CN114889445A - Vehicle driving force control method, system and storage medium based on working condition identification - Google Patents

Abstract

The invention discloses a vehicle driving force control method, system and storage medium based on working condition identification, comprising the following steps: collecting vehicle driving parameters, establishing a vehicle dynamics model; Estimator; analyze the characteristics of off-road working conditions, and normalize the driving resistance of the vehicle; classify off-road working conditions, design a fuzzy controller for off-road working condition identification combined with characteristic parameters, and obtain working condition utilization coefficients; according to working conditions Using coefficients and vehicle dynamics model, a feedforward torque adjustment controller is designed to estimate the vertical load of the vehicle and distribute the driving force of the vehicle according to the vertical load. The wheel torque compensation strategy is designed according to the wheel torque compensation control principle. The invention can realize the identification of off-road working conditions, the distribution of the vertical load torque of the four wheels and the dynamic moment compensation of the wheels, which is helpful for the driver to improve the driving maneuverability on the off-road road.

Description

Vehicle driving force control method, system and storage medium based on working condition identification

technical field

The invention relates to the field of off-road working condition identification and driving force control of in-wheel motor-driven vehicles, in particular to a vehicle driving force control method, system and storage medium based on working condition identification.

Background technique

Distributed drive vehicles, namely in-wheel motor-driven vehicles, have unique advantages in transmission efficiency, driving economy, active safety control, and adaptability to working conditions, and have become the main research objects of domestic and foreign enterprises and scientific research institutes. Invest a lot of money in research.

At present, there are many researches on the drive control of in-wheel motor-driven vehicles driving on well-paved roads. A well-paved road assumes that the road surface is smooth and there is only a change in the road adhesion coefficient. The wheels are all in contact with the ground, and the vertical force of the wheels is not zero. However, there are few studies on vehicle maneuverability and stability under complex off-road conditions. In addition, the driving conditions of off-road vehicles are complex and the road environment is changeable. For the control of in-wheel motor-driven vehicles, it is necessary to obtain state information through sensors for processing and decision-making control. Because some vehicle state observation sensors are expensive and can be obtained during vehicle driving. There are problems with data accuracy and real-time performance. At the same time, the working condition identification can accurately identify road roughness, road grade, etc. based on reliable algorithms. The processing of a large number of data sets causes the system to have a certain hysteresis. It is necessary to conduct rapid identification research on off-road working conditions to realize vehicle drive control, and adjust the vehicle by identifying the road surface in real time. state to improve driving maneuverability.

SUMMARY OF THE INVENTION

In view of this, embodiments of the present invention provide a vehicle driving force control method, system, and storage medium based on operating condition identification.

A first aspect of the present invention provides a vehicle driving force control method based on operating condition identification, comprising the following steps:

Collect vehicle driving parameters and establish vehicle dynamics model;

Obtain the state parameters of the vehicle based on the vehicle dynamics model, and design a parameter estimator;

Analyze the characteristics of off-road conditions and normalize the driving resistance of the vehicle;

The off-road working conditions are classified, and the fuzzy controller for off-road working condition identification is designed according to the characteristic parameters, and the working condition utilization coefficient is obtained;

According to the utilization factor of the working condition and the vehicle dynamics model, the feedforward torque regulation controller is designed

Estimate the vertical load of the vehicle, and distribute the driving force of the vehicle according to the vertical load;

The wheel torque compensation strategy is designed according to the wheel torque compensation control principle.

Further, the collecting vehicle driving parameters includes collecting vehicle controller input parameters, collecting driver input parameters and collecting road input parameters;

The vehicle dynamics model, including the tire model of the vehicle:

The tire model includes the following equations:

The equation of longitudinal force on the tire;

The equation of lateral force on the tire;

The equation for the tire slip angle;

From the tire model of the vehicle, the longitudinal force, lateral force and vertical load on each wheel, as well as the front wheel rotation angle of the vehicle, are summarized as the output parameters of the tire model.

Further, the parameter estimator includes a vehicle speed estimator and a road adhesion coefficient estimator;

The vehicle speed estimator calculates the vehicle speed through the three-directional motion equation of the vehicle;

The three-direction motion equation of the vehicle includes the longitudinal motion equation of the vehicle along the X axis, the lateral motion equation of the vehicle along the Y axis and the yaw motion equation of the vehicle along the Z axis:

The road adhesion coefficient of each wheel is obtained by combining the road surface adhesion coefficient estimator with the road surface input parameters;

The average value of the four-wheel adhesion coefficient is calculated according to the road adhesion coefficient of each wheel, and the difference value of the four-wheel adhesion condition is further calculated according to the average value of the four-wheel adhesion coefficient.

Further, by analyzing the characteristics of off-road working conditions and normalizing the driving resistance of the vehicle, the following steps are included:

Calculate the air resistance, hill resistance and rolling resistance of the vehicle, summed up as the dynamic driving resistance of the vehicle;

Calculate the actual driving resistance of the vehicle according to the vehicle dynamics model;

Calculate the variation deviation of the dynamic driving resistance of the vehicle according to the dynamic driving resistance and the actual driving resistance of the vehicle;

Normalize the vehicle's dynamic driving resistance variation deviation, air resistance, ramp resistance and rolling resistance;

The analyzing the characteristics of off-road working conditions further includes judging the suspended state of the wheels;

The wheel suspension state is obtained by judging the off-road working condition, judging the wheel slip flag position, judging the four-wheel torque and judging the actual driving resistance of the vehicle. The wheel suspension ratio is used as the output result of the wheel suspension state.

Further, according to the classification of off-road working conditions, a fuzzy controller for identifying off-road working conditions is designed in combination with characteristic parameters, and the utilization coefficient of working conditions is obtained, which specifically includes the following parts:

According to the normalized slope resistance, air resistance, rolling resistance and driving resistance, as well as the difference value of the four-wheel adhesion condition and the wheel suspension ratio, the off-road conditions are classified. The categories include the all-low adhesion ground condition, the adhesion difference Obvious ground condition, high-adhesion no-ramp undulating terrain condition, and high-adherence ramp undulating terrain condition;

With normalized ramp resistance, normalized air resistance, normalized rolling resistance, normalized running resistance variation deviation, four-wheel adhesion condition difference value and wheel suspension ratio as the input variables of the fuzzy controller, the vehicle driving uses The coefficients are used as the output variables of the fuzzy controller to design the fuzzy controller;

Determine the relationship between the vehicle adhesion rate and the road surface adhesion coefficient according to the vehicle driving adhesion restriction conditions; calculate the maximum adhesion rate of the vehicle driving;

According to the vehicle driving utilization coefficient and the maximum adhesion rate of the vehicle driving, the vehicle operating condition utilization coefficient is calculated;

The design steps of the fuzzy controller include:

Fuzzy input variables;

formulate fuzzy logic rules;

According to the area center of gravity method, the input variables after fuzzification are de-fuzzified, and the vehicle driving utilization coefficient is obtained.

Further, the design of the feedforward torque adjustment controller according to the operating condition utilization coefficient and the vehicle dynamics model specifically includes the following steps:

Calculate driver demand torque;

According to the driver's required torque and the utilization coefficient of vehicle operating conditions, the vehicle feedforward torque is calculated, and the feedforward torque adjustment controller is obtained;

The flag bit is designed in the feedforward torque adjustment controller to adjust the intervention and exit of the feedforward controller.

Further, estimating the vertical load of the vehicle and distributing the driving force of the vehicle according to the vertical load specifically includes the following steps:

Determine the four-wheel distribution load of the vehicle by analyzing and calculating the static load and dynamic load of the vehicle;

Through the load distribution in the grounded state of the four wheels, the distance between the center of mass of the vehicle and the front and rear axles and the distance from the center of mass to the left and right vehicle ends are identified, and the proportional distribution coefficients of the front axle, the rear axle, and the left and right sides are obtained;

According to the different grounding states of the four wheels, the vertical loads in each state are calculated respectively;

The different grounding states of the four wheels include single-wheel suspension, same-side double-wheel suspension and different-side double-wheel suspension.

Further, designing the wheel torque compensation strategy according to the wheel torque compensation control principle specifically includes the following steps;

According to the vertical load, determine the torque distribution coefficient of the rear axle;

According to the torque distribution coefficient of the rear axle, the optimal dynamic distribution torque of the front and rear axles is further determined;

Determine the total yaw moment of the vehicle, and further determine the four-wheel drive torque;

According to the torque compensation control principle, according to the classification of off-road working conditions, the specific torque compensation strategy under each working condition is designed.

The invention also discloses a system, comprising a processor and a memory;

the memory is used to store programs;

The processor executes the program to implement a vehicle driving force control method based on operating condition identification.

The invention also discloses a computer-readable storage medium, characterized in that the storage medium stores a program, and the program is executed by a processor to realize a vehicle driving force control method based on working condition identification.

The present invention has the following beneficial effects: the present invention obtains the state parameters through the built vehicle and tire dynamics model to complete the design of the parameter estimator, thereby estimating the longitudinal vehicle speed and the road adhesion coefficient, and studying the relevant characteristic parameters to obtain the road adhesion characteristics, undulations Four working conditions related to torsion characteristics are used to identify off-road conditions. On the premise of satisfying the driver's expected speed, the driver's accelerator pedal information is analyzed to obtain the vehicle's demand torque; and the four-wheel vertical load torque distribution is carried out based on the identification of different wheel states. The dynamic torque compensation of the wheel is carried out from the dynamic performance and stability of the whole vehicle, which helps the driver to improve the driving maneuverability on the off-road road.

Additional aspects and advantages of the present invention will be presented in the description which follows, in part, which will become apparent from the following description, or may be learned by practice of the invention.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the drawings that are used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

Figure 1 is a diagram of a vehicle driving force control architecture;

Figure 2 is a schematic diagram of a vehicle seven-degree-of-freedom dynamic model;

Figure 3 is the wheel force analysis diagram;

4 is a schematic diagram of a vehicle on an off-road road;

Figure 5 is a schematic diagram of a membership function;

Fig. 6 is a single-wheel slip and suspension moment compensation strategy diagram;

Fig. 7 is a strategy diagram of two-wheel slip and suspension moment compensation on the same side;

Fig. 8 is a strategy diagram of two-wheel slip on different sides and suspension moment compensation;

Figure 9 is a simulation identification diagram of off-road conditions.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

This embodiment describes a vehicle driving force control method based on operating condition identification. The implementation process is shown in Figure 1, including but not limited to the following steps:

S1 : collecting vehicle driving parameters, and establishing a vehicle dynamics model; step S1 obtains the state parameters of the vehicle by establishing a seven-degree-of-freedom dynamics model and a tire model of an in-wheel motor vehicle.

S2: Obtain the state parameters of the vehicle based on the vehicle dynamics model, and design a parameter estimator; step S2 uses the vehicle speed estimator and the road adhesion coefficient estimator to obtain the longitudinal vehicle speed and the road adhesion coefficient.

S3: Analyze the characteristics of off-road working conditions, and normalize the driving resistance of the vehicle; step S3 normalize the driving resistance of the vehicle, and define the four-wheel adhesion mean value and four-wheel difference value, judge the adhesion conditions, and propose Four identification criteria are used to identify the wheel suspension and grounding state.

S4: Classify off-road working conditions, design a fuzzy controller for off-road working condition identification based on characteristic parameters, and obtain working condition utilization coefficients.

S5: Design a feedforward torque adjustment controller according to the operating condition utilization coefficient and vehicle dynamics model.

S6: Estimate the vertical load of the vehicle, and distribute the driving force of the vehicle according to the vertical load.

S7: Design a wheel torque compensation strategy according to the wheel torque compensation control principle; Step S7 distributes the driving force based on the torque distribution coefficient, and designs a compensation adjustment coefficient based on the working condition utilization coefficient for different wheel slip and suspended off-road conditions. Torque compensation strategy.

The specific execution flow of each step of the present invention will be described below with different embodiments.

This embodiment describes the specific flow of step S1, and the vehicle dynamics model established in step S1 is referred to FIG. 2 . Collecting vehicle driving parameters includes collecting vehicle controller input parameters, collecting driver input parameters and collecting road input parameters; the four wheels of the vehicle driven by the in-wheel motor are all driving wheels. Considering the wheel rotation and forward state, the wheel dynamics model is studied. The force analysis of the wheel is shown in Figure 3, and the dynamic balance equation of the wheel force is obtained:

The moment of inertia of the electric wheel assembly is:

I _{w_i} =I _w +I _r +I _q

According to the empirical formula, the rolling resistance coefficient can be roughly estimated as:

f=0.0076+0.000056v _x

In the formula, F _{x_i} is the ground lateral force on the wheel, where i represents the four wheels respectively, T _i is the driving torque on each wheel, and I _{w_i} is the moment of inertia of the electric wheel assembly, including the moment of inertia I of the wheel _w , planetary reducer rotational inertia I _r , drive motor rotational inertia I _q , ω _i is the angular velocity of each wheel, f is the rolling resistance coefficient of the wheel, F _{z_i} is the vertical load of each wheel, r is the rolling radius of the wheel, and _Wi is the Wheel load, F _{p_i} is the inertial force at the wheel center.

The tire model includes the following equations:

The equation of longitudinal force on the tire;

The equation of lateral force on the tire;

The equation for the tire slip angle;

in:

为各轮胎侧偏角，S(η_i)为表征轮胎滑转状态相关函数，η_i为表征轮胎滑转状态系数，μ_i为路面附着系数，F_zi为各轮垂向载荷，v_x为车辆纵向车速，v_y为车辆横向车速；式中的i为fl、fr、rl、rr时表示四轮中的左前轮、右前轮、左后轮及右后轮。where C _x is the tire longitudinal stiffness coefficient, C _y is the tire lateral stiffness coefficient, S _i is the slip ratio of each tire,

is the side slip angle of each tire, S(η _i ) is the correlation function representing the tire slip state, η _i is the coefficient representing the tire slip state, μ _i is the road adhesion coefficient, F _zi is the vertical load of each wheel, and v _x is The longitudinal speed of the vehicle, v _y is the lateral speed of the vehicle; when i in the formula is fl, fr, rl, rr, it means the left front wheel, the right front wheel, the left rear wheel and the right rear wheel among the four wheels.

From the tire model of the vehicle, the longitudinal force F _{x_i} , the lateral force F _{y_i} and the vertical load F _zi on each wheel, as well as the front wheel turning angle δ of the vehicle, are summarized as output parameters of the tire model.

This embodiment describes the specific flow of step S2. In step S2, the state parameters of the vehicle are obtained based on the vehicle dynamics model, and a parameter estimator is designed, and the parameter estimator includes a vehicle speed estimator and a road adhesion coefficient estimator;

The vehicle speed estimator calculates the vehicle speed through the three-directional motion equation of the vehicle;

The three-direction motion equation of the vehicle includes the longitudinal motion equation of the vehicle along the X axis, the lateral motion equation of the vehicle along the Y axis and the yaw motion equation of the vehicle along the Z axis:

The equation of longitudinal motion of the vehicle along the X axis:

∑F _{x =} max =(F _{x_fl} +F _{x_fr} )cosδ-(F _{y_fl} +F _{y_fr} )sinδ+F _{x_rl} +F _{x_rr}

The equation of lateral motion of the vehicle along the Y axis:

∑F _y =ma _y =(F _{x_fl} +F _{x_fr} )sinδ+(F _{y_fl} +F _{y_fr} )cosδ+F _{y_rl} +F _{y_rr}

The equation of yaw motion of the vehicle along the Z axis:

∑M _z =L _f [(F _{x_fl} +F _{x_fr} )sinδ+(F _{y_fl} +F _{y_fr} )cosδ]-L _r (F _{y_rl} +F _{y_rr} )+B _r (F _{x_fr} cosδ-F _{y_ fr} sinδ+F _{x_rr} )-B _f (F _{x_fl} cosδ-F _{y_fl} sinδ+F _{x_rl} )

in:

L=L _f +L _r

B=B _f +B _r

In the formula, F _{x_i} and F _{y_i} are the longitudinal force and lateral force of each wheel (wherein, when i is fl, fr, rl, rr, it represents the left front wheel, right front wheel, left rear wheel and right rear wheel among the four wheels. ) v _x is the longitudinal speed of the vehicle, v _y is the lateral speed of the vehicle, a _x is the longitudinal acceleration of the vehicle, a _y is the lateral acceleration of the vehicle, γ is the yaw rate of the vehicle, m is the curb weight of the vehicle, δ is the front wheel angle of the vehicle, I _z is the moment of inertia of the vehicle around the specified z-axis, M _z is the sum of the torques of the vehicle around the specified z-axis, L is the wheelbase, L _f is the distance from the vehicle's center of mass to the front axle, and L _r is the distance from the vehicle's center of mass to the rear axle. distance, B is the wheel base, B _f is the distance from the center of the front axle of the vehicle to the left wheel, and B _r is the distance from the center of the front axle of the vehicle to the right wheel.

The road adhesion coefficient of each wheel is obtained through the road adhesion coefficient estimator combined with the road input parameters;

The average value of the four-wheel adhesion coefficient is calculated according to the road adhesion coefficient of each wheel, and the difference value of the four-wheel adhesion condition is further calculated according to the average value of the four-wheel adhesion coefficient.

The mean four-wheel adhesion coefficient is defined as:

E _μ = (μ _fl + μ _fr + μ _rl + μ _rr )/4

The difference value of the four-wheel attachment condition is defined as:

D _μ =(μ _fl -E _μ ) ² +(μ _fr -E _μ ) ² +(μ _rl -E _μ ) ² +(μ _rr -E _μ ) ²

In the formula, μ _fl is the road adhesion coefficient identified by the left front wheel, μ _fr is the road adhesion coefficient identified by the right front wheel, μ _rl is the road adhesion coefficient identified by the left rear wheel, and μ _rr is the road adhesion coefficient identified by the right rear wheel.

This embodiment describes the specific flow of step S3. Step S3 analyzes the characteristics of off-road working conditions, and normalizes the driving resistance of the vehicle, including the following steps:

Calculate the air resistance, hill resistance and rolling resistance of the vehicle, summed up as the dynamic driving resistance of the vehicle;

Calculate the actual driving resistance of the vehicle according to the vehicle dynamics model;

Calculate the variation deviation of the dynamic driving resistance of the vehicle according to the dynamic driving resistance and the actual driving resistance of the vehicle;

Normalize the vehicle's dynamic driving resistance variation deviation, air resistance, ramp resistance and rolling resistance;

The schematic diagram of vehicle driving on off-road roads is shown in Figure 4. According to the analysis of road adhesion, the road environment will be covered by soil, gravel, water, snow, etc., resulting in obvious differences in road adhesion, and the characteristics are related to the ground; Mixed roads such as potholes, soil slopes, ditches, craters, obstacles, etc., the characteristics are related to the terrain. Because the road environment is complex and there are many types, in order to ensure the responsiveness of the control system, the influence of road adhesion and road geometry characteristics on the vehicle state is analyzed from the perspective of vehicle dynamics.

The driving resistance of the vehicle is normalized. When the vehicle travels in a straight line, the driving resistance has the characteristics of time-varying and uncertainty, and the resistance caused by the external environment mainly includes air resistance, rolling resistance and ramp resistance.

The dynamic driving resistance of the vehicle is estimated by the longitudinal motion of the vehicle as:

F _r =F _w +F _i +F _f

The air resistance is:

where the ramp resistance is:

F _i =m·g·sinθ

where the rolling resistance is:

F _f =f·m·g·cosθ

Considering the follow-up responsiveness and real-time calculation, the kinematics method is selected for the rapid slope estimation, and the longitudinal acceleration method is selected for the estimation. The comprehensive information includes the longitudinal acceleration and gravitational acceleration components, and the estimated slope angle is:

In view of the fact that the vehicle is running on a twisted and uneven road and the grounding state of the four wheels changes, the actual resistance of the vehicle is calculated from the output of the motor to the wheel torque through the previous wheel dynamics model:

The variation deviation of vehicle dynamic driving resistance is:

F _e =|F _a -F _r |

The vehicle travels in off-road conditions, resulting in dynamic changes in the deviation of the driving resistance and various driving resistances. In order to compare the data of each state parameter at the same dimension and time to observe the state of the vehicle, the above four parameters are selected for normalization. , the maximum and minimum values of each parameter are collected from different working conditions as the base for calculation, and the normalized parameters are defined as:

分别为归一化行驶阻力变化偏差、空气阻力、坡道阻力与滚动阻力。In the formula,

They are the normalized running resistance variation deviation, air resistance, hill resistance and rolling resistance, respectively.

可一定程度反映道路的起伏程度，在平直路面行驶车辆行驶实际负载较大，

较小；在起伏路面行驶车轮出现悬空导致车辆行驶实际负载较小，

较大。

可反映车辆行驶速度，车辆以中低速通过复杂地形

较小或适中。

可反映车辆在坡道路面行驶状态，

较大则道路坡度较大，

较小则道路近似为平路。

受到路面坡度与行驶车速影响，车速对于

变化较大，与

分析相似。

It can reflect the undulation degree of the road to a certain extent, and the actual load of the vehicle driving on the flat road is relatively large.

Smaller; the suspension of the wheels on the undulating road results in the actual load of the vehicle being small.

larger.

It can reflect the driving speed of the vehicle, and the vehicle passes through complex terrain at medium and low speed

Small or moderate.

It can reflect the driving state of the vehicle on the slope surface,

The larger the road, the steeper the road gradient.

If it is smaller, the road is approximately flat.

Affected by road gradient and driving speed, the speed of

large changes, with

Analysis is similar.

Analyzing the characteristics of off-road conditions also includes judging the suspension state of the wheels;

The wheel suspension state is obtained by judging the off-road working condition, judging the wheel slip flag position, judging the four-wheel torque and judging the actual driving resistance of the vehicle. The wheel suspension ratio is used as the output result of the wheel suspension state.

Due to the complexity and variability of off-road working conditions, and the possibility of vehicle state jumps affected by noise, it is difficult to judge the wheel state positively through several vehicle state quantities. Loss, choose the reverse identification method to put forward four identification criteria for identification, the following is the identification principle process of wheel suspension and grounding state:

(1) Judgment of off-road conditions:

Vehicles driving on twisted and uneven roads will have their wheels suspended. Through the following study, the vehicle driving utilization coefficient D _u (the initial value is set to 1) is identified as high-adhesion and no-slope undulating terrain conditions or high-adhesion slope undulating terrain conditions. D _u is within the range of design thresholds D ₀ and D ₁ .

(2) Judgment of slip flag:

When the wheel is in a suspended state, that is, the wheel is in a slipping state. Observe the change of the slip flag bit Slip _i in the intervention condition of the vehicle drive anti-skid control to determine whether the wheel is in a slipping state.

(3) Four-wheel torque output judgment:

When a single wheel is suspended, the driving torque of the suspended wheel is smaller than that of the other three wheels that are not suspended. At the same time, it can be seen from the vehicle motion state that the vertical load of the diagonal wheel of the suspended wheel will decrease, and the driving torque is that of the three non-suspended wheels. The minimum value; when the two wheels are suspended, the driving torque of the suspended wheels is smaller than that of the other two wheels that are not suspended, and the grounding of the two wheels that are not suspended serves as the full power output of the vehicle, and its driving torque is the maximum value.

(4) Judgment of the actual driving resistance of the vehicle:

According to the analysis of the dynamic driving resistance of the vehicle above, when the wheel is in the suspended state, the angular velocity of the wheel increases sharply, and the instantaneous adjustment of the output torque decreases, so that the actual driving resistance is only determined by the inertial resistance moment of the wheel.

Based on the above four judgment conditions, the suspended state of each wheel can be identified, and the specific identification and judgment logic is shown in Table 1 below:

Table 1 Judgment conditions of wheel suspension state

Identify the wheel overhang results through different working conditions, and define the wheel overhang rate as:

in:

In the formula, Spin _i is the flag bit of the suspended wheel, and Count _{spin_i} is the number of the suspended wheel.

Spin _p can reflect the influence of undulating terrain and flat road on the grounding and suspension state of the wheels. If the road surface is smooth, the four-wheel grounding Spin _p is small, and the road surface is twisted and uneven, resulting in a moderate or large single-wheel or two-wheel suspension Spin _p .

This embodiment describes the specific flow of step S4. Step S4 classifies off-road working conditions, designs a fuzzy controller for off-road working condition identification in combination with characteristic parameters, and obtains the working condition utilization coefficient, which specifically includes the following parts:

According to the normalized slope resistance, air resistance, rolling resistance and driving resistance, as well as the difference value of the four-wheel adhesion condition and the wheel suspension ratio, the off-road conditions are classified. The categories include the all-low adhesion ground condition, the adhesion difference Obvious ground condition, high-adhesion no-ramp undulating terrain condition, and high-adherence ramp undulating terrain condition;

According to the analysis of step S3, the classification of working conditions and the summary of corresponding characteristic parameters can be carried out:

较小，归一化空气阻力

归一化滚动阻力

较小或适中，归一化行驶阻力变化偏差

较小，四轮附着条件差异值D_μ较小，车轮悬空率Spin_p较小。1) All low adhesion ground conditions: the road adhesion coefficient is low and the road undulation is small, and the normalized slope resistance

Smaller, normalized air resistance

normalized rolling resistance

Small or moderate, normalized driving resistance variation deviation

Smaller, the difference value D _μ of the four-wheel attachment condition is smaller, and the wheel suspension ratio Spin _p is smaller.

较小，归一化空气阻力

归一化滚动阻力

较小或适中，归一化行驶阻力变化偏差

较小，四轮附着条件差异值D_μ适中或较大，车轮悬空率Spin_p较小。(2) Obvious difference in adhesion Ground conditions: There are large differences in the adhesion conditions of the four wheels, such as docking or facing the road, the degree of road undulation is small, and the normalized slope resistance

Smaller, normalized air resistance

normalized rolling resistance

Small or moderate, normalized driving resistance variation deviation

Small, the four-wheel adhesion condition difference value D _μ is moderate or large, and the wheel suspension ratio Spin _p is small.

较小，归一化空气阻力

归一化滚动阻力

较小或适中，车轮出现悬空归一化行驶阻力变化偏差

适中或较大，出现悬空车轮的路面附着系数识别为0则四轮附着条件差异值D_μ较大或适中，车轮悬空率Spin_p适中或较大。(3) High-adhesion and no-ramp undulating terrain conditions: the road ramp is small and the degree of undulation is large, the road adhesion condition is a high-adhesion road, and the ramp resistance is normalized

Smaller, normalized air resistance

normalized rolling resistance

Small or moderate, the wheels appear overhanging normalized driving resistance variation deviation

Moderate or large, the road surface adhesion coefficient of the suspended wheels is identified as 0, the difference value D _μ of the four-wheel adhesion conditions is large or moderate, and the wheel suspension ratio Spin _p is moderate or large.

适中或较大，归一化滚动阻力

归一化空气阻力

较小或适中，车轮出现悬空归一化行驶阻力变化偏差

适中或较大，四轮附着条件差异值D_μ较大或适中，车轮悬空率Spin_p适中或较大。(4) High-adhesion slope undulating terrain conditions: the road slope is large and the degree of undulation is large, and the normalized slope resistance

Moderate or large, normalized rolling resistance

normalized air resistance

Small or moderate, the wheels appear overhanging normalized driving resistance variation deviation

Moderate or large, the four-wheel adhesion condition difference value D _μ is large or moderate, and the wheel suspension ratio Spin _p is moderate or large.

With normalized ramp resistance, normalized air resistance, normalized rolling resistance, normalized running resistance variation deviation, four-wheel adhesion condition difference value and wheel suspension ratio as the input variables of the fuzzy controller, the vehicle driving uses The coefficients are used as the output variables of the fuzzy controller to design the fuzzy controller;

The design steps of a fuzzy controller include:

Fuzzy input variables;

D_μ与Spin_p均选用3个模糊子集为{S，M，B}，模糊描述为较小、适中与较大，论域为[0，1]，其中仅Spin_p选取论域为[0，0.5]，对应选取3个隶属度函数为Z型、高斯型与S型。input variable

Both D _μ and Spin _p select three fuzzy subsets as {S, M, B}, the fuzzy descriptions are small, moderate and large, and the universe of discourse is [0, 1], of which only Spin _p selects the universe of discourse as [ 0, 0.5], correspondingly select three membership functions as Z-type, Gaussian-type and S-type.

In the output variables, D _u selects 4 fuzzy subsets as {S, M, U, R}, and the fuzzy description is the ground condition with full low attachment, the ground condition with obvious difference in attachment, the condition with high attachment without slope undulation, and the condition with high attachment. Attached to the undulating terrain condition of the ramp, the universe of discourse is [0, 1], and the three membership functions are correspondingly selected as Z-type, Gauss-type and S-type.

Refer to Figure 5 for the membership function of each input variable.

formulate fuzzy logic rules;

Fuzzy rules define multiple conditional statements, provide core logic for specific application conditions of fuzzy control, enumerate a variety of rules that conform to reality, and complete the establishment of inference models according to requirements covering typical conditions, as shown in Table 2 below.

Table 2 Fuzzy logic rules

According to the area center of gravity method, the input variables after fuzzification are defuzzified, and the vehicle driving utilization coefficient is obtained.

Through the fuzzy description of off-road working conditions based on fuzzy reasoning, defuzzification is carried out to obtain the specific values of the output variables, and the area centroid method is selected, which is in line with engineering practice and simple to calculate, and it is easy to observe the output results intuitively.

According to the expected results of off-road working condition identification and combined with the analysis of vehicle longitudinal driving force control requirements, the four working conditions are reflected from the vehicle driving force control results as the vehicle driving utilization coefficient under each working condition. The specific numerical range of the vehicle driving utilization coefficient for off-road condition identification is [0, 1], the range of the full low adhesion ground condition corresponding to the fuzzy description is [0, 0.25), and the range of the ground condition with obvious adhesion difference is [0.25, 0.5) , the range of high-adhesion and no-ramp undulating terrain conditions is [0.5, 0.75), and the range of high-adhesion ramp undulating terrain conditions is [0.75, 1].

Table 3 Analysis table of identification conditions and control objectives

Determine the relationship between the vehicle adhesion rate and the road surface adhesion coefficient according to the vehicle driving adhesion restriction conditions; calculate the maximum adhesion rate of the vehicle driving;

不满足条件车轮出现滑转现象，具体关系表达式为：If the condition that the vehicle can run stably is that the longitudinal driving force F _x is not greater than the road adhesion

If the conditions are not met, the wheel slips, and the specific relational expression is:

According to the vehicle driving adhesion restriction conditions, the relationship between the driving wheel adhesion rate and the road surface adhesion coefficient can be expressed as:

C _μ ≤ μ

C _μ =F _x /F _z

Based on the identification of the suspended and grounded state of the wheel, the driving force will be directly lost when the wheel is in the suspended state. At this time, considering the maximum output driving torque of the in-wheel motor, the maximum adhesion rate of the vehicle drive is defined as:

In the formula, i is the gear ratio of the reducer, and _Tmax is the maximum driving torque of the motor.

Considering the limitations of road adhesion conditions for vehicle driving, the vehicle drive adhesion utilization rate is defined based on the maximum value of the four-wheel adhesion conditions as the ratio of the maximum vehicle adhesion rate to the maximum four-wheel adhesion conditions. The specific expression is as follows:

According to the vehicle driving utilization coefficient and the maximum adhesion rate of the vehicle driving, the vehicle operating condition utilization coefficient is calculated;

Considering the suspended grounding state of the wheel and the identification results of the working conditions, in order to not affect the output power loss of the in-wheel motor in the vehicle driving force control, the working condition D is identified in the high-adhesion and no-ramp undulating terrain conditions and the high-adhesion ramp undulating terrain conditions. The larger of the two values of _u and C _c calculated in real time is used as the vehicle operating condition utilization factor for off-road conditions; considering that the road adhesion condition causes the vehicle to spin multiple wheels, the smaller of the above two values is used as the vehicle operating condition for off-road conditions. The coefficient is used as the feedforward power adjustment and feedback torque control coefficient for the output driving torque of the vehicle.

This embodiment describes the specific flow of step S6. Step S6 is to design a feedforward torque adjustment controller according to the operating condition utilization coefficient and the vehicle dynamics model, which specifically includes the following steps:

Calculate driver demand torque;

Since the driver himself affects the longitudinal driving force feedback control of the vehicle, and considering the in-wheel motor characteristics and the matching design of the vehicle, the driver can rely on the driver to complete the closed-loop control of the driving torque. The calculated driver demand torque is:

T _d =α _d ·T _m

In the formula, α _d is the accelerator pedal opening, T _d is the driver's demand torque, and T _m is the motor torque characteristic.

According to the driver's required torque and the utilization coefficient of vehicle operating conditions, the vehicle feedforward torque is calculated, and the feedforward torque adjustment controller is obtained;

T _fe =Power _c ·T _d

The flag bit is designed in the feedforward torque adjustment controller to adjust the intervention and exit of the feedforward controller.

Considering the extreme conditions of three-wheel or four-wheel suspension in the off-road road vehicle, the feed-forward control of the system may aggravate the instability of the vehicle, so the design flag Flag _fe adjusts the intervention and exit of the feed-forward controller, only in conventional off-road work. intervene in circumstances. In the condition of wheel slip caused by single-wheel or double-wheel suspension and road adhesion difference, the feedforward control is normally involved; in the extreme condition, the feedforward control is withdrawn, and the motion tracking is completed by the feedback control.

This embodiment describes the specific flow of step S7. Step S7 estimates the vertical load of the vehicle, and distributes the driving force of the vehicle according to the vertical load, which specifically includes the following steps:

Determine the four-wheel distribution load of the vehicle by analyzing and calculating the static load and dynamic load of the vehicle;

Considering the total load of the vehicle in the off-road driving condition when the wheels are not suspended in the air, and calculated by the static load and dynamic load of the vehicle, the four-wheel load distribution is:

The dynamic load component of longitudinal acceleration is:

ΔF _x =m·a _x ·h _g /2L

The dynamic load component of the vehicle pitching state is:

The dynamic load component of the lateral acceleration of the front axle is:

ΔF _{y_f} =m·a _y ·h _g ·L _r /L·B

The dynamic load component of the front axle roll state is:

ΔF _{r_f} =m·g·sinφ·h _g ·L _r /L·B

The dynamic load component of the rear axle lateral acceleration is:

ΔF _{y_r} =m·a _y ·h _g ·L _f /L·B

The dynamic load component of the rear axle roll state is:

ΔF _{y_r} =m·g·sinφ·h _g ·L _f /L·B

In the formula, F _{z_fl} is the vertical load of the left front wheel, F _{z_fr} is the vertical load of the right front wheel, F _{z_rl} is the vertical load of the left rear wheel, and F _{z_rr} is the vertical load of the right rear wheel.

Through the description of the above-mentioned wheel suspension and grounding states, the vertical load identification under different wheel suspension states is carried out according to the relationship between the wheelbase and wheelbase of the vehicle and the load distribution state of the four wheels.

Through the load distribution in the grounded state of the four wheels, the distance between the center of mass of the vehicle and the front and rear axles and the distance from the center of mass to the left and right vehicle ends are identified, and the proportional distribution coefficients of the front axle, the rear axle, and the left and right sides are obtained;

The coefficients are:

According to the different grounding states of the four wheels, the vertical loads in each state are calculated respectively;

Different grounding states of the four wheels include single-wheel suspension, two-wheel suspension on the same side and two-wheel suspension on different sides.

(1) For the single-wheel suspension state, it can be divided into left front wheel suspension, right front wheel suspension, left rear wheel suspension and right rear wheel suspension. The vertical load calculation of each state classification is shown in Table 4 below:

Table 4 Classification of single wheel suspended vertical load

Taking the left front wheel suspended as an example, the vertical load F _zfl of the left front wheel is 0, the right front wheel and the left rear wheel on the same side of the suspended wheel are completely grounded, and the corresponding vertical loads F _zfr and F _zrl are determined by the front axle and the left side. The proportional distribution coefficient is fully distributed and calculated, the right rear wheel as the left front wheel is not completely grounded, and has a tendency to leave the ground, and its driving torque is the smallest among the three grounded wheels. The vertical load F _zrr is approximately composed of four The proportional distribution coefficient is calculated to obtain a smaller value.

(2) For the same-side double-wheel suspension state, it can be divided into the front axle double-wheel suspension, the rear axle double-wheel suspension, the left double-wheel suspension and the right-side double-wheel suspension. The vertical load calculation of each state classification is shown in Table 5 below Show:

Table 5 Classification of suspended vertical loads of two wheels on the same side

For example, the front axle and two wheels are suspended, the vertical loads F _zfl and F _zfr of the left front wheel and the right front wheel are 0, and the two wheels of the rear axle are completely grounded. To the loads F _zrl and F _zrr .

(3) For the two-wheel suspension state on different sides, it can be divided into left front wheel and right rear wheel diagonally suspended and right front wheel and left rear wheel suspended diagonally. The vertical load calculation of each state classification is shown in Table 6 below:

Table 6. Classification of suspended vertical loads of two wheels on opposite sides

Taking the left front wheel and the right rear wheel suspended diagonally as an example, the vertical loads F _zfl and F _zrr of the left front wheel and the right rear wheel are 0, the right front wheel and the left rear wheel are completely grounded, and the proportional distribution coefficient is calculated approximately to the right front wheel. The diagonal directions of the wheel and the left rear wheel are distributed to obtain the vertical loads F _zfr and F _zrl .

This embodiment describes the specific flow of step S7. Step S7 is to design a wheel torque compensation strategy according to the wheel torque compensation control principle, which specifically includes the following steps;

According to the vertical load, determine the torque distribution coefficient of the rear axle;

The four-wheel vertical load calculation rear axle torque distribution coefficient is:

According to the torque distribution coefficient of the rear axle, the optimal dynamic distribution torque of the front and rear axles is further determined;

According to the rear axle torque distribution coefficient, the feedforward control torque can be further distributed to the front and rear axles so that the vehicle can achieve the optimal dynamic distribution of torque to the front and rear axles:

Determine the total yaw moment of the vehicle, and further determine the four-wheel drive torque;

The total yaw moment of the vehicle is:

The driving torque instead of the tire longitudinal force is expressed as:

In order to keep the total demand yaw moment unchanged, the differential torque of the front and rear axles is evenly distributed, and the distribution of the torque difference between the front and rear axles is:

Combining the above formula and distributing the four-wheel drive torque, we get:

According to the torque compensation control principle, according to the classification of off-road working conditions, the specific torque compensation strategy under each working condition is designed.

(1) Single wheel slip and suspended state:

Taking the slip of the left front wheel as an example, the single-wheel slip drives the torque loss after the anti-skid control is involved, and performs the same-side wheel torque compensation to meet the vehicle dynamic requirements. The same-side wheel torque T _rl that completes the torque distribution under the current working condition is increasing the compensation torque After ΔT _fl , if the road adhesion conditions and the in-wheel motor can output the maximum torque limit, the torque compensation of the opposite-side wheel is performed through the incomplete compensation torque ΔT _rl of the left rear wheel. The compensation torque of the opposite-side wheel may generate an undesired yaw moment. The vehicle operating condition utilizes the coefficient Power _c to be a small value, and the compensation torque of the right front wheel and the right rear wheel is adjusted through Power _c , and the restriction conditions are met at the same time.

Taking the left front wheel suspended as an example, the torque of the same-side wheel that completes the torque distribution under the current working condition can compensate the normal torque when it satisfies the road adhesion conditions and the maximum torque limit the in-wheel motor can output. The vertical load is small, the compensable moment is small, the vehicle operating condition utilization coefficient Power _c is a large value, and the vehicle stability is not the main consideration _. The fully compensated torque ΔT _rl adjusts the right rear wheel torque to ensure vehicle dynamics.

Refer to Figure 6 for the compensation strategy of single wheel slip and suspended moment.

(2) Slippage and suspension state of two wheels on the same side:

Taking the left front wheel and the left rear wheel slipping as an example, due to the slipping of the left two wheels, the wheels on the same side cannot perform torque compensation, which prevents the compensation torque of the two wheels without slipping, which leads to an increase in the torque difference between the front and rear axles and deteriorates the stability of the vehicle. The working conditions use the coefficient Power _c to directly adjust the compensation torques ΔT _fl and ΔT _rl .

Taking the left front wheel and the left rear wheel hanging in the air as an example, or one wheel hanging in the air and the other _{wheel slipping} are treated as the hanging state, and the power improvement is the control goal. Under the condition of the maximum output torque, the two wheels on opposite sides are directly compensated by the distributed torque; it is not satisfied that the compensation torques ΔT _fl and ΔT _rl are directly adjusted by the coefficient Power _c through the vehicle operating conditions.

Refer to Figure 7 for the compensation strategy of the two-wheel slip on the same side and the suspended moment.

(3) Two-wheel slip on different sides and suspended state:

Taking the left front wheel and the right front wheel as an example, since the wheels on the same side of the two wheels can perform torque compensation, in order to prevent a large torque difference, the compensation torques ΔT _fl and ΔT _fr both satisfy or do not satisfy the road adhesion. Condition and in-wheel motor can output the maximum torque limit, adopt the same adjustment torque strategy. Only one pulley satisfies the restriction conditions for normal torque compensation. In order to make the compensation torque difference between the two wheels smaller, the coefficient Power _c is used to adjust the compensation torque according to the vehicle operating conditions.

Taking the left front wheel and the right front wheel hanging in the air as an example, or one wheel hanging in the air and the other wheel slipping are treated as the hanging state. Under the premise of ensuring dynamic performance, the wheel torque compensation on both sides is based on the adjustable maximum value, and the road adhesion conditions are met. The in-wheel motor can output the maximum torque limit and the two wheels do not slip to perform a separate compensation torque strategy.

Refer to Figure 8 for the compensation strategy of opposite-side two-wheel slip and suspended moment

(4) Multi-wheel slip and suspended state:

If only the torque of one wheel is adjusted in the state of three-wheel slip, the stability of the vehicle will deteriorate. If the four-wheel slip, no wheel can perform torque compensation, and the torque compensation strategy cannot be implemented. The control torque is output by driving anti-skid control. The three-wheel or four-wheel suspended state is defined as the limit working condition above, and the intervention control aggravates the instability of the vehicle and does not carry out the strategy design.

Fig. 9 depicts the simulation results of a vehicle driving force control method based on working condition identification of the present invention. The results show that the present invention has a better torque compensation capability, and can realize the wheel suspension state for vehicles in off-road working conditions. Wheel dynamic torque compensation is performed for vehicle dynamics and stability.

The embodiment of the present invention also discloses a computer program product or computer program, where the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of the computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the method shown in FIG. 1 .

In some alternative implementations, the functions/operations noted in the block diagrams may occur out of the order noted in the operational diagrams. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/operations involved. Furthermore, the embodiments presented and described in the flowcharts of the present invention are provided by way of example in order to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of the various operations are altered and in which sub-operations described as part of larger operations are performed independently.

Furthermore, while the invention is described in the context of functional modules, it is to be understood that, unless stated to the contrary, one or more of the described functions and/or features may be integrated in a single physical device and/or or software modules, or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to understand the present invention. Rather, given the attributes, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the modules will be within the routine skill of the engineer. Accordingly, those skilled in the art, using ordinary skill, can implement the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are illustrative only and are not intended to limit the scope of the invention, which is to be determined by the appended claims along with their full scope of equivalents.

The logic and/or steps represented in flowcharts or otherwise described herein, for example, may be considered an ordered listing of executable instructions for implementing the logical functions, may be embodied in any computer-readable medium, For use with, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other system that can fetch instructions from and execute instructions from an instruction execution system, apparatus, or apparatus) or equipment. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or apparatus.

In the description of this specification, description with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples", etc., mean specific features described in connection with the embodiment or example , structure, material or feature is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the described embodiments, and those skilled in the art can also make various equivalent deformations or replacements on the premise of not violating the spirit of the present invention, These equivalent modifications or substitutions are all included within the scope defined by the claims of the present application.

Claims (10)

1. A vehicle driving force control method based on working condition identification is characterized by comprising the following steps:

collecting vehicle driving parameters and establishing a vehicle dynamic model;

acquiring state parameters of a vehicle based on a vehicle dynamics model, and designing a parameter estimator;

analyzing the characteristics of the cross-country working condition, and carrying out normalization processing on the running resistance of the vehicle;

classifying the off-road working conditions, designing a fuzzy controller for identifying the off-road working conditions by combining the characteristic parameters, and obtaining a working condition utilization coefficient;

designing a feedforward torque regulation controller according to a working condition utilization coefficient and a vehicle dynamics model

Estimating a vertical load of the vehicle, and distributing vehicle driving force according to the vertical load;

and designing a wheel moment compensation strategy according to a wheel moment compensation control principle.

2. The vehicle driving force control method based on the working condition identification is characterized in that the collecting of the vehicle driving parameters comprises collecting vehicle controller input parameters, collecting driver input parameters and collecting road surface input parameters;

the vehicle dynamics model comprises a tire model of the vehicle:

the tire model includes the following equations:

the longitudinal force equation to which the tire is subjected;

the lateral force equation to which the tire is subjected;

an equation for generating a slip angle for the tire;

the longitudinal force, the lateral force and the vertical load to which each wheel is subjected are summarized from the tire model of the vehicle, and the front wheel turning angle of the vehicle as output parameters of the tire model.

3. The vehicle driving force control method based on the working condition identification is characterized in that the parameter estimator comprises a vehicle speed estimator and a road adhesion coefficient estimator;

the vehicle speed estimator calculates the vehicle speed through a three-direction motion equation of the vehicle;

the three directional equations of motion for the vehicle include a longitudinal equation of motion for the vehicle along the X-axis and a lateral equation of motion for the vehicle along the Y-axis and a yaw equation of motion for the vehicle along the Z-axis:

obtaining the road adhesion coefficient of each wheel by combining the road adhesion coefficient estimator with the road input parameters;

and calculating the four-wheel adhesion coefficient mean value according to the road adhesion coefficient of each wheel, and further calculating according to the four-wheel adhesion coefficient mean value to obtain the four-wheel adhesion condition difference value.

4. A vehicle driving force control method based on operating condition identification as claimed in claim 3, wherein the analysis of the off-road operating condition characteristics and the normalization of the vehicle running resistance comprise the following steps:

calculating the air resistance, the ramp resistance and the rolling resistance of the vehicle, and summarizing the air resistance, the ramp resistance and the rolling resistance into the dynamic driving resistance of the vehicle;

calculating the actual running resistance of the vehicle according to the vehicle dynamic model;

calculating the variation deviation of the dynamic running resistance of the vehicle according to the dynamic running resistance and the actual running resistance of the vehicle;

normalizing the dynamic running resistance variation deviation, the air resistance, the ramp resistance and the rolling resistance of the vehicle;

analyzing the off-road working condition characteristics further comprises judging the suspension state of the wheels;

the wheel suspension state is obtained by comprehensively summarizing the wheel suspension state through judging the off-road working condition, judging the wheel slip zone bit, judging the four-wheel torque and judging the actual running resistance of the vehicle, and the wheel suspension rate is used as the output result of the wheel suspension state.

5. The vehicle driving force control method based on working condition identification as claimed in claim 4, wherein the classification of off-road working conditions is carried out, a fuzzy controller for off-road working condition identification is designed by combining characteristic parameters, and a working condition utilization coefficient is obtained, and the method specifically comprises the following parts:

classifying off-road working conditions according to the ramp resistance, the air resistance, the rolling resistance and the driving resistance after normalization processing, the difference value of four-wheel attachment conditions and the wheel suspension ratio, wherein the categories comprise a full-low attachment ground working condition, a surface working condition with obvious attachment difference, a high-attachment ramp-free undulating terrain working condition and a high-attachment ramp undulating terrain working condition;

the method comprises the following steps of taking normalized ramp resistance, normalized air resistance, normalized rolling resistance, normalized running resistance variation deviation, four-wheel attachment condition difference values and wheel suspension ratios as input variables of a fuzzy controller, taking a vehicle driving utilization coefficient as an output variable of the fuzzy controller, and designing the fuzzy controller;

determining the relation between the vehicle adhesion rate and the road adhesion coefficient according to the vehicle running adhesion limiting condition; calculating the maximum driving adhesion rate of the whole vehicle;

calculating a vehicle working condition utilization coefficient according to the vehicle driving utilization coefficient and the maximum attachment rate of the whole vehicle driving;

the fuzzy controller design steps comprise:

fuzzification processing is carried out on input variables;

formulating a fuzzy logic rule;

and according to an area gravity center method, performing defuzzification processing on the input variable after fuzzification to obtain a vehicle driving utilization coefficient.

6. The vehicle driving force control method based on the working condition identification as claimed in claim 5, wherein the step of designing the feedforward torque regulation controller according to the working condition utilization coefficient and the vehicle dynamics model specifically comprises the following steps:

calculating a driver demand torque;

calculating to obtain a vehicle feedforward torque according to the driver required torque and the vehicle working condition utilization coefficient to obtain a feedforward torque adjustment controller;

and designing a flag bit in the feedforward torque regulation controller to regulate the intervention and exit of the feedforward controller.

7. The vehicle driving force control method based on the working condition identification as claimed in claim 6, wherein the estimating of the vertical load of the vehicle and the distribution of the vehicle driving force according to the vertical load comprise the following steps:

determining four-wheel distribution load of the vehicle by analyzing and calculating static load and dynamic load of the vehicle;

the identification of the distance from the center of mass of the vehicle to the front and rear axles and the distance from the center of mass to the left and right vehicle ends is completed through the load distribution of the four-wheel grounding state, and the proportional distribution coefficients of the front axle, the rear axle, the left side and the right side are obtained;

respectively calculating vertical loads in each state aiming at different grounding states of four wheels;

the different grounding states of the four wheels comprise single-wheel suspension, same-side double-wheel suspension and different-side double-wheel suspension.

8. The vehicle driving force control method based on the working condition identification is characterized in that a wheel torque compensation strategy is designed according to a wheel torque compensation control principle, and the method specifically comprises the following steps;

determining a rear axle torque distribution coefficient according to the vertical load;

further determining the optimal dynamic distribution torque of the front axle and the rear axle according to the torque distribution coefficient of the rear axle;

determining the total yaw moment of the vehicle, and further determining the four-wheel drive torque;

according to the torque compensation control principle, a specific torque compensation strategy under each working condition is designed according to the cross-country working condition classification.

9. A system comprising a processor and a memory;

the memory is used for storing programs;

the processor executing the program realizes the method according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that the storage medium stores a program, which is executed by a processor to implement the method according to any one of claims 1-8.

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