A method, system, device and storage medium for power take-off control self-learning

Abstract

This invention discloses a method, system, device, and storage medium for power take-off (PTO) control self-learning. The method involves: presetting the gearbox state, PTO, and brake pedal opening; if these conditions are met, activating the PTO self-learning program; within a first preset time period, if the accelerator pedal opening exceeds a first opening threshold, entering the first self-learning phase; otherwise, exiting; recording the first time and the first maximum opening value; within a second preset time period, if the accelerator pedal opening is detected to exceed the first opening threshold, exiting if otherwise, and entering the second self-learning phase if yes, recording the second time and the second maximum opening value; determining the effectiveness of the self-learning based on the difference between the first and second maximum opening values; if ineffective, exiting; if effective, proceeding to parameter calculation and storage to complete the self-learning process. This invention can adapt to different load requirements, achieve autonomous learning and storage of control parameters, support modifications throughout the vehicle's entire lifecycle, reduce costs, optimize acceleration response, and reduce operational intensity.

Description

Technical Field

[0001] This invention belongs to the field of electric control technology for new energy commercial vehicles, specifically relating to a method, system, device, and storage medium for power take-off control self-learning. Background Technology

[0002] With the continuous development of new energy commercial vehicle technology and the sustained growth of market penetration, new energy commercial vehicles are no longer limited to traditional use cases such as logistics vehicles and dump trucks. Special vehicles such as tractor trucks, sanitation vehicles, and powder tank trucks with superstructures are also gradually becoming electric. Currently, to meet the superstructure requirements of these vehicles, the mainstream low-cost solution is to use a transmission to take power, driving the oil pump, air compressor, and other superstructure equipment. This modification method is generally carried out by end users or superstructure manufacturers who purchase a Class II chassis from the OEM and complete the modification themselves, which brings the following potential technical problems: In general, the power take-off (PTO) of a pure electric vehicle's transmission is controlled by the vehicle control unit (VCU). To reduce the driver's workload during long-term PTO operation, the VCU sets a PTO idle speed (accelerator pedal opening is 0). The relationship between the PTO idle speed and the accelerator pedal opening and PTO operating speed is written into the VCU when the vehicle rolls off the production line and cannot be modified by the user. This makes it impossible to meet the speed requirements of different superstructure equipment. During the vehicle's lifecycle, it may be modified for different uses. For example, a tractor-trailer with a cargo box tipping function might have an oil pump as the load on the PTO. When this vehicle is modified into a powder tanker truck, the PTO load becomes an air compressor. The high-pressure gas generated during operation is used to blow out powder particles. Unlike an oil pump, an air compressor has different input speed requirements. Therefore, the original PTO control strategy cannot adapt to the new modification scheme. Therefore, in summary, the power take-off (PTO) units in current pure electric vehicles generally use a fixed idle speed or no idle speed, which is not suitable for different load requirements such as air compressors and oil pumps; retrofitting requires rewriting the vehicle controller, and the slope of the curve between the accelerator pedal opening and the motor speed when the PTO is working is preset and cannot be adjusted, making it difficult to meet the PTO operating speed requirements of different usage scenarios. Summary of the Invention

[0003] This invention provides a method, system, device, and storage medium for power take-off (PTO) control self-learning. The purpose is to solve the problems that current PTOs in pure electric vehicles generally use a fixed idle speed or no idle speed, which is not suitable for different load requirements such as air compressors and oil pumps; retrofitting requires rewriting the vehicle controller; and the slope of the curve between the accelerator pedal opening and the motor speed during PTO operation is preset and cannot be adjusted, making it difficult to meet the PTO operating speed requirements of different usage scenarios.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides a method for power take-off (PTO) control self-learning, comprising the following steps: S1. When the vehicle is detected to be stationary and the transmission is in neutral, if the power take-off switch is pressed and the power take-off is engaged, and the brake pedal opening is greater than a preset threshold and continues for a preset time, the power take-off self-learning program is activated. S2. If the accelerator pedal opening is detected to be greater than the first opening threshold within the first preset time after the self-learning program is activated, the first self-learning process will be entered; otherwise, the power take-off idle speed will be set to the default value and the self-learning process will be exited. S3. During the first self-learning process, record the first maximum opening value of the accelerator pedal and the first time required for the accelerator pedal opening to increase from the first opening threshold to the maximum opening value. S4. If, within the second preset time after completing the first self-learning process, the accelerator pedal opening is detected to be greater than the first opening threshold again, the second self-learning process will begin; otherwise, the self-learning process will exit and the default parameters will be restored. S5. During the second self-learning process, record the second maximum opening value of the accelerator pedal and the second time required for the accelerator pedal opening to increase from the first opening threshold to the second maximum opening value. S6. Determine whether self-learning is effective based on the difference between the first maximum opening value and the second maximum opening value. If it is effective, proceed to the parameter calculation and storage process; otherwise, exit self-learning and restore the default parameters. S7. In the parameter calculation and storage process, calculate the idle accelerator pedal opening value and the average acceleration time value, query the preset calibration curve based on the idle accelerator pedal opening value to obtain the target motor speed, calculate the slope, and store the target motor speed and slope in non-volatile memory to complete the power take-off control self-learning.

[0005] In some implementations, in S1, the preset threshold for brake pedal opening is controlled to be 75-100%, and the preset time is controlled to be 5-10 seconds.

[0006] In some implementations, in S2, the first preset time is 1-10 seconds and the first opening threshold is 5%.

[0007] In some implementations, in S2, if the accelerator pedal opening is not detected to be greater than the first opening threshold, the power take-off idle speed is set to zero, and the slope of the curve between the accelerator pedal opening and the power take-off operating speed is set.

[0008] In some implementations, in S6, the criterion for determining whether self-learning is effective is the difference between the first maximum opening value and the second maximum opening value, using the following formula: ; in, This is the first maximum opening value. This is the second maximum opening value.

[0009] In some implementations, the idle accelerator pedal opening value is calculated in S7 using the following formula: ; The average acceleration time is calculated using the following formula: ; The slope is calculated using the following formula: ; in, To be the first, For the second time, This represents the average acceleration time. The slope The target motor speed.

[0010] In some implementations, in S7, the calibration curve is a preset mapping relationship between the accelerator pedal opening and the motor speed, and the non-volatile memory is the EEPROM of the vehicle controller.

[0011] This invention also provides a system for power take-off (PTO) control self-learning, the system being used to execute a method for PTO control self-learning; the system includes a signal input layer, a vehicle controller, an execution control layer, and a mechanical control layer; wherein: Signal input layer: includes power take-off rocker switch, accelerator pedal sensor, brake pedal sensor, and motor speed sensor. The execution control layer includes the power take-off solenoid valve and the motor controller; the mechanical control layer includes the transmission power take-off and the drive motor. Vehicle controller: Used to receive input signals from the signal input layer, perform calculations during the self-learning process, and then control the mechanical execution layer through the execution control layer.

[0012] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the power take-off control self-learning method described above.

[0013] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the power take-off control self-learning method described above.

[0014] Compared with the prior art, the present invention provides a method, system, device, and storage medium for power take-off control self-learning, which has the following advantages: This invention discloses a power take-off (PTO) control self-learning method. Compared to a fixed idle speed or no idle speed, it can dynamically learn the target motor speed to adapt to different load requirements such as air compressors and oil pumps. Previously, retrofitting required rewriting the vehicle control unit (VCU), but this invention's method enables autonomous learning and storage of control parameters, supporting retrofitting throughout the vehicle's entire lifecycle, thus reducing user operating costs. Furthermore, in traditional solutions, the slope of the accelerator pedal opening and motor speed curve during PTO operation is preset and cannot be adjusted. This invention's method generates an adaptive slope through self-learning, optimizing acceleration response, reducing driver workload, and improving overall vehicle reliability.

[0015] The computer device of this invention, through a processor executing a specific computer program, can efficiently implement the steps of the method of this invention. When performing data processing tasks, the computer device can accurately perform numerical calculations and logical judgments, avoiding errors caused by human factors. Simultaneously, due to the high stability and reliability of the computer program, the accuracy and consistency of the data processing results can be ensured. The computer-readable storage medium of this invention, by programming the steps of the method of this invention into a computer program and storing it on the computer-readable storage medium, allows users to easily load and execute these programs on any compatible computer device without rewriting or converting the code, greatly improving the convenience and flexibility of program execution. Attached Figure Description

[0016] The accompanying drawings are provided to further understand the invention and constitute a part of this invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0017] Figure 1 This is a flowchart illustrating a power take-off control self-learning method according to the present invention. Figure 2 This is a schematic diagram showing the relationship between the accelerator pedal opening value and time during the first self-learning process in the power take-off control self-learning method of the present invention. Figure 3 This is a schematic diagram showing the relationship between the accelerator pedal opening value and time during the second self-learning process in the power take-off control self-learning method of the present invention. Figure 4 This is a schematic diagram of the system architecture in the self-learning method for power take-off control of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0019] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0020] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0021] It should be noted that the apparatus and methods disclosed in the embodiments herein can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments herein. In this regard, each block in a flowchart or block diagram may represent a module, program, or part of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system to perform the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0022] In addition, the functional modules in the various embodiments of this article can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0023] This invention provides a method for power take-off (PTO) control self-learning, comprising the following steps: S1. When the vehicle is detected to be stationary and the transmission is in neutral, if the power take-off switch is pressed and the power take-off is engaged, and the brake pedal opening is greater than a preset threshold and continues for a preset time, the power take-off self-learning program is activated. S2. If the accelerator pedal opening is detected to be greater than the first opening threshold within the first preset time after the self-learning program is activated, the first self-learning process will be entered; otherwise, the power take-off idle speed will be set to the default value and the self-learning process will be exited. S3. During the first self-learning process, record the first maximum opening value of the accelerator pedal and the first time required for the accelerator pedal opening to increase from the first opening threshold to the maximum opening value. S4. If, within the second preset time after completing the first self-learning process, the accelerator pedal opening is detected to be greater than the first opening threshold again, the second self-learning process will begin; otherwise, the self-learning process will exit and the default parameters will be restored. S5. During the second self-learning process, record the second maximum opening value of the accelerator pedal and the second time required for the accelerator pedal opening to increase from the first opening threshold to the second maximum opening value. S6. Determine whether self-learning is effective based on the difference between the first maximum opening value and the second maximum opening value. If it is effective, proceed to the parameter calculation and storage process; otherwise, exit self-learning and restore the default parameters. S7. In the parameter calculation and storage process, calculate the idle accelerator pedal opening value and the average acceleration time value, query the preset calibration curve based on the idle accelerator pedal opening value to obtain the target motor speed, calculate the slope, and store the target motor speed and slope in non-volatile memory to complete the power take-off control self-learning.

[0024] This invention provides a self-learning method for power take-off (PTO) control, which improves upon the current problem that pure electric vehicles cannot meet the varying operating speed requirements of PTOs in different usage scenarios. It provides a control method that dynamically adapts the PTO's idle speed through self-learning based on driver operation behavior. Specifically, it designs a composite condition activation mechanism; establishes a two-stage learning process; and develops a parameter dynamic adaptation algorithm based on mean calculation. This solves the problem of fixed and unadjustable parameters in existing technologies, enabling the vehicle to adapt to the speed requirements of different superstructures throughout its entire lifecycle. While ensuring overall vehicle reliability, it significantly reduces modification costs, demonstrating significant practical value.

[0025] like Figure 4As shown, the present invention also provides a power take-off (PTO) control self-learning system, which is used to execute a PTO control self-learning method; the system includes a signal input layer, a vehicle controller, an execution control layer, and a mechanical control layer; wherein: Signal input layer: includes power take-off rocker switch, accelerator pedal sensor, brake pedal sensor, and motor speed sensor. The execution control layer includes the power take-off solenoid valve and the motor controller; the mechanical control layer includes the transmission power take-off and the drive motor. Vehicle controller: Used to receive input signals from the signal input layer, perform calculations during the self-learning process, and then control the mechanical execution layer through the execution control layer.

[0026] In actual operating conditions, the power take-off (PTO) solenoid valve, motor controller, and other components form the execution and control parts, while the motor, gearbox, and PTO form the mechanical execution hardware. The PTO rocker switch, accelerator pedal, and brake pedal form the human-machine interface execution parts.

[0027] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the power take-off control self-learning method described above. The memory of the electronic device of the present invention stores instructions executable by the processor, which are executed by the processor to enable the processor to perform the methods described in the above aspects and any possible implementations.

[0028] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the power take-off control self-learning method described above. The computer-readable storage medium of the present invention stores at least one instruction, which is loaded and executed by a processor to implement the power take-off control self-learning method described above.

[0029] The following detailed description of a power take-off control self-learning method, system, device, and storage medium of the present invention will be provided through specific embodiments.

[0030] like Figures 1-3 As shown, the power take-off control self-learning method provided in one embodiment of this application is specifically performed as follows: Step 1: Activate condition detection. When the following conditions are met simultaneously, activate the power take-off self-learning and proceed to Step 2.

[0031] 1) The vehicle is stationary and the transmission is in neutral; 2) The power take-off rocker switch is pressed and the power take-off is engaged; 3) The brake pedal opening should be greater than 75% for more than 5 seconds.

[0032] (The brake pedal opening of this invention needs to be greater than a certain value, which can be selected within the range of 75-100% as needed. The duration needs to be greater than 5 seconds, which can be controlled between 5-10 seconds.) Step Two: Operation Timeout Detection. Within 10 seconds (this time can be preset to 1-10 seconds as needed), the Vehicle Control Unit (VCU) detects that the accelerator pedal is depressed (opening greater than 5%), enters the first self-learning phase, and proceeds to Step Three. Otherwise, it enters the exception handling phase. The program defaults to setting the PTO idle speed to 0, and the slope of the curve between accelerator pedal opening and PTO operating speed is a fixed value. .

[0033] Step 3: During the first self-learning process, after the driver depresses the accelerator pedal, they should gradually press the pedal deeper according to their own habits. Once the motor speed reaches the required speed, the driver should completely release the accelerator pedal. The vehicle control unit (VCU) records the maximum opening of the accelerator pedal during this process. Accelerator pedal opening from 5% to maximum opening time After fully releasing the accelerator pedal, proceed to step four.

[0034] Step 4: Operation timeout detection. If the vehicle control unit (VCU) detects the accelerator pedal being pressed (opening greater than 5%) within 10 seconds, it will enter the second self-learning process and proceed to Step 5. Otherwise, it will enter the exception handling process.

[0035] Step 5: Second self-learning. Repeat the first self-learning operation. The vehicle control unit (VCU) records the maximum accelerator pedal opening during this process. Accelerator pedal opening from 5% to maximum opening time After fully releasing the accelerator pedal, proceed to step six.

[0036] Step Six: Self-learning effectiveness verification. Based on the results of the two self-learning sessions, when... and If the absolute value of the difference is less than 20%, the self-learning is considered valid, and step seven is executed. Otherwise, the self-learning is invalid, the exception handling process is initiated, and the default parameters are restored.

[0037] Step 7: Parameter calculation and storage process. Based on the results of two self-learning sessions, the idle accelerator pedal opening value is obtained. Average acceleration time value The idle accelerator pedal opening value can be obtained by referring to a table based on the calibration curve of the idle accelerator pedal opening value and the motor speed. target motor speed This will be used as the drive motor speed during the power take-off's idle operation for this self-learning process. This self-learning process uses the slope of the curve showing the accelerator pedal opening and motor speed during power take-off operation. The program will... and Stored in the vehicle controller (VCU) EEPROM, supports power-off storage, and self-learning ends.

[0038] In summary, this invention provides a method, system, device, and storage medium for power take-off (PTO) control self-learning. The PTO control self-learning method achieves dynamic control and adaptation of PTO control parameters through a self-learning mechanism. It acquires driver operation data through two self-learning processes and calculates idle speed and slope based on the average, enabling the PTO to adapt to the speed requirements of different superstructures, overcoming the limitations of the original fixed and unadjustable VCU parameters. The activation conditions and validity verification mechanism of the self-learning process ensure the reliability and practicality of parameter learning, avoiding control failures caused by misoperation or abnormal input, and improving control effectiveness. Furthermore, by storing the final parameters in non-volatile memory, it supports multiple modifications and adaptations throughout the vehicle's lifecycle, reducing the VCU rewriting cost for users due to equipment replacement, and improving economy and reliability.

[0039] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Anyone skilled in the art can readily implement the present invention according to the description and above. Any modifications, alterations, or equivalent variations made using the technical content disclosed above are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, or variations made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the present invention.

Claims

1. A method for self-learning power take-off (PTO) control, characterized in that, Includes the following steps: S1. When the vehicle is detected to be stationary and the transmission is in neutral, if the power take-off switch is pressed and the power take-off is engaged, and the brake pedal opening is greater than a preset threshold and continues for a preset time, the power take-off self-learning program is activated. S2. If the accelerator pedal opening is detected to be greater than the first opening threshold within the first preset time after the self-learning program is activated, the first self-learning process will be entered; otherwise, the power take-off idle speed will be set to the default value and the self-learning process will be exited. S3. During the first self-learning process, record the first maximum opening value of the accelerator pedal and the first time required for the accelerator pedal opening to increase from the first opening threshold to the maximum opening value. S4. If, within the second preset time after completing the first self-learning process, the accelerator pedal opening is detected to be greater than the first opening threshold again, the second self-learning process will begin; otherwise, the self-learning process will exit and the default parameters will be restored. S5. During the second self-learning process, record the second maximum opening value of the accelerator pedal and the second time required for the accelerator pedal opening to increase from the first opening threshold to the second maximum opening value. S6. Determine whether self-learning is effective based on the difference between the first maximum opening value and the second maximum opening value. If it is effective, proceed to the parameter calculation and storage process; otherwise, exit self-learning and restore the default parameters. S7. In the parameter calculation and storage process, calculate the idle accelerator pedal opening value and the average acceleration time value, query the preset calibration curve based on the idle accelerator pedal opening value to obtain the target motor speed, calculate the slope, and store the target motor speed and slope in non-volatile memory to complete the power take-off control self-learning.

2. The power take-off control self-learning method according to claim 1, characterized in that, In S1, the preset threshold for brake pedal opening is controlled at 75-100%, and the preset time is controlled at 5-10 seconds.

3. The power take-off control self-learning method according to claim 1, characterized in that, In S2, the first preset time is 1-10 seconds, and the first opening threshold is 5%.

4. The power take-off control self-learning method according to claim 1, characterized in that, In S2, if the accelerator pedal opening is not detected to be greater than the first opening threshold, the idle speed of the power take-off is set to zero, and the slope of the curve between the accelerator pedal opening and the power take-off operating speed is set.

5. The power take-off control self-learning method according to claim 1, characterized in that, In step S6, the difference between the first maximum opening value and the second maximum opening value is used to determine whether the self-learning is effective, according to the following formula: ； in, This is the first maximum opening value. This is the second maximum opening value.

6. The method for power take-off control self-learning according to claim 1, characterized in that, In S7, the idle accelerator pedal opening value is calculated using the following formula: ； The average acceleration time is calculated using the following formula: ； The slope is calculated using the following formula: ； in, To be the first, For the second time, This represents the average acceleration time. The slope The target motor speed.

7. The power take-off control self-learning method according to claim 1, characterized in that, In S7, the calibration curve is a preset mapping relationship between the accelerator pedal opening and the motor speed, and the non-volatile memory is the EEPROM of the vehicle controller.

8. A power take-off control self-learning system, characterized in that, The system is used to execute the power take-off control self-learning method according to any one of claims 1-7; the system includes a signal input layer, a vehicle controller, an execution control layer, and a mechanical control layer; wherein: Signal input layer: includes power take-off rocker switch, accelerator pedal sensor, brake pedal sensor, and motor speed sensor. The execution control layer includes the power take-off solenoid valve and the motor controller; the mechanical control layer includes the transmission power take-off and the drive motor. Vehicle controller: Used to receive input signals from the signal input layer, perform calculations during the self-learning process, and then control the mechanical execution layer through the execution control layer.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the power take-off control self-learning method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the power take-off control self-learning method as described in any one of claims 1-7.

Images