Collaborative optimization method for mass and power system of fuel cell tractor

Abstract

A collaborative optimization method for mass and a power system of a fuel cell tractor relates to the field of optimization design of power systems of tractors, and associates tractor counterweight design, power component design and energy storage component design, and ensures operation stability and traction performance of the tractor by setting and optimizing counterweight. The spatial positions and the mass of the hydrogen storage tank, the power battery, the fuel battery and the motor are cooperatively optimized based on the power performance, and the spatial positions and the mass of the hydrogen storage tank, the power battery, the fuel battery and the motor and the balance weight are cooperatively optimized by utilizing a genetic algorithm, so that the traction performance is improved while the operation stability of the tractor is ensured; the use quality of the whole machine reaches the optimal value, the manufacturing cost of the whole machine is reduced, the energy consumption economy is improved, collaborative optimization of the quality and the spatial position of each part of the fuel cell tractor and power system parameters is achieved, and the system can be developed according to limited development data. And the mass and position information of each component of the fuel cell tractor can be quickly obtained, and reasonable power system parameters can be calculated.

Description

A method for synergistic optimization of mass and power system of fuel cell tractor Technical Field

[0001] This invention relates to the field of tractor power system optimization design, specifically a method for the coordinated optimization of the mass and power system of a fuel cell tractor. Background Technology

[0002] With rapid economic development, my country's mechanization level is increasing, and energy consumption is also growing rapidly. Traditional tractors suffer from high energy consumption and severe exhaust pollution. To achieve green agriculture, it is essential to find new power sources. Compared to batteries, fuel cells have higher energy density, making them suitable for tractors operating under heavy loads and large-area field conditions. Furthermore, fuel cells can achieve zero emissions, overcoming the problems of low efficiency, high noise, and high energy consumption associated with traditional internal combustion engines. Therefore, researching fuel cell tractors suitable for agricultural operating environments is of great significance.

[0003] Many scholars have conducted research on fuel cell tractors, mainly focusing on energy management and integrated application analysis. However, research on the mass and spatial position of fuel cell tractors is relatively limited. As a novel type of power tractor, the mass and spatial position of its components are unknown at the initial design stage. Different component masses and spatial positions lead to different power system parameters and tractor operating quality, directly affecting the tractor's traction performance, operational stability, and energy economy. Therefore, conducting synergistic optimization of tractor mass and power system is essential for improving the efficiency of tractor parameter optimization design. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for the coordinated optimization of the mass and power system of a fuel cell tractor to improve the efficiency of tractor parameter optimization design.

[0005] The technical solution adopted by this invention to solve the above-mentioned technical problems is: a method for synergistic optimization of the mass and power system of a fuel cell tractor. The fuel cell tractor adopts dual-motor drive, with the fuel cell and power battery coordinating power supply. By setting and optimizing the counterweight, the tractor's operational stability and traction performance are ensured. Based on the power performance, the spatial position and mass of the hydrogen storage tank, power battery, fuel cell, and motor are synergistically optimized. The method includes the following steps: Step 1: Generating a population containing the spatial position of the hydrogen storage tank, power battery, fuel cell, and motor, as well as the mass of the hydrogen storage tank and power battery, using a genetic algorithm; Step 2: Distributing the hydrogen storage tank and power battery mass at the front counterweight box and rear drive wheel sides of the tractor. Do not add front or rear counterweights. Based on the spatial position and mass of the hydrogen storage tank, power battery, fuel cell, and motor, optimize the front counterweight mass to meet the design index of the front axle load distribution coefficient, and optimize the rear counterweight mass to meet the design index of tractor slip efficiency. Step 3: Input the tractor's predetermined operating condition information. Based on the optimized front and rear counterweight masses in Step 2, and the spatial position and mass population of the hydrogen storage tank, power battery, fuel cell, and motor generated in Step 1, obtain the power of the dual motors and fuel cell under the constraints of the power performance index and the operating condition information. Then, allocate the power of the dual motors. Under the power allocation ratio, the mass of the dual motors and fuel cell is obtained based on their power and power density; Step 4: The optimal dual motor torque is obtained using an instantaneous optimization algorithm. Then, the power of the fuel cell and the power battery is allocated according to the power demand of the dual motors under the predetermined operating conditions, and the energy consumption of the fuel cell, the power battery, and the tractor is solved. The mass of the power battery and the hydrogen storage tank is calculated based on the energy consumption of the power battery and the fuel cell; Step 5: It is determined whether the power allocation of the dual motors is complete. If it is complete, proceed to Step 6; if not, return to Step 3 and perform the power allocation of the dual motors again; Step 6: Based on different dual motor power allocation ratios... The tractor energy consumption under the specified ratio is determined by selecting the optimal dual-motor power allocation ratio and the corresponding masses of the dual motors, fuel cell, power battery, and hydrogen storage tank with the goal of minimizing energy consumption. The difference between the mass of the power battery and hydrogen storage tank generated by the genetic algorithm and the mass of the power battery and hydrogen storage tank obtained under the predetermined working conditions is compared. It is determined whether the absolute value of this difference is less than a set threshold. If it is satisfied, proceed to step seven. If it is not satisfied, return to step one and repeat the optimization process after updating the population through the genetic algorithm. Step seven: Output the mass and position of the front counterweight, rear counterweight, hydrogen storage tank, power battery, fuel cell, and motor, as well as the corresponding power system optimization parameters.

[0006] In step two, the front axle load of the tractor is calculated based on the spatial location and mass of the hydrogen storage tank, power battery, fuel cell, and motor. The design load of the front axle is calculated based on the tractor's operating mass and the designed front axle load distribution coefficient. The front counterweight is then optimized and adjusted based on the difference between the front axle load and the design load. The front axle load is then recalculated based on the adjusted front counterweight until the front counterweight meets the design requirements of the front axle load distribution coefficient. The rear axle wheelbase and front axle load of the tractor are calculated separately using the following formulas: in, The rear axle wheelbase of the nth generation tractor. For the nth generation front axle load, For the quality of the nth generation tractor, For the quality of the power battery, For the quality of the motor, For the quality of fuel cells, For the quality of the hydrogen storage tank, For the overall structural quality, Let the mass of the front counterweight of the nth generation tractor be [value]. For the rear counterweight mass of the tractor, For the horizontal coordinates of the power battery, The horizontal coordinate of the motor For the horizontal coordinates of the fuel cell, The horizontal coordinates of the hydrogen storage tank are: The horizontal coordinates of the entire machine structure The horizontal coordinate of the rear counterweight; It is the acceleration due to gravity. For tractor wheelbase, The rolling resistance torque of the tractor's front wheels, The rolling resistance torque of the tractor's rear wheels, For tractor traction resistance, The height of the traction point. The horizontal distance from the traction point of the agricultural implement to the rear axle. The angle between the traction resistance and the horizontal plane; the mass of the nth generation tractor is: Calculate the front axle design load based on the designed front axle load distribution coefficient, and adjust the front counterweight accordingly. The formula is as follows: in, Design load for the front axle of the nth generation. The front axle load distribution factor is the design factor. Let be the front counterweight mass of the (n+1)th generation tractor.

[0007] In step two, the rear axle load of the tractor is calculated based on the spatial position and mass of the hydrogen storage tank, power battery, fuel cell and motor. The slip efficiency of the tractor is then calculated based on the rear axle load. If the slip efficiency does not meet the design requirements, the design load of the rear axle is calculated based on the tractor's operating mass. The counterweight is then optimized and adjusted based on the difference between the rear axle load and the design load until the design requirements for the tractor's slip rate are met.

[0008] The formulas for calculating the front axle wheelbase and rear axle load of the tractor are as follows: in, The front axle wheelbase of the nth generation tractor. For the front counterweight mass of the tractor, The mass of the rear counterweight of the nth generation tractor. The rear axle load is for the nth generation; the tractor slip efficiency is: in, Let n be the slip efficiency of the tractor in the nth generation. Characteristic slip ratio, This is the maximum load utilization factor for the drive wheels. For the tractor's driving force; the updated formulas for the tractor's rear axle design load and rear counterweight are: in, Design load for the rear axle of the nth generation. The rolling resistance coefficient, Let be the mass of the rear counterweight of the (n+1)th generation tractor.

[0009] In step three, the rated power of the dual motors and fuel cell to meet the tractor's power requirements is determined based on the plowing conditions, using the following formula: in, The power of motor A, The power of motor B, The speed of the tractor. For traction efficiency, For motor efficiency, Tractor transmission efficiency. Tractor rolling efficiency, For slip efficiency, The rolling resistance coefficient, For the quality of tractor use, It is the acceleration due to gravity. For tractor traction resistance, Let be the angle between the traction resistance and the horizontal plane; the rated power distribution of the two motors is expressed as: in, The power allocation ratio for the dual motors is set within a range of (0,1); the mass of the dual motors and fuel cell is obtained based on their power and power density, and is expressed as follows: in, For the power of motor A in the nth generation, For the power of motor B in the nth generation, For the mass of motor A in the nth generation, For the mass of motor B in the nth generation, For the quality of the nth generation dual motor, For the power density of the motor, This represents the discharge power of the nth generation fuel cell. For the mass of the nth generation fuel cell, This represents the power density of the fuel cell.

[0010] In step four, based on the operating condition information, an instantaneous optimization algorithm is used to obtain the optimal torque of the dual motors and the output power of the energy source composed of the fuel cell and the power battery. When the fuel cell tractor is in a steady-state operating condition and the fluctuation of the energy source output power does not exceed the liter power of the fuel cell, the fuel cell provides power. When the output power fluctuation exceeds the liter power of the fuel cell, the power battery makes up the difference in power. The energy consumption of the fuel cell and the power battery is calculated based on the power distribution of the fuel cell and the power battery, and then the mass of the fuel cell and the power battery is calculated based on the energy density of the fuel cell and the power battery.

[0011] The output power of the energy source consisting of the fuel cell and the power battery is obtained based on the speed, torque, and efficiency of the dual motors, and is expressed as: in, Let be the power of the energy source at time t. Let be the torque of motor A at time t. Let t be the torque of motor B. Let t be the speed of motor A. Let t be the speed of motor B. Let be the efficiency of motor A at time t. Let be the efficiency of motor B at time t; when the power output fluctuation of the energy source exceeds the power output of the fuel cell, the output power of the fuel cell and the power battery can be expressed as: in, Let be the fuel cell power at time t. Let be the power of the energy source at time t-1. Let t be the power of the battery. The maximum power output of the fuel cell is given by the given value. When the power output fluctuation of the energy source does not exceed the power output of the fuel cell, the output power of the fuel cell and the power battery can be expressed as: Using the energy consumption of fuel cell tractors as the objective function: in, For fuel cell tractors, For power battery energy consumption, For fuel cell energy consumption, This refers to the discharge power of the power battery. For fuel cell discharge power, For power battery efficiency, For fuel cell efficiency; the mass of the power battery and hydrogen storage tank is: in, For battery energy density, This refers to the energy density of the hydrogen storage tank.

[0012] In step five, within the given dual-motor power allocation ratio range, the dual-motor power allocation is considered complete when all predetermined allocation methods have been completed.

[0013] In step six, the difference between the mass of the hydrogen storage tank and battery generated by the genetic algorithm and the actual required mass can be expressed as: in, This represents the difference between the assumed mass of the hydrogen storage tank and the power battery and the actual required mass. For optimized power battery quality, For the optimized quality of hydrogen storage tanks.

[0014] The beneficial effects of this invention are: it links the design of tractor counterweight, power components, and energy storage components; it uses a genetic algorithm to synergistically optimize the spatial position and mass of the hydrogen storage tank, power battery, fuel cell, and motor with the counterweight; it improves traction performance while ensuring the stability of tractor operation; it optimizes the overall machine's performance; it reduces the overall machine manufacturing cost and improves energy efficiency; it achieves synergistic optimization of the mass and spatial position of each component of the fuel cell tractor with the power system parameters; and it can quickly obtain the mass and position information of each component of the fuel cell tractor and calculate reasonable power system parameters based on limited development data. Attached Figure Description

[0015] Figure 1 is a schematic diagram of the structure of a fuel cell tractor.

[0016] Figure 2 is a flowchart of the method for synergistic optimization of the mass and power system of the fuel cell tractor according to the present invention.

[0017] The markings in the diagram are: 1. Motor A, 2. Motor B, 3. Coupling device, 4. PTO reducer, 5. Power output shaft, 6. Main reducer, 7. Central transmission device. Detailed Implementation

[0018] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments. The specific contents listed in the following embodiments are not limited to the technical features necessary to solve the technical problem of the present invention. Furthermore, the listed embodiments are merely a part of the present invention, and not all embodiments.

[0019] As shown in Figure 1, the fuel cell tractor includes a hydrogen storage tank, a fuel cell, a DC / DC converter, a power battery, dual motors (motor A1 and motor B2), a coupling device 3, a PTO reducer 4, a power output shaft 5, a main reducer 6, a central transmission device 7, and wheels. The fuel cell tractor is driven by dual motors, with the fuel cell and power battery working together to provide power. At the initial design stage, the mass and spatial position of each component of the fuel cell tractor are unknown, making it impossible to accurately obtain the tractor's performance indicators. This invention proposes a tractor mass and position co-optimization method based on a genetic algorithm, integrating tractor counterweight design methods, energy storage component design methods, and power component design methods.

[0020] First, a genetic algorithm is used to generate a population containing the positions of the hydrogen storage tank, power battery, fuel cell, and motor, as well as the assumed masses of the hydrogen storage tank and power battery. Second, a counterweight design method is used to add counterweights to the front counterweight box and the rear drive wheel at determined locations to ensure the tractor's handling performance while improving its traction performance. Then, the power component design method and the energy storage component design method are used to optimize the design of the power component and the energy storage component. Finally, the difference between the masses of the hydrogen storage tank and power battery generated by the genetic algorithm and the masses of the hydrogen storage tank and power battery designed by the energy storage component is determined, and the optimization parameters with the minimum energy consumption are output. This completes the coordinated optimization of the mass and spatial position of each component of the fuel cell tractor with the parameters of the power system.

[0021] The specific optimization design process is shown in Figure 2.

[0022] Step 1: Given the effective mass and spatial location of the main structure of the fuel cell tractor, a population containing the spatial locations and masses of the hydrogen storage tank, power battery, fuel cell, and motor is generated using a genetic algorithm. Step 2: Using a counterweight design method, front and rear counterweights are added to the front counterweight box and the rear drive wheel side of the tractor, respectively. Based on the spatial locations and masses of the hydrogen storage tank, power battery, fuel cell, and motor, the loads on the front and rear axles during tractor operation are calculated to determine whether the tractor is within the designed drive wheel slip ratio range and maintains steering performance, thus meeting the front axle load distribution coefficient design requirements. The first step involves optimizing the initial counterweight mass to meet the tractor's slip efficiency design target, and then optimizing the subsequent counterweight mass. The third step involves inputting the tractor's predetermined operating condition information, including the population and front / rear axle counterweights, into the power component design method. Given the known positions of the tractor's front and rear counterweights, hydrogen storage tank, battery, fuel cell, and motor, as well as the masses of the front and rear counterweights, hydrogen storage tank, and battery, and the tractor's structural mass and spatial position, the power of the dual motors and fuel cell is obtained based on the operating condition information under dynamic performance constraints. The power of the dual motors is then allocated, and finally, the power and power density of the dual motors and fuel cell are considered. Step 4: Obtain the mass of the dual motors and fuel cell; Step 5: In the energy storage component design method, use an instantaneous optimization algorithm to obtain the optimal dual motor torque, then allocate the power of the fuel cell and battery according to the power requirements of the dual motors, and solve the energy consumption of the fuel cell, power battery, and tractor. Calculate the mass of the power battery and hydrogen storage tank based on the energy consumption of the power battery and fuel cell; Step 6: Determine whether the power allocation of the dual motors is complete. If complete, proceed to Step 7; if not, return to Step 8 and perform the power allocation of the dual motors again; Step 7: Based on the tractor energy consumption under different dual motor power allocation ratios, select the lowest energy... The optimal dual-motor power allocation ratio and the corresponding masses of the dual motors, fuel cell, power battery, and hydrogen storage tank are selected with energy consumption as the objective. The difference between the mass of the power battery and hydrogen storage tank generated by the genetic algorithm and the mass of the power battery and hydrogen storage tank obtained under the predetermined working conditions is compared. It is determined whether the absolute value of this difference is less than the set threshold C (minimum value). If it is satisfied, proceed to step seven. If it is not satisfied, return to step one and repeat the optimization process after updating the population through the genetic algorithm. Step seven: Output the mass and position of the front counterweight, rear counterweight, hydrogen storage tank, power battery, fuel cell, and motor, as well as the corresponding power system optimization parameters.

[0023] The specific methods for each step are as follows: 1. Tractor Counterweight Design Method: The counterweight mass of a tractor is unknown during operation. It is necessary to continuously adjust the front and rear counterweight masses based on the working conditions of the implements to make the load distribution between the front and rear axles of the tractor as close to the optimal state as possible. However, repeated installation and removal of counterweights is time-consuming and labor-intensive, affecting work efficiency. Furthermore, adjusting the front and rear counterweight masses by manually observing the tractor's operating state cannot achieve the optimal operating state. To solve this problem, a counterweight design method incorporating front and rear counterweight adjustment is proposed to obtain a tractor front and rear axle counterweight that meets the actual working conditions.

[0024] (1) Tractor front counterweight adjustment design: When the rear suspension implements are lifted by the tractor's three-point suspension device, the weight will be transferred from the front wheel to the rear wheel. Based on the spatial position and mass of the hydrogen storage tank, power battery, fuel cell and motor, the tractor's front axle load is calculated. The tractor's rear axle wheelbase and front axle load can be expressed as: (1) (2) In the formula, The rear axle wheelbase of the nth generation tractor. For the nth generation front axle load, For the quality of the nth generation tractor, For the quality of the power battery, For the quality of the motor, For the quality of fuel cells, For the quality of the hydrogen storage tank, For the overall structural quality, Let the mass of the front counterweight of the nth generation tractor be [value]. For the rear counterweight mass of the tractor, For the horizontal coordinates of the power battery, The horizontal coordinate of the motor For the horizontal coordinates of the fuel cell, The horizontal coordinates of the hydrogen storage tank are: The horizontal coordinates of the entire machine structure The horizontal coordinate of the rear counterweight; It is the acceleration due to gravity. For tractor wheelbase, The rolling resistance torque of the tractor's front wheels, The rolling resistance torque of the tractor's rear wheels, For tractor traction resistance, The height of the traction point. The horizontal distance from the traction point of the agricultural implement to the rear axle. The angle between the traction resistance and the horizontal plane.

[0025] The mass of the nth generation tractor is: (3) To stabilize the tractor's attitude and steering control and ensure stability during operation, the front axle load distribution coefficient of the tractor must be greater than or equal to 20%. The front axle design load is calculated based on the tractor's operating weight and the designed front axle load distribution coefficient. The front counterweight is then optimized and adjusted based on the difference between the front axle load and the front axle design load, as expressed in: (4) (5) Among them, Design load for the front axle of the nth generation. The front axle load distribution factor is the design factor. Let be the front counterweight mass of the (n+1)th generation tractor.

[0026] Update the tractor's operating weight, rear axle wheelbase, and front axle load based on the matched front counterweight: (6) (7) (8) Among them, For the (n+1)th generation tractor's operating mass, This refers to the rear axle wheelbase of the (n+1)th generation tractor. This is the front axle load of the (n+1)th generation.

[0027] Therefore, through continuous iteration and updates, it is eventually possible to achieve the design target for the front axle load distribution coefficient of the tractor when a suitable front counterweight is matched, thus ensuring the operational stability of the tractor.

[0028] (2) Tractor Rear Counterweight Adjustment Design: During heavy-duty operations such as plowing, an unreasonable axle load distribution or low-quality tractor can easily lead to a low drive axle load, resulting in a high slip rate of the tractor's drive wheels and affecting the tractor's traction performance. Therefore, it is necessary to adjust the rear counterweight according to the slip rate during operation to obtain optimal traction performance. Based on the spatial position and mass of the hydrogen storage tank, power battery, fuel cell, and motor, the tractor's rear axle load is calculated. The tractor's front axle wheelbase and rear axle load can be expressed as: (9) (10) Among them, The front axle wheelbase of the nth generation tractor. For the front counterweight mass of the tractor, The mass of the rear counterweight of the nth generation tractor. This is the rear axle load of the nth generation.

[0029] Calculate the tractor slip efficiency based on the rear axle load: (11) Among them, Let n be the slip efficiency of the tractor in the nth generation. Characteristic slip ratio, This is the maximum load utilization factor for the drive wheels. It provides the driving force for the tractor.

[0030] To improve the tractor's traction performance, the rear counterweight needs to be adjusted based on the slip ratio during operation. If the slip ratio does not meet the design requirements, the rear axle design load is calculated based on the tractor's operating weight, and the rear counterweight is optimized and adjusted based on the difference between the rear axle load and the rear axle design load, expressed as: (12) (13) Among them, Design load for the rear axle of the nth generation. The rolling resistance coefficient, Let be the mass of the rear counterweight of the (n+1)th generation tractor.

[0031] Update the tractor's operating weight, front axle wheelbase, and rear axle load based on the matched rear counterweight: (14) (15) (16) Among them, For the (n+1)th generation tractor's operating mass, This refers to the front axle wheelbase of the (n+1)th generation tractor. This is the rear axle load of the (n+1)th generation.

[0032] Therefore, through continuous iteration and updates, it is eventually possible to ensure that the slip ratio of the tractor's drive wheel reaches the design target under the condition of matching the appropriate tractor rear counterweight, thereby improving the tractor's traction performance.

[0033] It should be noted that in the first iteration of the genetic algorithm, the initial population does not generate a population of motor and fuel cell mass, and the mass of motor and fuel cell has not yet been updated using the power component design method. Therefore, in the first iteration, the front and rear counterweights can be matched as if the mass of motor and fuel cell is 0. The power component and energy storage component design can be carried out after the front and rear counterweights are updated.

[0034] This tractor counterweight design method effectively solves the problem of changes in performance caused by repeated counterweight adjustments during tractor design, improving tractor traction performance while ensuring operational stability.

[0035] 2. Power Component Design Method: The operating weight of a fuel cell tractor mainly consists of six parts: structural weight, motor weight, fuel cell weight, power battery weight, hydrogen storage tank weight, and counterweight weight. The optimization design of the front and rear counterweights is completed in the tractor counterweight design method, while the optimization of the hydrogen storage tank and power battery is completed in the energy storage component design method. Here, the power component design method is used to optimize the design of the fuel cell and motor. Given the positions of the tractor's front and rear counterweights, hydrogen storage tank, battery, fuel cell, and motor, as well as the masses, structural weights, and spatial positions of the front and rear counterweights, hydrogen storage tank, and battery, the power component design method can obtain reasonable motor and fuel cell masses based on performance constraints and operating condition information. The operating condition information refers to the operating parameters of a reference tractor with the same horsepower selected according to the tractor's design horsepower. For example, if the designed tractor is a 50-horsepower fuel cell tractor, then the reference tractor is also 50 horsepower, and the input specific operating condition information is the full-load plowing parameters of the reference 50-horsepower tractor. The power of the dual motors and fuel cell is matched based on the plowing parameters, and then the mass parameters of the power components are calculated. The optimal energy storage component parameters are obtained by using an instantaneous optimization algorithm based on the plowing parameters.

[0036] (1) Calculate the power of the motor and fuel cell: The power of the dual motors and fuel cell of the fuel cell tractor must meet the power requirements of the tractor. Since plowing is the heaviest working condition in tractor traction operations, the rated power design of the dual motors and fuel cell should meet the following requirements based on the plowing working condition: (17) (18) (19) (20) Among them, The power of motor A, The power of motor B, The speed of the tractor. For traction efficiency, For motor efficiency, Tractor transmission efficiency. Tractor rolling efficiency, For slip efficiency, The rolling resistance coefficient, For the quality of tractor use, It is the acceleration due to gravity. For tractor traction resistance, The angle between the traction resistance and the horizontal plane.

[0037] (2) Power distribution of dual motors in fuel cell tractors: Since the power distribution of dual motors affects the overall operating efficiency of the machine, it is necessary to reasonably optimize the rated power distribution of the motors. Therefore, the power distribution of dual motors can be expressed as follows: (twenty one) In equation (22), The power allocation ratio for the two motors is set to a range of (0,1).

[0038] (3) The mass of the motor and fuel cell is: In the design process, we assume that the power density of the motor and fuel cell is constant during the optimization process. Therefore, the mass of the motor and fuel cell can be calculated based on their power: (twenty three) (twenty four) (25) (26) Among them, For the power of motor A in the nth generation, For the power of motor B in the nth generation, For the mass of motor A in the nth generation, For the mass of motor B in the nth generation, For the quality of the nth generation dual motor, For the power density of the motor, This represents the discharge power of the nth generation fuel cell. For the mass of the nth generation fuel cell, This represents the power density of the fuel cell.

[0039] 3. Energy Storage Component Design Method: To reduce tractor manufacturing costs, an instantaneous optimization algorithm is employed in the energy storage component design method to improve the operating efficiency of the power system. Tractors often operate under low-speed, high-torque conditions; therefore, torque coupling is commonly used in dual-motor coupling devices. The speeds of the dual motors are calculated based on the vehicle speed, transmission ratio, and coupling ratio under the given operating conditions. After determining the speed, the required torque is calculated based on the plowing resistance and transmission ratio. Then, the torques of the dual motors (the torque range achievable by each motor at known speeds) are iterated and searched to find the optimal torque distribution and minimum energy consumption for each motor under different torque conditions. Finally, the optimal torque distribution and corresponding speed for each motor under different required torque conditions are output. Based on the known power distribution ratio of the dual motors in the fuel cell tractor and the optimized torque distribution, the energy consumption of the fuel cell and battery is calculated. Finally, hydrogen storage tanks and batteries of appropriate capacity and mass are matched according to the energy consumption.

[0040] (1) During the optimization process, the output power of the energy source composed of fuel cell and battery can be expressed by the speed, torque and efficiency of the dual motors as follows: (27) Among them, Let be the power of the energy source at time t. Let be the torque of motor A at time t. Let t be the torque of motor B. Let t be the speed of motor A. Let t be the speed of motor B. Let be the efficiency of motor A at time t. Let be the efficiency of motor B at time t.

[0041] (2) Fuel Cell and Battery Output Power Considering the poor dynamic performance of the fuel cell in the fuel cell tractor, when the operating power fluctuates significantly, the power battery assists the fuel cell in operation to maintain energy source output efficiency and extend the fuel cell's lifespan. When the motor output power fluctuation exceeds the fuel cell's output power, the power battery compensates for the power difference. The output power of the fuel cell and battery can be expressed as: (28) Among them, Let be the fuel cell power at time t. Let be the power of the energy source at time t-1. Let t be the power of the battery. This represents the maximum power output per liter of the fuel cell.

[0042] If the fuel cell tractor is in steady-state operation and the power fluctuation of the drive motor does not exceed the power output of the fuel cell, the output power of the fuel cell and the drive battery can be expressed as: (29) (3) Solving for tractor energy consumption: The energy consumption of fuel cells and power batteries, as well as the energy consumption of tractors, is as follows: The energy consumption of fuel cell tractors is expressed as: In equation (30), For fuel cell tractors, For power battery energy consumption, For fuel cell energy consumption, This refers to the discharge power of the power battery. For fuel cell discharge power, For power battery efficiency, For fuel cell efficiency.

[0043] (4) The mass of the power battery and hydrogen storage tank required to meet the overall machine requirements under specific operating conditions, calculated using the operating condition method, is as follows: (31) In equation (32), For the energy density of power batteries, This refers to the energy density of the hydrogen storage tank.

[0044] 4. The power distribution range of the dual motors in the objective function is set to (0,1). Within this range, the power is distributed proportionally according to a predetermined method. After each proportional distribution, the power component design method and the energy storage component design method are used for optimization.

[0045] To improve the operating efficiency of the fuel cell tractor power system, after all proportional allocations are completed, the minimum fuel cell tractor energy consumption is taken as the objective function: (33) Compare the energy consumption of tractors under different dual-motor power distribution ratios, select the dual-motor power distribution ratio with the lowest tractor energy consumption and the corresponding mass of dual motors, fuel cells, power batteries and hydrogen storage tanks, and use them as the parameters after this round of optimization.

[0046] Compare the differences between the population of power battery and hydrogen storage tank masses generated by the genetic algorithm and the optimized power battery and hydrogen storage tank masses under predetermined operating conditions: (34) Among them, This represents the difference between the assumed mass of the hydrogen storage tank and the power battery and the actual required mass. For optimized power battery quality, For the optimized quality of hydrogen storage tanks.

[0047] Determine if the absolute value of the value is less than the set threshold. If not, return to the first step of updating and generating the population through the genetic algorithm and repeat the optimization process. If it is satisfied, output the mass and position of the currently optimized front counterweight, rear counterweight, hydrogen storage tank, power battery, fuel cell and motor, as well as the corresponding power system optimization parameters.

[0048] As can be seen from the above optimization, the method of co-optimization of the mass and power system of fuel cell tractors can co-optimize and match suitable power components and energy storage devices, improve traction performance while ensuring the stability of tractor operation, achieve the optimal quality of the whole machine, reduce the manufacturing cost of the whole machine and improve energy consumption economy, and realize the co-optimization of the mass and spatial position of each component of fuel cell tractors with the parameters of the power system.

[0049] The above description of specific embodiments is only for the purpose of helping to understand the technical concept and core idea of ​​the present invention. Although specific preferred embodiments have been used to describe and illustrate the technical solutions, they should not be construed as limiting the present invention itself. Those skilled in the art can make various changes in form and detail without departing from the technical concept of the present invention. These easily conceived changes or substitutions should all be covered within the protection scope of the present invention.

Claims

1. A method for synergistic optimization of the mass and power system of a fuel cell tractor, wherein the fuel cell tractor is driven by dual motors, with the fuel cell and power battery providing power collaboratively. The method ensures the tractor's operational stability and traction performance by setting and optimizing the counterweight, and synergistically optimizes the spatial position and mass of the hydrogen storage tank, power battery, fuel cell, and motor based on power performance. The method is characterized by: The process includes the following steps: Step 1: Generate a population containing the spatial locations of the hydrogen storage tank, power battery, fuel cell, and motor, as well as the masses of the hydrogen storage tank and power battery, using a genetic algorithm; Step 2: Add front and rear counterweights to the front counterweight box and rear drive wheel sides of the tractor, respectively. Based on the spatial locations and masses of the hydrogen storage tank, power battery, fuel cell, and motor, optimize the front counterweight mass to meet the front axle load distribution coefficient design target, and optimize the rear counterweight mass to meet the tractor slip efficiency design target; Step 3: Input the tractor's predetermined operating condition information. Based on the optimized front and rear counterweight masses from Step 2, and the population containing the spatial locations and masses of the hydrogen storage tank, power battery, fuel cell, and motor generated in Step 1, obtain the power of the dual motors and fuel cell under dynamic performance constraints, and then allocate the power of the dual motors. Under this dual motor power allocation ratio, obtain the masses of the dual motors and fuel cell based on their power and power density; Step 4: Use an instantaneous optimization algorithm to obtain the optimal dual motor torque, and then, based on the predetermined operating condition... Under the condition of dual motor power demand, the power of fuel cell and power battery is allocated, and the energy consumption of fuel cell and power battery as well as tractor energy consumption are solved. Based on the energy consumption of power battery and fuel cell, the mass of power battery and hydrogen storage tank is calculated. Step 5: Determine whether the power allocation of dual motors is completed. If completed, proceed to step 6. If not completed, return to step 3 and perform dual motor power allocation again. Step 6: Based on the tractor energy consumption under different dual motor power allocation ratios, select the optimal dual motor power allocation ratio and the corresponding mass of dual motors, fuel cell, power battery and hydrogen storage tank with the goal of minimum energy consumption. Compare the population of power battery and hydrogen storage tank mass generated by genetic algorithm with the mass of power battery and hydrogen storage tank obtained under the predetermined working condition. Determine whether the absolute value of the difference is less than the set threshold. If satisfied, proceed to step 7. If not satisfied, return to step 1 and repeat the optimization process after updating the population through genetic algorithm. Step 7: Output the mass and position of front counterweight, rear counterweight, hydrogen storage tank, power battery, fuel cell and motor and the corresponding power system optimization parameters.

2. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 1, characterized in that: In step two, the front axle load of the tractor is calculated based on the spatial position and mass of the hydrogen storage tank, power battery, fuel cell and motor. The front axle design load is calculated based on the tractor's operating mass and the designed front axle load distribution coefficient. The front counterweight is then optimized and adjusted based on the difference between the front axle load and the front axle design load. The front axle load is then recalculated based on the adjusted front counterweight until the front counterweight meets the design requirements of the front axle load distribution coefficient.

3. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 2, characterized in that: The formulas for calculating the rear axle wheelbase and front axle load of the tractor are as follows: in, The rear axle wheelbase of the nth generation tractor. For the nth generation front axle load, For the quality of the nth generation tractor, For the quality of the power battery, For the quality of the motor, For the quality of fuel cells, For the quality of the hydrogen storage tank, For the overall structural quality, Let the mass of the front counterweight of the nth generation tractor be [value]. For the weight of the tractor's rear counterweight, For the horizontal coordinates of the power battery, The horizontal coordinate of the motor For the horizontal coordinates of the fuel cell, The horizontal coordinates of the hydrogen storage tank are: The horizontal coordinates of the entire machine structure The horizontal coordinate of the rear counterweight; It is the acceleration due to gravity. For tractor wheelbase, The rolling resistance torque of the tractor's front wheels, The rolling resistance torque of the tractor's rear wheels, For tractor traction resistance, The height of the traction point. The horizontal distance from the traction point of the agricultural implement to the rear axle. The angle between the traction resistance and the horizontal plane; the mass of the nth generation tractor is: Calculate the front axle design load based on the designed front axle load distribution coefficient, and adjust the front counterweight accordingly. The formula is as follows: in, Design load for the front axle of the nth generation. The front axle load distribution factor is the design factor. Let be the front counterweight mass of the (n+1)th generation tractor.

4. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 3, characterized in that: In step two, the rear axle load of the tractor is calculated based on the spatial position and mass of the hydrogen storage tank, power battery, fuel cell and motor. The slip efficiency of the tractor is then calculated based on the rear axle load. If the slip efficiency does not meet the design requirements, the design load of the rear axle is calculated based on the tractor's operating mass. The counterweight is then optimized and adjusted based on the difference between the rear axle load and the design load until the design requirements for the tractor's slip rate are met.

5. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 4, characterized in that: The formulas for calculating the front axle wheelbase and rear axle load of the tractor are as follows: in, The front axle wheelbase of the nth generation tractor. For the front counterweight mass of the tractor, The mass of the rear counterweight of the nth generation tractor. The rear axle load is for the nth generation; the tractor slip efficiency is: in, Let n be the slip efficiency of the tractor in the nth generation. Characteristic slip ratio, This is the maximum load utilization factor for the drive wheels. For the tractor's driving force; the updated formulas for the tractor's rear axle design load and rear counterweight are: in, Design load for the rear axle of the nth generation. The rolling resistance coefficient, Let be the mass of the rear counterweight of the (n+1)th generation tractor.

6. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 1, characterized in that: In step three, the rated power of the dual motors and fuel cell to meet the tractor's power requirements is determined based on the plowing conditions, using the following formula: in, The power of motor A, The power of motor B, The speed of the tractor. For traction efficiency, For motor efficiency, Tractor transmission efficiency. Tractor rolling efficiency For slip efficiency, The rolling resistance coefficient, For the quality of tractor use, It is the acceleration due to gravity. For tractor traction resistance, Let be the angle between the traction resistance and the horizontal plane; the rated power distribution of the two motors is expressed as: in, The power allocation ratio for the dual motors is set within a range of (0,1); the mass of the dual motors and fuel cell is obtained based on their power and power density, and is expressed as follows: in, For the power of motor A in the nth generation, For the power of motor B in the nth generation, For the mass of motor A in the nth generation, For the mass of the nth generation motor B, For the quality of the nth generation dual motor, For the power density of the motor, This represents the discharge power of the nth generation fuel cell. For the mass of the nth generation fuel cell, This represents the power density of the fuel cell.

7. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 1, characterized in that: In step four, based on the operating condition information, an instantaneous optimization algorithm is used to obtain the optimal torque of the dual motors and the output power of the energy source composed of the fuel cell and the power battery. When the fuel cell tractor is in a steady-state operating condition and the fluctuation of the energy source output power does not exceed the liter power of the fuel cell, the fuel cell provides power. When the output power fluctuation exceeds the liter power of the fuel cell, the power battery makes up the difference in power. The energy consumption of the fuel cell and the power battery is calculated based on the power distribution of the fuel cell and the power battery, and then the mass of the fuel cell and the power battery is calculated based on the energy density of the fuel cell and the power battery.

8. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 7, characterized in that: The output power of the energy source consisting of the fuel cell and the power battery is obtained based on the speed, torque, and efficiency of the dual motors, and is expressed as: in, Let be the power of the energy source at time t. Let be the torque of motor A at time t. Let t be the torque of motor B. Let t be the speed of motor A. Let t be the speed of motor B. Let be the efficiency of motor A at time t. Let be the efficiency of motor B at time t; when the power output fluctuation of the energy source exceeds the power output per liter of the fuel cell, the output power of the fuel cell and the power battery are expressed as: in, Let be the fuel cell power at time t. Let be the power of the energy source at time t-1. Let t be the power of the battery. The maximum power output of the fuel cell is given by: When the power output fluctuation of the energy source does not exceed the power output of the fuel cell, the output power of the fuel cell and the power battery are expressed as: Using the energy consumption of fuel cell tractors as the objective function: in, For fuel cell tractors, For power battery energy consumption, For fuel cell energy consumption, This refers to the discharge power of the power battery. For fuel cell discharge power, For power battery efficiency, For fuel cell efficiency; the mass of the power battery and hydrogen storage tank is: in, For battery energy density, This refers to the energy density of the hydrogen storage tank.

9. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 1, characterized in that: In step five, within the given dual-motor power allocation ratio range, the dual-motor power allocation is considered complete when all predetermined allocation methods have been completed.

10. The method for synergistic optimization of the mass and power system of a fuel cell tractor as described in claim 1, characterized in that: In step six, the difference between the mass of the hydrogen storage tank and battery generated by the genetic algorithm and the actual required mass is expressed as: in, This represents the difference between the assumed mass of the hydrogen storage tank and the power battery and the actual required mass. For optimized power battery quality, For the optimized quality of hydrogen storage tanks.

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