Hybrid power tractor energy management method and system

Abstract

The invention discloses a hybrid power tractor energy management method and system, and relates to the technical field of intelligent energy management, and the method comprises the steps: collecting multi-source data of a tractor, carrying out the preprocessing, calculating the load intensity, judging the operation condition type of the tractor, and calculating the transmission input demand power based on the multi-source data. The condition assignment function is used for generating battery correction power, and amplitude limiting operation is carried out on the battery correction power based on the working condition type; and based on the transmission input demand power and the battery deviation rectification power after amplitude limiting, the target power of the engine is calculated, and the target power is converted into the target torque. Battery energy deviation analysis is combined with a working condition amplitude limiting strategy, the flexibility and safety of battery charging and discharging management are enhanced, engine target power is combined with an energy bin clearing mechanism, the stability of engine power output and the long-term energy balance capacity are improved, dynamic compensation power calculation is combined with motor power optimization distribution, and the energy balance capacity is improved. And the cooperative control effect between the engine and the motor is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent energy management, and in particular to a hybrid tractor energy management method and system. BACKGROUND

[0002] With the continuous improvement of agricultural mechanization, as an important power equipment for farmland operation, the energy utilization efficiency and operation economy of tractors have attracted widespread attention. Hybrid power technology has been gradually introduced into the field of agricultural vehicles, aiming to realize efficient energy management and energy recovery of the power system through the coordinated action of the engine and the motor, so as to reduce fuel consumption and emissions. In existing research, typical hybrid tractor energy management methods mainly include rule-based power distribution strategies, model prediction-based energy optimization control methods, and fuzzy logic or artificial intelligence-based intelligent control strategies.

[0003] The existing hybrid tractor energy management method still has shortcomings. The existing method only considers a small number of working condition parameters such as engine speed and vehicle speed, and lacks comprehensive modeling of key influencing factors such as torque, implement resistance and slope, so that the energy distribution lags behind the response to the actual working state. In the process of adjusting the battery SOC, the existing scheme usually adopts fixed proportion correction or empirical threshold method, ignoring the difference of battery power distribution under different working load categories, and it is difficult to balance the traction demand and energy balance. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a hybrid tractor energy management method and system, which solves the problem that the existing method only considers a small number of working condition parameters such as engine speed and vehicle speed, and lacks comprehensive modeling of key influencing factors such as torque, implement resistance and slope, so that the energy distribution lags behind the response to the actual working state. In the process of adjusting the battery SOC, the existing scheme usually adopts fixed proportion correction or empirical threshold method, ignoring the difference of battery power distribution under different working load categories, and it is difficult to balance the traction demand and energy balance.

[0006] To solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a hybrid tractor energy management method, which comprises, Collecting multi-source data of the tractor and preprocessing, calculating load intensity and determining the running working condition category of the tractor, calculating the transmission input demand power based on the multi-source data, generating the battery correction power using the conditional assignment function, and performing amplitude limiting operation on the battery correction power based on the working condition category; Based on the transmission input demand power and the limited battery correction power, the engine target power is calculated, the target power is converted into target torque, the rate and steady state limits are comprehensively calculated, the reachable torque interval is calculated, the target torque is projected to the reachable torque interval using the limiting function, the projected torque instruction is generated, the torque error is calculated, the energy bin is updated, and the energy bin is cleared to generate the final engine torque instruction; Based on the final engine torque instruction, the dynamic compensation power is calculated, the dynamic compensation power is limited, the limited dynamic compensation power is generated, the motor power instruction is generated by combining the limited battery correction power and the dynamic compensation power, the optimal speed and torque combination is found using the optimization function, and the engine joint instruction is generated; A visual interface is constructed to display the motor power instruction and the engine joint instruction.

[0007] As a preferred scheme of the hybrid tractor energy management method, the battery correction power is generated using the conditional assignment function, based on the working condition category, the battery correction power is limited, including: Based on the axle torque and the axle speed, the axle power contribution is calculated, and based on the vehicle speed and the implement resistance, the implement power contribution is calculated; The load intensity is calculated by combining the axle power contribution and the implement power contribution, and the load intensity is used to set the classification range using statistical analysis method to determine the tractor working condition category; Based on the multi-source data, the transmission input demand power is calculated; Based on the transmission input demand power, the engine surplus power is calculated; Based on the engine surplus power, the maximum sustainable charging power is calculated using the minimum value function, and the battery correction power is generated using the conditional assignment function according to the energy deviation and the maximum sustainable charging power; The battery correction power is limited based on the working condition category.

[0008] As a preferred scheme of the hybrid tractor energy management method, the battery correction power is generated using the conditional assignment function, based on the working condition category, the battery correction power is limited, including: Based on the transmission input demand power and the limited battery correction power, the engine target power is calculated; Based on the engine speed and the mechanical transmission efficiency, the target power is converted into target torque; The torque interval caused by the rate limit is calculated, the torque interval caused by the steady state limit is calculated, and the reachable torque interval is calculated by comprehensively calculating the rate and steady state limits; The target torque is projected to the reachable torque range using a limiting function to generate a projected torque instruction; A torque error is calculated, an energy corresponding to the error is calculated based on the torque error, an energy bin is updated, the energy bin is cleared, and a final engine torque instruction is generated.

[0009] As a preferred scheme of the hybrid tractor energy management method, the limiting operation on the dynamic compensation power is performed to generate a limited dynamic compensation power, including: Based on the final engine torque instruction, the dynamic compensation power is calculated, the limiting operation on the dynamic compensation power is performed to generate a limited dynamic compensation power.

[0010] As a preferred scheme of the hybrid tractor energy management method, the limited battery correction power and the dynamic compensation power are combined to generate a motor power instruction, an optimal speed and torque combination is found using an optimization function, and an engine joint instruction is generated, including: The limited battery correction power and the dynamic compensation power are combined to generate a motor power instruction; Based on the engine power, an optimal speed and torque combination is found using an optimization function, and an engine joint instruction is generated; An assignment function is used to convert the engine joint instruction into an ECU instruction and the motor power instruction into a torque instruction for the motor controller; And the generated ECU instruction and the torque instruction for the motor controller are executed.

[0011] As a preferred scheme of the hybrid tractor energy management method, the visual interface is constructed to display the motor power instruction and the engine joint instruction, including: A visual tool Matplotlib is used to construct a visual interface to display the motor power instruction and the engine joint instruction in real time; Allowing users to access through real-name verification.

[0012] As a preferred scheme of the hybrid tractor energy management method, the multi-source data of the tractor is collected and preprocessed, including: The multi-source data of the tractor is collected by sensors and is denoised and normalized; The sensors include inertial measurement units, Hall, wheel speed, torque, wheel speed, temperature, and force sensors; The multi-source data includes slope angle, current, vehicle speed, axle torque, axle speed, engine speed, temperature, and implement resistance data.

[0013] In a second aspect, the present application provides a hybrid tractor energy management system, comprising, The acquisition preprocessing module is used for collecting multi-source data and performing denoising and normalization processing. The working condition correction module is used for determining the tractor running working condition category, calculating the input demand power, generating the battery correction power using the conditional assignment function, and performing the amplitude limiting operation on the battery correction power according to the running working condition category. The target adjustment module is used for combining the transmission demand power and the battery correction power, determining the engine target power and converting it into the target torque, calculating the reachable torque interval through the rate limiting and the steady state limiting, calculating the energy bin mechanism compensation torque error, and generating the final engine torque instruction. The compensation instruction module is used for calculating the dynamic compensation power, performing the amplitude limiting processing, combining the battery correction power and the dynamic compensation power to generate the motor power instruction, and optimizing the engine speed and torque combination through the optimization function and performing the execution. The visualization module is used for displaying the motor power instruction and the engine joint instruction.

[0014] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, any step of the hybrid tractor energy management method according to the first aspect of the present application is implemented.

[0015] In a fourth aspect, the present application provides a computer readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, any step of the hybrid tractor energy management method according to the first aspect of the present application is implemented.

[0016] The present application has the following beneficial effects: the present application enhances the flexibility and safety of battery charge and discharge management through battery energy deviation analysis combined with working condition amplitude limiting strategy, increases the stability and long-term energy balance ability of engine power output through engine target power combined with energy bin compensation mechanism, and improves the collaborative control effect between the engine and the motor through dynamic compensation power calculation combined with motor power optimization distribution. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Figure 1 The flowchart of the hybrid tractor energy management method in embodiment 1.

[0019] Figure 2 A schematic diagram of the energy management system of the hybrid tractor in Example 1. DETAILED DESCRIPTION

[0020] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0021] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present application, therefore the present application is not limited by the specific embodiments disclosed below.

[0022] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. "In one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an embodiment that is independent of or mutually exclusive with other embodiments.

[0023] Example 1, Reference Figure 1 and Figure 2 , the first embodiment of the present application provides a hybrid tractor energy management method, comprising the following steps: S1, collecting multi-source data of the tractor and preprocessing, calculating the load intensity and determining the running condition category of the tractor, calculating the transmission input demand power based on the multi-source data, generating the battery correction power using the conditional assignment function, and performing the limiting operation on the battery correction power based on the working condition category; Specifically, collecting multi-source data of the tractor and preprocessing, including: Collecting multi-source data of the tractor through sensors and performing denoising and normalization processing; The sensor includes an inertial measurement unit, a Hall, a wheel speed, a torque, a wheel speed, a temperature and a force sensor; The multi-source data includes slope angle, current, vehicle speed, axle torque, axle speed, engine speed, temperature and implement resistance data.

[0024] Through multi-source data combined with signal preprocessing, the accurate perception of the state of the tractor under complex working conditions is realized, the energy distribution deviation caused by the measurement error of a single sensor is avoided, the stability and robustness of subsequent model calculation are enhanced through denoising and normalization, and the influence of external interference, working condition fluctuation, etc. on energy management is reduced.

[0025] Further, the battery correction power is generated using a conditional assignment function, an amplitude limiting operation is performed on the battery correction power based on the working condition category, and the amplitude limiting operation includes: Based on the axle torque and the axle speed, the axle power contribution is calculated, and the formula is: , Wherein is the axle power contribution, k is the current sampling time, that is, the kth sampling point in the discrete time sequence, is the axle torque, is the axle speed; Based on the vehicle speed and the implement resistance, the implement power contribution is calculated, and the formula is: , Wherein is the implement power contribution, is the implement resistance, is the vehicle speed; The load intensity is calculated by combining the axle power contribution and the implement power contribution, and the formula is: , Wherein is the load intensity; Based on the load intensity, the classification range is set using statistical analysis method, and the tractor working condition category is determined; The working condition category includes: if the load intensity is less than the classification range, it is determined as light load; if the load intensity is within the classification range, it is determined as medium load; if the load intensity is greater than the classification range, it is determined as heavy load; Based on the multi-source data, the transmission input demand power is calculated, and the formula is: , Wherein is the transmission input demand power, is the transmission efficiency, m is the total mass of the tractor, g is the acceleration of gravity, is the slope angle; Based on the current, the battery state of charge is calculated using the coulomb counting method, and based on the battery state of charge, the battery energy deviation is calculated, and the formula is: , , Wherein is the battery energy deviation, which represents the energy difference of the current SOC relative to the midpoint, is the battery SOC midpoint, is the battery state of charge, is the battery nominal energy, which is provided by the battery manufacturer, and upper and lower battery state of charge limits, respectively; Based on the transmission input demand power, the engine surplus power is calculated, with the formula: , wherein is the engine surplus power, representing the remaining power available for SOC correction, is the engine maximum sustainable power, is the engine speed; If the vehicle speed and the vehicle axle torque are both less than the light load vehicle speed threshold and the light load vehicle axle torque threshold, the engine speed is forced to be the minimum stable speed, and the surplus power is calculated according to the minimum engine speed; The light load vehicle speed threshold and the light load vehicle axle torque threshold are set using the percentile method, and the minimum engine speed is provided by the engine manufacturer; Based on the engine surplus power, the maximum sustainable charging power is calculated using the minimum function, with the formula: , wherein is the maximum sustainable charging power, representing the upper limit of the power available for battery charging, is the maximum allowed battery charging power, is the battery temperature, is the motor / inverter efficiency, and are the motor speed and the motor torque, respectively; According to the energy deviation and the maximum sustainable charging power, the battery correction power is generated using the conditional assignment function; The battery correction power includes, if the energy deviation is greater than 0, it is determined that the SOC is too high: , wherein is the battery correction power, with a positive value indicating charging and a negative value indicating discharging; If the energy deviation is equal to 0, it is determined that there is no surplus power: , If the energy deviation is less than 0, it is determined that the SOC is too low: , Based on the working condition category, the battery correction power is subjected to a limiting operation, with the formula: , wherein is the limited battery correction power, and are the minimum allowed battery power and the maximum allowed battery power, respectively, Battery temperature, Working condition limiting coefficient, using calibration experiment method to convert working condition category, for example, light = 1, maximum power range, medium load 0.9, balance traction and correction, heavy load = 0.8, priority traction demand, Working condition category.

[0026] Through the kinetic calculation combined with the agricultural machinery operation resistance, the energy consumption characteristics of the working condition of the tractor can be truly reflected, instead of relying on the engine output power only. By introducing the implement resistance variable, the off-road working condition characteristics of agricultural operation are fully considered, the adaptability of the model to the actual agricultural operation conditions is improved, the scientificity and objectivity of the working condition classification are improved through the statistical method combined with the load intensity distribution, the misjudgment caused by relying on the experience threshold is avoided, the accurate quantification of the power system demand is realized through the mechanical formula combined with the transmission efficiency model, the power demand is avoided to be underestimated due to the neglect of the slope or mechanical loss, the difference between the battery residual energy and the target interval can be dynamically reflected through the coulomb counting combined with the energy deviation analysis, the forward-looking of the energy management is improved, the energy deviation is used as the basis for generating the correction power, which can avoid the long-term operation of the battery deviating from the healthy interval, thereby prolonging the service life, the residual output capacity of the engine can be accurately evaluated through the transmission demand combined with the engine characteristic curve, the invalid charging or over-discharging is avoided, the engine is prevented from being unstable or stalling at low load by introducing the minimum stable speed constraint, the system safety is improved, the reasonable division of work between the engine and the battery in different operation stages is ensured through the load intensity combined with the SOC deviation, the overcharging and over-discharging and the temperature out of control are effectively avoided through the maximum sustainable charging power combined with the working condition limiting, the dynamic balance between the power demand and the energy management is realized through the engine surplus power combined with the correction power limiting, the fuel consumption is reduced and the operation reliability is improved.

[0027] S2, based on the transmission input demand power and the limited battery correction power, the engine target power is calculated, the target torque is converted, the reachable torque interval is calculated by comprehensively considering the speed and steady state limit, the target torque is projected to the reachable torque interval using the limiting function, the projected torque instruction is generated, the torque error is calculated, the energy bin is updated, and the energy bin is cleared to generate the final engine torque instruction; Specifically, the target torque is projected to the reachable torque interval using the limiting function, the projected torque instruction is generated, the torque error is calculated, the energy bin is updated, and the energy bin is cleared to generate the final engine torque instruction, including: Based on the transmission input demand power and the limited battery correction power, the engine target power is calculated, the formula is: , Wherein is the engine target power, Transmission drive efficiency; Based on the engine speed and the mechanical drive efficiency, the target power is converted to a target torque, with the formula: , where is the target engine torque, is the mechanical drive efficiency; The torque interval caused by the speed limit is calculated, with the formula: , , where and are the lower and upper limits of the speed limit, is the torque of the engine, is the upper limit of the engine torque change rate, is the sampling period; The torque interval caused by the steady-state limit is calculated, with the formula: , , where and are the lower and upper limits of the steady-state torque, and are the minimum steady-state torque of the engine and the maximum steady-state torque of the engine, respectively; The reachable torque interval is calculated by integrating the speed and steady-state limits, with the formula: , where is the reachable torque interval, representing the closed interval , and are the lower and upper limits of the reachable torque, respectively; The target torque is projected into the reachable torque interval using a clipping function, generating the projected torque command, with the formula: , where is the projected engine torque command candidate; The torque error is calculated, with the formula: , where is the torque error; Based on the torque error, the energy corresponding to the error is calculated, with the formula: , , wherein is the error energy, is the error power; updating the energy bin and discharging the energy bin to generate a final engine torque command, according to the formula: , wherein is the current energy bin; calculating the upper and lower margins of the reachable torque interval, according to the formula: , , wherein and are the increaseable torque margin and the decreaseable torque margin, respectively; said discharging the energy bin to generate a final engine torque command comprises, if the energy bin is greater than 0 (the engine does less work and needs to increase output): , , , wherein is the discharge torque, is the discharged energy bin, is the final engine torque command; if the energy bin is less than 0 (the engine does more work and needs to reduce output): , , , if the energy bin is equal to 0, .

[0028] By comprehensively considering the battery correction power and the transmission demand power, the engine not only bears the traction demand, but also participates in the dynamic compensation of the battery energy, avoiding the traditional method based on traction demand only, improving the coordination of power and energy, mapping the power instruction to the torque instruction, which is closer to the actual execution mode of the engine controller, introducing the mechanical transmission efficiency factor to truly reflect the energy loss in the transmission process, ensuring the physical accessibility of the instruction, limiting the torque change rate to avoid excessive output jump of the engine in a short time, reducing mechanical impact, combining with the speed limit to realize the unification of dynamic constraint and static constraint, improving the reliability of the control system, converting the torque error into energy error and storing it in the "energy bin", which can accumulate and remember the historical deviation, the energy bin mechanism makes the system not only pursue short-term optimization, but also considers long-term energy balance, the energy bin clearing mechanism ensures that the system does not accumulate too much energy error in long-term operation, improving the adaptability and self-correction ability of the control system.

[0029] S3、based on the final engine torque instruction, calculate the dynamic compensation power, perform the limiting operation on the dynamic compensation power, generate the limited dynamic compensation power, combine the limited battery correction power and the dynamic compensation power, generate the motor power instruction, use the optimization function to find the optimal speed and torque combination, generate the engine joint instruction; Specifically, performing the limiting operation on the dynamic compensation power to generate the limited dynamic compensation power comprises: Based on the final engine torque instruction, calculate the engine actual power, the formula is: , Wherein is the engine actual power; Calculate the dynamic compensation power, the formula is: , Wherein is the dynamic compensation power; Perform the limiting operation on the dynamic compensation power to generate the limited dynamic compensation power, the formula is: , Wherein is the limited dynamic compensation power.

[0030] The conversion from the "torque control domain" to the "power evaluation domain" is established, so that the motor and the battery control can be coordinated in a unified energy dimension, improving the accuracy of engine operation monitoring, which is beneficial to ensure reasonable power matching in field work. The dynamic compensation power is used to measure the difference between the target and the actual value, so that the system can compensate at the motor end, avoid the instantaneous power shortage or excess caused by engine hysteresis, unstable speed, etc. Combined with the battery SOC limit, it ensures that the compensation behavior will not cause the battery to be over-discharged or over-charged.

[0031] Further, combined with the limited battery correction power and dynamic compensation power, the motor power instruction is generated, the optimal speed and torque combination is found using the optimization function, and the engine joint instruction is generated, including: Combined with the limited battery correction power and dynamic compensation power, the motor power instruction is generated, and the formula is: , Among them is the motor power instruction, a positive value represents the motor output power, and a negative value represents the charging; Based on the engine power, the optimal speed and torque combination is found using the optimization function, and the engine joint instruction is generated, and the formula is: , , Among them and are the optimal engine speed and optimal engine torque, is the engine torque, is the fuel consumption rate, is the engine feasible operation domain, is the engine output efficiency, is the power tolerance, which is set using a fixed threshold; The assignment function is used to convert the engine joint instruction into an ECU instruction and the motor power instruction into a motor controller torque instruction, and the formula is: , Among them is the motor controller torque instruction, is the motor efficiency, is the motor speed And the generated ECU instruction and motor controller torque instruction are executed.

[0032] Taking fuel economy as an optimization target, ensuring that the engine operating point is always close to the low fuel consumption area, mapping the power distribution result of the energy management layer to the torque control signal of the execution layer, realizing the closed loop of the control chain, coupling the motor power instruction with the battery correction and dynamic compensation power, avoiding SOC deviation, quickly supporting the load when the power gap occurs, realizing the complementary cooperation of the battery and the engine, selecting the optimal speed and torque combination through the optimization function, making the engine run in the low fuel consumption interval as much as possible, considering power output and economy, which is helpful for the green and low-carbon development of agricultural machinery. The limiting mechanism is introduced in multiple links to ensure that the motor, battery and engine are running in a safe working condition, and the stability and reliability of the system in complex working environment are improved.

[0033] S4, a visual interface is constructed to display the motor power instruction and the engine joint instruction; Specifically, the visual interface is constructed to display the motor power instruction and the engine joint instruction, comprising: A visual tool Matplotlib is used to construct the visual interface to display the motor power instruction and the engine joint instruction in real time. Allowing users to check through real-name verification.

[0034] Through the visual interface, the distribution process of the motor and engine instructions is intuitively presented, and the user can master the power system operation logic in real time, improve the understandability of the system, and avoid illegal operation and misuse through the real-time monitoring and real-name verification mechanism to ensure the stable operation of the agricultural machinery in complex working scenarios.

[0035] The embodiment also provides a hybrid power tractor energy management system, comprising: A collection preprocessing module is configured to collect multi-source data and perform denoising and normalization processing; A working condition correction module is configured to determine the tractor running working condition category, calculate the input demand power, generate the battery correction power using a conditional assignment function, and perform an amplitude limiting operation on the battery correction power according to the running working condition category; A target adjustment module is configured to combine the transmission demand power and the battery correction power, determine the engine target power and convert it into a target torque, calculate the reachable torque interval through rate limiting and steady-state limiting, calculate the energy bin mechanism compensation torque error, and generate a final engine torque instruction; A compensation instruction module is configured to calculate the dynamic compensation power, perform amplitude limiting processing, combine the battery correction power and the dynamic compensation power to generate a motor power instruction, and find the optimal engine speed and torque combination through an optimization function and perform the same; A visual module is configured to display the motor power instruction and the engine joint instruction.

[0036] The embodiment also provides a computer device suitable for the hybrid tractor energy management method, including a memory and a processor.

[0037] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner. The wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0038] The embodiment also provides a storage medium having a computer program stored thereon, and the program is executed by a processor to implement the hybrid tractor energy management method. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk or an optical disk.

[0039] To sum up, the application enhances the flexibility and safety of battery charge and discharge management by battery energy deviation analysis combined with working condition limiting strategy, increases the stability of engine power output and long-term energy balance ability by engine target power combined with energy bin clearing mechanism, and improves the collaborative control effect between the engine and the motor by dynamic compensation power calculation combined with motor power optimization distribution.

[0040] It should be noted that the above examples are only used to illustrate the technical solutions of the present application but not to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application, and all modifications and equivalents should be included in the scope of the claims of the present application.

Claims

1. A hybrid tractor energy management method, characterized by: The method comprises the following steps: Collecting and preprocessing multi-source data of the tractor, calculating load intensity and determining the running working condition category of the tractor, calculating transmission input demand power based on the multi-source data, generating battery correction power using a conditional assignment function, performing amplitude limiting operation on the battery correction power based on the working condition category; Based on the transmission input demand power and the amplitude-limited battery correction power, calculate the engine target power, convert the target power to target torque, calculate the reachable torque interval by comprehensively limiting the rate and the steady state, project the target torque to the reachable torque interval using the limiting function to generate the projected torque instruction, calculate the torque error, update the energy bin, and clear the energy bin to generate the final engine torque instruction; Based on the final engine torque instruction, calculate the dynamic compensation power, perform amplitude limiting operation on the dynamic compensation power to generate the amplitude-limited dynamic compensation power, combine the amplitude-limited battery correction power and the dynamic compensation power to generate the motor power instruction, use the optimization function to find the optimal speed and torque combination to generate the engine joint instruction; A visual interface is constructed to display the motor power instruction and the engine joint instruction.

2. The hybrid tractor energy management method of claim 1, wherein: The use of the conditional assignment function to generate the battery correction power and the amplitude limiting operation on the battery correction power based on the working condition category comprises: Based on the axle torque and the axle speed, calculate the axle power contribution, based on the vehicle speed and the implement resistance, calculate the implement power contribution; Combine the axle power contribution and the implement power contribution to calculate the load intensity, and based on the load intensity, use statistical analysis method to set the classification range to determine the running working condition category of the tractor; Based on the multi-source data, calculate the transmission input demand power; Based on the transmission input demand power, calculate the engine surplus power; Based on the engine surplus power, use the minimum function to calculate the maximum sustainable charging power, and according to the energy deviation and the maximum sustainable charging power, use the conditional assignment function to generate the battery correction power; Based on the working condition category, perform amplitude limiting operation on the battery correction power.

3. The hybrid tractor energy management method of claim 2, wherein: The use of the limiting function to project the target torque to the reachable torque interval to generate the projected torque instruction, calculate the torque error, update the energy bin, and clear the energy bin to generate the final engine torque instruction, comprises: Based on the transmission input demand power and the amplitude-limited battery correction power, calculate the engine target power; Based on the engine speed and the mechanical transmission efficiency, convert the target power to target torque; Calculate the torque interval caused by the rate limit, calculate the torque interval caused by the steady state limit, and calculate the reachable torque interval by comprehensively limiting the rate and the steady state; Use the limiting function to project the target torque to the reachable torque interval to generate the projected torque instruction; Calculate the torque error, calculate the error corresponding energy based on the torque error, update the energy bin, and clear the energy bin to generate the final engine torque instruction.

4. The hybrid tractor energy management method of claim 3, wherein: The amplitude limiting operation on the dynamic compensation power to generate the amplitude-limited dynamic compensation power comprises: Based on the final engine torque instruction, calculate the dynamic compensation power, perform amplitude limiting operation on the dynamic compensation power to generate the amplitude-limited dynamic compensation power.

5. The hybrid tractor energy management method of claim 4, wherein: The combined limited battery correction power and dynamic compensation power generates motor power instruction, uses optimization function to find the optimal speed and torque combination, generates engine joint instruction, including: The combined limited battery correction power and dynamic compensation power generates motor power instruction; Based on the engine power, use the optimization function to find the optimal speed and torque combination, generate engine joint instruction; Use the assignment function to convert the engine joint instruction to the ECU instruction, and convert the motor power instruction to the torque instruction of the motor controller; And the generated ECU instruction and torque instruction of the motor controller are executed.

6. The hybrid tractor energy management method of claim 5, wherein: The visualization interface displays the motor power instruction and engine joint instruction, including: Use the visualization tool Matplotlib to build the visualization interface, and display the motor power instruction and engine joint instruction in real time; Allow users to check through real-name verification.

7. The hybrid tractor energy management method of claim 6, wherein: The multi-source data of the tractor is collected and preprocessed, including: Collecting multi-source data of the tractor through sensors and performing denoising and normalization processing; The sensor includes an inertial measurement unit, a Hall, a wheel speed, a torque, a wheel speed, a temperature, and a force sensor; The multi-source data includes slope angle, current, vehicle speed, axle torque, axle speed, engine speed, temperature, and implement resistance data.

8. A hybrid tractor energy management system based on the hybrid tractor energy management method of any one of claims 1 to 7, characterized by: Including, The acquisition and preprocessing module is used to collect multi-source data and perform denoising and normalization processing; The working condition correction module is used to determine the tractor running working condition category, calculate the input demand power, use the conditional assignment function to generate the battery correction power, and perform the limiting operation on the battery correction power according to the running working condition category; The target adjustment module is used to combine the transmission demand power and the battery correction power, determine the engine target power and convert it to the target torque, calculate the reachable torque interval through the rate limit and the steady-state limit, calculate the energy bin mechanism to compensate the torque error, and generate the final engine torque instruction; The compensation instruction module is used to calculate the dynamic compensation power and perform limiting processing, combine the battery correction power and the dynamic compensation power to generate the motor power instruction, and find the optimal engine speed and torque combination through the optimization function, and execute; The visualization module is used to display the motor power instruction and engine joint instruction.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that: The processor executes the computer program to realize the steps of the hybrid power tractor energy management method in any one of claims 1-7.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the hybrid power tractor energy management method in any one of claims 1-7.

Images