Hybrid unmanned aerial vehicle energy control method, equipment and product based on methanol fuel

Abstract

The invention provides a hybrid unmanned aerial vehicle energy control method, device and product based on methanol fuel, and relates to the technical field of unmanned aerial vehicle control. The method comprises the steps that state parameters representing the current working state of the hybrid unmanned aerial vehicle are acquired; determining the total demand power of the hybrid unmanned aerial vehicle according to the state parameters; determining a first target power of a methanol fuel cell carried by the hybrid unmanned aerial vehicle and a second target power of a lithium battery carried by the hybrid unmanned aerial vehicle according to the total demand power and the state parameters; determining a first power instruction corresponding to the methanol fuel cell and a second power instruction corresponding to the lithium battery according to the first target power and the second target power; and controlling the methanol fuel cell to operate according to the first power instruction and the lithium battery to operate according to the second power instruction. In this way, the problem that energy conversion efficiency is insufficient due to the fact that a traditional unmanned aerial vehicle energy control mode is not flexible enough in energy control can be solved.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) control technology, and more specifically, to a method, device, and product for energy control of a hybrid UAV based on methanol fuel. Background Technology

[0002] With the rapid development of drone technology, diverse drones have gradually penetrated various industries. They have particularly broad applications and value in agriculture, transportation, and military industries, and with their low cost and high efficiency, they are gradually becoming irreplaceable tools in various sectors.

[0003] In the field of drone technology, drones powered by hydrogen fuel cells, methanol fuel cells, and other similar fuel cells are widely used due to their long range and low emissions. To further improve the range and operational stability of drones, some drones have adopted a hybrid power system combining fuel cells and lithium batteries. This hybrid system fully utilizes the range of fuel cells and the rapid response capability of lithium batteries to compensate for the shortcomings of a single power system and improve the overall performance of the drone's power system.

[0004] However, existing hybrid drones, especially those that use methanol fuel as their main power source, lack flexibility in energy control during operation and suffer from insufficient energy conversion efficiency. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide a method, device and product for energy control of a hybrid drone based on methanol fuel, which can improve the problem that the traditional drone energy control method is not flexible enough in energy control and thus has insufficient energy conversion efficiency.

[0006] To achieve the above technical objectives, the technical solution adopted in this application is as follows:

[0007] In a first aspect, embodiments of this application provide an energy control method for a hybrid unmanned aerial vehicle (UAV) based on methanol fuel, the method comprising:

[0008] Obtain the state parameters that characterize the current operating state of the hybrid drone;

[0009] The total power demand of the hybrid drone is determined based on the state parameters.

[0010] Based on the total power demand and the state parameters, determine the first target power of the methanol fuel cell carried by the hybrid drone and the second target power of the lithium battery carried by the hybrid drone;

[0011] Based on the first target power and the second target power, a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery are determined.

[0012] The methanol fuel cell is controlled to operate at the first power command, and the lithium battery is controlled to operate at the second power command.

[0013] In conjunction with the first aspect, in some optional implementations, the state parameters include stage parameters characterizing the flight phase of the hybrid UAV, environmental disturbance parameters characterizing the impact of the flight environment on the hybrid UAV, and maneuver parameters characterizing the impact of the flight commands on the hybrid UAV.

[0014] Determining the total power requirement of the hybrid drone based on the state parameters includes:

[0015] Based on the stage parameters, determine the base power corresponding to the stage parameters;

[0016] The total required power is determined based on the base power, the environmental disturbance parameters, and the maneuver parameters.

[0017] In conjunction with the first aspect, in some optional embodiments, the state parameter includes the current state of charge of the lithium battery;

[0018] Based on the total power demand and the state parameters, determine the first target power of the methanol fuel cell carried by the hybrid drone and the second target power of the lithium battery carried by the hybrid drone, including:

[0019] Based on the current state of charge, an equivalence factor is determined, which characterizes the conversion efficiency of converting the electrical energy of the lithium battery into methanol fuel.

[0020] Based on the equivalence factor and the total required power, the first target power and the second target power are determined, wherein the total required power is the sum of the first target power and the second target power.

[0021] In conjunction with the first aspect, in some optional implementations, determining the first target power and the second target power based on the equivalence factor and the total required power includes:

[0022] With the constraints that the current state of charge is within a first preset interval, the first target power is within a second preset interval, and the second target power is within a third preset interval, the following equation is solved to obtain the first target power:

[0023]

[0024] In the formula, This represents the first target power at the current moment. This indicates the fuel consumption rate at the current moment. Indicates the equivalent factor. This represents the second target power at the current moment. Indicates the low calorific value of the fuel;

[0025] The difference between the total required power and the first target power is determined as the second target power.

[0026] In conjunction with the first aspect, in some optional embodiments, determining a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery based on the first target power and the second target power includes:

[0027] The first target power is subjected to a first-order low-pass filter to generate a smoothing command, which is used as the first power command.

[0028] The difference between the total power demand and the actual output power of the methanol fuel cell is determined as the second power command.

[0029] In conjunction with the first aspect, in some optional embodiments, determining a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery based on the first target power and the second target power further includes:

[0030] Based on the second target power and the preset fluctuation margin, the second power command is limited to become a new second power command.

[0031] In conjunction with the first aspect, in some alternative implementations, the method further includes:

[0032] When the current state of charge in the state parameters is lower than the preset state of charge, a prompt message indicating insufficient power is issued.

[0033] When the methanol fuel content in the status parameters is lower than the preset fuel content, a prompt message indicating insufficient fuel is issued.

[0034] Secondly, embodiments of this application also provide an electronic device, which includes a processor and a memory coupled to each other. The memory stores a computer program, and when the computer program is executed by the processor, the electronic device performs the above-described method.

[0035] Thirdly, embodiments of this application also provide a computer program product, including a computer program that implements the above-described method when executed by a processor.

[0036] The invention employing the above technical solution has the following advantages:

[0037] The technical solution provided in this application first acquires state parameters and determines the total power demand of the hybrid drone based on these parameters. Then, based on the total power demand and state parameters, a first target power for the methanol fuel cell carried by the hybrid drone and a second target power for the lithium battery carried by the hybrid drone are determined. Next, based on the first and second target power, a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery are determined. Finally, the methanol fuel cell is controlled to operate under the first power command, and the lithium battery is controlled to operate under the second power command. In this way, the output power of the methanol fuel cell and lithium battery can be flexibly adjusted based on the real-time state of the hybrid drone, improving the energy utilization rate of the fuel cell and addressing the problem of insufficient energy conversion efficiency caused by the inflexible energy control of traditional drone energy control methods. Attached Figure Description

[0038] This application can be further illustrated by the non-limiting embodiments given in the accompanying drawings. It should be understood that the following drawings only illustrate some embodiments of this application and should not be considered as limiting the scope. For those skilled in the art, other related drawings can be obtained from these drawings without any inventive effort.

[0039] Figure 1 A structural block diagram of an electronic device provided in an embodiment of this application.

[0040] Figure 2 A flowchart illustrating the energy control method for a methanol-fueled hybrid unmanned aerial vehicle provided in this application embodiment.

[0041] Icons: 100 - Electronic device; 101 - Processor; 102 - Memory. Detailed Implementation

[0042] The present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that similar or identical parts are referred to by the same reference numerals in the drawings or description. Implementations not shown or described in the drawings are forms known to those skilled in the art. In the description of this application, terms such as "first" and "second" are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0043] Please refer to Figure 1 This application provides an electronic device 100 that may include a processor 101 and a memory 102. The memory 102 stores a computer program, which, when executed by the processor 101, enables the electronic device 100 to perform the corresponding steps in the following methanol-fueled hybrid unmanned aerial vehicle energy control method.

[0044] In this embodiment, the processor 101 can be an integrated circuit chip with signal processing capabilities. The processor 101 can be a general-purpose processor. For example, the processor 101 can be a central processing unit (CPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0045] The memory 102 can be, but is not limited to, random access memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, etc. In this embodiment, the memory can be used to store state parameters, total power demand, first target power, second target power, first power instruction, second power instruction, etc. Of course, the memory 102 can also be used to store programs, which the processor 101 executes after receiving an execution instruction.

[0046] Understandable, Figure 1 The electronic device 100 shown is only a schematic diagram; the electronic device 100 may also include components that are more... Figure 1 More components are shown. Figure 1 The components shown can be implemented using hardware, software, or a combination thereof.

[0047] In this embodiment, the electronic device 100 may be a controller for the hybrid drone, a console communicatively connected to the hybrid drone, a motion controller, etc. It is used to acquire state parameters characterizing the current operating state of the hybrid drone, and determine the total power demand of the hybrid drone based on the state parameters. Then, based on the total power demand and the state parameters, it determines a first target power for the methanol fuel cell carried by the hybrid drone, and a second target power for the lithium battery carried by the hybrid drone. Then, based on the first and second target power, it determines a first power command corresponding to the methanol fuel cell, and a second power command corresponding to the lithium battery. Finally, it controls the methanol fuel cell to operate according to the first power command, and the lithium battery to operate according to the second power command.

[0048] Please refer to Figure 2This application also provides an energy control method for a methanol-fueled hybrid unmanned aerial vehicle (UAV), which can be applied to the aforementioned electronic device 100, and the electronic device 100 executes or implements the steps of the method. The methanol-fueled hybrid UAV energy control method may include the following steps:

[0049] Step 210: Obtain the state parameters that characterize the current working state of the hybrid UAV;

[0050] Step 210: Determine the total power demand of the hybrid drone based on the state parameters;

[0051] Step 210: Based on the total power demand and the state parameters, determine the first target power of the methanol fuel cell carried by the hybrid drone and the second target power of the lithium battery carried by the hybrid drone;

[0052] Step 210: Based on the first target power and the second target power, determine the first power command corresponding to the methanol fuel cell and the second power command corresponding to the lithium battery;

[0053] Step 210: Control the methanol fuel cell to operate at the first power command and the lithium battery to operate at the second power command.

[0054] In the above implementation, state parameters are first acquired, and the total power demand of the hybrid drone is determined based on these parameters. Then, based on the total power demand and state parameters, a first target power for the methanol fuel cell carried by the hybrid drone and a second target power for the lithium battery carried by the hybrid drone are determined. Next, based on the first and second target power, a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery are determined. Finally, the methanol fuel cell is controlled to operate under the first power command, and the lithium battery is controlled to operate under the second power command. In this way, the output power of the methanol fuel cell and lithium battery can be flexibly adjusted based on the real-time state of the hybrid drone, improving the energy utilization rate of the fuel cell and addressing the problem of insufficient energy conversion efficiency caused by the inflexible energy control of traditional drone energy control methods.

[0055] The steps of the energy control method for methanol-fueled hybrid drones will be described in detail below:

[0056] In step 210, the state parameters may include stage parameters characterizing the flight phase of the hybrid UAV, environmental disturbance parameters characterizing the impact of the hybrid UAV's flight environment, maneuver parameters characterizing the impact of the hybrid UAV's flight commands, and the current state of charge of the lithium battery. Each state parameter can be sensed by the front-end sensors mounted on the UAV and uploaded in real time to the processor 101 of the aforementioned electronic device 100 for further processing; alternatively, the state parameters can be acquired during the early testing phase of this technical solution, whereby the user pre-inputs various data simulating the UAV's operating state, stores them in the memory 102 of the aforementioned electronic device 100, and then invokes them through the processor 101 based on user commands during subsequent method execution. The specific method for acquiring the state parameters is not limited here.

[0057] In step 220, determining the total power requirement of the hybrid drone based on the state parameters may include:

[0058] Based on the stage parameters, determine the base power corresponding to the stage parameters;

[0059] The total required power is determined based on the base power, the environmental disturbance parameters, and the maneuver parameters.

[0060] In this embodiment, the hybrid UAV can be determined to be in any stage of flight, including takeoff and climb, high-power cruise, normal cruise, maneuvering (such as turning and obstacle avoidance), or descent and landing, based on its attitude and a preset flight profile. The corresponding stage parameters are then determined. Based on these stage parameters, the base power of the UAV corresponding to each flight stage is retrieved from a preset lookup table. In this embodiment, the environmental disturbance parameters can be flexibly adjusted according to changes in the environment in which the hybrid UAV is located, and the maneuvering parameters can be flexibly adjusted according to maneuvering commands issued by the user based on the processor 101. In this embodiment, wind speed is used as an example for environmental disturbance parameters, and acceleration is used as an example for maneuvering parameters.

[0061] Then, based on the base power, environmental disturbance parameters, and maneuver parameters, the total power demand is determined:

[0062] (1)

[0063] In the formula, express Total power demand at any given moment This indicates the base power corresponding to the current flight phase. , These represent the acceleration power coefficient related to the mass and efficiency of the drone, and the drag power coefficient related to aerodynamics, respectively. , These represent acceleration and wind speed, respectively. This indicates the variable power of the payload (such as gimbal, communication equipment, etc.) when the hybrid drone performs a flight mission.

[0064] In step 230, the first target power of the methanol fuel cell carried by the hybrid drone and the second target power of the lithium battery carried by the hybrid drone are determined based on the total required power and the state parameters, which may include:

[0065] Based on the current state of charge, an equivalence factor is determined, which characterizes the conversion efficiency of converting the electrical energy of the lithium battery into methanol fuel.

[0066] Based on the equivalence factor and the total required power, the first target power and the second target power are determined, wherein the total required power is the sum of the first target power and the second target power.

[0067] In this embodiment, the equivalent factor is first dynamically adjusted based on the current state of charge of the lithium battery, so that the energy consumption / storage of the lithium battery is equivalent to the consumption of methanol fuel. The algorithm for adjusting the equivalent factor is as follows:

[0068] (2)

[0069] In the formula, Indicates the equivalent factor. The benchmark equivalence factor is typically determined by the ratio of the average efficiency of a methanol fuel cell to the average charge-discharge efficiency of a lithium battery. This represents the adjustment factor, used to maintain the state of charge of the lithium battery near the midpoint (e.g., 60%, 50%). This represents the target value of the desired state of charge to be maintained. Indicates the current state of charge.

[0070] After determining the equivalence factor, the first target power and the second target power are determined based on the equivalence factor and the total required power.

[0071] In this embodiment, determining the first target power and the second target power based on the equivalence factor and the total required power may include:

[0072] With the constraints that the current state of charge is within a first preset interval, the first target power is within a second preset interval, and the second target power is within a third preset interval, the following equation is solved to obtain the first target power:

[0073] (3)

[0074] In the formula, This represents the first target power at the current moment. This indicates the fuel consumption rate at the current moment. Indicates the equivalent factor. This represents the second target power at the current moment. Indicates the low calorific value of the fuel;

[0075] The difference between the total required power and the first target power is determined as the second target power.

[0076] In this embodiment, constraints are first established, namely power balance: ,in, express The first target power at any given time, express Second target power at any given time; Lithium battery state of charge limitation: ,in, Indicates the first preset range; methanol fuel cell power limit: ,in, Indicates the second preset range; Lithium battery power limit: ,in, This indicates the third preset interval.

[0077] Then, based on the above constraints, with the goal of minimizing methanol fuel consumption, the objective function shown in equation (3) is solved to obtain the optimal solution for the first target power. The optimal solution is then used as the final first target power value. The total required power is then subtracted from the first target power to obtain the second target power.

[0078] In this way, the energy conversion and utilization of methanol fuel cells can be maximized, thereby improving the endurance of hybrid drones.

[0079] In step 240, determining the first power command corresponding to the methanol fuel cell and the second power command corresponding to the lithium battery based on the first target power and the second target power may include:

[0080] The first target power is subjected to a first-order low-pass filter to generate a smoothing command, which is used as the first power command.

[0081] The difference between the total power demand and the actual output power of the methanol fuel cell is determined as the second power command.

[0082] In this embodiment, after determining the first target power and the second target power, the first target power is subjected to a first-order low-pass filter to obtain a smooth power command, which is used as the first power command.

[0083] (4)

[0084] In the formula, This represents the time constant, which can be flexibly set according to the dynamic response capability of the methanol fuel cell (usually on the order of seconds). Indicates the first power command. This indicates the first target power.

[0085] In this embodiment, since the actual power output of the methanol fuel cell typically responds slowly and cannot accurately track the total power demand, after the hybrid UAV controls the output power of the methanol fuel cell based on the first power command, the actual output power of the methanol fuel cell is obtained, and the lithium battery handles all the rapid power fluctuations to ensure the stability of the bus voltage. Therefore, the second power command is the difference between the total power demand and the actual output power of the methanol fuel cell.

[0086] (5)

[0087] In the formula, Indicates the second power command. Indicates the total power demand. This indicates the actual output power of the methanol fuel cell.

[0088] In this way, the performance and safety of the drone's power supply system are guaranteed through the rapid compensation of lithium batteries, and the high-frequency, sudden power "peak shaving and valley filling" work is achieved by lithium batteries.

[0089] In this embodiment, to ensure the safe operation of the lithium battery, the second power command also needs to be limited and monitored based on the second target power. The limiting and monitoring rules are as follows:

[0090] (6)

[0091] In the formula, This indicates a new second power command. It is a dynamic fluctuation margin preset by the user (i.e., preset fluctuation margin), which ensures the rapid compensation capability of the lithium battery and prevents it from deviating too much from the optimal operating power.

[0092] In step 250, after determining the first power command for the methanol fuel cell and the second power command for the lithium battery, the actuators mounted on the hybrid drone control the methanol fuel cell to operate under the first power command and the lithium battery to operate under the second power command. This achieves flexible control of the hybrid drone's power supply system (mainly including the methanol fuel cell and lithium battery), maximizing the conversion of the methanol fuel cell's energy into the hybrid drone's kinetic energy, avoiding energy waste, and simultaneously improving the hybrid drone's range.

[0093] As an optional implementation, the method may further include:

[0094] When the current state of charge in the state parameters is lower than the preset state of charge, a prompt message indicating insufficient power is issued.

[0095] When the methanol fuel content in the status parameters is lower than the preset fuel content, a prompt message indicating insufficient fuel is issued.

[0096] In this embodiment, when the lithium battery is low on power or the methanol fuel cell is low on fuel, a warning message indicating low power or low fuel is issued via the hybrid drone or a warning device (such as a display, buzzer, or audible and visual alarm) on the hybrid drone's controller. This provides timely alerts when the hybrid drone malfunctions due to insufficient lithium battery power or insufficient methanol fuel cell fuel, prompting the user to charge or replenish fuel, thus preventing work losses such as drone crashes or operational interruptions.

[0097] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the electronic device 100 described above can be referred to the corresponding process of each step in the aforementioned method, and will not be elaborated further here.

[0098] This application also provides a computer program product, including a computer program that, when executed by processor 101, implements the methanol-fuel-based hybrid drone energy control method as described in the above embodiments.

[0099] Based on the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by hardware or by using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This software product can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various implementation scenarios of this application.

[0100] In summary, this application provides an energy control method, device, and product for a hybrid unmanned aerial vehicle (UAV) based on methanol fuel. In this technical solution, state parameters are first acquired, and the total power demand of the hybrid UAV is determined based on these parameters. Then, based on the total power demand and state parameters, a first target power for the methanol fuel cell carried by the hybrid UAV and a second target power for the lithium battery carried by the hybrid UAV are determined. Next, based on the first and second target power, a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery are determined. Finally, the methanol fuel cell is controlled to operate under the first power command, and the lithium battery is controlled to operate under the second power command. In this way, the output power of the methanol fuel cell and the lithium battery can be flexibly adjusted based on the real-time state of the hybrid UAV, improving the energy utilization rate of the fuel cell and addressing the problem of insufficient energy conversion efficiency caused by the lack of flexibility in traditional UAV energy control methods.

[0101] In the embodiments provided in this application, it should be understood that the disclosed methods can also be implemented in other ways. The method embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or part of code, which includes one or more executable instructions for implementing a specified logical function. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0102] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An energy control method for a hybrid unmanned aerial vehicle (UAV) based on methanol fuel, characterized in that, The method includes: Obtain the state parameters that characterize the current operating state of the hybrid drone; The total power demand of the hybrid drone is determined based on the state parameters. Based on the total power demand and the state parameters, determine the first target power of the methanol fuel cell carried by the hybrid drone and the second target power of the lithium battery carried by the hybrid drone; Based on the first target power and the second target power, a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery are determined. The methanol fuel cell is controlled to operate at the first power command, and the lithium battery is controlled to operate at the second power command.

2. The method according to claim 1, characterized in that, The state parameters include stage parameters characterizing the flight phase of the hybrid UAV, environmental disturbance parameters characterizing the impact of the flight environment on the hybrid UAV, and maneuver parameters characterizing the impact of the flight commands on the hybrid UAV. Determining the total power requirement of the hybrid drone based on the state parameters includes: Based on the stage parameters, determine the base power corresponding to the stage parameters; The total required power is determined based on the base power, the environmental disturbance parameters, and the maneuver parameters.

3. The method according to claim 1, characterized in that, The state parameters include the current state of charge of the lithium battery; Based on the total power demand and the state parameters, determine the first target power of the methanol fuel cell carried by the hybrid drone and the second target power of the lithium battery carried by the hybrid drone, including: Based on the current state of charge, an equivalence factor is determined, which characterizes the conversion efficiency of converting the electrical energy of the lithium battery into methanol fuel. Based on the equivalence factor and the total required power, the first target power and the second target power are determined, wherein the total required power is the sum of the first target power and the second target power.

4. The method according to claim 3, characterized in that, Determining the first target power and the second target power based on the equivalence factor and the total required power includes: With the constraints that the current state of charge is within a first preset interval, the first target power is within a second preset interval, and the second target power is within a third preset interval, the following equation is solved to obtain the first target power: In the formula, This represents the first target power at the current moment. This indicates the fuel consumption rate at the current moment. Indicates the equivalent factor. This represents the second target power at the current moment. Indicates the low calorific value of the fuel; The difference between the total required power and the first target power is determined as the second target power.

5. The method according to claim 1, characterized in that, Based on the first target power and the second target power, a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery are determined, including: The first target power is subjected to a first-order low-pass filter to generate a smoothing command, which is used as the first power command. The difference between the total power demand and the actual output power of the methanol fuel cell is determined as the second power command.

6. The method according to claim 5, characterized in that, Based on the first target power and the second target power, determining a first power command corresponding to the methanol fuel cell and a second power command corresponding to the lithium battery further includes: Based on the second target power and the preset fluctuation margin, the second power command is limited to become a new second power command.

7. The method according to claim 1, characterized in that, The method further includes: When the current state of charge in the state parameters is lower than the preset state of charge, a prompt message indicating insufficient power is issued. When the methanol fuel content in the status parameters is lower than the preset fuel content, a prompt message indicating insufficient fuel is issued.

8. An electronic device, characterized in that, The electronic device includes a processor and a memory coupled together, the memory storing a computer program that, when executed by the processor, causes the electronic device to perform the method as described in any one of claims 1-7.

9. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1-7.

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