Traction force control method and system of vehicle and computing equipment

Abstract

The invention discloses a traction force control method and system of a vehicle and computing equipment. The method comprises the steps that the operation working condition and operation parameters of the vehicle and environment parameters of the environment where a wheel speed sensor of the vehicle is located are obtained; performing wheel speed compensation on the vehicle based on the operation condition, the operation parameter and the environment parameter to obtain the actual wheel speed of the vehicle; calculating the actual slip rate of the vehicle based on the actual wheel speed; and performing traction control on the vehicle based on the actual slip rate to adjust the traction force of the vehicle. The problems that in the prior art, a wheel speed sensor is prone to being affected by the environment, so that the accuracy of collected data is low, correspondingly generated traction force does not necessarily meet the traction requirement of wheels, the probability of wheel slipping is large, and the safety of vehicle driving is reduced are solved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle traction control method, system, and computing device. Background Art

[0002] When a vehicle is driving on the road, its wheels can easily rotate due to acceleration, causing wheel slip. To reduce tire slip, conventional traction control systems are typically incorporated into vehicle systems. These systems use wheel speeds detected by wheel speed sensors to control the traction system and generate traction to pull the wheels. However, wheel speed sensors are susceptible to environmental influences, resulting in low accuracy in the collected data. The resulting traction may not always meet the wheel's traction requirements, increasing the probability of wheel slip and reducing vehicle driving safety. Summary of the Invention

[0003] In order to overcome the problem in the prior art that wheel speed sensors are easily affected by the environment, resulting in low accuracy of the collected data, the corresponding traction force may not necessarily meet the traction requirements of the wheels, the probability of wheel slippage is high, and the safety of vehicle driving is reduced, the present application provides a vehicle traction control method, system and computing device.

[0004] In a first aspect, in order to solve the above technical problems, the present application provides a vehicle traction control method, comprising:

[0005] Obtaining the operating conditions and operating parameters of the vehicle, as well as the environmental parameters of the environment in which the vehicle's wheel speed sensor is located;

[0006] Perform wheel speed compensation on the vehicle based on operating conditions, operating parameters and environmental parameters to obtain the actual wheel speed of the vehicle;

[0007] The actual slip ratio of the vehicle is calculated based on the actual wheel speed;

[0008] The vehicle is traction-controlled based on the actual slip ratio to adjust the vehicle's traction.

[0009] In a second aspect, the present application further provides a vehicle traction control system, comprising:

[0010] An acquisition module is used to acquire the operating conditions and operating parameters of the vehicle, as well as the environmental parameters of the environment in which the vehicle's wheel speed sensor is located;

[0011] A wheel speed compensation module is used to compensate the vehicle's wheel speed based on operating conditions, operating parameters, and environmental parameters to obtain the vehicle's actual wheel speed;

[0012] A calculation module, configured to calculate an actual slip rate of the vehicle based on an actual wheel speed;

[0013] The traction control module is configured to perform traction control on the vehicle based on the actual slip ratio to adjust the traction force of the vehicle.

[0014] In a third aspect, the present application also provides a computing device, including a memory, a processor, and a program stored in the memory and running on the processor, and when the processor executes the program, the steps of a vehicle traction control method as described above are implemented.

[0015] In a fourth aspect, the present application also provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes the steps of a vehicle traction control method.

[0016] The beneficial effects of this application are as follows: First, based on the vehicle's operating conditions and operating parameters, as well as the environmental parameters of the environment in which the vehicle's wheel speed sensor is located, the vehicle's wheel speed is compensated to obtain the vehicle's actual wheel speed, thereby reducing the impact of the wheel speed sensor's environment on the actual wheel speed obtained, thereby improving the accuracy of the actual wheel speed so that the actual wheel speed meets the wheel speed accuracy requirements under the current environment. Second, based on the actual wheel speed that meets the wheel speed accuracy requirements, the vehicle's actual slip rate that meets the wheel speed accuracy requirements can be calculated, and based on the actual slip rate that meets the wheel speed accuracy requirements, targeted traction control is performed on the vehicle, so that the adjusted traction force can meet the current traction requirements of the wheel, thereby reducing the probability of wheel slippage and further improving vehicle driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a vehicle traction control method according to an exemplary embodiment of the present application;

[0018] Figure 2 This is a flow chart for determining whether an operating parameter is valid in an exemplary embodiment of the present application;

[0019] Figure 3 A flowchart for determining the actual wheel speed of a vehicle in an exemplary embodiment of the present application;

[0020] Figure 4 The figure is a schematic structural diagram of a vehicle traction control system according to an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0021] The following examples are provided to further explain and supplement the present application and do not constitute any limitation to the present application.

[0022] Existing traction control systems (TCS) are used to prevent wheels from spinning due to acceleration. Vehicle wheel slippage usually occurs on slippery surfaces, such as snow or ponds, where the wheels cannot generate enough traction to propel the vehicle. TCS can help better utilize the road adhesion coefficient. When the drive wheels begin to slip, TCS will sense it and reduce engine torque or apply brake pressure to help restore traction. It is applicable to vehicles with front cameras and IBCU (Integrated Brake Control Unit) products.

[0023] The existing technology mainly uses the vehicle wheel speed sensor to collect data, calculate the degree of vehicle drive wheel slip, and restore traction by controlling the vehicle engine torque through feedback or applying braking pressure to the wheel ends to apply braking force. However, the existing technology still has the following shortcomings:

[0024] (1) The wheel speed value error caused by the wheel speed sensor acquisition accuracy is not taken into account, which affects the control accuracy;

[0025] (2) The collected signal values of the vehicle operating parameters and the wheel speed sensor are not necessarily reliable. Even in the scenario of wheel slippage, the traction control system will not be triggered, so the probability of wheel slippage is still high, resulting in safety risks for the vehicle and the driver.

[0026] In order to solve the above problems, embodiments of the present application provide a vehicle traction control method, system, and computing device, which will be described in detail below.

[0027] The vehicle traction control method provided in the embodiments of the present application can be specifically executed by a server. It should be noted that the server can be a standalone server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms, and is not limited here.

[0028] See also Figure 1 , Figure 1 A vehicle traction control method is shown as an exemplary embodiment of the present application. Figure 1 As shown, the present application provides a vehicle traction control method, comprising:

[0029] Step S11, obtaining the operating conditions and operating parameters of the vehicle, as well as the environmental parameters of the environment in which the wheel speed sensor of the vehicle is located;

[0030] Step S12, performing wheel speed compensation on the vehicle based on the operating conditions, operating parameters, and environmental parameters to obtain the actual wheel speed of the vehicle;

[0031] Step S13, calculating the actual slip rate of the vehicle based on the actual wheel speed;

[0032] In step S14, traction control is performed on the vehicle based on the actual slip ratio to adjust the traction force of the vehicle.

[0033] The vehicle traction control method of this embodiment provided by the present application firstly compensates the vehicle's wheel speed based on the vehicle's operating conditions and operating parameters, as well as the environmental parameters of the environment in which the vehicle's wheel speed sensor is located, to obtain the vehicle's actual wheel speed. This reduces the impact of the wheel speed sensor's environment on the acquired actual wheel speed, thereby improving the accuracy of the actual wheel speed so that the actual wheel speed meets the wheel speed accuracy requirements under the current environment. Secondly, based on the actual wheel speed that meets the wheel speed accuracy requirements, the vehicle's actual slip ratio that meets the wheel speed accuracy requirements is calculated. Based on the actual slip ratio that meets the wheel speed accuracy requirements, targeted traction control is performed on the vehicle, ensuring that the adjusted traction force meets the current traction requirements of the wheels, thereby reducing the probability of wheel slip and improving vehicle driving safety.

[0034] Optionally, performing wheel speed compensation on the vehicle based on the operating conditions, operating parameters, and environmental parameters to obtain the actual wheel speed of the vehicle includes:

[0035] Obtaining the signal valid flag and signal change value of the operating parameter, as well as the functional status of the vehicle's integrated brake control unit;

[0036] If the signal valid flag is valid, the signal change value is less than the threshold value, and the functional state is no functional degradation, then the compensated wheel speed of the wheel speed sensor is determined based on the environmental parameters;

[0037] Perform dynamic control based on operating parameters and operating conditions to obtain the predicted wheel speed of the vehicle;

[0038] The predicted wheel speed and the compensated wheel speed are combined to obtain the actual wheel speed of the vehicle.

[0039] In the embodiment provided by the present application, only when the signal validity flag for determining the operating parameters is valid, the signal change value is less than the threshold value (to prevent signal value jumps), and the functional state of the vehicle's integrated brake control unit is no functional degradation, indicating that the vehicle's sensors and control system are normal, the accuracy of the collected operating parameters is high, the operating parameters are valid, and accurate traction control of the vehicle can be performed, will the subsequent enabling function be performed normally, that is, wheel speed compensation of the vehicle based on the operating conditions, operating parameters, and environmental parameters can be performed, which can improve the accuracy of the wheel speed compensation and thus improve the accuracy of the actual wheel speed of the vehicle obtained by compensation. At the same time, when performing wheel speed compensation, the compensated wheel speed determined based on the environmental parameters and the predicted wheel speed obtained by dynamic control based on the operating parameters and operating conditions are fused, which can reduce the impact of the environment on the actual wheel speed, thereby improving the accuracy of the actual wheel speed obtained by fusion.

[0040] See also Figure 2 , Figure 2 In an exemplary embodiment of the present application, a flow chart for determining whether an operating parameter is valid is shown as follows: Figure 2 As shown, the operating parameters are input signals, including vehicle speed, wheel speed detected by wheel speed sensor, lateral and longitudinal acceleration, steering angle, yaw angular velocity, etc. Only when the three conditions of the input signal valid flag is valid, the signal change value is not overshoot (less than the threshold), and the functional status is no functional degradation are met at the same time, the operating parameters are determined to be valid as input signals. However, as long as any one of the conditions is not met, the operating parameters are determined to be invalid as input signals.

[0041] Optionally, the environmental parameters include a temperature parameter and a humidity parameter; and determining the compensated wheel speed of the wheel speed sensor based on the environmental parameters includes:

[0042] Find the corresponding temperature compensation value in the preset temperature compensation table based on the temperature parameter;

[0043] Based on the humidity parameter, the corresponding humidity compensation value is found in the preset humidity compensation table;

[0044] The sum of the temperature compensation value and the humidity compensation value is determined as the environmental compensation value of the wheel speed sensor;

[0045] Obtaining a zero drift compensation value of the wheel speed sensor, and calculating the environment compensation value and the zero drift compensation value based on a preset first weight parameter to obtain a wheel speed compensation value of the wheel speed sensor;

[0046] The detected wheel speed of the wheel speed sensor is obtained, and the sum of the detected wheel speed and the wheel speed compensation value is determined as the compensated wheel speed of the wheel speed sensor.

[0047] In the embodiment provided by the present application, first, the sum of the temperature compensation value corresponding to the temperature parameter and the humidity compensation value corresponding to the humidity parameter is determined as the environmental compensation value of the wheel speed sensor, thereby compensating and quantifying the temperature and humidity effects. Secondly, the environmental compensation value and the zero drift compensation value of the wheel speed sensor are calculated based on a preset first weight parameter to obtain the wheel speed compensation value of the wheel speed sensor, and the sum of the detected wheel speed of the wheel speed sensor and the wheel speed compensation value is determined as the compensated wheel speed of the wheel speed sensor. This facilitates the consideration of data acquisition errors caused by the temperature, humidity, and zero drift effects on the wheel speed sensor during subsequent wheel speed compensation for the vehicle, thereby improving the accuracy of the compensated wheel speed of the wheel speed sensor, thereby improving the control accuracy of subsequent traction control of the vehicle, reducing the probability of wheel slip, and improving vehicle driving safety.

[0048] In this embodiment, the temperature and humidity parameters can first be acquired using other modules or sensors in the vehicle. By repeatedly acquiring the effects of the temperature parameter t and humidity parameter h of the wheel speed sensor's environment on the wheel speed sensor's acquisition accuracy, the change in the wheel speed sensor's acquisition error is determined. The acquisition errors under the influence of multiple temperatures are used as temperature compensation values, and their corresponding relationships with the corresponding temperature parameters are stored in a temperature compensation table. The acquisition errors under the influence of humidity are used as humidity compensation values, and their corresponding relationships with the corresponding humidity parameters are stored in a humidity compensation table. Then, based on the multiple acquisition errors (corresponding to the compensation values), the calculation formula for the environmental compensation value WheelSpdOffset1 is fitted: WheelSpdOffset1 = f(t) + f(h), where f(t) represents the temperature compensation value corresponding to the temperature parameter t, and f(h) represents the humidity compensation value corresponding to the temperature parameter h.

[0049] Secondly, when the sensor input signal is zero (or under static reference conditions), the output signal undergoes unexpected offsets due to external factors such as time, temperature, and power supply voltage. This phenomenon is called sensor drift, which is usually caused by the sensor's internal characteristics, environmental factors, or circuit noise. Therefore, in this implementation, in order to reduce the impact of sensor drift on the acquisition error of the wheel speed sensor, it is necessary to obtain the zero drift compensation value of the wheel speed sensor to compensate for the wheel speed. The zero drift compensation value of the wheel speed sensor, WheelSpdOffset2, is obtained by self-testing the wheel speed sensor after it is powered on, and collecting the wheel speed value at this time when the vehicle is stationary.

[0050] Then, the first weight parameter includes the target environmental compensation weight Factor1 and the target zero drift compensation weight Factor2. Based on the preset first weight parameter, the environmental compensation value WheelSpdOffset1 and the zero drift compensation value WheelSpdOffset2 are calculated to obtain the vehicle's wheel speed compensation value WheelSpdOffset. The corresponding calculation formula is as follows:

[0051] WheelSpdOffset=Factor1*WheelSpdOffset1+Factor2*WheelSpdOffset2.

[0052] Then the compensated wheel speed of the wheel speed sensor WheelSpd1=WheelSpd sensor +WheelSpdOffset. Among them, WheelSpd sensor Indicates the wheel speed detected by the wheel speed sensor, and WheelSpdOffset indicates the wheel speed compensation value.

[0053] Optionally, the preset first weight parameter is obtained as follows:

[0054] A preset fuzzy logic algorithm is used to set multiple fuzzy logic Sugeno-type rules of the vehicle, wherein the fuzzy logic Sugeno-type rules represent the correspondence rules between the vehicle's wheel speed level and wheel speed change rate and the initial environmental compensation weight;

[0055] Get the rule triggering strength for triggering fuzzy logic Sugeno type rules;

[0056] A target environmental compensation weight for the vehicle is obtained by performing a weighted average calculation based on multiple rule triggering intensities and multiple initial environmental compensation weights;

[0057] The target zero drift compensation weight of the vehicle is calculated based on the target environment compensation weight, and the sum of the target environment compensation weight and the target zero drift compensation weight is 1;

[0058] A preset first weight parameter is formed based on the target environment compensation weight and the target zero drift compensation weight.

[0059] In the embodiment provided herein, a preset fuzzy logic algorithm is used to set multiple fuzzy logic Sugeno-type rules for the vehicle. A weighted average calculation is performed based on multiple rule triggering intensities corresponding to the multiple fuzzy logic Sugeno-type rules and multiple initial environmental compensation weights to obtain a target environmental compensation weight for the vehicle. A target zero drift compensation weight for the vehicle is then calculated based on the target environmental compensation weight to form a preset first weight parameter. In this way, calculating the target environmental compensation weight and target zero drift compensation weight for the vehicle based on multiple fuzzy rules comprehensively considers the impact of the vehicle's wheel speed level and wheel speed change rate on the wheel speed in the current environment, improving the accuracy of the obtained target environmental compensation weight and target zero drift compensation weight. This improves the accuracy of subsequent wheel speed compensation for the vehicle using wheel speed compensation values calculated based on the target environmental compensation weight and target zero drift compensation weight, thereby reducing the probability of vehicle slippage and improving vehicle driving safety.

[0060] In this embodiment, when the wheel speed is less than the first speed, the wheel speed level is determined to be low speed; when the wheel speed is greater than or equal to the first speed and less than the second speed, the wheel speed level is determined to be medium speed; when the wheel speed is greater than or equal to the second speed and less than the third speed, the wheel speed level is determined to be high speed; wherein, the first speed < the second speed < the third speed.

[0061] When the wheel speed change rate is less than the first change rate, it means that the vehicle wheel speed changes slowly; when the wheel speed change rate is greater than or equal to the first change rate and less than the second change rate, it means that the vehicle wheel speed changes moderately; when the wheel speed change rate is greater than or equal to the second change rate and less than the third change rate, it means that the vehicle wheel speed changes quickly; among them, the first change rate < the second change rate < the third change rate.

[0062] Using the preset fuzzy logic algorithm, first, the wheel speed level and wheel speed change rate are divided into fuzzy sets (such as "low speed, medium speed, high speed", "slow wheel speed change, medium wheel speed change, fast wheel speed change"), and a triangular or trapezoidal membership function is designed to specify the wheel speed range and peak value of the wheel speed level and wheel speed change rate. Secondly, a fuzzy rule base is designed, and a plurality of fuzzy logic Sugeno type rules are designed in the fuzzy rule base. For example: the fuzzy logic Sugeno type rule can be: if the wheel speed level is low speed, and the wheel speed change rate corresponds to slow wheel speed change, then the initial environmental compensation weight corresponding to the wheel speed level and the wheel speed change rate is 0.8, and the initial zero drift compensation weight at this time is 0.2; the fuzzy logic Sugeno type rule can also be: if the wheel speed level is low speed, and the wheel speed change rate corresponds to medium wheel speed change, then the initial environmental compensation weight corresponding to the wheel speed level and the wheel speed change rate is 0.5, and the initial zero drift compensation weight at this time is 0.5. Then, the rule triggering strength for triggering the fuzzy logic Sugeno-type rule is calculated. Specifically, for each fuzzy logic Sugeno-type rule, the minimum membership of the preconditions (wheel speed level and wheel speed change rate) is calculated. For example, if the membership of the wheel speed level is 0.6 (high speed) and the membership of the wheel speed change rate is 0.7 (slow wheel speed change), the resulting rule triggering strength is min(0.6, 0.7) = 0.6. Finally, the initial environmental compensation weights and rule triggering strengths of all fuzzy logic Sugeno-type rules are summarized to calculate the target environmental compensation weight. Based on the sum of the target environmental compensation weight and the target zero drift compensation weight being 1, the target zero drift compensation weight is obtained.

[0063] The calculation formulas for target environment compensation weight and target zero drift compensation weight are as follows:

[0064]

[0065] Target zero drift compensation weight = 1-target environment compensation weight.

[0066] Optionally, dynamic control is performed based on operating parameters and operating conditions to obtain predicted wheel speeds of the vehicle, including:

[0067] Calculating a first wheel speed of the vehicle under the operating condition based on the operating parameters;

[0068] Constructing a wheel dynamics model of the vehicle and using the dynamics model to calculate the operating parameters to obtain the second wheel speed of the vehicle;

[0069] Performing linear regression on the wheel dynamics model to obtain a linear regression wheel dynamics model of the vehicle, and using the linear regression wheel dynamics model to calculate the operating parameters to obtain the third wheel speed of the vehicle;

[0070] The first wheel speed, the second wheel speed, and the third wheel speed are calculated based on a preset second weight parameter to obtain a predicted wheel speed of the vehicle.

[0071] In the embodiment provided herein, by predicting the vehicle's wheel speeds under different conditions and performing weighted calculations, the impact of various conditions on the vehicle can be comprehensively considered, ensuring that the accuracy of the predicted wheel speeds meets requirements, further improving the accuracy of the subsequently obtained actual wheel speeds, thereby further reducing the probability of wheel slip and further improving vehicle driving safety. The second weighting parameter includes a first wheel speed weight corresponding to the first wheel speed, a second wheel speed weight corresponding to the second wheel speed, and a third wheel speed weight corresponding to the third wheel speed.

[0072] In an exemplary embodiment provided herein, first, operating conditions include a straight-line operating condition, a differential speed distribution operating condition during low-speed cornering, an operating condition that takes slip ratio correction error into account, and an operating condition determined independently by a single wheel of the vehicle; then, based on the operating parameters, a first wheel speed of the vehicle under the operating condition is calculated, and the specific steps are as follows:

[0073] When the operating condition is a straight line condition, the first wheel speed ω (rad / s) is calculated using the vehicle longitudinal speed v (m / s) included in the operating parameters. The calculation formula is:

[0074]

[0075] Where r represents the effective rolling radius of the wheel (m);

[0076] When the operating condition is a differential speed distribution condition of low-speed turning, the first wheel speed ω is calculated using the steering angle included in the operating parameters. The calculation formula is:

[0077]

[0078] Where R represents the turning radius, L represents the wheelbase, δ represents the steering angle, vleft represents the linear speed of the left rear wheel, v represents the longitudinal speed of the vehicle, T represents the wheelbase, vright represents the linear speed of the right rear wheel, ωleft represents the detected wheel speed of the left rear wheel, ωright represents the detected wheel speed of the right rear wheel, and r represents the effective rolling radius of the wheel;

[0079] When the operating condition is a condition that takes slip ratio correction error into consideration, the first wheel speed ω is calculated using the initial slip ratio corresponding to the detected wheel speed included in the operating parameters. The calculation formula is:

[0080] When the vehicle is in driving state, When the vehicle is in braking state,

[0081] Where v represents the longitudinal velocity of the vehicle, s represents the initial slip rate corresponding to the detected wheel speed, and r represents the effective rolling radius of the wheel;

[0082] When the operating condition is determined independently by a single wheel of the vehicle, the yaw angular velocity ω included in the operating parameters is used. z , center of mass velocity v x and v y , and wheel position (a i ,b i ), steering angle δ i , calculate the first wheel speed ω, which is calculated as follows:

[0083] v xi =v x -ω z b i

[0084] v yi =v y -ω z ·a i

[0085]

[0086] Among them, v xi and v yi represents the linear velocity component of the wheel at the i-th moment, b i and a i represents a constant, ω i represents the first wheel speed at the i-th moment, r represents the effective rolling radius of the wheel, δ i represents the steering angle at the i-th moment.

[0087] Secondly, construct the vehicle's wheel dynamics model. The specific steps are as follows:

[0088] Construct an initial dynamic model of the vehicle. Based on the characteristics of the tires, which affect the dynamics of the entire vehicle, this model can capture the dynamic load conditions of the vehicle tires.

[0089] Tire model (longitudinal force calculation): using a linear simplified model, longitudinal force F x Proportional to the slip rate s: F x =C·s, where C represents the longitudinal stiffness of the tire;

[0090] Dynamic load distribution, load transfer caused by vehicle acceleration (taking the longitudinal direction as an example):

[0091]

[0092] Among them, F z,front Indicates the front load, F z,rearrepresents the rear load, m represents the vehicle mass, g represents the acceleration of gravity; l f 、l r They represent the distances from the front and rear axles to the center of mass, l represents the wheelbase, h represents the height of the center of mass, and a represents the longitudinal acceleration;

[0093] Establish the relationship between wheel speed and dynamic variables: wheel speed w satisfies , where J represents the wheel moment of inertia, T represents the driving torque, and F x represents the longitudinal force of the tire; then the tire model and slip rate definition are combined and substituted into the dynamic equation to obtain the vehicle wheel dynamics model:

[0094]

[0095] Then, a linear regression is performed on the wheel dynamics model to obtain the linear regression wheel dynamics model of the vehicle. The specific steps are as follows:

[0096] The nonlinear equation of the above wheel dynamics model is approximately:

[0097] Among them, v0 represents the reference speed;

[0098] When the slip ratio is small, the above approximate equation is linearized, and the vehicle speed v and driving torque T are used as input variables, and the wheel speed change rate is As output, the approximation equation is organized into a linear form:

[0099]

[0100] The above equation is further discretized (sampling time Δt):

[0101]

[0102] make:

[0103]

[0104] Then the linear regression wheel dynamics model is: k+1 =w k +β0T k +β1v k +β2w k , where w k Indicates the current wheel speed; T k Indicates driving torque; v k Indicates the vehicle speed.

[0105] Optionally, the predicted wheel speed and the compensated wheel speed are combined to obtain the actual wheel speed of the vehicle, including:

[0106] Get the fault status of the wheel speed sensor;

[0107] When the fault state is in a non-fault state, the predicted wheel speed and the compensated wheel speed are calculated based on a preset third weight parameter to obtain an actual wheel speed of the vehicle;

[0108] When the fault state is a faulty state, the predicted wheel speed is determined as the actual wheel speed of the vehicle.

[0109] In the embodiment provided herein, when the wheel speed sensor's fault state is non-faulty, indicating a high degree of accuracy in the sensor's detection parameters, the predicted wheel speed and the corresponding compensated wheel speed are weighted, enabling wheel speed compensation based on the environmental influences of the sensor's environment. This improves the accuracy of the actual wheel speed and reduces the probability of wheel slip. When the fault state is faulty, indicating that the wheel speed sensor's signal is invalid and unreliable, the predicted wheel speed is directly determined as the vehicle's actual wheel speed. This allows for a relatively accurate actual wheel speed to be obtained, even without considering the sensor's environmental influences. This allows the vehicle to operate normally even in a slipping state, reducing the probability of wheel slip and ensuring user and vehicle safety as well as vehicle functional reliability.

[0110] In this embodiment, the third weight parameter includes the wheel speed prediction weight Factor Estimated and wheel speed compensation weight Factor sensor , and the sum of the predicted wheel speed weight and the wheel speed compensation weight is 1, that is, Factor sensor +Factor Estimated =1, then the calculation formula of the actual wheel speed WheelSpdMerge of the fused vehicle is: WheelSpdMerge=Factor sensor *WheelSpd1+Factor Estimated *WheelSpd2, where WheelSpd1 represents the compensated wheel speed of the wheel speed sensor after compensation, and WheelSpd2 represents the predicted wheel speed of the vehicle.

[0111] See also Figure 3 , Figure 3 In an exemplary embodiment of the present application, a flow chart for determining the actual wheel speed of a vehicle is shown as follows: Figure 3As shown, when the fault state of the wheel speed sensor is in a non-fault state, it is determined that the wheel speed sensor is valid, that is, the compensated wheel speed of the wheel speed sensor is accurate, and then wheel speed fusion processing is performed: the predicted wheel speed and the compensated wheel speed are calculated based on the preset third weight parameter to obtain the fused vehicle wheel speed value (actual wheel speed) of the vehicle; and when the fault state is in a fault state, it is determined that the wheel speed sensor is invalid, and the predicted wheel speed is determined as the fused vehicle wheel speed value (actual wheel speed) of the vehicle.

[0112] Optionally, the actual slip ratio of the vehicle is calculated based on the actual wheel speed, including:

[0113] Get the target wheel speed of the vehicle;

[0114] Based on the target wheel speed and the actual wheel speed, the actual slip ratio of the vehicle is calculated.

[0115] In this embodiment provided herein, the actual slip ratio calculation takes into account the environmental influence of the wheel speed sensor's environment, based on the vehicle's target wheel speed and the actual wheel speed after environmental compensation. This improves the accuracy of the calculated actual slip ratio, facilitating accurate traction control of the vehicle based on the actual slip ratio, reducing the probability of wheel slip and thereby improving vehicle driving safety. The actual slip ratio can be calculated as follows: actual slip ratio = (|actual wheel speed - target wheel speed|) / ratio of actual wheel speed.

[0116] Optionally, traction control is performed on the vehicle based on the actual slip ratio to adjust the traction of the vehicle, including:

[0117] Obtain the proportional coefficient, integral coefficient, and differential coefficient of the vehicle's PID controller;

[0118] The torque parameters of the vehicle are calculated based on the proportional coefficient, the integral coefficient, the differential coefficient and the actual slip ratio;

[0119] The torque parameter is the drive shaft torque value or the braking torque value, and the calculation formula of the torque parameter is:

[0120]

[0121] Where u(t) represents the driving shaft torque or braking torque at the tth moment, K p Represents the proportionality coefficient, K i Indicates the integral coefficient, K d represents the differential coefficient, e(t) represents the slip rate at the tth moment;

[0122] The vehicle traction is controlled according to the torque parameter to adjust the vehicle's traction.

[0123] In the embodiment provided by the present application, based on the proportional coefficient, integral coefficient and differential coefficient of the vehicle's PID controller, as well as the actual slip rate, the torque parameters required for targeted traction of the vehicle are calculated, and the vehicle is subjected to targeted traction control according to the torque parameters, so that the adjusted traction force can meet the current traction requirements of the wheels, thereby reducing the probability of wheel slippage and thus improving the safety of vehicle driving.

[0124] In this embodiment, the torque parameter is the drive shaft torque value or the braking torque value. When the vehicle is traction controlled according to the torque parameter, the driving torque of the vehicle's drive shaft is actually adjusted (generally reduced when slipping) according to the drive shaft torque value (the drive shaft torque value transmitted to the drive wheel by the engine or motor through the transmission system to drive the vehicle forward or backward), or, the wheel end braking force is applied to the slipping wheel according to the braking torque value (the torque applied to the wheel by the braking system through the brake disc or brake drum to slow down or stop the vehicle) to adjust the vehicle's traction, reduce the probability of wheel slippage, and improve vehicle driving safety.

[0125] See also Figure 4 , Figure 4 A traction control system for a vehicle is shown as an exemplary embodiment of the present application. Figure 4 As shown, the present application provides a vehicle traction control system 400, comprising:

[0126] An acquisition module 401 is used to acquire the operating conditions and operating parameters of the vehicle, as well as environmental parameters of the environment in which the vehicle's wheel speed sensor is located;

[0127] A wheel speed compensation module 402 is configured to perform wheel speed compensation on the vehicle based on operating conditions, operating parameters, and environmental parameters to obtain the actual wheel speed of the vehicle;

[0128] A calculation module 403 is configured to calculate an actual slip rate of the vehicle based on the actual wheel speed;

[0129] The traction control module 404 is configured to perform traction control on the vehicle based on the actual slip ratio to adjust the traction force of the vehicle.

[0130] The vehicle traction control system 700 of this embodiment provided by the present application first uses a wheel speed compensation module 402 to compensate for the vehicle's wheel speed based on the vehicle's operating conditions and operating parameters acquired by the acquisition module 401, as well as the environmental parameters of the vehicle's wheel speed sensor's environment, to obtain the vehicle's actual wheel speed. This reduces the impact of the wheel speed sensor's environment on the acquired actual wheel speed, thereby improving the accuracy of the actual wheel speed so that the actual wheel speed meets the wheel speed accuracy requirements under the current environment. Secondly, a calculation module 403 calculates the vehicle's actual slip rate that meets the wheel speed accuracy requirements based on the actual wheel speed that meets the wheel speed accuracy requirements. A traction control module 404 performs targeted traction control on the vehicle based on the actual slip rate that meets the wheel speed accuracy requirements, ensuring that the adjusted traction force meets the current traction requirements of the wheels, thereby reducing the probability of wheel slip and improving vehicle driving safety.

[0131] Optionally, the wheel speed compensation module is specifically configured to:

[0132] Obtaining the signal valid flag and signal change value of the operating parameter, as well as the functional status of the vehicle's integrated brake control unit;

[0133] If the signal valid flag is valid, the signal change value is less than the threshold value, and the functional state is no functional degradation, then the compensated wheel speed of the wheel speed sensor is determined based on the environmental parameters;

[0134] Perform dynamic control based on operating parameters and operating conditions to obtain the predicted wheel speed of the vehicle;

[0135] The predicted wheel speed and the compensated wheel speed are combined to obtain the actual wheel speed of the vehicle.

[0136] Optionally, the environmental parameters include temperature parameters and humidity parameters; the wheel speed compensation module is specifically used to:

[0137] Find the corresponding temperature compensation value in the preset temperature compensation table based on the temperature parameter;

[0138] Based on the humidity parameter, the corresponding humidity compensation value is found in the preset humidity compensation table;

[0139] The sum of the temperature compensation value and the humidity compensation value is determined as the environmental compensation value of the wheel speed sensor;

[0140] Obtaining a zero drift compensation value of the wheel speed sensor, and calculating the environment compensation value and the zero drift compensation value based on a preset first weight parameter to obtain a wheel speed compensation value of the wheel speed sensor;

[0141] The detected wheel speed of the wheel speed sensor is obtained, and the sum of the detected wheel speed and the wheel speed compensation value is determined as the compensated wheel speed of the wheel speed sensor.

[0142] Optionally, the wheel speed compensation module includes a weight parameter acquisition unit, which is specifically configured to:

[0143] A preset fuzzy logic algorithm is used to set multiple fuzzy logic Sugeno-type rules of the vehicle, wherein the fuzzy logic Sugeno-type rules represent the correspondence rules between the vehicle's wheel speed level and wheel speed change rate and the initial environmental compensation weight;

[0144] Get the rule triggering strength for triggering fuzzy logic Sugeno type rules;

[0145] A target environmental compensation weight for the vehicle is obtained by performing a weighted average calculation based on multiple rule triggering intensities and multiple initial environmental compensation weights;

[0146] The target zero drift compensation weight of the vehicle is calculated based on the target environment compensation weight, and the sum of the target environment compensation weight and the target zero drift compensation weight is 1;

[0147] A preset first weight parameter is formed based on the target environment compensation weight and the target zero drift compensation weight.

[0148] Optionally, the wheel speed compensation module is specifically configured to:

[0149] Calculating a first wheel speed of the vehicle under the operating condition based on the operating parameters;

[0150] Constructing a wheel dynamics model of the vehicle and using the dynamics model to calculate the operating parameters to obtain the second wheel speed of the vehicle;

[0151] Performing linear regression on the wheel dynamics model to obtain a linear regression wheel dynamics model of the vehicle, and using the linear regression wheel dynamics model to calculate the operating parameters to obtain the third wheel speed of the vehicle;

[0152] The first wheel speed, the second wheel speed, and the third wheel speed are calculated based on a preset second weight parameter to obtain a predicted wheel speed of the vehicle.

[0153] Optionally, the wheel speed compensation module is specifically configured to:

[0154] Get the fault status of the wheel speed sensor;

[0155] When the fault state is in a non-fault state, the predicted wheel speed and the compensated wheel speed are calculated based on a preset third weight parameter to obtain an actual wheel speed of the vehicle;

[0156] When the fault state is a faulty state, the predicted wheel speed is determined as the actual wheel speed of the vehicle.

[0157] Optionally, the computing module is specifically configured to:

[0158] Get the target wheel speed of the vehicle;

[0159] Based on the target wheel speed and the actual wheel speed, the actual slip ratio of the vehicle is calculated.

[0160] Optionally, the traction control module is specifically configured to:

[0161] Obtain the proportional coefficient, integral coefficient, and differential coefficient of the vehicle's PID controller;

[0162] The torque parameters of the vehicle are calculated based on the proportional coefficient, the integral coefficient, the differential coefficient and the actual slip ratio;

[0163] The vehicle traction is controlled according to the torque parameter to adjust the vehicle's traction.

[0164] It should be noted that the vehicle traction control system provided in the above-described embodiment and the vehicle traction control method provided in the above-described embodiment share the same concept. The specific manner in which the various modules and units perform their operations has been described in detail in the method embodiments and will not be repeated here. In actual applications, the vehicle traction control system provided in the above-described embodiment may, as needed, allocate the aforementioned functions to different functional modules, i.e., divide the system's internal structure into different functional modules to perform all or part of the aforementioned functions, and this is not intended to be limiting herein.

[0165] A computing device according to an embodiment of the present application includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, some or all of the steps of the above-mentioned vehicle traction control method are implemented.

[0166] Among them, the computing device can be a computer, and correspondingly, its program is computer software. The above-mentioned parameters and steps in a computing device of the present application can refer to the parameters and steps in the embodiment of a vehicle traction control method above, and will not be repeated here.

[0167] In an embodiment of the present application, a computer-readable storage medium is provided, wherein instructions are stored in the computer-readable storage medium. When the instructions are executed, the steps of the above-mentioned vehicle traction control method are executed.

[0168] The computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0169] The technical solution of the embodiments of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method of the embodiments of the present disclosure. The aforementioned computer-readable storage medium can be a non-transitory computer-readable storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program code, or a transient computer-readable storage medium.

[0170] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0171] Those skilled in the art will appreciate that the present application may be implemented as a system, method, or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "module" or "system." Furthermore, in some embodiments, the present application may also be implemented in the form of a computer program product in one or more computer-readable media, the computer-readable medium containing a computer-readable program code. Computer-readable storage media may be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination thereof.

[0172] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0173] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A vehicle traction control method, characterized in that: include: Acquiring the operating conditions and operating parameters of the vehicle, as well as environmental parameters of the environment in which the wheel speed sensor of the vehicle is located; Performing wheel speed compensation on the vehicle based on the operating condition, the operating parameter, and the environmental parameter to obtain an actual wheel speed of the vehicle; Calculating an actual slip ratio of the vehicle based on the actual wheel speed; Traction control is performed on the vehicle based on the actual slip ratio to adjust traction of the vehicle.

2. The method according to claim 1, characterized in that The performing wheel speed compensation on the vehicle based on the operating condition, the operating parameter, and the environmental parameter to obtain the actual wheel speed of the vehicle includes: Acquiring a signal valid flag and a signal change value of the operating parameter, and a functional state of an integrated brake control unit of the vehicle; If the signal valid flag is valid, the signal change value is less than a threshold, and the functional state is no functional degradation, determining the compensated wheel speed of the wheel speed sensor based on the environmental parameter; performing dynamic control based on the operating parameters and the operating conditions to obtain a predicted wheel speed of the vehicle; The predicted wheel speed and the compensated wheel speed are combined to obtain the actual wheel speed of the vehicle.

3. The method according to claim 2, characterized in that The environmental parameters include a temperature parameter and a humidity parameter; and determining the compensated wheel speed of the wheel speed sensor based on the environmental parameters includes: Finding a corresponding temperature compensation value in a preset temperature compensation table based on the temperature parameter; Based on the humidity parameter, a corresponding humidity compensation value is searched in a preset humidity compensation table; determining a sum of the temperature compensation value and the humidity compensation value as an environmental compensation value of the wheel speed sensor; Acquiring a zero drift compensation value of the wheel speed sensor, and calculating the environment compensation value and the zero drift compensation value based on a preset first weight parameter to obtain a wheel speed compensation value of the wheel speed sensor; A detected wheel speed of the wheel speed sensor is acquired, and a sum of the detected wheel speed and the wheel speed compensation value is determined as the compensated wheel speed of the wheel speed sensor.

4. The method according to claim 3, characterized in that The method for obtaining the preset first weight parameter is as follows: Setting a plurality of fuzzy logic Sugeno-type rules for the vehicle using a preset fuzzy logic algorithm, wherein the fuzzy logic Sugeno-type rules represent a correspondence rule between the wheel speed level and the wheel speed change rate of the vehicle and an initial environmental compensation weight; Obtaining a rule triggering strength for triggering the fuzzy logic Sugeno-type rule; Performing a weighted average calculation based on the plurality of rule triggering intensities and the plurality of initial environment compensation weights to obtain a target environment compensation weight for the vehicle; Calculating a target zero drift compensation weight for the vehicle based on the target environment compensation weight, wherein the sum of the target environment compensation weight and the target zero drift compensation weight is 1; A preset first weight parameter is formed based on the target environment compensation weight and the target zero drift compensation weight.

5. The method according to claim 2, characterized in that The performing dynamic control based on the operating parameters and the operating conditions to obtain the predicted wheel speed of the vehicle includes: calculating a first wheel speed of the vehicle under the operating condition based on the operating parameters; constructing a wheel dynamics model of the vehicle, and calculating the operating parameters using the dynamics model to obtain a second wheel speed of the vehicle; performing a linear regression on the wheel dynamics model to obtain a linear regression wheel dynamics model of the vehicle, and calculating the operating parameter using the linear regression wheel dynamics model to obtain a third wheel speed of the vehicle; The first wheel speed, the second wheel speed, and the third wheel speed are calculated based on a preset second weight parameter to obtain a predicted wheel speed of the vehicle.

6. The method according to claim 2, characterized in that The step of fusing the predicted wheel speed and the compensated wheel speed to obtain the actual wheel speed of the vehicle includes: obtaining a fault status of the wheel speed sensor; When the fault state is in a non-fault state, calculating the predicted wheel speed and the compensated wheel speed based on a preset third weight parameter to obtain an actual wheel speed of the vehicle; When the fault state is a faulty state, the predicted wheel speed is determined as the actual wheel speed of the vehicle.

7. The method according to any one of claims 1 to 6, characterized in that The calculating the actual slip rate of the vehicle based on the actual wheel speed includes: Obtaining a target wheel speed of the vehicle; An actual slip ratio of the vehicle is calculated based on the target wheel speed and the actual wheel speed.

8. The method according to any one of claims 1 to 6, characterized in that The performing traction control on the vehicle based on the actual slip ratio to adjust the traction force of the vehicle includes: Obtaining a proportional coefficient, an integral coefficient, and a differential coefficient of a PID controller of the vehicle; Calculating a torque parameter of the vehicle based on the proportional coefficient, the integral coefficient, the differential coefficient, and the actual slip ratio; Traction control is performed on the vehicle according to the torque parameter to adjust the traction force of the vehicle.

9. A vehicle traction control system, characterized in that: include: An acquisition module, configured to acquire the operating conditions and operating parameters of the vehicle, and environmental parameters of the environment in which the wheel speed sensor of the vehicle is located; a wheel speed compensation module, configured to perform wheel speed compensation on the vehicle based on the operating condition, the operating parameters, and the environmental parameters to obtain an actual wheel speed of the vehicle; a calculation module, configured to calculate an actual slip rate of the vehicle based on the actual wheel speed; A traction control module is configured to perform traction control on the vehicle based on the actual slip ratio to adjust the traction force of the vehicle.

10. A computing device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of the vehicle traction control method according to any one of claims 1 to 8 are implemented.

Images