A method for distributing torque in an electric four-wheel drive vehicle based on uphill working conditions

Abstract

The application relates to the field of power control, and particularly discloses a torque distribution method for an electric four-wheel drive vehicle 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; performing torque calculation by using Julia, considering axle load, a friction coefficient, motor efficiency and a yaw angular velocity correction, obtaining comprehensive weights of front and rear axles and normalizing and distributing the torque; and verifying the effectiveness of the distribution scheme by building a model simulation through Modelica. The application can improve the climbing performance of the vehicle, improve the control flexibility and driving stability of the vehicle, reduce energy consumption and enhance dynamic stability, and is suitable for power control of the electric four-wheel drive vehicle under the climbing working condition.

Description

Technical Field

[0001] This invention relates to the field of power control technology, and in particular to an electric four-wheel drive torque distribution method based on hill climbing conditions. Background Technology

[0002] In the field of power control for electric four-wheel drive vehicles, a reasonable torque distribution strategy has a significant impact on vehicle performance, energy consumption, and driving stability. It directly determines the vehicle's core performance, energy efficiency, and driving stability and safety. Traditional power distribution methods often only consider the motor torque limit or a single vehicle driving parameter, such as simply distributing torque between the front and rear axles in a fixed ratio, or unilaterally adjusting the total torque output based solely on the accelerator pedal opening, while ignoring changes in the vehicle's real-time status and road conditions. Although this mode has simple control logic and low cost, it is difficult to achieve optimal power output under complex operating conditions.

[0003] In different gradient scenarios: When a vehicle is driving on a steep slope, whether going uphill or downhill, the vehicle's center of gravity shifts dramatically. Going uphill, the rear axle load increases, requiring more rear axle torque to prevent slippage and provide driving force; going downhill, the front axle motor may be needed for stronger energy recovery and to maintain stability. A fixed weight distribution cannot adapt to these dynamic load changes, potentially leading to insufficient driving force (going uphill) or unbalanced braking force (going downhill). In these situations, it's necessary to dynamically increase the torque percentage of the rear axle (or front axle) based on information from the gradient sensor to improve climbing ability or enhance braking stability. On flat roads, a more balanced weight distribution is needed to reduce energy consumption.

[0004] Traditional strategies cannot detect or quickly respond to microscopic friction differences when faced with varying road surface friction coefficients. On wet or icy surfaces, the coefficient of friction is low, and improper torque distribution between the front and rear axles can easily lead to slippage on one axle. For example, excessive torque on the front axle may cause front wheel slippage, resulting in loss of steering control; excessive torque on the rear axle may cause fishtailing. In such cases, it is necessary to combine wheel slip rate detected by wheel speed sensors to adjust the torque distribution ratio in real time, allocating more torque to the wheels with higher coefficients of friction to prevent slippage and ensure vehicle driving efficiency and stability.

[0005] When a vehicle is cornering, significant lateral acceleration and load transfer occur during high-speed cornering or emergency lane changes (increased load on the outer wheels and decreased load on the inner wheels). If torque distribution remains the same as for straight-line driving, especially if excessive torque is distributed to the inner wheels with low traction or to the axle causing understeer (usually the front axle), insufficient front wheel grip can cause the vehicle's turning radius to exceed expectations, easily leading to understeer. Alternatively, insufficient rear wheel grip can cause the rear of the vehicle to slide outwards, resulting in oversteer. This also increases energy consumption; ineffective skidding consumes a significant amount of electrical energy, and frequent intervention of the Electronic Stability Control (ESC) system during braking further increases energy consumption.

[0006] Traditional strategies cannot dynamically and coordinately adjust the torque of the inner and outer wheels and the front and rear axles during steering based on parameters such as yaw rate, steering wheel angle, and lateral acceleration to actively shape the desired vehicle dynamics. Furthermore, energy consumption is closely related to torque distribution. In low-load scenarios such as constant-speed driving, improper torque distribution may cause one motor to operate in an inefficient range (e.g., low speed, high torque), resulting in energy waste. Dynamic adjustment, allowing both front and rear motors to operate in their efficient range, can significantly improve the vehicle's driving range.

[0007] Therefore, compared with traditional strategies, dynamic torque distribution strategies based on multiple parameters (such as vehicle speed, acceleration, wheel speed, gradient, steering angle, road friction coefficient, etc.) can flexibly adjust the torque ratio between the front and rear axles according to real-time operating conditions. While ensuring vehicle power performance and driving stability, it can minimize energy consumption and is an important development direction for electric four-wheel drive vehicle power control technology. Summary of the Invention

[0008] The purpose of this invention is to solve the problems and shortcomings of torque distribution in existing technologies under different slopes, road surface friction, or vehicle steering conditions. The invention proposes an electric four-wheel drive torque distribution method based on climbing conditions, which realizes torque distribution considering different slopes, road surface friction, or vehicle steering conditions through Julia programming and Modelica model simulation.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] An electric four-wheel drive torque distribution method based on hill climbing conditions includes:

[0011] 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.

[0012] S2: Julia torque distribution calculation: Based on the parameters defined in step S1, the torque distribution is calculated using the formula;

[0013] S21: Front and rear axle load calculation: Based on vehicle condition parameters, considering the influence of vehicle slope (slope angle α) and center of gravity position (center of gravity height h) on axle load, the following formula is used for calculation:

[0014] Fzr = mg·(Lf·cosα+ h·sinα) / L

[0015] Fzf = mg·[(L-Lf)·cosα- h·sinα] / L

[0016] Where: Fzr is the rear axle load, and Fzf is the front axle load;

[0017] The slope angle α significantly alters the component of gravity's direction relative to the vehicle coordinate system (along the slope). cosα represents the component of gravity perpendicular to the slope (i.e., the vehicle's Z-axis direction). The steeper the slope, the smaller cosα becomes, meaning a decrease in the total normal force required to support the vehicle. sinα represents the component of gravity parallel to the slope. This component itself does not directly contribute to the vertical axle load, but it affects the load distribution between the front and rear axles by changing the lever arm. This factor is crucial for the formula to accurately reflect the axle load distribution of the vehicle under different working conditions such as uphill, downhill, or level roads.

[0018] The formula uses "Lf" (horizontal distance from the center of gravity to the front axle), "L" (wheelbase), and "h" (center of gravity height) to reflect the role of the center of gravity position. The closer the center of gravity is to the front axle, the greater the load on the front wheels on flat ground. The center of gravity height (h) amplifies the effect of the slope on the axle load. The higher the center of gravity, the more obvious the fluctuation of the front and rear axle load caused by the change in slope.

[0019] 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:

[0020] Tf_max = min(front_motor_max, Fzf·μ_front·r)

[0021] Tr_max = min(rear_motor_max, Fzr·μ_rear·r)

[0022] 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;

[0023] This set of formulas combines powertrain parameters, vehicle state parameters, and road condition parameters, and uses a minimum function to achieve dual-constraint calculation of the maximum available driving torque (Tf_max, Tr_max) for the front and rear axles. It not only considers the output capability of the power source, but also the core safety boundary of the tire adhesion physical limit (Fz·μ·r). Its calculation results directly affect the vehicle's active safety system (preventing slippage), power performance optimization, and torque distribution. This formula ensures that the vehicle's power output is efficient, safe, and controllable, effectively converting the power source capability into the kinetic energy for the actual vehicle's forward movement.

[0024] S23: Efficiency Calculation: Efficiency calculation is a key step in the powertrain control logic. Its core lies in combining the vehicle's real-time dynamics with the powertrain characteristics to accurately obtain the working efficiency of the front and rear motors, providing data support for subsequent power distribution optimization. Based on the current vehicle speed in the vehicle's dynamic state, the maximum available drive torque of the front and rear axles calculated in step S22, and the efficiency MAP in the powertrain parameters, the front motor efficiency eff_front and the rear motor efficiency eff_rear are obtained through an index matrix, providing a basis for subsequent power distribution weight calculation.

[0025] The final result of this calculation provides a key basis for subsequent power distribution weight calculation. By clarifying the efficiency levels of the front and rear motors under the current operating conditions, it is possible to further determine how to distribute torque, thereby maximizing the efficiency of the overall power system and reducing energy consumption while meeting the vehicle's power requirements.

[0026] S24: Dynamic stability correction: Based on the yaw rate in the real-time driving state of the vehicle, the following formula is used for correction: yaw_factor = 1 - 0.1·|ω|, where: yaw_factor is the yaw rate correction factor (used to adjust the power distribution when the vehicle shows a yaw tendency to enhance driving stability), and |ω| is the absolute value of the yaw rate yaw_rate;

[0027] The core of dynamic stability correction is to quantify the yaw trend of the vehicle and adjust the power distribution accordingly to enhance driving stability. Its formula design accurately considers the magnitude of the vehicle's yaw rate and achieves dynamic intervention through correction factors.

[0028] The formula takes into account the influence of the vehicle's yaw rate, which is a key parameter for measuring the vehicle's rotational tendency around the vertical axis. Its absolute value |ω| directly reflects the degree to which the vehicle deviates from a stable driving state. The larger |ω| is, the higher the risk of the vehicle sideslipping, fishtailing, or oversteering or understeering. By introducing |ω| into the formula, the degree of violent rotation of the vehicle body at present can be accurately captured.

[0029] S25: Front and Rear Axle Integrated Weight Calculation: The integrated weight calculation is the core step in torque distribution decision-making. Its formula integrates three key parameters—axle load, motor efficiency, and yaw rate correction factor—to quantify the power distribution priority between the front and rear axles, providing a basis for the final power output ratio. It is calculated using the following formula:

[0030] front_ratio = Fzf·eff_front·yaw_factor

[0031] rear_ratio = Fzr·eff_rear·yaw_factor

[0032] Where: front_ration is the front axis composite weight, and rear_ratio is the rear axis composite weight;

[0033] Axle load reflects the vertical pressure currently borne by the front and rear axles and is a key factor in determining tire grip. The greater the load, the stronger the friction potential between the tire and the ground, and the greater the driving torque it can withstand. The formula uses axle load as a basic parameter to ensure that the power distribution matches the actual load-bearing capacity of the tire, avoiding slippage caused by the driving force exceeding the grip.

[0034] 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 by the efficiency parameter, more power is preferentially allocated to the shaft where the high-efficiency motor is located, thereby improving the energy utilization efficiency of the entire power system and reducing energy consumption.

[0035] The yaw rate correction factor reflects the current stability state of the vehicle. Its value is dynamically adjusted as the yaw rate changes. When the vehicle shows a yaw tendency (yaw_factor < 1), the weight ratio of the front and rear axles can be reduced simultaneously, which indirectly adjusts the power distribution to suppress yaw and ensures that vehicle stability takes precedence over efficiency or load requirements.

[0036] The calculated front_ratio and rear_ratio intuitively reflect the weight allocation priority of the front and rear axles under the current working conditions, making the torque distribution more optimized in terms of load capacity, efficiency, stability adaptability, etc., and realizing the optimal torque distribution strategy that takes into account load safety, energy efficiency and driving stability.

[0037] In summary, this formula, through the weighted integration of multi-dimensional parameters, achieves a comprehensive consideration of vehicle power demand, efficiency targets, and stability requirements, providing a quantitative basis for dynamic and precise power distribution.

[0038] 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:

[0039] total_weight = front_ratio + rear_ratiofront_weight = front_ratio / total_weight

[0040] rear_weight = rear_ratio / total_weight;

[0041] Normalized distribution is the final step in torque distribution decision-making. Its formula standardizes the combined weights of the front and rear axles, transforming abstract weight values ​​into directly applicable torque distribution ratios. It converts the front and rear axle weights into percentages, eliminating the influence of absolute values ​​and retaining only their relative proportions, which intuitively reflects which axle the power should be tilted towards.

[0042] Unified quantification standard: Regardless of the absolute value of the combined weight of the front and rear axles, after normalization, they are all converted into a ratio between 0 and 1, ensuring that the power distribution coefficient is calculated under a unified dimension and avoiding decision-making bias due to differences in the magnitude of the weight values;

[0043] The obtained front_weight and rear_weight can be directly used as the power distribution ratio between the front and rear axles, transforming the abstract weights into a specific control scheme, ensuring that the torque is distributed and output in the optimal ratio, taking into account the comprehensive requirements of load-bearing capacity, efficiency and stability.

[0044] S27: Result obtained: The final output power distribution result is [front_weight / 2, front_weight / 2, rear_weight / 2, rear_weight / 2], which provides a reference for the torque control of the front and rear axle motors of the vehicle;

[0045] S3: Input the output scheme into the model built based on the Modelica language to obtain the simulation results.

[0046] As a further technical solution of the present invention, the vehicle state parameters specifically include: mg as the total weight of the vehicle (mass × gravitational acceleration, unit: N), L as the front and rear wheelbase (m), h as the height of the center of gravity (m), Lf as the distance from the center of gravity to the front axle (m), α as the slope angle (radians), and r as the tire radius (m).

[0047] As a further technical solution of the present invention, 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 an efficiency MAP, which is a two-dimensional matrix reflecting the efficiency of the motor under different vehicle speeds and torques.

[0048] As a further technical solution of the present invention, the real-time driving status parameters of the vehicle specifically include: velocity (current vehicle speed, m / s), yaw_rate (yaw rate, rad / s), and steer_angle (steering wheel angle, rad).

[0049] As a further technical solution of the present invention, 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.

[0050] As a further technical solution of the present invention, 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; this correction factor will directly affect the subsequent power distribution logic, suppressing the yaw tendency by reducing or adjusting the power output ratio of a specific axle, thereby quickly stabilizing the vehicle body posture and improving the driving safety of the vehicle under complex working conditions.

[0051] As a further technical solution of the present invention, 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, in order to optimize steering performance and avoid understeer;

[0052] This steering torque vectoring strategy takes into full account the dynamic characteristics and handling requirements of the vehicle during steering.

[0053] Using a steering wheel angle steer_angle > 0.1 as the activation threshold is essentially an intervention for medium and large steering conditions. No additional torque distribution adjustment is needed when driving at small angles or in a straight line. However, when the angle exceeds the threshold, it means that the driver needs a more proactive steering response. Activating torque distribution correction at this time can specifically solve the handling problems that may occur in this scenario.

[0054] Front axle weight reduction (front_weight*0.8): Reducing the proportion of front axle torque can prevent the front wheels from dragging due to excessive torque; if the front axle weight is too high, the front wheels are prone to exceeding the ground adhesion limit when turning, resulting in sluggish steering action and exacerbating understeer; reducing the front axle weight can reduce the burden on the front wheels and make steering commands more efficiently translated into changes in vehicle posture.

[0055] Rear axle weight increase (rear_weight*1.2): Increasing the rear axle torque distribution is the core of the optimization; after the rear axle torque ratio is increased, it can generate yaw moment through the difference in braking force or driving force of the wheels on one side, actively helping the vehicle body to rotate around the longitudinal axis and improving steering flexibility; this adjustment is equivalent to applying moderate steering assistance to the rear of the vehicle to counteract the understeer tendency caused by inertia or center of gravity distribution.

[0056] Through the above modifications, the system achieves dynamic rebalancing of torque distribution between the front and rear axles, avoiding steering lag caused by excessive front axle torque and enhancing vehicle steering response by increasing rear axle torque. Ultimately, this allows the vehicle to more accurately follow the driver's intentions during medium to large turns, reducing understeer phenomena such as "the front of the car deviates to the outside of the curve when turning and a larger turning angle is required to complete the turn," thus improving handling safety.

[0057] As a further technical solution of the present invention, in S3, the model built based on the Modelica language adopts a modular modeling concept, decoupling the complex vehicle dynamics system into several core functional subsystem modules, including the following modules:

[0058] Speed ​​Follow Module: Responsible for setting or tracking the target vehicle speed;

[0059] Power source module: used to simulate the drive unit;

[0060] Transmission system module: used to realize power transmission and speed change;

[0061] Vehicle body model module: Responsible for representing the vehicle's mass, inertia, and attitude;

[0062] Braking system module: used to simulate the generation and distribution of braking force;

[0063] Road Model Module: Provides road surface environment and geometric information for vehicle travel.

[0064] As a further technical solution of the present invention, the module in the model built based on the Modelica language is based on physical characteristics and dynamic behavior, and is non-causal modeled using the Modelica language, and abstracted into corresponding mathematical equations (such as higher-order differential equations or algebraic equations).

[0065] As a further technical solution of the present invention, the model built based on the Modelica language can achieve automatic, 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, body and road model, etc.) through Modelica's powerful physical connectors; finally, by connecting predefined, parameterized model modules, a complete and high-fidelity vehicle dynamics system simulation model can be efficiently constructed.

[0066] The beneficial effects of this invention are as follows:

[0067] 1. Under climbing conditions, the front and rear axle load calculation of electric four-wheel drive vehicles takes into account the influence of vehicle slope and center of gravity position on axle load. Adjusting the front and rear axle torque distribution can significantly improve efficiency compared with traditional fixed ratio distribution or average distribution. The principle is to optimize the matching of power output with road adhesion and vehicle center of gravity transfer, thereby reducing energy waste.

[0068] 2. Considering that the front wheels need to bear both steering and driving simultaneously and that the adhesion is easily saturated, an average torque distribution is adopted. Excessive driving torque on the front wheels will squeeze out the lateral force margin required for steering and cause understeer. Therefore, when the steering wheel angle δ > 0.1, the steering torque vector distribution is activated to correct the problem, so as to optimize the steering performance and avoid understeer.

[0069] 3. Input the final torque distribution scheme into the Modelica model for simulation experiments. Different torque distribution ratios can be directly input into the model to simulate the vehicle's power response under the distribution strategy. At the same time, the transmission system module will also interact with other parts of the model to convert the adjusted torque distribution scheme into specific power output parameters. Finally, the impact of different distribution strategies on climbing performance is presented intuitively through the whole vehicle simulation results. Attached Figure Description

[0070] Figure 1 This is a flowchart of the Julia torque distribution algorithm for an electric four-wheel drive torque distribution method based on hill climbing conditions proposed in this invention.

[0071] Figure 2 This is an overall flowchart of an electric four-wheel drive torque distribution method based on hill climbing conditions proposed in this invention;

[0072] Figure 3 This is a schematic diagram of a specific Modelica model. Detailed Implementation

[0073] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0074] Please see the appendix Figure 1 -Appendix Figure 3 An electric four-wheel drive torque distribution method based on hill climbing conditions includes:

[0075] 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.

[0076] The specific vehicle status parameters include: mg is the total weight of the vehicle (mass × gravitational acceleration, unit: N), L is the front and rear wheelbase (m), h is the height of the center of gravity (m), Lf is the distance from the center of gravity to the front axle (m), α is the slope angle (radians), and r is the tire radius (m).

[0077] The powertrain 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, which is a two-dimensional matrix reflecting the efficiency of the motor at different vehicle speeds and torques;

[0078] The specific parameters of the vehicle's real-time driving status include: velocity (current vehicle speed, m / s), yaw_rate (yaw rate, rad / s), and steer_angle (steering wheel angle, rad).

[0079] The parameters describing the contact characteristics between the road surface and the tire specifically include: μ_front, which is the coefficient of friction for the front tire; and μ_rear, which is the coefficient of friction for the rear tire.

[0080] S2: Julia torque distribution calculation: Based on the parameters defined in step S1, the torque distribution is calculated using the formula;

[0081] S21: Front and rear axle load calculation: Based on vehicle condition parameters, considering the influence of vehicle slope (slope angle α) and center of gravity position (center of gravity height h) on axle load, the following formula is used for calculation:

[0082] Fzr = mg·(Lf·cosα+ h·sinα) / L

[0083] Fzf = mg·[(L-Lf)·cosα- h·sinα] / L

[0084] Where: Fzr is the rear axle load, and Fzf is the front axle load;

[0085] The slope angle α significantly alters the component of gravity's direction relative to the vehicle coordinate system (along the slope). cosα represents the component of gravity perpendicular to the slope (i.e., the vehicle's Z-axis direction). The steeper the slope, the smaller cosα becomes, meaning a decrease in the total normal force required to support the vehicle. sinα represents the component of gravity parallel to the slope. This component itself does not directly contribute to the vertical axle load, but it affects the load distribution between the front and rear axles by changing the lever arm. This factor is crucial for the formula to accurately reflect the axle load distribution of the vehicle under different working conditions such as uphill, downhill, or level roads.

[0086] The formula uses "Lf" (horizontal distance from the center of gravity to the front axle), "L" (wheelbase), and "h" (center of gravity height) to reflect the role of the center of gravity position. The closer the center of gravity is to the front axle, the greater the load on the front wheels on flat ground. The center of gravity height (h) amplifies the effect of the slope on the axle load. The higher the center of gravity, the more obvious the fluctuation of the front and rear axle load caused by the change in slope.

[0087] 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:

[0088] Tf_max = min(front_motor_max, Fzf·μ_front·r)

[0089] Tr_max = min(rear_motor_max, Fzr·μ_rear·r)

[0090] 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;

[0091] This set of formulas combines powertrain parameters, vehicle state parameters, and road condition parameters, and uses a minimum function to achieve dual-constraint calculation of the maximum available driving torque (Tf_max, Tr_max) for the front and rear axles. It not only considers the output capability of the power source, but also the core safety boundary of the tire adhesion physical limit (Fz·μ·r). Its calculation results directly affect the vehicle's active safety system (preventing slippage), power performance optimization, and torque distribution. This formula ensures that the vehicle's power output is efficient, safe, and controllable, effectively converting the power source capability into the kinetic energy for the actual vehicle's forward movement.

[0092] S23: Efficiency Calculation: Efficiency calculation is a key step in the powertrain control logic. Its core lies in combining the vehicle's real-time dynamics with the powertrain characteristics to accurately obtain the working efficiency of the front and rear motors, providing data support for subsequent power distribution optimization. Based on the current vehicle speed in the vehicle's dynamic state, the maximum available drive torque of the front and rear axles calculated in step S22, and the efficiency MAP in the powertrain parameters, the front motor efficiency eff_front and the rear motor efficiency eff_rear are obtained through an index matrix, providing a basis for subsequent power distribution weight calculation.

[0093] The final result of this calculation provides a key basis for subsequent power distribution weight calculation. By clarifying the efficiency levels of the front and rear motors under the current operating conditions, it is possible to further determine how to distribute torque, thereby maximizing the efficiency of the overall power system and reducing energy consumption while meeting the vehicle's power requirements.

[0094] S24: Dynamic stability correction: Based on the yaw rate in the real-time driving state of the vehicle, the following formula is used for correction: yaw_factor = 1 - 0.1·|ω|, where: yaw_factor is the yaw rate correction factor (used to adjust the power distribution when the vehicle shows a yaw tendency to enhance driving stability), and |ω| is the absolute value of the yaw rate yaw_rate;

[0095] The core of dynamic stability correction is to quantify the yaw trend of the vehicle and adjust the power distribution accordingly to enhance driving stability. Its formula design accurately considers the magnitude of the vehicle's yaw rate and achieves dynamic intervention through correction factors.

[0096] The formula takes into account the influence of the vehicle's yaw rate, which is a key parameter for measuring the vehicle's rotational tendency around the vertical axis. Its absolute value |ω| directly reflects the degree to which the vehicle deviates from a stable driving state. The larger |ω| is, the higher the risk of the vehicle sideslipping, fishtailing, or oversteering or understeering. By introducing |ω| into the formula, the degree of violent rotation of the vehicle body at present can be accurately captured.

[0097] When the vehicle has no yaw tendency, 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 as |ω| increases. This correction factor will directly affect the subsequent power distribution logic, suppressing the yaw tendency by reducing or adjusting the power output ratio of a specific axle, thereby quickly stabilizing the vehicle's attitude and improving the vehicle's driving safety under complex conditions.

[0098] S25: Front and Rear Axle Integrated Weight Calculation: The integrated weight calculation is the core step in torque distribution decision-making. Its formula integrates three key parameters—axle load, motor efficiency, and yaw rate correction factor—to quantify the power distribution priority between the front and rear axles, providing a basis for the final power output ratio. It is calculated using the following formula:

[0099] front_ratio = Fzf·eff_front·yaw_factor

[0100] rear_ratio = Fzr·eff_rear·yaw_factor

[0101] Where: front_ration is the front axis composite weight, and rear_ratio is the rear axis composite weight;

[0102] Axle load reflects the vertical pressure currently borne by the front and rear axles and is a key factor in determining tire grip. The greater the load, the stronger the friction potential between the tire and the ground, and the greater the driving torque it can withstand. The formula uses axle load as a basic parameter to ensure that the power distribution matches the actual load-bearing capacity of the tire, avoiding slippage caused by the driving force exceeding the grip.

[0103] 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 by the efficiency parameter, more power is preferentially allocated to the shaft where the high-efficiency motor is located, thereby improving the energy utilization efficiency of the entire power system and reducing energy consumption.

[0104] The yaw rate correction factor reflects the current stability state of the vehicle. Its value is dynamically adjusted as the yaw rate changes. When the vehicle shows a yaw tendency (yaw_factor < 1), the weight ratio of the front and rear axles can be reduced simultaneously, which indirectly adjusts the power distribution to suppress yaw and ensures that vehicle stability takes precedence over efficiency or load requirements.

[0105] The calculated front_ratio and rear_ratio intuitively reflect the weight allocation priority of the front and rear axles under the current working conditions, making the torque distribution more optimized in terms of load capacity, efficiency, stability adaptability, etc., and realizing the optimal torque distribution strategy that takes into account load safety, energy efficiency and driving stability.

[0106] In summary, this formula, through the weighted integration of multi-dimensional parameters, achieves a comprehensive consideration of vehicle power demand, efficiency targets, and stability requirements, providing a quantitative basis for dynamic and precise power distribution.

[0107] 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:

[0108] total_weight = front_ratio + rear_ratiofront_weight = front_ratio / total_weight

[0109] rear_weight = rear_ratio / total_weight; Normalized allocation is the final step in torque distribution decision-making. Its formula standardizes the combined weights of the front and rear axles, transforming abstract weight values ​​into directly applicable torque distribution ratios. It converts the front and rear axle weights into percentage forms, eliminating the influence of absolute values ​​and retaining only the relative proportions, which intuitively reflects which axle the power should be tilted towards.

[0110] Unified quantification standard: Regardless of the absolute value of the combined weight of the front and rear axles, after normalization, they are all converted into a ratio between 0 and 1, ensuring that the power distribution coefficient is calculated under a unified dimension and avoiding decision-making bias due to differences in the magnitude of the weight values;

[0111] The obtained front_weight and rear_weight can be directly used as the power distribution ratio between the front and rear axles, transforming the abstract weights into a specific control scheme. This ensures that torque is distributed and output in the optimal ratio, taking into account the comprehensive requirements of load-bearing capacity, efficiency, and stability. When the steering wheel angle steer_angle > 0.1, the steering torque vectoring is activated to correct front_weight and rear_weight: front axle weight factor front_weight * 0.8 and rear axle weight factor rear_weight * 1.2, to optimize steering performance and avoid understeer.

[0112] This steering torque vectoring strategy takes into full account the dynamic characteristics and handling requirements of the vehicle during steering.

[0113] Using a steering wheel angle steer_angle > 0.1 as the activation threshold is essentially an intervention for medium and large steering conditions. No additional torque distribution adjustment is needed when driving at small angles or in a straight line. However, when the angle exceeds the threshold, it means that the driver needs a more proactive steering response. Activating torque distribution correction at this time can specifically solve the handling problems that may occur in this scenario.

[0114] Front axle weight reduction (front_weight*0.8): Reducing the proportion of front axle torque can prevent the front wheels from dragging due to excessive torque; if the front axle weight is too high, the front wheels are prone to exceeding the ground adhesion limit when turning, resulting in sluggish steering action and exacerbating understeer; reducing the front axle weight can reduce the burden on the front wheels and make steering commands more efficiently translated into changes in vehicle posture.

[0115] Rear axle weight increase (rear_weight*1.2): Increasing the rear axle torque distribution is the core of the optimization; after the rear axle torque ratio is increased, it can generate yaw moment through the difference in braking force or driving force of the wheels on one side, actively helping the vehicle body to rotate around the longitudinal axis and improving steering flexibility; this adjustment is equivalent to applying moderate steering assistance to the rear of the vehicle to counteract the understeer tendency caused by inertia or center of gravity distribution.

[0116] Through the above modifications, the system achieves dynamic rebalancing of torque distribution between the front and rear axles, avoiding steering lag caused by excessive front axle torque and enhancing vehicle steering response by increasing rear axle torque. Ultimately, this allows the vehicle to more accurately follow the driver's intentions during medium to large turns, reducing understeer phenomena such as "the front of the car deviates to the outside of the curve when turning and a larger turning angle is required to complete the turn," thus improving handling safety.

[0117] S27: Result obtained: The final output power distribution result is [front_weight / 2, front_weight / 2, rear_weight / 2, rear_weight / 2], which provides a reference for the torque control of the front and rear axle motors of the vehicle;

[0118] S3: Input the output scheme into the model built based on the Modelica language to obtain the simulation results;

[0119] The model built on the Modelica language adopts a modular modeling concept, decoupling 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, it is an intelligent speed controller that converts the target vehicle speed into physical control signals for the drive / braking system through configurable PID algorithms and driver behavior parameters; its design takes into account accuracy (PID adjustment), realism (driver delay simulation) and flexibility (steering coordination extension), providing core control logic for autonomous driving testing and vehicle dynamic performance analysis;

[0120] Power source module: Used to simulate the drive unit, it is the core actuator of the vehicle drive chain. It converts control commands into physical drive torque through a linear mapping relationship and can control the total output torque.

[0121] Transmission system module: Used to realize power transmission and speed change, it is a four-wheel drive system that can control the torque distribution ratio between the front and rear axles and can input the final torque distribution scheme.

[0122] Vehicle body model module: Responsible for representing vehicle mass, inertia and attitude, it is the physical core of the simulation model. In the representation of vehicle inertia, it defines the vehicle mass, center of gravity position, determines the spatial position of the vehicle's center of gravity (affecting pitch / roll stability) and moment of inertia; in the initial conditions of motion, it defines the initial position and initial velocity; in the tire system, it integrates and controls tire layout, tire recognition, and initial rotation state.

[0123] Braking system module: Used to simulate the generation and distribution of braking force, it is the core actuator of the vehicle safety system. As the conversion center, it converts control signals into hydraulic pressure and finally outputs braking torque. It ensures stable braking dynamic simulation through pressure distribution curves and ABS / ESC functions, affects the dynamics of the whole vehicle through braking force output, and realizes closed-loop control through sensor feedback.

[0124] Road Model Module: Provides road surface environment and geometric information for vehicle travel, controls road length and slope, provides road friction coefficient for simulation, constructs road geometry through mathematical description, and also provides simulation visualization of the road model.

[0125] This model allows for direct input of different torque distribution ratios (e.g., 60% front axle + 40% rear axle, 45% front axle + 55% rear axle), simulating the vehicle's dynamic response under these distribution strategies. Simultaneously, the transmission system module interacts with other parts of the model (e.g., the power source module, vehicle dynamics module, road module), converting the adjusted torque distribution scheme into specific power output parameters. Ultimately, the simulation results visually demonstrate the impact of different distribution strategies on climbing performance, providing a reliable basis for optimizing the scheme. The modules in the model, built using the Modelica language, are based on physical characteristics and dynamic behavior, employing non-causal modeling with Modelica to abstract them into corresponding mathematical equations (e.g., higher-order differential equations or algebraic equations), specifically:

[0126] Speed ​​following module: Uses PID control to adjust the target vehicle speed, the formula is:

[0127] ,

[0128] in: For vehicle speed error, For control signals, (Proportional gain): It is directly proportional to the error between the current vehicle speed and the target vehicle speed. It can quickly adjust the vehicle speed to reduce the error, but it may cause oscillation. (Integral gain): Accumulates past errors, eliminates steady-state errors, and prevents the vehicle speed from deviating from the target value for a long time, but may cause overshoot; (Differential gain): Related to the rate of change of error, it suppresses rapidly changing errors, reduces the oscillation amplitude during vehicle speed adjustment, and improves system stability.

[0129] Power source module: Converts control signals into physical driving torque, the formula is as follows. The total torque is then distributed to the transmission system according to the allocation ratio, using the following formula:

[0130] and ,

[0131] in: This is the gain coefficient of the motor; This represents the total output torque of the motor. The control signal output by the speed follower module is used to adjust the output torque of the power source module. It is usually a dimensionless value, ranging from 0 to 1, representing the intensity of the power output. and These are the output torques allocated to the front and rear axles, respectively.

[0132] Transmission system module: Implements power distribution between the front and rear axles, considering transmission efficiency, the formula is as follows. . and ,in: For transmission efficiency, it is usually a coefficient slightly less than 1.

[0133] Vehicle body model module: This module involves vehicle mass, inertia, attitude, and other characteristics. The vehicle kinematics formula is:

[0134] ,

[0135] in: It refers to the overall vehicle quality; It is vehicle acceleration; It is the coefficient of friction between the tire and the ground; It is air resistance; It is rolling resistance.

[0136] Braking system module: Braking torque affects the angular acceleration of the tires, as shown in the formula:

[0137] and ,

[0138] in: It is the braking torque; It is the coefficient of the brake; It is braking pressure; It is the moment of inertia of the wheel.

[0139] Road model module: Provides road surface geometry and friction coefficients, such as slope angle. The front wheel friction coefficient is μ_front, and the rear wheel friction coefficient is μ_rear. The model is built using the Modelica language. Through Modelica's powerful physical connectors, automatic, bidirectional transmission and system-level coupling of physical quantities (such as torque, speed, force, displacement, and road adhesion coefficient) can be achieved between modules (such as power source output and transmission system input, braking system and wheels, vehicle body and road model, etc.). Finally, by connecting predefined, parameterized model modules, a complete and high-fidelity vehicle dynamics system simulation model can be efficiently constructed.

[0140] Therefore, this model library fully utilizes Modelica's non-causal modeling capabilities, effectively combining functional modeling based on physical components (such as engines, transmissions, and vehicle bodies) with abstract modeling based on dynamic characteristics (such as torque transmission, vehicle kinematics, and tire-road interaction). This approach significantly simplifies the modeling process and improves simulation efficiency while ensuring model simulation accuracy. Furthermore, all parameters for each module are clearly defined and can be flexibly configured and invoked, greatly facilitating model simulation testing, parametric research, and debugging analysis.

[0141] As can be seen from the above description, the above embodiments of the present invention achieve the following technical effects: Precise improvement in climbing performance: By comprehensively considering vehicle state parameters such as slope and center of gravity position, the front and rear axle loads are accurately calculated and the torque is reasonably distributed, so that the vehicle can make more efficient use of driving force when climbing, avoid power waste, and significantly enhance climbing ability.

[0142] Optimized steering handling: When the vehicle is turning, the torque vectoring is adjusted according to the steering wheel angle to adjust the torque distribution between the front and rear axles, effectively preventing understeer and improving the vehicle's handling agility and driving stability.

[0143] Significant energy consumption reduction: By using an efficiency map, the system dynamically tracks the high-efficiency operating range of the motor and intelligently adjusts the torque output of the front and rear motors to reduce inefficient operating time, thereby significantly reducing energy consumption and extending the vehicle's driving range.

[0144] Enhanced dynamic stability: The torque distribution is adjusted in real time based on the vehicle's yaw rate. When a yaw tendency is detected, the power output of a specific axle is reduced to suppress the yaw in time, ensuring the safety and stability of the vehicle when driving in complex road conditions.

[0145] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention is limited to these examples; within the framework of the invention, 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 variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.

[0146] This invention is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of this specification. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the scope of protection of this invention.

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 formulas are 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: Maximum Available Drive Torque Calculation 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 formulas are 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 driving torque of the front axle, and Tr_max is the maximum available driving torque of the rear axle; S23: Efficiency Calculation: Based on the current vehicle speed in the vehicle's dynamic state, and the maximum available driving torque of the front and rear axles calculated in step S22, and the efficiency MAP in the power system parameters, the front motor efficiency eff_front and the rear motor efficiency eff_rear are obtained through an 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 rate yaw_rate; S25: Front and Rear Axle Integrated Weight Calculation: By integrating the three key parameters of axle load, motor efficiency, and yaw rate correction factor, the power distribution priority of 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; The vehicle status parameters specifically include: mg as the total weight of the vehicle, L as the front and rear wheelbase, h as the height of the center of gravity, Lf as the distance from the center of gravity to the front axle, α as the slope angle, and r as the tire radius; 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 the efficiency MAP is a two-dimensional matrix reflecting the efficiency of the motor at different vehicle speeds and torques. 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). 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.

2. 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.

3. The electric four-wheel drive torque distribution method based on hill-climbing conditions according to claim 2, 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.

4. 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 ​​following 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.

5. The electric four-wheel drive torque distribution method based on hill-climbing conditions according to claim 4, 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.

6. The electric four-wheel drive torque distribution method based on hill-climbing conditions according to claim 5, 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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