Electronic traction force control method and device of range-extender tractor and storage medium

Abstract

The application discloses a kind of electronic traction control method, device and storage medium of range-extending tractor in the technical field of agricultural tractor, method includes: according to first positioning speed, second travel speed, third estimated speed and fourth motor speed, final output vehicle speed is calculated;According to final output vehicle speed and the wheel speed of four wheels, the actual slip rate of four wheels is calculated;Based on the current road adhesion coefficient obtained in real time and the road μ-λ characteristic database pre-constructed, the best slip rate of four wheels is obtained;Based on the best slip rate and actual slip rate, slip rate difference and slip rate difference change rate are calculated;When the actual slip rate is less than the preset minimum slip rate, the driver demand torque is output;When the slip rate difference change rate exceeds the preset change rate threshold, the correction torque output by fuzzy PID control architecture is output.The application can solve the technical problem of working condition limitation caused by dependence on tillage depth adjustment in the prior art.

Description

Technical Field

[0001] This invention relates to the field of agricultural tractor technology, and in particular to an electronic traction control method, device and storage medium for a range-extended tractor. Background Technology

[0002] Electronic traction control is a key technology for improving the efficiency and quality of agricultural machinery operations. Currently, most tractors in China still use mechanical differential locks or rely on manual intervention of electronic traction based on driver experience. These traditional methods are difficult to adapt to complex working conditions such as slippery fields and loose, uneven soil, which can easily lead to problems such as excessive slippage of the drive wheels, sinking, or even getting stuck. This not only reduces operating efficiency but also causes soil compaction, affecting crop growth.

[0003] Furthermore, existing technologies also involve adjusting tillage depth by controlling the hydraulic suspension to change the working resistance of the tractor unit, thereby controlling the slip rate of the tractor drive wheels and ultimately optimizing traction efficiency and preventing drive slippage. However, this method has potential negative impacts on the quality of specific operational processes. 1) In heavy-duty operations such as plowing and deep loosening, where the stability and consistency of tillage depth are extremely important, tillage depth is a core technological indicator for ensuring operational quality. This control strategy, which frequently adjusts tillage depth to control slippage rate, may lead to uneven tillage depth in the field, resulting in some areas being under-tilled while others are over-tilled. This unevenness directly affects the quality of seedbed preparation, leading to inconsistent soil conditions, which in turn affects the uniformity of subsequent crop emergence and growth, making it difficult to meet the high quality requirements of precision agriculture. Therefore, the application of this strategy in quality-sensitive operations is significantly limited.

[0004] 2) Risk of functional failure under low load conditions: When the tractor is carrying a light load, or when its working resistance varies little (e.g., when attaching a trailer or spraying pesticides), adjusting the tillage depth has a negligible impact on the overall traction resistance, rendering the control system ineffective. In this situation, no matter how optimized the control algorithm is, it cannot generate sufficient resistance changes through tillage depth adjustment to effectively control the slip ratio, leading to the near failure of traction efficiency optimization and drive anti-skid functions.

[0005] Therefore, there is an urgent need for an electronic traction control method, device, and storage medium for range-extended tractors to solve the above-mentioned technical problems. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide an electronic traction control method, device and storage medium for range-extended tractors, which can solve the technical problem of the working condition limitation caused by the reliance on tillage depth adjustment in the prior art.

[0007] To achieve the above objectives, the present invention is implemented using the following technical solution: In a first aspect, the present invention provides an electronic traction control method for a range-extended tractor, comprising: The system acquires the first positioning speed, second travel speed, third estimated speed, fourth motor speed, wheel speed of the four wheels, and slippage status of the range-extended tractor. The final output vehicle speed is calculated based on the first positioning speed, the second driving speed, the third estimated speed, and the fourth motor speed. The actual slip ratio of the four wheels is calculated based on the final output vehicle speed and the wheel speed of the four wheels. Based on the real-time acquired current road surface adhesion coefficient and the pre-built road surface μ-λ characteristic database, the optimal slip ratio of the four wheels is obtained; Based on the optimal slip ratio and the actual slip ratio, calculate the slip ratio difference and the rate of change of the slip ratio difference; When at least one wheel is determined to be slipping, and the slippage lasts for more than a preset safe time, while the vehicle is traveling in a straight line or the steering wheel angle is within 2°, the differential lock is engaged. After the front axle differential lock and rear axle differential lock are engaged, if any of the following conditions occur: the actual slip ratio still exceeds the safety threshold, the system determines that the condition is a double-sided slipping condition, or the differential lock activation conditions are no longer met, adjustments will be made based on the actual slip ratio: When the actual slip ratios are all less than the preset minimum slip ratio, the low slip ratio strategy is entered, and the torque required by the driver is output. When the rate of change of the slip ratio difference exceeds the preset rate of change threshold, the slip ratio strategy is entered, and the corrected torque is output through the fuzzy PID control architecture.

[0008] Furthermore, obtaining the vehicle's third estimated speed includes: When the wheel speeds of all four wheels are less than or equal to a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If none of the four wheels slip, the minimum value between the average front wheel speed and the average rear wheel speed is taken as the initial speed estimate; If at least one of the four wheels slips, the wheel speeds of the four wheels are sorted by size to obtain the maximum wheel speed, the second largest wheel speed, the second smallest wheel speed, and the minimum wheel speed. When the vehicle is under braking, the average of the maximum wheel speed and the second largest wheel speed is taken as the initial estimated speed. When the vehicle is not under braking, the average of the second smallest wheel speed and the minimum wheel speed is taken as the initial estimated speed. When the wheel speed of one or two of the wheels exceeds a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If at least one of the four wheels slips, the minimum of the remaining normal wheel speeds is taken as the initial estimated speed. If none of the four wheels slips, the average of the remaining normal wheel speeds is taken as the initial estimated speed. The normal wheel speed is a wheel speed that is greater than or equal to a preset minimum wheel speed threshold and less than or equal to a maximum wheel speed threshold. When at least three wheels have wheel speeds greater than a preset maximum wheel speed threshold, the current wheel speed is not used to calculate the third estimated speed. The preliminary estimated velocity at the current moment and the longitudinal acceleration collected in real time are input into the pre-built state prediction model to obtain the third estimated velocity at the current moment; The pre-built state prediction model includes a process model and an observation model: The expression for the process model is: , The expression for the observation model is: , , in, For the present The system state variables at time t. for The longitudinal speed of the vehicle at any given moment. for The longitudinal acceleration of the entire vehicle at any given moment. Here is the state transition matrix. for Time-based process noise, for The observed variables at each time point include the preliminary estimated velocity and IMU longitudinal acceleration. For the observation matrix, for Measurement noise at specific times; Recursive filtering is performed. Before obtaining the vehicle's longitudinal speed and acceleration at the current moment, prediction is made based on the model. The prediction equation is expressed as follows: , , After obtaining the vehicle's longitudinal speed and longitudinal acceleration at the current moment, the model is updated, and the update equation is expressed as follows: , , , , in, Let be the prior state estimate at time k. for Post-hoc state estimate at time step [time]. for The prior estimate of covariance at time t, for The posterior estimate of the covariance at time t. This is the transpose of the state transition matrix. For the process excitation noise covariance, for Kalman gain at time step For the transpose of the observation matrix, To measure the noise covariance matrix, for The posterior state estimate at time t. for The posterior estimate of the covariance at time t. It is the identity matrix. For the updated The longitudinal acceleration of the entire vehicle at any given moment. This is the third estimated speed.

[0009] Furthermore, the expression for obtaining the speed of the fourth motor includes: , in, The speed of the fourth motor. This refers to the motor speed. The tire's rolling radius, The gear ratio of the gearbox. This represents the overall reduction ratio.

[0010] Furthermore, the final output vehicle speed is calculated based on the first positioning speed, the second driving speed, the third estimated speed, and the fourth motor speed. The expression includes: + + , , , in, This represents the final output vehicle speed. This is represented as the first positioning speed. This is indicated as the second driving speed. This is represented as the third estimated velocity. This is represented as the speed of the fourth motor. Represented as the first Confidence level Represented as the first Signal quality factor Represented as the first Model consistency factor Represented as the first Sensor state factor Represented as the first Signal quality factor Represented as the first Model consistency factor Represented as the first Sensor state factors.

[0011] Furthermore, when the rate of change of the slip ratio difference exceeds a preset rate of change threshold, the corrected torque output through the fuzzy PID control architecture includes: The inputs of the fuzzy PID control architecture include the slip ratio difference and the slip ratio difference change rate. The slip ratio difference and the slip ratio difference change rate are mapped to the fuzzy domain of the first fuzzy subset. The proportional coefficient and integral coefficient are mapped to the fuzzy domain of the second fuzzy subset through the fuzzy rule base. The actual torque correction value is obtained by defuzzifying the fuzzy domain using the centroid method. The torque correction value is added to the torque required by the driver to obtain the corrected torque, thereby realizing the adaptive adjustment of the wheel slip ratio.

[0012] Furthermore, the expression for obtaining the current road surface adhesion coefficient includes: , , , , , , in, The current road surface adhesion coefficient, This refers to the longitudinal adhesion of the tire. For the load on the tires, It's the motor torque. It is the braking torque. It is the moment of inertia of the tire. It is the first derivative of the wheel angular acceleration. It is the wheel radius. The load on the front left tire. This refers to the load on the front right tire. For the load on the rear left tire, For the load on the rear right tire, For the overall vehicle quality, It is the acceleration due to gravity. This refers to the wheelbase of the entire vehicle. It is the distance from the center of gravity of the structure above the suspension to the front axle of the vehicle. This is the distance from the center of gravity of the upper structure of the suspension to the rear axle. For the front wheel track, The rear wheel track. This refers to the height of the vehicle's center of gravity. For longitudinal acceleration, This is lateral acceleration.

[0013] Furthermore, it also includes: If, after the torque adjustment, the rate of change of the slip ratio difference still exceeds the preset rate of change threshold, a high slip ratio strategy is entered: the torque is output based on the preset proportional coefficient. The low slip rate strategy, medium slip rate strategy and high slip rate strategy are smoothly transitioned through a fuzzy weighted algorithm, and the weight coefficients in the fuzzy weighted algorithm are calculated in real time based on the slip rate and its rate of change.

[0014] Secondly, the present invention provides an electronic traction control device for a range-extended tractor, comprising: The speed acquisition module is used to acquire the first positioning speed, the second travel speed, the third estimated speed, the fourth motor speed, the wheel speed of the four wheels, and the slippage status of the range-extended tractor. The output vehicle speed calculation module is used to calculate the final output vehicle speed based on the first positioning speed, the second driving speed, the third estimated speed, and the fourth motor speed. The actual slip ratio calculation module is used to calculate the actual slip ratio of the four wheels based on the final output vehicle speed and the wheel speed of the four wheels; The optimal slip ratio acquisition module is used to obtain the optimal slip ratio of the four wheels based on the real-time acquired current road surface adhesion coefficient and the pre-built road surface μ-λ characteristic database. The module for calculating the slip ratio difference and the rate of change of the slip ratio difference is used to calculate the slip ratio difference and the rate of change of the slip ratio difference based on the optimal slip ratio and the actual slip ratio. The automatic differential lock control module is used to lock the differential lock when at least one wheel is determined to be slipping for more than a preset safe time, and the vehicle is traveling in a straight line or the steering wheel angle is within 2°. The lower-level driving torque control module is used to adjust based on the actual slip rate after the front axle differential lock and rear axle differential lock are engaged, provided that the actual slip rate still exceeds the safety threshold, the system determines that the slip condition is a double-sided slip condition, or the differential lock activation conditions are no longer met. When the actual slip rate is less than the preset minimum slip rate, a low slip rate strategy is entered, outputting the torque required by the driver. When the rate of change of the slip rate difference exceeds the preset rate of change threshold, a medium slip rate strategy is entered, outputting the corrected torque output through the fuzzy PID control architecture. Furthermore, it also includes: Four wheel speed sensors, installed inside the front and rear drive axles of the vehicle, are used to obtain the wheel speed of the four wheels. An IMU installed at the vehicle's center of gravity is used to collect the vehicle's longitudinal acceleration, lateral acceleration, and yaw rate. A ground-viewing radar installed in the middle of the vehicle chassis, facing the ground, is used to directly measure the vehicle's second speed relative to the ground. The front wheel differential lock, installed at the front axle main reducer of the vehicle, is used to automatically lock the front wheels, thereby actively distributing the driving torque to the wheels on both sides of the same axle. The rear wheel differential lock, installed at the rear axle main reducer of the vehicle, is used to automatically lock the front wheels, thereby actively distributing the driving torque to the wheels on both sides of the same axle. A GNSS receiver mounted on the roof of the vehicle is used to directly measure the vehicle's first positioning speed. The front wheel steering angle sensor, installed at the front axle steering knuckle, is used to monitor the yaw rate of the steering wheel in real time and determine whether the vehicle is currently driving in a straight line or turning. A steering wheel angle sensor mounted on the steering column is used to detect the driver's steering wheel angle in real time; and The electronic traction controller is used to ultimately send drive torque correction commands to the lower-level motor.

[0015] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0016] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: This invention first proposes an electronic traction control method for range-extended tractors. By changing the core indicator of traction control from the traditional load parameter to the slip ratio parameter, it breaks through the dependence of existing technologies on specific operating modes. Based on real-time slip ratio monitoring and road surface recognition technology, the system can automatically adapt to all operating scenarios, from heavy-load plowing to light-load transportation. It can maintain optimal slip ratio control on road surfaces with different adhesion coefficients, such as dry hard fields, muddy fields, and asphalt roads, effectively solving the problem of operating condition limitations caused by existing technologies relying on tillage depth adjustment. Enhancing the reliability of the control system under complex operating conditions: By employing a vehicle speed estimation method that dynamically weights and fuses multi-source information, combined with real-time sensor status monitoring and fault diagnosis mechanisms, the system's reliability under abnormal operating conditions such as sensor failure and signal interference is significantly improved. Even if some sensors fail, the system can still provide reliable vehicle speed estimates through the remaining normal sensors, ensuring the continuous and effective operation of the traction control function.

[0017] A hierarchical strategy combining differential lock control and torque control is adopted. This strategy effectively solves the efficiency loss caused by unilateral slippage through differential lock, while three-level torque control precisely suppresses unilateral slippage. Furthermore, a fuzzy weighted algorithm is used to achieve a smooth transition between control strategies, overcoming the torque abrupt change problem when switching between traditional control methods. Attached Figure Description

[0018] Figure 1 This is a flowchart of an electronic traction control method for a range-extended tractor provided in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the principle of the adaptive interference noise cancellation algorithm provided in this embodiment of the invention; Figure 3 This is a schematic diagram of the impulse-type grain flow sensor provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the workflow of the yield measurement system for a high-impact grain combine harvester; Figure 5 This is a schematic diagram illustrating the principle of the adaptive interference noise cancellation algorithm; The components include: 1. Wheel speed sensor; 2. IMU; 3. Ground radar; 4. Front wheel differential lock; 5. Rear wheel differential lock; 6. GNSS receiver; 7. Front wheel angle sensor; 8. Steering wheel angle sensor; and 9. Electronic traction controller. Detailed Implementation

[0019] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0020] In this invention, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B together, or B alone. Additionally, in this invention, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Example 1

[0021] Figure 1 This is a flowchart of the electronic traction control method for a range-extended tractor according to Embodiment 1 of the present invention. This flowchart merely illustrates the logical sequence of the method described in this embodiment. Without conflict, in other possible embodiments of the present invention, different methods may be used. Figure 1 Complete the steps shown or described in the order indicated.

[0022] The electronic traction control method for range-extended tractors provided in this embodiment can be applied to a terminal and can be executed by a mechanical equipment fault identification device. This device can be implemented in software and / or hardware and can be integrated into the terminal, such as any smartphone, tablet, or computer device with communication capabilities. The method in this embodiment specifically includes the following steps: Step 1: Obtain the first positioning speed, second travel speed, third estimated speed, fourth motor speed, wheel speed of the four wheels, and slippage status of the range-extended tractor; Specifically, a GNSS receiver, such as GPS or BeiDou, installed on the tractor can be used to obtain the vehicle's current first positioning speed by employing real-time dynamic carrier phase differential technology with a fixed ground reference station. The ground-based radar is controlled to transmit radar waves to the ground through the Doppler effect. Since the vehicle is moving, the frequency of the reflected radar waves will change. By measuring the frequency difference between the transmitted and received waves, the vehicle's second speed relative to the ground can be directly calculated. Four sensors installed inside the front and rear drive axles of the vehicle are used to detect the wheel speed and slippage status of the four wheels in a non-contact manner using the high-precision Hall effect principle. The single-sided slippage status can be the wheel status when a continuous wheel speed difference is detected between the two wheels on the same axle, and the wheel speed difference exceeds a threshold and the duration exceeds a timeout. Obtaining the vehicle's third estimated speed includes: When the wheel speeds of all four wheels are less than or equal to a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If none of the four wheels slip, the minimum value between the average front wheel speed and the average rear wheel speed is taken as the initial speed estimate; If at least one of the four wheels slips, the wheel speeds of the four wheels are sorted by size to obtain the maximum wheel speed, the second largest wheel speed, the second smallest wheel speed, and the minimum wheel speed. When the vehicle is under braking, the average of the maximum wheel speed and the second largest wheel speed is taken as the initial estimated speed. When the vehicle is not under braking, the average of the second smallest wheel speed and the minimum wheel speed is taken as the initial estimated speed. When the wheel speed of one or two of the wheels exceeds a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If at least one of the four wheels slips, the minimum of the remaining normal wheel speeds is taken as the initial estimated speed. If none of the four wheels slips, the average of the remaining normal wheel speeds is taken as the initial estimated speed. The normal wheel speed is a wheel speed that is greater than or equal to a preset minimum wheel speed threshold and less than or equal to a maximum wheel speed threshold. When at least three wheels have wheel speeds exceeding a preset maximum wheel speed threshold, the third estimated speed is not calculated using the current wheel speeds, indicating that the system lacks reliable wheel speed signals. The final calculated wheel speed values ​​are then subjected to Kalman filtering, and vehicle dynamics constraints are applied in conjunction with longitudinal acceleration measured by the IMU to obtain a preliminary optimized vehicle speed value. The specific method for Kalman filtering under vehicle dynamics constraints is as follows: The preliminary estimated velocity at the current moment and the longitudinal acceleration collected in real time are input into the pre-built state prediction model to obtain the third estimated velocity at the current moment; The pre-built state prediction model includes a process model and an observation model: The expression for the process model is: , The expression for the observation model is: , , in, For the present The system state variables at time t. for The longitudinal speed of the vehicle at any given moment. for The longitudinal acceleration of the entire vehicle at any given moment. Here is the state transition matrix. for Time-based process noise, for The observed variables at each time point include the preliminary estimated velocity and IMU longitudinal acceleration. For the observation matrix, for Measurement noise at specific times; Recursive filtering is performed. Before obtaining the vehicle's longitudinal speed and acceleration at the current moment, prediction is made based on the model. The prediction equation is expressed as follows: , , After obtaining the vehicle's longitudinal speed and longitudinal acceleration at the current moment, the model is updated, and the update equation is expressed as follows: , , , , in, Let be the prior state estimate at time k. for Post-hoc state estimate at time step [time]. for The prior estimate of covariance at time t, for The posterior estimate of the covariance at time t. This is the transpose of the state transition matrix. For the process excitation noise covariance, for Kalman gain at time step For the transpose of the observation matrix, To measure the noise covariance matrix, for The posterior state estimate at time t. for The posterior estimate of the covariance at time t. It is the identity matrix. For the updated The longitudinal acceleration of the entire vehicle at any given moment. The third estimated speed, i.e., attached Figure 3 Kalman's speed in the middle.

[0023] The expressions for obtaining the speed of the fourth motor include: ; in, The speed of the fourth motor. This refers to the motor speed. The tire's rolling radius, The gear ratio of the gearbox. This represents the overall reduction ratio.

[0024] Step Two: Calculate the final output vehicle speed based on the first positioning speed, the second driving speed, the third estimated speed, and the fourth motor speed. The expression includes: + + , , , in, This represents the final output vehicle speed. This is represented as the first positioning speed. This is indicated as the second driving speed. This is represented as the third estimated velocity. This is represented as the speed of the fourth motor. Represented as the first Confidence level Represented as the first Signal quality factor Represented as the first Model consistency factor Represented as the first Sensor state factor Represented as the first Signal quality factor Represented as the first Model consistency factor Represented as the first Sensor state factors.

[0025] The confidence level depends on three factors: Signal quality factor It is used to check the physical rationality (whether it is within a reasonable range), noise level and rate of change continuity of each model source signal; Model consistency factor This is used to calculate the deviation of the model's estimate from the average of all other model estimates. The smaller the deviation, the higher the consistency, and the greater the weight. Sensor state factor This is used to reduce the weights of models that rely on this sensor; The three factors can be updated in real time as the model is monitored during operation. The specific update process is existing technology and will not be elaborated here.

[0026] The overall process for steps one and two can be found in the appendix. Figure 3 The flowchart shown is for calculating the final output speed.

[0027] Step 3: Calculate the actual slip ratio of the four wheels based on the final output vehicle speed and the wheel speeds of the four wheels. The expression is: , in, Expressed as actual slip ratio, This refers to the wheel speed.

[0028] Step 4: Based on the real-time acquired current road surface adhesion coefficient and the pre-built road surface μ-λ characteristic database, obtain the optimal slip ratio for the four wheels; Specifically, the determination of the optimal slip ratio is based on a matching mechanism between real-time road surface adhesion coefficient identification and a preset database. First, in the preliminary experimental phase, data such as wheel speed, vehicle speed, and driving torque are collected when vehicles travel on various typical road surfaces (including but not limited to dry asphalt, wet asphalt, dry hard fields, muddy fields, snow, and ice). Based on this, adhesion coefficient-slip ratio relationship curves for different road surfaces are plotted, and the optimal slip ratio corresponding to the peak point of each curve is extracted, thus establishing an optimal slip ratio reference database with the road surface adhesion coefficient as the key index. The calculated current road surface adhesion coefficient is matched with the preset typical road surface μ-λ characteristic database to retrieve the corresponding optimal slip ratio.

[0029] In addition, current methods for obtaining the road surface adhesion coefficient include: , , , , , , in, The current road surface adhesion coefficient, This refers to the longitudinal adhesion of the tire. For the load on the tires, It's the motor torque. It is the braking torque. It is the moment of inertia of the tire. It is the first derivative of the wheel angular acceleration, which can be calculated from the wheel speed. It is the wheel radius. The load on the front left tire. This refers to the load on the front right tire. For the load on the rear left tire, For the load on the rear right tire, For the overall vehicle quality, It is the acceleration due to gravity. This refers to the wheelbase of the entire vehicle. It is the distance from the center of gravity of the structure above the suspension to the front axle of the vehicle. This is the distance from the center of gravity of the upper structure of the suspension to the rear axle. For the front wheel track, The rear wheel track. This refers to the height of the vehicle's center of gravity. For longitudinal acceleration, This is lateral acceleration.

[0030] Step 4: Based on the optimal slip ratio and the actual slip ratio, calculate the slip ratio difference and the rate of change of the slip ratio difference.

[0031] Step 5: When at least one wheel is determined to be slipping, and the duration exceeds the preset safe time, while the vehicle is traveling in a straight line or the steering wheel angle is within 2°, the differential lock is engaged. Specifically, the vehicle can be judged as being in a straight line or slightly turning state based on the steering wheel angle and yaw rate. Slight turning state refers to a steering wheel angle within 2°. The specific judgment method is conventional existing technology and will not be elaborated here.

[0032] Step Six: After the front and rear axle differential locks are engaged, if any of the following conditions occur: the actual slip ratio still exceeds the safety threshold, the system determines it to be a double-sided slip condition, or the differential lock activation conditions are no longer met, the system automatically switches to the lower-level driving torque control strategy. This lower-level driving torque control strategy implements three levels of adjustment based on the actual slip ratio level, such as... Figure 4 As shown: When the actual slip ratios are all less than the preset minimum slip ratio, the low slip ratio strategy is entered: output the torque required by the driver and do not process it. When the rate of change of the slip ratio difference exceeds a preset rate of change threshold (in this embodiment, the rate of change threshold can be 0.2), a medium slip ratio strategy is entered, such as... Figure 5 As shown: the output is the corrected torque after passing through the fuzzy PID control architecture, and the output corrected torque is limited within the dynamic safety threshold.

[0033] The inputs of the fuzzy PID control architecture include the slip ratio difference and the slip ratio difference change rate. The slip ratio difference and the slip ratio difference change rate are mapped to the fuzzy domain of the first fuzzy subset. The proportional coefficient KP and integral coefficient KI are mapped to the fuzzy domain of the second fuzzy subset through the fuzzy rule base. The actual torque correction value is obtained by defuzzifying the fuzzy domain using the centroid method. The torque correction value is added to the torque required by the driver to obtain the corrected torque, thereby realizing the adaptive adjustment of the wheel slip ratio.

[0034] In this embodiment, the first fuzzy subset can be {NB, NS, ZO, PS, PB}, the second fuzzy subset can be {ZO, S, M, B, VB}, and the fuzzy rule base includes: IF e is NB AND ec is NB THEN KP is VB AND KI is B; IF e is NB AND ec is NS THEN KP is B AND KI is M; IF e is NB AND ec is ZO THEN KP is S AND KI is M; IF e is NB AND ec is PS THEN KP is B AND KI is M; IF e is NB AND ec is PB THEN KP is VB AND KI is ZO; IF e is NS AND ec is NB THEN KP is M AND KI is B; IF e is NS AND ec is NS THEN KP is S AND KI is M; IF e is NS AND ec is ZO THEN KP is S AND KI is M; IF e is NS AND ec is PS THEN KP is M AND KI is M; IF e is NS AND ec is PB THEN KP is B AND KI is ZO; IF e is ZO AND ec is NB THEN KP is S AND KI is S; IF e is ZO AND ec is NS THEN KP is S AND KI is M; IF e is ZO AND ec is ZO THEN KP is ZO AND KI is M; IF e is ZO AND ec is PS THEN KP is S AND KI is M; IF e is ZO AND ec is PB THEN KP is M AND KI is ZO; IF e is PS AND ec is NB THEN KP is B AND KI is B; IF e is PS AND ec is NS THEN KP is M AND KI is M; IF e is PS AND ec is ZO THEN KP is S AND KI is M; IF e is PS AND ec is PS THEN KP is M AND KI is S; IF e is PS AND ec is PB THEN KP is B AND KI is ZO; IF e is PB AND ec is NB THEN KP is VB AND KI is VB; IF e is PB AND ec is NS THEN KP is B AND KI is B; IF e is PB AND ec is ZO THEN KP is M AND KI is M; IF e is PB AND ec is PS THEN KP is B AND KI is ZO; IF e is PB AND ec is PB THEN KP is VB AND KI is ZO; Among them, NB stands for Negative-Big, NS stands for Negative-Small, ZO stands for Zero, PS stands for Positive-Small, PB stands for Positive-Big, S stands for Small, M stands for Medium, B stands for Big, and VB stands for Very-Big. e represents the slip ratio difference, and ec represents the rate of change of the slip ratio difference.

[0035] If, after the torque correction adjustment, the rate of change of the slip ratio difference still exceeds the preset rate of change threshold, the high slip ratio strategy is entered: at this time, the torque is output based on the preset proportional coefficient. The low slip rate strategy, medium slip rate strategy and high slip rate strategy are smoothly transitioned through a fuzzy weighted algorithm, and the weight coefficients in the fuzzy weighted algorithm are calculated in real time based on the slip rate and its rate of change.

[0036] Example 2: Embodiment 2 of the present invention provides an electronic traction control device for a range-extended tractor, comprising: The speed acquisition module is used to acquire the first positioning speed, the second driving speed, the third estimated speed, the fourth motor speed, the wheel speed of the four wheels, and the slippage status. The output vehicle speed calculation module is used to calculate the final output vehicle speed based on the first positioning speed, the second driving speed, the third estimated speed, and the fourth motor speed. The actual slip ratio calculation module is used to calculate the actual slip ratio of the four wheels based on the final output vehicle speed and the wheel speed of the four wheels; The optimal slip ratio acquisition module is used to obtain the optimal slip ratio of the four wheels based on the real-time acquired current road surface adhesion coefficient and the pre-built road surface μ-λ characteristic database. The module for calculating the slip ratio difference and the rate of change of the slip ratio difference is used to calculate the slip ratio difference and the rate of change of the slip ratio difference based on the optimal slip ratio and the actual slip ratio. The automatic differential lock control module is used to lock the differential lock when at least one wheel is determined to be slipping for more than a preset safe time, and the vehicle is traveling in a straight line or the steering wheel angle is within 2°. The lower-level driving torque control module is used to adjust based on the actual slip rate after the front axle differential lock and rear axle differential lock are engaged, provided that the actual slip rate still exceeds the safety threshold, the system determines that the slip condition is a double-sided slip condition, or the differential lock activation conditions are no longer met. When the actual slip rate is less than the preset minimum slip rate, a low slip rate strategy is entered, outputting the torque required by the driver. When the rate of change of the slip rate difference exceeds the preset rate of change threshold, a medium slip rate strategy is entered, outputting the corrected torque output through the fuzzy PID control architecture.

[0037] In addition, such as Figure 2 As shown, it also includes: Four wheel speed sensors 1, installed inside the front and rear drive axles of the vehicle, are used to obtain the wheel speed of the four wheels in a non-contact manner using the high-precision Hall effect principle. The IMU2 (Inertial Measurement Unit) installed at the vehicle's center of gravity is a conventional existing technology and will not be described in detail here. It uses three-axis MEMS technology to collect longitudinal acceleration, lateral acceleration and yaw rate of the vehicle body at high frequency. The ground-targeting radar 3, installed in the center of the vehicle chassis and facing the ground, is based on the Doppler effect principle. It transmits and receives radar waves to directly measure the vehicle's second speed relative to the ground (i.e., the speed of the vehicle's second speed relative to the ground). Figure 3 (Radar vehicle speed in the system), the speed information provided by this sensor is unaffected by wheel slippage, providing the system with a highly reliable independent vehicle speed reference benchmark; The front wheel differential lock 4, installed at the front axle main reducer of the vehicle, is an electromagnetically controlled proportional valve type differential lock device used to realize the automatic locking of the front wheels, thereby actively distributing the driving torque of the wheels on both sides of the same axle. It is one of the core actuators to suppress slippage of one side of the wheel. The rear wheel differential lock 5, installed at the rear axle main reducer of the vehicle, is an electromagnetically controlled proportional valve type differential lock device used to realize the automatic locking of the rear wheels, thereby actively distributing the driving torque of the wheels on both sides of the same axle. It is one of the core actuators to suppress slippage of one side of the wheel. The GNSS receiver 6, mounted on the vehicle roof, communicates with fixed ground reference stations or network RTK services. Employing real-time dynamic carrier phase differential technology, it provides centimeter-level accuracy in the vehicle's absolute position and time. Through position differential calculation, it directly measures the vehicle's first positioning velocity (i.e., the attached velocity). Figure 3 The navigation vehicle speed (in the system) serves as the highest-level vehicle speed verification and calibration source for the system. The front wheel steering angle sensor 7, installed at the front axle steering knuckle, is used to monitor the yaw rate of the steering wheel in real time with high precision, and to determine whether the vehicle is currently in a straight-line driving or steering condition. It is one of the key decision inputs for whether the upper differential lock control strategy intervenes. The steering wheel angle sensor 8, mounted on the steering column, detects the driver's steering wheel angle in real time, accurately determines the driver's steering intention, and provides forward-looking information for the pre-intervention or pre-disengagement of the differential lock, preventing tire wear and steering performance degradation caused by locking the differential during steering; and The electronic traction controller 9 receives signals from all sensing units in real time via the CAN bus. Internally, it runs a multi-source information fusion algorithm and a hierarchical intelligent control strategy. It first calculates the optimal estimated vehicle speed and real-time road adhesion coefficient based on the fusion of multi-source information such as wheel speed, radar, GNSS, and IMU2. Then, the upper-level decision-maker determines whether to activate differential lock control or directly switch to torque control, and finally sends precise drive torque correction commands to the lower-level motor.

[0038] The electronic traction control device for the range-extended tractor provided in Embodiment 2 of the present invention can execute the electronic traction control method for the range-extended tractor provided in Embodiment 1 of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0039] Example 3: Embodiment 3 of the present invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the method described in Embodiment 1, and has the corresponding functional modules and beneficial effects of the method.

[0040] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0041] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0042] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0043] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0044] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An electronic traction control method for a range-extended tractor, characterized in that, include: The first positioning speed of the vehicle is measured by a GNSS receiver (6) installed on the roof of the vehicle; the second driving speed of the vehicle relative to the ground is measured by a ground radar (3) installed in the middle of the vehicle chassis facing the ground. Obtain the vehicle's third estimated speed, fourth motor speed, wheel speeds of all four wheels, and slippage status; Obtaining the vehicle's third estimated speed includes: When the wheel speeds of all four wheels are less than or equal to a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If none of the four wheels slip, the minimum value between the average front wheel speed and the average rear wheel speed is taken as the initial speed estimate; If at least one of the four wheels slips, the wheel speeds of the four wheels are sorted by size to obtain the maximum wheel speed, the second largest wheel speed, the second smallest wheel speed, and the minimum wheel speed. When the vehicle is in a braking state, the average of the maximum wheel speed and the second largest wheel speed is taken as the initial estimated speed. When the vehicle is in a non-braking state, the average of the second smallest wheel speed and the minimum wheel speed is taken as the initial estimated speed. When the wheel speed of one or two of the wheels exceeds a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If at least one of the four wheels slips, the minimum of the remaining normal wheel speeds is taken as the initial estimated speed. If none of the four wheels slips, the average of the remaining normal wheel speeds is taken as the initial estimated speed. The normal wheel speed is a wheel speed that is greater than or equal to a preset minimum wheel speed threshold and less than or equal to a maximum wheel speed threshold. When at least three wheels have wheel speeds greater than a preset maximum wheel speed threshold, the current wheel speed is not used to calculate the third estimated speed. The preliminary estimated velocity at the current moment and the longitudinal acceleration collected in real time are input into the pre-built state prediction model to obtain the third estimated velocity at the current moment; The final output vehicle speed is calculated based on the first positioning speed, the second driving speed, the third estimated speed, and the fourth motor speed. The actual slip ratio of the four wheels is calculated based on the final output vehicle speed and the wheel speed of the four wheels. Based on the real-time acquired current road surface adhesion coefficient and the pre-built road surface μ-λ characteristic database, the optimal slip ratio of the four wheels is obtained; Based on the optimal slip ratio and the actual slip ratio, calculate the slip ratio difference and the rate of change of the slip ratio difference; When at least one wheel is determined to be slipping, and the slippage lasts for more than a preset safe time, while the vehicle is traveling in a straight line or the steering wheel angle is within 2°, the differential lock is engaged. After the front axle differential lock and rear axle differential lock are engaged, if any of the following conditions occur: the actual slip ratio still exceeds the safety threshold, the system determines that the condition is a double-sided slipping condition, or the differential lock activation conditions are no longer met, adjustments will be made based on the actual slip ratio: When the actual slip ratios are all less than the preset minimum slip ratio, the low slip ratio strategy is entered, and the torque required by the driver is output. When the rate of change of the slip ratio difference exceeds the preset rate of change threshold, the slip ratio strategy is entered, and the corrected torque is output through the fuzzy PID control architecture.

2. The electronic traction control method for a range-extended tractor according to claim 1, characterized in that, The pre-built state prediction model includes a process model and an observation model: The expression for the process model is: , The expression for the observation model is: , ， in, For the present The system state variables at time t. for The longitudinal speed of the vehicle at any given moment. for The longitudinal acceleration of the entire vehicle at any given moment. Here is the state transition matrix. for Time-based process noise, for The observed variables at each time point include the preliminary estimated velocity and IMU longitudinal acceleration. For the observation matrix, for Measurement noise at specific times; Recursive filtering is performed. Before obtaining the vehicle's longitudinal speed and acceleration at the current moment, prediction is made based on the model. The prediction equation is expressed as follows: ， ， After obtaining the vehicle's longitudinal speed and longitudinal acceleration at the current moment, the model is updated, and the update equation is expressed as follows: ， ， ， , in, Let k be the prior state estimate at time k. for Posterior state estimate at time step 1. for The prior estimate of covariance at time t, for The posterior estimate of the covariance at time t. This is the transpose of the state transition matrix. For the process excitation noise covariance, for Kalman gain at time step For the transpose of the observation matrix, To measure the noise covariance matrix, for The posterior state estimate at time t. for The posterior estimate of the covariance at time t. It is the identity matrix. For the updated The longitudinal acceleration of the entire vehicle at any given moment. This is the third estimated speed.

3. The electronic traction control method for a range-extended tractor according to claim 1, characterized in that, The expressions for obtaining the speed of the fourth motor include: ， in, The speed of the fourth motor. This refers to the motor speed. The tire's rolling radius, The gear ratio of the gearbox. This represents the overall reduction ratio.

4. The electronic traction control method for a range-extended tractor according to claim 3, characterized in that, When the rate of change of the slip ratio difference exceeds a preset rate of change threshold, the corrected torque output through the fuzzy PID control architecture includes: The inputs of the fuzzy PID control architecture include the slip ratio difference and the slip ratio difference change rate. The slip ratio difference and the slip ratio difference change rate are mapped to the fuzzy domain of the first fuzzy subset. The proportional coefficient and integral coefficient are mapped to the fuzzy domain of the second fuzzy subset through the fuzzy rule base. The actual torque correction value is obtained by defuzzifying the fuzzy domain using the centroid method. The torque correction value is added to the torque required by the driver to obtain the corrected torque, thereby realizing the adaptive adjustment of the wheel slip ratio.

5. The electronic traction control method for a range-extended tractor according to claim 1, characterized in that, The expressions for obtaining the current road surface adhesion coefficient include: ， ， ， ， ， ， in, The current road surface adhesion coefficient, This refers to the longitudinal adhesion of the tire. For the load on the tires, It's the motor torque. It is the braking torque. It is the moment of inertia of the tire. It is the first derivative of the wheel angular acceleration. It is the wheel radius. The load on the front left tire. This refers to the load on the front right tire. For the load on the rear left tire, For the load on the rear right tire, For the overall vehicle quality, It is the acceleration due to gravity. This refers to the wheelbase of the entire vehicle. This is the distance from the center of gravity of the structure above the suspension to the front axle of the vehicle. This is the distance from the center of gravity of the upper suspension structure to the rear axle. For the front wheel track, The rear wheel track. This refers to the height of the vehicle's center of gravity. For longitudinal acceleration, This is lateral acceleration.

6. The electronic traction control method for a range-extended tractor according to claim 1, characterized in that, Also includes: If, after the torque correction adjustment, the rate of change of the slip ratio difference still exceeds the preset rate of change threshold, the high slip ratio strategy is entered: at this time, the torque is output based on the preset proportional coefficient. The low slip rate strategy, medium slip rate strategy and high slip rate strategy are smoothly transitioned through a fuzzy weighted algorithm, and the weight coefficients in the fuzzy weighted algorithm are calculated in real time based on the slip rate and its rate of change.

7. An electronic traction control device for a range-extended tractor, characterized in that, include: A speed acquisition module is used to measure the vehicle's first positioning speed via a GNSS receiver (6) mounted on the roof; The second speed of the vehicle relative to the ground is measured by a ground-viewing radar (3) installed in the middle of the vehicle chassis facing the ground. Obtain the vehicle's third estimated speed, fourth motor speed, wheel speeds of all four wheels, and slippage status; Obtaining the vehicle's third estimated speed includes: When the wheel speeds of all four wheels are less than or equal to a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If none of the four wheels slip, the minimum value between the average front wheel speed and the average rear wheel speed is taken as the initial speed estimate; If at least one of the four wheels slips, the wheel speeds of the four wheels are sorted by size to obtain the maximum wheel speed, the second largest wheel speed, the second smallest wheel speed, and the minimum wheel speed. When the vehicle is in a braking state, the average of the maximum wheel speed and the second largest wheel speed is taken as the initial estimated speed. When the vehicle is in a non-braking state, the average of the second smallest wheel speed and the minimum wheel speed is taken as the initial estimated speed. When the wheel speed of one or two of the wheels exceeds a preset maximum wheel speed threshold, the vehicle speed is estimated based on the wheel slippage state: If at least one of the four wheels slips, the minimum of the remaining normal wheel speeds is taken as the initial estimated speed. If none of the four wheels slips, the average of the remaining normal wheel speeds is taken as the initial estimated speed. The normal wheel speed is a wheel speed that is greater than or equal to a preset minimum wheel speed threshold and less than or equal to a maximum wheel speed threshold. When at least three wheels have wheel speeds greater than a preset maximum wheel speed threshold, the current wheel speed is not used to calculate the third estimated speed. The preliminary estimated velocity at the current moment and the longitudinal acceleration collected in real time are input into the pre-built state prediction model to obtain the third estimated velocity at the current moment; The output vehicle speed calculation module is used to calculate the final output vehicle speed based on the first positioning speed, the second driving speed, the third estimated speed, and the fourth motor speed. The actual slip ratio calculation module is used to calculate the actual slip ratio of the four wheels based on the final output vehicle speed and the wheel speed of the four wheels; The optimal slip ratio acquisition module is used to obtain the optimal slip ratio of the four wheels based on the real-time acquired current road surface adhesion coefficient and the pre-built road surface μ-λ characteristic database. The module for calculating the slip ratio difference and the rate of change of the slip ratio difference is used to calculate the slip ratio difference and the rate of change of the slip ratio difference based on the optimal slip ratio and the actual slip ratio. The automatic differential lock control module is used to lock the differential lock when at least one wheel is determined to be slipping for more than a preset safe time, and the vehicle is traveling in a straight line or the steering wheel angle is within 2°. The lower-level driving torque control module is used to adjust the torque based on the actual slip ratio when, after the front and rear axle differential locks are engaged, the actual slip ratio still exceeds the safety threshold, the system determines that the condition is a double-sided slippage, or the differential lock activation conditions are no longer met. When the actual slip ratios are all less than the preset minimum slip ratio, the low slip ratio strategy is entered, and the torque required by the driver is output. When the rate of change of the slip ratio difference exceeds the preset rate of change threshold, the slip ratio strategy is entered, and the corrected torque is output through the fuzzy PID control architecture.

8. The electronic traction control device for a range-extended tractor according to claim 7, characterized in that, Also includes: Four wheel speed sensors (1) are installed inside the front and rear drive axles of the vehicle to obtain the wheel speed of the four wheels. An IMU (2) installed at the vehicle's center of gravity is used to collect the vehicle's longitudinal acceleration, lateral acceleration, and yaw rate. The front wheel differential lock (4) installed at the front axle main reducer of the vehicle is used to automatically lock the front wheels, thereby actively distributing the driving torque of the wheels on both sides of the same axle. The rear wheel differential lock (5) installed at the rear axle main reducer of the vehicle is used to automatically lock the rear wheels, thereby actively distributing the driving torque of the wheels on both sides of the same axle. The front wheel steering angle sensor (7) installed at the front axle steering knuckle is used to monitor the yaw rate of the steering wheel in real time and determine whether the vehicle is currently in a straight-line driving or steering condition. A steering wheel angle sensor (8) installed on the steering column is used to detect the driver's steering wheel angle in real time. as well as The electronic traction controller (9) is used to ultimately send drive torque correction commands to the lower-level motor.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 6.

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