. It will also increase energy consumption, and the frequent intervention of the electronic stability system (ESC) will also increase energy consumption.

[0006] The traditional strategy cannot dynamically and coordinately adjust the torque of the inner and outer wheels and the front and rear axles according to parameters such as yaw rate, steering wheel angle, lateral acceleration, etc. during turning to actively shape the desired vehicle dynamic characteristics. In addition, the energy consumption problem is also closely related to torque distribution. In low-load scenarios such as uniform speed driving, if the torque distribution is unreasonable, it may cause one motor to be in an inefficient working interval (such as low speed and high torque state), causing energy waste; and by dynamically adjusting, the front and rear motors are allowed to work in the efficient interval, which can significantly improve the vehicle's range.

[0007] Therefore, compared with the traditional strategy, the dynamic torque distribution strategy based on multiple parameters (such as vehicle speed, acceleration, wheel speed, slope, steering angle, road friction coefficient, etc.) can flexibly adjust the front and rear axle torque ratio according to real-time working conditions, while ensuring vehicle dynamic performance and driving stability, and minimizing energy consumption. It is an important development direction of electric four-wheel drive power control technology. SUMMARY

[0008] The purpose of the present application is to solve the problems and deficiencies of torque distribution of vehicles in different slope, road friction or turning conditions in the prior art, and to propose an electric four-wheel drive torque distribution method based on climbing conditions. The torque distribution under different slope, road friction or turning conditions of the vehicle is realized through julia language programming and modelica model simulation.

[0009] In order to achieve the above purpose, the present application adopts the following technical scheme: An electric four-wheel drive torque distribution method based on climbing conditions, comprising: S1: parameter definition: defining vehicle state parameters, describing the basic structure of the vehicle and the driving environment; defining power system parameters for describing the characteristics of the vehicle power system; defining vehicle dynamic state, recording real-time driving state parameters of the vehicle; defining road conditions, including parameters describing the contact characteristics of the road and the tire; S2: julia torque distribution calculation: according to the parameters defined in step S1, the formula is used to calculate the torque distribution; S21: front and rear axle load calculation: according to the vehicle state parameters, considering the influence of vehicle slope (slope angle a) and mass center position (mass center height h) on axle load, the following formula is used to calculate: Fzr = mg·(Lf·cosα+ h·sinα) / L Fzf = mg·[(L-Lf)·cosα- h·sinα] / L Where: Fzr is the rear axle load, Fzf is the front axle load; The slope angle a significantly changes the component of the direction of gravity relative to the vehicle coordinate system (along the slope surface), and cos a represents the component of gravity along the direction perpendicular to the slope surface (i.e. the Z-axis direction of the vehicle); the larger the slope, the smaller cos a, meaning that the total normal force required to support the vehicle decreases; sin a represents the component of gravity along the direction parallel to the slope surface, which itself does not directly contribute to the vertical axle load, but it will affect the load distribution of the front and rear axles by changing the lever arm; this factor is the key to the formula to accurately reflect the axle load distribution of the vehicle under different working conditions such as uphill, downhill or horizontal road surface, etc. In the formula, the effect of the mass center position is reflected by "Lf" (the horizontal distance from the mass center to the front axle), "L" (the wheelbase) and "h" (the mass center height); the closer the mass center is to the front axle, the greater the front wheel load on flat ground; and the mass center height (h) will amplify the influence of slope on axle load, the higher the mass center, the more obvious the front and rear axle load fluctuation caused by slope change; S22: calculation of maximum available driving torque of front and rear axles: combined with the motor peak torque in the power system parameters, the axle load calculated in step S21, and the friction coefficient in the road condition, the tire radius in the vehicle state parameters, the following formula is used to calculate: Tf_max = min(front_motor_max,Fzf·μ_front·r) Tr_max = min(rear_motor_max, Fzr·μ_rear·r) Where: Tf_max is the maximum available driving torque of the front axle, and Tr_max is the maximum available driving torque of the rear axle; This group of formulas combines the vehicle state parameters and road condition parameters in the power system parameters, and uses the minimum function to realize the double constraint calculation of the maximum available driving torque (Tf_max, Tr_max) of the front and rear axles; it not only considers the output capacity of the power source, but also considers the core safety boundary of tire adhesion physical limit (Fz·μ· r), and the calculation result directly acts on the vehicle active safety system (to prevent slipping), power performance optimization and first torque distribution; the formula ensures that the vehicle power output is efficient, safe and controllable, and effectively converts the power source capacity into actual vehicle kinetic energy; S23: Efficiency calculation: Efficiency calculation is a key link in the power system control logic, the core of which is to combine the real-time dynamics of the vehicle with the characteristics of the power system, accurately obtain the working efficiency of the front and rear motors, and provide data support for subsequent optimization of power distribution; according to the current vehicle speed in the vehicle dynamic state, and the maximum available driving torque of the front and rear axles calculated in step S22 and the efficiency MAP diagram in the power system parameters, the front motor efficiency eff front and the rear motor efficiency eff rear are obtained through the index matrix method, which provides the basis for subsequent power distribution weight calculation; The final result of this calculation is to provide a key basis for subsequent power distribution weight calculation. By determining the efficiency level of the front and rear motors under the current working condition, it can be further judged how to distribute the torque, so as to maximize the efficiency of the overall power system and reduce energy consumption while meeting the power demand of the vehicle; S24: Dynamic stability correction: According to the yaw rate yaw rate in the real-time driving state of the vehicle, the following formula is used for correction: yaw_factor = 1 - 0.1·|ω|, wherein: yaw_factor is the yaw rate correction factor (used to adjust power distribution when the vehicle has a yaw trend, to enhance driving stability), and |ω| is the absolute value of the yaw rate yaw_rate; The core of dynamic stability correction is to quantitatively adjust the power distribution to enhance driving stability according to the yaw trend of the vehicle, and the formula design accurately considers the size of the yaw rate of the vehicle and realizes dynamic intervention through the correction factor; The formula takes into account the influence of the yaw rate of the vehicle. The yaw rate is a key parameter for measuring the rotation trend of the vehicle around the vertical axis, and its absolute value |ω| directly reflects the degree of deviation of the vehicle from stable driving state. The larger |ω| is, the higher the risk of vehicle side slip, spin or excessive or insufficient steering. By introducing |ω| in the formula, the current degree of rotation of the vehicle body is accurately captured; S25: Front and rear axle comprehensive weight calculation: Comprehensive weight calculation is the core link of torque distribution decision, and the formula integrates three key parameters of axle load, motor efficiency and yaw rate correction factor to quantify the power distribution priority of the front and rear axles, and provides the basis for the final power output ratio. The following formula is used for calculation: front_ratio = Fzf·eff_front·yaw_factor rear_ratio = Fzr·eff_rear·yaw_factor Wherein: front_ration is the front axle comprehensive weight, rear_ratio is the rear axle comprehensive weight; The axle load reflects the vertical pressure currently borne by the front and rear axles, and is a key factor in determining the tire grip. The greater the load, the stronger the potential friction between the tire and the ground, and the greater the driving torque that can be borne. In the formula, the axle load is taken as a basic parameter to ensure that the power distribution matches the actual load-bearing capacity of the tire and to avoid slipping caused by driving force exceeding grip; Motor efficiency is directly related to the energy utilization rate of power output. The higher the efficiency of the motor, the lower the energy consumption under the same power output. In the formula, by multiplying the efficiency parameter, more power is preferentially allocated to the axle with high-efficiency motor, thereby improving the energy utilization efficiency of the entire power system and reducing energy consumption. The yaw rate correction factor reflects the current stability state of the vehicle, and its value is dynamically adjusted with the yaw angular velocity. When the vehicle has a yaw tendency (yaw_factor < 1), the weight proportion of the front and rear axles is simultaneously weakened, and the power distribution is indirectly adjusted to suppress yaw, ensuring that vehicle stability takes priority over efficiency or load requirements. The calculated front_ratio and rear_ratio directly reflect the weight distribution priority of the front and rear axles under the current working condition, making the torque distribution more optimal in terms of load-bearing capacity, efficiency, stability, and adaptability, and achieving an optimal torque distribution strategy that balances load safety, energy efficiency, and driving stability. In summary, the formula achieves a comprehensive consideration of vehicle power demand, rate target, and stability requirements through the weighted integration of multiple parameters, providing a quantitative basis for dynamic and accurate power distribution. S26: Normalized distribution: Calculate the total weight total_weight, front axle weight factor front_weight, and rear axle weight factor rear_weight by the following formula: total_weight = front_ratio + rear_ratio front_weight = front_ratio / total_weight rear_weight = rear_ratio / total_weight Normalized distribution is the final link in the torque distribution decision-making process. The formula standardizes the comprehensive weights of the front and rear axles, converting abstract weight values into directly applicable torque distribution ratios. By converting the front and rear axle weights into proportions, the influence of absolute values is eliminated, and only the relative proportions of the two are retained, directly reflecting which axle the power should be inclined to. Unified quantitative standard: Regardless of the absolute value of the comprehensive weight of the front and rear axles, the normalized value is converted to a ratio between 0 and 1, ensuring that the power distribution coefficient is calculated under a unified dimension, avoiding decision-making bias caused by the difference in the magnitude of the weight value. The obtained front_weight and rear_weight can be directly used as the power distribution ratio of the front and rear axles, so as to convert the abstract weight into a specific control scheme, ensure that the torque is distributed and output in an optimal ratio, and balance the comprehensive requirements of carrying capacity, efficiency and stability. S27: obtaining a result: the final output power distribution result is [front_weight / 2, front_weight / 2, rear_weight / 2, rear_weight / 2], which provides a reference for torque control of the front and rear axle motors of the vehicle; S3: inputting the output scheme into a model built based on the Modelica language to obtain a simulation result.

[0010] As a further technical solution of the application, the vehicle state parameters specifically include: mg is the total weight of the automobile (mass x gravity acceleration, unit: N), L is the front and rear wheelbase (m), h is the height of the center of mass (m), Lf is the distance from the center of mass to the front axle (m), alpha is the slope angle (radian), and r is the tire radius (m).

[0011] As a further technical solution of the application, the power system parameters specifically include: front_motor_max is the peak torque of the front motor (Nm), rear_motor_max is the peak torque of the rear motor (Nm), and efficiency_map is the efficiency MAP graph, which is a two-dimensional matrix reflecting the efficiency of the motor under different vehicle speeds and torques.

[0012] As a further technical solution of the application, the real-time driving state parameters of the vehicle specifically include: velocity is the current vehicle speed (m / s), yaw_rate is the yaw rate (rad / s), and steer_angle is the steering wheel angle (rad).

[0013] As a further technical solution of the application, the parameters describing the contact characteristics of the road surface and the tire specifically include: mu_front is the front wheel friction coefficient; and mu_rear is the rear wheel friction coefficient.

[0014] As a further technical solution of the application, in S24, when the vehicle has no yaw tendency, yaw_factor=1, at this time the power distribution is performed according to the conventional strategy; when the yaw rate increases, i.e. |ω|>0, yaw_factor decreases with the increase of |ω|; this correction factor will directly act on the subsequent power distribution logic, and by reducing or adjusting the power output ratio of a specific axle, the yaw tendency is suppressed, so as to quickly stabilize the vehicle body posture and improve the driving safety of the vehicle under complex working conditions.

[0015] As a further technical solution of the present application, in S26, when the steering wheel angle steer_angle > 0.1, the front weight and rear weight are corrected by starting the steering torque vectoring distribution: the front axle weight factor front_weight * 0.8, and the rear axle weight factor rear_weight * 1.2, to optimize the steering performance and avoid understeering; The setting of this steering torque vectoring distribution strategy fully considers the dynamic characteristics and handling requirements in the vehicle steering process; Taking the steering wheel angle steer_angle > 0.1 as the starting threshold, the essence is to intervene in the medium and large steering conditions; When the steering angle is small or straight driving, there is no need to adjust the torque distribution additionally; When the steering angle exceeds the threshold, it means that the driver needs more active steering response, at which time the torque distribution correction is started, which can solve the handling problems that may occur in this scenario; Front axle weight reduction (front_weight * 0.8): reducing the front axle torque ratio can avoid the drag effect of the front wheels due to excessive torque; If the front axle weight is too high, the front wheels are easy to break through the ground adhesion limit during steering, causing steering delay and aggravating understeering; Reducing the front axle weight can reduce the burden on the front wheels and make the steering command more efficiently converted into body attitude change; Rear axle weight increase (rear_weight * 1.2): increasing the rear axle torque distribution is the core of optimization; After increasing the rear axle torque ratio, the lateral force moment can be generated through the difference between the braking force or driving force of the single-sided wheels, actively helping the vehicle body to rotate around the longitudinal axis, improving the flexibility of steering; This adjustment is equivalent to applying appropriate steering assistance to the tail of the vehicle, offsetting the understeering trend caused by inertia or center of gravity distribution; Through the above correction, the system realizes the dynamic rebalancing of front and rear axle torque distribution, avoiding the steering delay caused by excessive front axle torque, and enhancing the body steering response by increasing the rear axle torque; Ultimately, the vehicle can more accurately follow the driver's intention during medium and large steering, reducing the understeering phenomenon that the vehicle head deviates to the outside of the curve during steering and requires a larger steering angle to complete the steering, and improving the handling safety.

[0016] As a further technical solution of the present application, in S3, the model built based on the Modelica language adopts a modular modeling concept to decouple the complex vehicle dynamics system into several core functional subsystem modules, including the following modules: Speed following module: responsible for setting or tracking the target vehicle speed; Power source module: used to simulate the driving unit; Transmission system module: used to realize power transmission and gear shifting; Vehicle body model module: responsible for representing vehicle mass, inertia and attitude; Braking system module: for simulating brake force generation and distribution; Road model module: for providing road surface environment and geometric information for vehicle driving.

[0017] As a further technical solution of the application, each module in the model built based on the Modelica language is based on physical characteristics and dynamic behavior, and uses the Modelica language for non-causal modeling, and is abstracted into corresponding mathematical equations (such as high-order differential equations or algebraic equations).

[0018] As a further technical solution of the application, the construction of the model built based on the Modelica language realizes automatic and bidirectional transmission and system-level coupling of physical quantities (such as torque, speed, force, displacement, road adhesion coefficient, etc.) between modules (such as power source output and transmission system input, braking system and wheels, vehicle body and road model, etc.) through the powerful physical connectors (Physical Connectors) of Modelica; and finally, by connecting predefined and parameterized model modules, a complete and high-fidelity vehicle dynamics system simulation model can be efficiently constructed.

[0019] The application has the following beneficial effects: 1. In the climbing working condition, the front and rear axle load calculation of the electric four-wheel drive vehicle considers the influence of vehicle slope and mass center position on axle load, and the adjustment of front and rear axle torque distribution can significantly improve the efficiency compared with the traditional fixed proportional distribution or average distribution, and the principle is to optimize the matching of power output and road adhesion force and vehicle gravity center shift, and reduce energy waste.

[0020] 2. Considering that the front wheels need to bear steering and driving at the same time, and the adhesion force is easy to saturate, the average torque distribution is adopted, and excessive driving torque of the front wheels will occupy the remaining lateral force required for steering, causing insufficient steering, therefore, when the steering wheel angle δ is greater than 0.1, the steering torque vectoring distribution is started to be corrected to optimize the steering performance and avoid insufficient steering.

[0021] 3. The final distribution scheme is input into the modelica model for simulation experiment, different torque distribution ratios can be directly input through the model, so as to simulate the power response of the vehicle under the distribution strategy; at the same time, the transmission system module also interacts with other parts in the model, converts the adjusted torque distribution scheme into specific power output parameters, and finally presents the influence of different distribution strategies on the climbing performance through the whole vehicle simulation result. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 A julia torque distribution algorithm flowchart of an electric four-wheel drive torque distribution method based on a climbing working condition is provided. Figure 2 A flow chart of an electric four-wheel drive torque distribution method based on climbing working conditions is proposed for the present application. Figure 3 A Modelica specific model schematic diagram. DETAILED DESCRIPTION

[0023] To make the technical means, creative features, purposes and effects of the present application easy to understand, the present application will be further described below in conjunction with specific embodiments.

[0024] Please refer to the accompanying Figure 1 -Appendix Figure 3 An electric four-wheel drive torque distribution method based on climbing working conditions, comprising: S1: Parameter definition: define vehicle state parameters, describe vehicle basic structure and driving environment; define power system parameters for describing vehicle power system characteristics; define vehicle dynamic state to record vehicle real-time driving state parameters; define road conditions including parameters describing road surface and tire contact characteristics; The vehicle state parameters specifically include: mg is the total weight of the car (mass x gravity acceleration, unit: N), L is the front and rear wheelbase (m), h is the height of the center of mass (m), Lf is the distance from the center of mass to the front axle (m), alpha is the slope angle (radian), r is the tire radius (m); The power system parameters specifically include: front_motor_max is the peak torque of the front motor (Nm), rear_motor_max is the peak torque of the rear motor (Nm), efficiency_map is the efficiency MAP, which is a two-dimensional matrix reflecting the efficiency of the motor at different speeds and torques; The vehicle real-time driving state parameters specifically include: velocity is the current speed (m / s), yaw_rate is the yaw rate (rad / s), steer_angle is the steering wheel angle (rad);

[0025] The parameters describing the road surface and tire contact characteristics specifically include: mu_front is the front wheel friction coefficient; mu_rear is the rear wheel friction coefficient.

[0026] S2: julia torque distribution calculation: according to the parameters defined in step S1, the torque distribution calculation is carried out by using the formula; S21: front and rear axle load calculation: according to the vehicle state parameters, considering the influence of vehicle slope (slope angle alpha) and center of mass position (center of mass height h) on axle load, the following formula is used to calculate: Fzr = mg·(Lf·cosα+ h·sinα) / L Fzf = mg·[(L-Lf)·cosα- h·sinα] / L Wherein: Fzr is the rear axle load, Fzf is the front axle load; The slope angle a significantly changes the component of the gravity direction relative to the vehicle coordinate system (along the slope surface), and cos a represents the component of the gravity along the direction perpendicular to the slope surface (i.e. the Z-axis direction of the vehicle); the greater the slope, the smaller cos a, which means that the total normal force required to support the vehicle decreases; sin a represents the component of the gravity along the direction parallel to the slope surface, which itself does not directly contribute to the vertical axle load, but it will affect the load distribution of the front and rear axles by changing the force arm; this factor is the key to the formula to accurately reflect the axle load distribution of the vehicle under different working conditions such as uphill, downhill or horizontal road surface, etc. In the formula, the effects of the center of mass position are reflected by "Lf" (the horizontal distance from the center of mass to the front axle), "L" (the wheelbase) and "h" (the center of mass height); the closer the center of mass is to the front axle, the greater the front wheel load on the flat ground; and the center of mass height (h) will amplify the effect of the slope on the axle load, the higher the center of mass, the more obvious the front and rear axle load fluctuation caused by the slope change; S22: Calculation of the maximum available driving torque of the front and rear axles: combined with the motor peak torque in the power system parameters, the axle load calculated in step S21, and the friction coefficient in the road condition and the tire radius in the vehicle state parameter, the maximum available driving torque of the front and rear axles is calculated by the following formula: Tf_max = min(front_motor_max, Fzf·μ_front·r) Tr_max = min(rear_motor_max, Fzr·μ_rear·r) Wherein: Tf_max is the maximum available driving torque of the front axle, and Tr_max is the maximum available driving torque of the rear axle; This group of formulas combines the power system parameters, vehicle state parameters and road condition parameters, and uses the minimum function to realize the double constraint calculation of the maximum available driving torque (Tf_max, Tr_max) of the front and rear axles; it not only considers the output capability of the power source, but also considers the core safety boundary of the tire adhesion physical limit (Fz·μ·r), and the calculation result directly acts on the vehicle active safety system (to prevent slipping), power performance optimization and first torque distribution; the formula ensures that the vehicle power output is efficient, safe and controllable, and effectively converts the power source capability into actual vehicle kinetic energy; S23: Efficiency calculation: Efficiency calculation is a key link in the power system control logic, the core of which is to combine the real-time dynamics of the vehicle with the characteristics of the power system to accurately obtain the working efficiency of the front and rear motors, and to provide data support for subsequent optimization of power distribution; according to the current vehicle speed in the vehicle dynamic state, and the maximum available driving torque of the front and rear axles calculated in step S22 and the efficiency MAP diagram in the power system parameters, the front motor efficiency eff front and the rear motor efficiency eff rear are obtained through the index matrix method, which provides the basis for subsequent power distribution weight calculation; The final result of this calculation is to provide a key basis for subsequent power distribution weight calculation. By determining the efficiency level of the front and rear motors under the current working condition, it can further determine how to distribute the torque, so as to maximize the efficiency of the overall power system and reduce energy consumption while meeting the power demand of the vehicle; S24: Dynamic stability correction: According to the yaw rate yaw rate in the real-time driving state of the vehicle, the following formula is used for correction: yaw_factor = 1 - 0.1·|ω|, wherein: yaw_factor is a yaw rate correction factor (used to adjust power distribution when the vehicle has a yaw trend to enhance driving stability), and |ω| is the absolute value of the yaw rate yaw_rate; The core of dynamic stability correction is to adjust the power distribution to enhance driving stability by quantifying the yaw trend of the vehicle. The formula accurately considers the size of the vehicle yaw rate and realizes dynamic intervention through the correction factor; The formula takes into account the influence of the vehicle yaw rate, which is a key parameter for measuring the rotation trend of the vehicle around the vertical axis. The absolute value |ω| directly reflects the degree of deviation of the vehicle from the stable driving state. The larger |ω| is, the higher the risk of vehicle side slip, spin or excessive or insufficient steering. By introducing |ω| in the formula, the current degree of vehicle body rotation is accurately captured; When the vehicle has no yaw trend, yaw_factor = 1, and the power distribution is executed according to the normal strategy. When the yaw rate increases, i.e. |ω| > 0, yaw_factor decreases with the increase of |ω|. This correction factor will directly affect the subsequent power distribution logic, and by reducing or adjusting the power output ratio of a specific axle, it will suppress the yaw trend, thereby quickly stabilizing the vehicle body posture and improving the driving safety of the vehicle under complex working conditions.

[0027] S25: Front and rear axle comprehensive weight calculation: Comprehensive weight calculation is the core link of torque distribution decision, and its formula integrates three key parameters of axle load, motor efficiency and yaw rate correction factor to quantify the power distribution priority of the front and rear axles, and provides the basis for the final power output ratio. It is calculated by the following formula: front_ratio = Fzf·eff_front·yaw_factor rear_ratio = Fzr·eff_rear·yaw_factor Wherein: front_ration is the front axle comprehensive weight, rear_ratio is the rear axle comprehensive weight; The axle load reflects the vertical pressure currently borne by the front and rear axles, and is a key factor in determining the tire grip. The greater the load, the stronger the potential friction between the tire and the ground, and the greater the driving torque that can be borne. In the formula, the axle load is taken as a basic parameter to ensure that the power distribution matches the actual load-bearing capacity of the tire and to avoid slipping due to driving force exceeding grip; The motor efficiency is directly related to the energy utilization rate of power output. The higher the efficiency of the motor, the lower the energy consumption under the same power output. In the formula, by multiplying the efficiency parameter, more power is preferentially distributed to the axle with high-efficiency motor, thereby improving the energy utilization efficiency of the entire power system and reducing energy consumption; The yaw rate correction factor reflects the current stability state of the vehicle, and its value is dynamically adjusted with the yaw angular velocity. After being included in the formula, when the vehicle appears a yaw trend (yaw_factor < 1), the weight proportion of the front and rear axles is simultaneously weakened, and the power distribution is indirectly adjusted to suppress yaw, ensuring that the vehicle stability is prioritized over efficiency or load demand; The calculated front_ratio and rear_ratio directly reflect the weight distribution priority of the front and rear axles under the current working condition, making the comprehensive conditions of torque distribution in load-bearing capacity, efficiency, stability adaptability, etc. more optimal, and realizing the optimal torque distribution strategy that takes into account load safety, energy efficiency, and driving stability; In summary, the formula realizes the comprehensive consideration of vehicle power demand, rate target, and stability requirement through the weighted integration of multi-dimensional parameters, and provides a quantitative basis for dynamic and accurate power distribution; S26: Normalized distribution: Calculate the total weight total_weight, front axle weight factor front_weight, and rear axle weight factor rear_weight by the following formula: total_weight = front_ratio + rear_ratiofront_weight = front_ratio / total_weight rear_weight = rear_ratio / total_weight; The normalization allocation is the final link of the torque allocation decision, and the formula is standardized by the front and rear axle comprehensive weight, which converts the abstract weight value into a directly applicable torque allocation ratio; The front and rear axle weight is converted into the proportion form, which eliminates the influence of the absolute value size, only retains the relative proportion of the two, and directly reflects which axis the power should be inclined to; Unified quantization standard: no matter what the absolute value of the front and rear axle comprehensive weight is, it is converted to a ratio between 0 and 1 after normalization, ensuring that the power distribution coefficient is calculated under a unified dimension, avoiding decision bias caused by the magnitude difference of the weight value; The front_weight and rear_weight obtained can be directly used as the front and rear axle power distribution ratio, which converts the abstract weight into a specific control scheme, ensures that the torque is distributed and output according to the optimal ratio, and considers the comprehensive needs of carrying capacity, efficiency and stability; When the steering angle steer_angle>0.1, the steering torque vector distribution is modified to front_weight*0.8 and rear_weight*1.2 to optimize the steering performance and avoid understeering; This steering torque vector distribution strategy fully considers the dynamic characteristics and control requirements in the vehicle steering process; Taking the steering angle steer_angle>0.1 as the starting threshold, the essence is to intervene in the medium and large steering conditions; When the steering angle is small or straight driving, there is no need to adjust the torque distribution additionally; When the steering angle exceeds the threshold, it means that the driver needs more active steering response, so the torque distribution modification is started, which can solve the control problems that may occur in this scene; Front axle weight reduction (front_weight*0.8): reducing the front axle torque ratio can avoid the drag effect of the front wheels due to excessive torque; If the front axle weight is too high, the front wheels are easy to break through the ground adhesion limit during steering, causing steering lag and aggravating understeering; Reducing the front axle weight can reduce the burden on the front wheels and make the steering command more efficiently converted into body posture change; Rear axle weight increase (rear_weight*1.2): increasing the rear axle torque distribution is the core of optimization; After increasing the rear axle torque ratio, the lateral force moment can be generated through the difference between the driving force and the braking force of the single wheel, which actively helps the vehicle body rotate around the longitudinal axis and improves the steering flexibility; This adjustment is equivalent to applying appropriate steering assistance to the tail of the vehicle, which offsets the understeering trend caused by inertia or center of gravity distribution; Through the above modification, the system realizes dynamic rebalancing of front and rear axle torque distribution, avoids steering lag caused by excessive front axle torque, and enhances vehicle body steering response by increasing rear axle torque; ultimately, the vehicle can more accurately follow the driver's intention when making a large steering, reducing the steering deficiency phenomenon of "steering to the outside of the curve, requiring a larger steering angle to complete the steering", and improving the safety of the steering.

[0028] S27: Get the result: the final output power distribution result is [front_weight / 2, front_weight / 2, rear_weight / 2, rear_weight / 2], which provides a reference for torque control of the front and rear axle motors of the vehicle; S3: input the output scheme into the model built based on the Modelica language to obtain the simulation result; The model built based on the Modelica language adopts a modular modeling concept, decouples the complex vehicle dynamics system into several core functional subsystem modules, including the following modules: speed following module: responsible for setting or tracking the target vehicle speed, is an intelligent speed controller, which converts the target vehicle speed into physical control signals of the drive / brake system through a configurable PID algorithm and driver behavior parameters; its design takes into account precision (PID adjustment), authenticity (driver delay simulation) and flexibility (steering coordination expansion), providing core control logic for automatic driving test and vehicle dynamic performance analysis; Power source module: used for simulating the driving unit, which is the core actuator of the vehicle driving chain, converts the control command into physical driving torque in a linear mapping relationship, and can control the total torque output; Transmission system module: used for realizing power transmission and gear shifting, which is a four-wheel drive transmission that can control the distribution ratio of front and rear axle torque and input the final torque distribution scheme; Vehicle body model module: responsible for representing vehicle mass, inertia and attitude, which is the physical core in the simulation model, defines the vehicle mass, center of mass position, determines the spatial position of the vehicle center of gravity (affects the stability of pitch / roll), moment of inertia, initial position and initial speed in the initial conditions of the motion state, and integrates the tire layout, tire identification and rotation initial state in the tire system; Brake system module: used for simulating brake force generation and distribution, which is the core actuator of the vehicle safety system, as a conversion hub: converts the control signal into hydraulic pressure and finally outputs the brake torque, ensures stable braking dynamic simulation through pressure distribution curve and ABS / ESC function, affects the vehicle dynamics through brake force output, and realizes closed-loop control through sensor feedback; Road model module: used to provide the road surface environment and geometric information of the vehicle driving, control the road length and road slope, provide the road friction coefficient for simulation, construct the road geometry through mathematical description, and provide the simulation visualization of the road model.

[0029] Through the model, different torque distribution ratios (such as 60% front axle + 40% rear axle, 45% front axle + 55% rear axle, etc.) can be directly input to simulate the power response of the vehicle under the distribution strategy. At the same time, the transmission system module also interacts with other parts of the model (such as the power source module, vehicle dynamics module, road module, etc.) to convert the adjusted torque distribution scheme into specific power output parameters, and finally intuitively present the influence of different distribution strategies on the climbing performance through the whole vehicle simulation results, providing a reliable basis for the optimization of the scheme. The modules in the model built based on the Modelica language are based on physical characteristics and dynamic behavior, and use the Modelica language for non-causal modeling, abstracted as corresponding mathematical equations (such as high-order differential equations or algebraic equations), which are: Speed following module: uses PID control to adjust the target vehicle speed, the formula is: , Where: is the speed error, is the control signal, (proportional gain): directly proportional to the error between the current speed and the target speed, quickly adjusts the speed to reduce the error, but may cause oscillation; (integral gain): accumulates past errors, eliminates steady-state errors, and avoids long-term deviation of the vehicle speed from the target value, but may cause overshoot; (differential gain): related to the error change rate, suppresses rapidly changing errors, reduces the oscillation amplitude in the vehicle speed adjustment process, and improves system stability.

[0030] Power source module: converts the control signal into physical driving torque, the formula is and distributes the total torque to the transmission system according to the distribution ratio, the formula is: and , Where: is the gain coefficient of the motor; is the total output torque of the motor; is the control signal output by the speed following module, used to adjust the output torque of the power source module, usually a dimensionless value, ranging from 0 to 1, indicating the strength of power output; and are the output torques distributed to the front and rear axles, respectively.

[0031] Transmission module: to realize the power distribution between front and rear axles, considering the transmission efficiency, the formula is where: is the transmission efficiency, usually a coefficient slightly less than 1.

[0032] Vehicle body module: related to vehicle mass, inertia, attitude, etc., the vehicle kinematics formula is: where: is the total vehicle mass; is the vehicle acceleration; is the tire-ground friction coefficient; is the air resistance; is the rolling resistance.

[0033] Braking system module: braking torque affects the angular acceleration of the tire, the formula is: where: is the braking torque; is the coefficient of the brake; is the brake pressure; is the moment of inertia of the wheel.

[0034] Road model module: provides the geometric information and friction coefficient of the road surface, such as slope angle , front wheel friction coefficient μ_front, rear wheel friction coefficient μ_rear. Based on the Modelica language, the model is built, through the powerful physical connectors (Physical Connectors) of Modelica, the physical quantities (such as torque, speed, force, displacement, road adhesion coefficient, etc.) between modules (such as power source output and transmission system input, braking system and wheel, vehicle body and road model, etc.) can be automatically and bidirectionally transmitted and system-level coupled; finally, by connecting the predefined and parameterized model modules, a complete and high-fidelity vehicle dynamics system simulation model can be efficiently built. Therefore, this model library fully utilizes the non-causal modeling characteristics of Modelica, effectively combining functional modeling based on physical components (such as engine, gearbox, vehicle body) and abstract modeling based on dynamic characteristics (such as torque transmission, vehicle kinematics, tire-road interaction). This scheme significantly simplifies the modeling process and improves the simulation efficiency while ensuring the accuracy of the model simulation; at the same time, all parameters of each module are clearly defined and can be flexibly configured and called, greatly facilitating the simulation testing, parameterized research and debugging analysis of the model.

[0035] ​​​​​From the above description, it can be seen that the above-mentioned embodiments of the present application achieve the following technical effects: Precise climbing performance improvement: By comprehensively considering the vehicle state parameters such as slope and center of mass position, accurately calculating the front and rear axle loads, and reasonably distributing the torque, the vehicle can more efficiently utilize the driving force when climbing, avoid power waste, and significantly enhance the climbing ability.

[0036] Optimized steering control: When the vehicle is steering, the torque vectoring distribution correction is started according to the steering wheel angle, the front and rear axle torque distribution is adjusted, the understeering is effectively prevented, and the vehicle's control flexibility and driving stability are improved.

[0037] Significant energy consumption reduction: With the help of the efficiency MAP, the high-efficiency working interval of the motor is dynamically tracked, the front and rear motor torque output is intelligently adjusted, the inefficient running time is reduced, and thus the energy consumption is greatly reduced, and the vehicle's cruising range is extended.

[0038] Enhanced dynamic stability: According to the vehicle yaw angular velocity, the torque distribution is adjusted in real time, when the vehicle yaw trend is detected, the power output of a specific axle is reduced to timely suppress the yaw, and the safety and stability of the vehicle driving on complex road conditions are ensured.

[0039] Those skilled in the art should understand that the above discussion of any embodiment is only exemplary and is not intended to imply that the scope of the present application is limited to these examples; under the idea of the present application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes of different aspects of the present application as described above. In order to be brief, they are not provided in details.

[0040] The present application is intended to cover all such alternatives, modifications and variations as fall within the broad scope of the description. Therefore, any omission, modification, equivalent replacement, improvement, etc. made in the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for torque distribution in an electric four-wheel drive system based on hill-climbing conditions, characterized in that, include: S1: Parameter Definition: Define vehicle state parameters to describe the basic structure and driving environment of the vehicle; define power system parameters to describe the characteristics of the vehicle power system; define vehicle dynamic state to record the real-time driving state parameters of the vehicle; define road conditions, including parameters describing the contact characteristics between the road surface and the tires. S2: Julia torque distribution calculation: Based on the parameters defined in step S1, the torque distribution is calculated using the formula; S21: Front and rear axle load calculation: Based on vehicle condition parameters, considering the influence of vehicle slope and center of gravity position on axle load, the following formula is used for calculation: Fzr = mg·(Lf·cosα+ h·sinα) / L Fzf = mg·[(L-Lf)·cosα- h·sinα] / L Where: Fzr is the rear axle load, and Fzf is the front axle load; S22: Calculation of maximum available drive torque for front and rear axles: Combining the peak motor torque in the powertrain parameters, the axle load calculated in step S21, the friction coefficient in road conditions, and the tire radius in vehicle condition parameters, the following formula is used for calculation: Tf_max = min(front_motor_max, Fzf·μ_front·r) Tr_max = min(rear_motor_max, Fzr·μ_rear·r) Where: Tf_max is the maximum available drive torque of the front axle, and Tr_max is the maximum available drive torque of the rear axle; S23: Efficiency Calculation: Based on the current vehicle speed in the vehicle's dynamic state, and the efficiency MAP diagram in the maximum available drive torque of the front and rear axles and power system parameters calculated in step S22, obtain the front motor efficiency eff_front and the rear motor efficiency eff_rear through the index matrix. S24: Dynamic stability correction: Based on the yaw rate (yaw_rate) in the vehicle's real-time driving state, the following formula is used for correction: yaw_factor = 1 - 0.1·|ω|, Where: yaw_factor is the yaw rate correction factor, and |ω| is the absolute value of the yaw angular velocity yaw_rate; S25: Front and Rear Axle Integrated Weight Calculation: By integrating three key parameters—axle load, motor efficiency, and yaw rate correction factor—the power distribution priority between the front and rear axles is quantified and calculated using the following formula: front_ratio = Fzf·eff_front·yaw_factor rear_ratio = Fzr·eff_rear·yaw_factor Where: front_ration is the front axis composite weight, and rear_ratio is the rear axis composite weight; S26: Normalized Allocation: Calculate the total weight (total_weight), front axis weight factor (front_weight), and rear axis weight factor (rear_weight) using the following formulas: total_weight = front_ratio + rear_ratiofront_weight = front_ratio / total_weight rear_weight = rear_ratio / total_weight; S27: Result obtained: The final output power distribution result is [front_weight / 2, front_weight / 2, rear_weight / 2, rear_weight / 2]; S3: Input the output scheme into the model built based on the Modelica language to obtain the simulation results.

2. The electric four-wheel drive torque distribution method based on climbing conditions according to claim 1, characterized in that, The vehicle status parameters specifically include: mg as the total weight of the vehicle, L as the front and rear wheelbase, h as the center of gravity height, Lf as the distance from the center of gravity to the front axle, α as the slope angle, and r as the tire radius.

3. The electric four-wheel drive torque distribution method based on hill-climbing conditions according to claim 1, characterized in that, The power system parameters specifically include: front_motor_max is the peak torque of the front motor, rear_motor_max is the peak torque of the rear motor, and efficiency_map is an efficiency map, which is a two-dimensional matrix reflecting the efficiency of the motor at different vehicle speeds and torques.

4. The electric four-wheel drive torque distribution method based on climbing conditions according to claim 1, characterized in that, The specific parameters of the vehicle's real-time driving status include: velocity (current vehicle speed), yaw_rate (yaw rate), and steer_angle (steering wheel angle).

5. The electric four-wheel drive torque distribution method based on climbing conditions according to claim 1, characterized in that, The parameters describing the contact characteristics between the road surface and the tire specifically include: μ_front, which is the front wheel friction coefficient; and μ_rear, which is the rear wheel friction coefficient.

6. The electric four-wheel drive torque distribution method based on climbing conditions according to claim 1, characterized in that, In S24, when the vehicle has no yaw tendency, yaw_factor=1, and the power distribution is executed according to the conventional strategy; when the yaw angular velocity increases, that is, when |ω|>0, yaw_factor decreases as |ω| increases.

7. The electric four-wheel drive torque distribution method based on climbing conditions according to claim 4, characterized in that, In S26, when the steering wheel angle steer_angle > 0.1, the steering torque vector distribution is activated to correct front_weight and rear_weight: front axle weight factor front_weight * 0.8, rear axle weight factor rear_weight * 1.

2.

8. The electric four-wheel drive torque distribution method based on climbing conditions according to claim 1, characterized in that, In S3, the model built based on the Modelica language includes the following modules: Speed ​​Follow Module: Responsible for setting or tracking the target vehicle speed; Power source module: used to simulate the drive unit; Transmission system module: used to realize power transmission and speed change; Vehicle body model module: Responsible for representing the vehicle's mass, inertia, and attitude; Braking system module: used to simulate the generation and distribution of braking force; Road Model Module: Provides road surface environment and geometric information for vehicle travel.

9. The electric four-wheel drive torque distribution method based on climbing conditions according to claim 8, characterized in that, The modules in the model built on the Modelica language are based on physical characteristics and dynamic behavior, and are non-causal modeled using the Modelica language, which is then abstracted into corresponding mathematical equations.

10. The electric four-wheel drive torque distribution method based on hill-climbing conditions according to claim 9, characterized in that, The model built on the Modelica language is constructed through Modelica's powerful physics connectors, enabling automatic, bidirectional transfer of physical quantities and system-level coupling between modules. Finally, by connecting predefined, parameterized model modules, a vehicle dynamics system simulation model can be constructed.

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