Methanol generator set-battery hybrid power system mode switching control system and method

Abstract

The invention discloses a methanol generator set-battery hybrid power system mode switching control system and method, belongs to the field of ship hybrid power systems, and aims to solve the problem that mode management control is performed according to battery SOC and energy storage module power distribution in an existing hybrid power mode switching method, but the characteristic of multiple working conditions of a push ship is not considered. And thus, the obtained switching control strategy is not optimal. The system comprises a working condition judgment module for judging the working condition of the ship; the data processing module is used for determining proportions of different working conditions according to historical navigation data; the control strategy module is used for selecting an optimal operation mode by taking the battery SOC, the battery temperature, the power and the working condition proportion as evaluation factors; and the monitoring module is used for continuously monitoring the ship navigation condition after the working mode is changed and feeding back the monitoring data to the working condition judgment module for re-judgment. The method is suitable for switching control of different modes of the push boat of the methanol generator set-battery hybrid power system.

Description

Technical Field

[0001] The present invention belongs to the field of ship hybrid power systems, and in particular relates to a mode switching control system and a control method for a methanol generator set-battery hybrid power system. Background Art

[0002] Current research on hybrid power systems and control strategies focuses primarily on theoretical analysis such as energy efficiency calculation and energy conservation and emission reduction. However, research on the scientific classification of hybrid power system propulsion modes and energy management control strategies is less in-depth. For pusher boats, which have multiple operating conditions, studying hybrid power system switching control strategies is a key technology for achieving optimal performance and a core component of energy management systems. The degree of sophistication of strategy design directly determines the overall system's economy, power, and emissions. Existing hybrid power mode switching methods generally manage and control the mode based on battery SOC and energy storage module power allocation. These methods fail to consider the multi-operating characteristics of pusher boats, resulting in suboptimal switching control strategies.

[0003] This paper proposes a method for switching between different propulsion modes for a methanol generator-battery hybrid system, taking into account the proportion of different propulsion conditions. The methanol generator-battery hybrid system, consisting of a methanol engine, batteries, and a propulsion motor, has three operating modes: battery-only power, generator-only power, and combined battery and generator power.

[0004] The operating conditions of push boats can be summarized into the following three types: self-propelled condition, which refers to the situation where no barges are pushed; fully loaded condition, which refers to the most commonly used operating condition of push boats; and extreme condition, which refers to the most extreme operating condition of the ship and cannot push any more barges. Summary of the Invention

[0005] In order to solve the problem that the existing hybrid power mode switching method mostly performs mode management and control based on the battery SOC and energy storage module power distribution, but does not consider the multi-working condition characteristics of the pusher itself, resulting in a suboptimal switching control strategy.

[0006] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, the present invention provides a methanol generator set-battery hybrid system mode switching control system, the control system comprising: A working condition judgment module for judging the working condition of the ship; A data processing module for determining the proportion of different operating conditions based on historical navigation data; A control strategy module used to select the optimal operating mode based on battery SOC, battery temperature, power, and operating condition ratio as evaluation factors; A monitoring module that continuously monitors the ship's navigation conditions after changing the working mode, and feeds the monitoring data back to the working condition judgment module for further judgment.

[0007] In a second aspect, the present invention further provides a method for controlling mode switching of a methanol generator set-battery hybrid power system. The method is implemented based on the above control system and includes: Step S1: Obtain ship resistance and speed and the number of barges , judge the working condition of the ship; Step S2: Analyze the proportion of the total sailing time occupied by different operating conditions according to the operating conditions of the ship, and determine the proportion of different operating conditions; Step S3: Constructing an operation mode switching strategy based on fuzzy comprehensive evaluation logic rules; Step S4: Taking battery SOC, battery temperature, power, and the proportion of different operating conditions as influencing factors, the constructed operating mode switching strategy is used to perform weight distribution, affiliation, and comprehensive evaluation on the influencing factors to obtain the optimal operating mode.

[0008] Furthermore, the operating conditions of the above-mentioned ship include self-propelled operating conditions, fully loaded operating conditions and extreme operating conditions.

[0009] Furthermore, the above step S1 is specifically as follows: like , , it is the self-propelled condition; like and , then it is full load condition; like or , then it is the extreme working condition.

[0010] in, To trigger the minimum resistance of full load condition, , is the resistance of the pusher itself, is the resistance experienced by the barge itself; It is the upper limit of resistance under full load condition.

[0011] Furthermore, the time proportion of different operating conditions of the pusher during actual navigation is used as the key weight factor, and is input into the fuzzy rule base together with the weights of battery SOC, temperature, and power demand for comprehensive evaluation.

[0012] Furthermore, the above operating condition proportion weight is a dynamic weight.

[0013] Furthermore, the above step S4 is specifically as follows: The analytic hierarchy process was used to determine the relative weights of each factor on the three operating modes and obtain the comprehensive weights; The fuzzy comprehensive evaluation method is used to comprehensively judge the comprehensive weights of multiple factors through the membership function to obtain the optimal operation mode.

[0014] Furthermore, the above-mentioned operating modes include a generator set operating mode, a pure battery operating mode and a methanol generator set-battery hybrid operating mode.

[0015] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, executes any one of the above-mentioned methanol generator set-battery hybrid power system mode switching control methods.

[0016] In a fourth aspect, the present invention also provides a computer device comprising a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes any one of the above-mentioned methanol generator set-battery hybrid system mode switching control methods.

[0017] The beneficial effects of the present invention are: The present invention provides a methanol generator set-battery hybrid system mode switching control system and control method. This method considers the switching control method of different modes of the pusher propulsion system based on the proportion of different operating conditions of the pusher. The proportion of time of different operating conditions of the pusher during actual navigation is used as a key weight factor. This factor is input into a fuzzy rule library together with the weights of the battery SOC, temperature, and power demand for comprehensive evaluation. The weight distribution of battery SOC, battery temperature, and power is evaluated according to the hierarchical analysis method, and the most suitable operating mode is selected based on the fuzzy comprehensive evaluation. For example, during the free navigation phase, the battery is mainly used to provide power. However, if the data processing module predicts that a longer free navigation phase will follow, the control strategy will select the generator set operating mode to reduce repeated switching of operating modes. At the same time, the control strategy will be adjusted based on real-time detection feedback, continuously updating and adjusting the weights of each operating condition, and continuously optimizing the navigation status.

[0018] The present invention is applied to the switching control of different modes of a pusher boat of a methanol generator set-battery hybrid power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is a circuit diagram of the methanol generator set-battery hybrid power system of the present invention; Figure 2 This is a structural diagram of the mode switching control system of the methanol generator set-battery hybrid power system of the present invention; Figure 3 This is a flow chart of the mode switching control method of the methanol generator set-battery hybrid power system described in the present invention. DETAILED DESCRIPTION

[0021] In the following description, the specific implementation details of the "Methanol Generator Set-Battery Hybrid Power System Mode Switching Control System and Method" provided in this specification (such as experimental equipment, operating procedures, data processing steps and example parameters) are for illustrative purposes rather than restrictive definitions, and are intended to help those skilled in the art to thoroughly understand the principles and implementation of the present invention; however, those skilled in the art should be clear that these details only represent one of the feasible embodiments, and the core concept of the present invention can be fully implemented through other technical means or workarounds that are not fully described without departing from its spirit, and the omission of conventional experimental methods and device details known in the art in the specification is to avoid redundant information interfering with the understanding of the innovative points. This does not mean that these known technologies are not required for implementation, and technical personnel should be able to supplement and apply them on their own based on professional knowledge.

[0022] The specific embodiments of the present invention are further described below in conjunction with the accompanying drawings. The following embodiments will help those skilled in the art further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that those skilled in the art may make various changes and improvements without departing from the scope of the present invention, and these are all within the scope of protection of the present invention.

[0023] Implementation Method 1: Combination Figure 1 and Figure 2 This embodiment is described. To solve the problem that the existing hybrid power mode switching method mostly performs mode management and control based on the battery SOC and energy storage module power distribution, but does not consider the characteristics of the pusher ship's own multi-operating conditions, resulting in a suboptimal switching control strategy. Therefore, a methanol generator set-battery hybrid power system mode switching control system is proposed. Figure 2As shown, the control system includes a working condition judgment module, a data processing module, a control strategy module and a monitoring module; The working condition judgment module is used to judge the working condition of the ship; The data processing module is used to determine the proportion of different working conditions based on historical navigation data; The control strategy module is used to select the optimal operating mode based on battery SOC, battery temperature, power, and operating condition ratio as evaluation factors; The monitoring module is used to continuously monitor the navigation status of the ship after changing the working mode, and feed the monitoring data back to the working condition judgment module for further judgment.

[0024] The hybrid power system described in this embodiment is composed of a methanol engine group, a battery, a propulsion motor, etc., and has three working modes.

[0025] Mode 1: Generator set working mode.

[0026] The power demand of the push ship load fluctuates slightly and is between the maximum and minimum output power of the methanol generator. The methanol generator set needs to bear the load power of the entire ship, such as Figure 1 As shown in the figure, power is transmitted to the propulsion motor through the AC / DC converter and DC / AC inverter, which drives the propeller to rotate, allowing the ship to sail normally. This is the most commonly used mode for pushing a boat.

[0027] Mode 2: Pure battery working mode.

[0028] Ships require relatively low propulsion power, making pure battery operation suitable. In this mode, the methanol generator operates at idle speed, with the battery pack providing the full ship load. This mode is often used when pushing a ship near a port.

[0029] Mode 3: Methanol generator set-battery hybrid mode.

[0030] The methanol engine maintains power output within its high-efficiency range, and the remaining insufficient power is supplemented by batteries to meet navigation requirements.

[0031] In actual application, the working condition judgment module monitors the ship's resistance , speed , number of barges The ship's operating conditions are determined, including self-propelled, fully loaded, and extreme conditions. The data in the data processing module mirrors the data collected by the monitoring module, including data such as resistance and speed. The ship spends varying amounts of time in different operating conditions. The time spent in each condition is determined, and the proportion of each condition's total voyage time is statistically analyzed to determine the condition's contribution. Conditions with higher time contributions are assigned higher weights. Conditions with higher weights receive higher priority in the evaluation process, favoring the preferred operating mode (e.g., preferring generator or hybrid mode under full load / extreme conditions). This allows the system to more accurately select the mode that best suits the prevailing operating conditions, reducing unnecessary mode switching and improving system efficiency and stability under key operating conditions. The voyage time statistics for this section represent historical voyage data from the past 24 hours, and the weights for the operating conditions are periodically updated based on the most recent voyage time data. The control strategy module establishes an operating mode switching strategy based on fuzzy comprehensive evaluation logic to achieve efficient control of the energy system under different operating modes. Battery SOC, battery temperature, power, and operating condition ratio all have varying impacts on the hybrid system. These factors are weighted, correlated, and comprehensively evaluated to ultimately select the appropriate operating mode. The monitoring module continues to monitor the ship's navigational conditions after changing operating modes, ensuring control accuracy and response speed. This data is then collected and fed back to the operating condition assessment module for further assessment to optimize system efficiency and stability.

[0032] Implementation Method 2: Combination Figure 3 This embodiment provides a method for controlling mode switching of a methanol generator set-battery hybrid system. The control method is implemented based on the control system described in the first embodiment. Figure 3 As shown, the control method includes the following steps: Step S1: Obtain ship resistance , speed and the number of barges , judge the working condition of the ship; Step S2: Analyze the proportion of the total sailing time occupied by different operating conditions according to the operating conditions of the ship, and determine the proportion of different operating conditions; Step S3: Constructing an operation mode switching strategy based on fuzzy comprehensive evaluation logic rules; Step S4: Taking battery SOC, battery temperature, power, and the proportion of different operating conditions as influencing factors, the constructed operating mode switching strategy is used to perform weight distribution, affiliation, and comprehensive evaluation on the influencing factors to obtain the optimal operating mode.

[0033] Implementation 3: This implementation is to specifically describe the mode switching control method of a methanol generator set-battery hybrid power system described in Implementation 2 above; Step S1: Obtain ship resistance , speed and the number of barges , judge the working condition of the ship; Specifically: Get ship resistance , speed and the number of barges , judge the working condition of the ship, and the judgment boundaries of each working condition are: like , , it is the self-propelled condition; like and , then it is full load condition; like or , then it is the extreme working condition.

[0034] in, To trigger the minimum resistance of full load condition, , is the resistance of the pusher itself, is the resistance experienced by the barge itself; It is the upper limit of resistance under full load condition.

[0035] The self-propelled condition refers to the situation where there is no barge being pushed, which is a light-load mode. The resistance encountered is the resistance encountered by the pushing boat itself, and the speed is generally stable and fast; the fully loaded condition refers to the condition that the pushing boat is most often in. The resistance in this condition is the resistance encountered by the pushing boat itself and the pushed barge, and the speed is generally lower than the speed in the self-propelled condition; the extreme mode refers to the situation where the ship is heavily loaded and cannot push more barges. The resistance in this condition is the resistance encountered by the pushing boat itself and the pushed barge, and the speed is generally lower than the speed in the fully loaded condition.

[0036] Step S2: Analyze the proportion of the total sailing time occupied by different operating conditions according to the operating conditions of the ship, and determine the proportion of different operating conditions; Specifically: By collecting historical navigation data for the past 24 hours, the proportion of total navigation time occupied by different operating conditions is analyzed to determine the proportion of each operating condition. The duration of time a ship spends in different operating conditions varies, and the proportion of time occupied by each operating condition in the total navigation time is calculated and statistically analyzed to determine the proportion of each operating condition. Conditions with higher time proportions are given higher weights. The preferred operating mode corresponding to these conditions (such as the preference for generator set or hybrid mode under full load / extreme conditions) is given higher priority in the evaluation. This makes the system more likely to select the mode that best suits the characteristics of the primary operating condition, reduces unnecessary mode switching, and improves the system's efficiency and stability under key operating conditions.

[0037] Step S3: Constructing an operation mode switching strategy based on fuzzy comprehensive evaluation logic rules; Step S4: Taking battery SOC, battery temperature, power, and the proportion of different operating conditions as influencing factors, the constructed operating mode switching strategy is used to perform weight distribution, affiliation, and comprehensive evaluation on the influencing factors to obtain the optimal operating mode.

[0038] Specifically: The time proportion of different operating conditions of the pusher boat during actual navigation is taken as the key weight factor and input into the fuzzy rule base together with the weights of battery SOC, temperature and power demand for comprehensive evaluation.

[0039] The analytic hierarchy process was used to determine the relative weights of each factor on the three operating modes and obtain the comprehensive weights; The fuzzy comprehensive evaluation method is used to comprehensively judge the comprehensive weights of multiple factors through the membership function to obtain the optimal operation mode.

[0040] During actual operation, an operating mode switching strategy based on fuzzy comprehensive evaluation logic rules is established to achieve efficient control of the energy system under different operating modes. Battery SOC, battery temperature, power, and operating mode ratio have different impacts on the hybrid system. These factors are selected and weighted, and their relationships are determined through comprehensive evaluation to ultimately select the appropriate operating mode.

[0041] The time proportion of different operating conditions of the pusher boat (self-propelled, fully loaded, and extreme) in actual navigation is taken as the key weight factor and introduced into the fuzzy comprehensive evaluation logic of the hybrid power system mode switching.

[0042] The operating condition weight is a dynamically changing input factor obtained by the data processing module. In the fuzzy comprehensive evaluation, this dynamic weight is input into the fuzzy rule base along with the weights for battery SOC, temperature, and power demand.

[0043] The following is an introduction to the weight allocation method and the fuzzy comprehensive evaluation method: Weight distribution: The analytic hierarchy process is used to determine the relative weights of each factor for the three operating modes and obtain the comprehensive weights.

[0044] Related formulas of analytic hierarchy process: The judgment matrix A is:

[0045] in, For indicators and The ratio of Relative to The importance of The weight vector Multiplying the matrix A on the right yields:

[0046] Expressed in matrix, that is:

[0047] According to mathematical principles, there is a unique non-zero maximum characteristic , the largest characteristic root The corresponding eigenvector , so we only need to output The maximum eigenvalue and eigenvector of , and the eigenvector corresponding to the maximum eigenvalue is the weight value of each corresponding indicator.

[0048] The fuzzy comprehensive evaluation method proposed in this embodiment is a statistical calculation method based on the principles of fuzzy mathematics and using a membership function to perform comprehensive evaluation on a multi-factor complex system.

[0049] Fuzzy comprehensive evaluation mainly consists of the following three elements: (a) Establishing a set of evaluation indicators and factors

[0050] The evaluation object factor set is the various indicators contained in the evaluation object (battery SOC, battery temperature, power, and proportion of different working conditions). The collection of these indicators becomes the evaluation object indicator set, which is recorded as .

[0051] (b) Determine the weight vector of the evaluation object indicators

[0052] The weight value is the importance of each indicator relative to the target. Different indicators have different importance. The corresponding weight value should be given according to its importance , a set of indicator vector weight values .

[0053] The fuzzy vector is expressed as ,This control method uses the hierarchical analysis method to obtain the index weight vector.

[0054] (c) Constructing a review rating set

[0055] The performance of the hybrid propulsion system is evaluated at m levels, and the set of these evaluation levels is called the evaluation level set Experts judge based on the level of comments Perform fuzzy judgment on each indicator.

[0056] The number of comment levels m is usually greater than 4 and less than 9. If the value of m is too large, there will be too many comment levels, which will exceed people's ability to distinguish and judge. If the value of m is too small, it cannot correctly reflect the actual situation and accuracy requirements of fuzzy comprehensive evaluation. Commonly used comment levels are odd numbers, such as very good, good, average, poor, very poor, etc. For fuzzy concepts that are difficult to judge, the middle value is often taken.

[0057] (d) Single factor fuzzy comprehensive evaluation The set of evaluation object indicators and factors Calculate the membership of each evaluation indicator according to the corresponding membership function, or assign the index factor to the evaluation index according to the evaluation level. The membership of the evaluation object is evaluated. Relative to the review level The membership degree is recorded as , so the single factor comprehensive fuzzy vector is .

[0058] (e) Establishing the fuzzy relationship matrix Perform fuzzy comprehensive evaluation on all indicators in the indicator factor set, and obtain the single factor fuzzy evaluation vector as follows: , so the indicator factor set and review level set The fuzzy comprehensive evaluation matrix of the membership relationship between them is:

[0059] (f) Multi-level comprehensive evaluation The comprehensive calculation model of fuzzy comprehensive evaluation is:

[0060] in, It is a fuzzy matrix composed of the target program and the evaluation level. is the weight vector corresponding to the scheme indicator, A set of indicators for program evaluation Relative to the review level The corresponding fuzzy membership matrix is ​​actually a function mapping relationship matrix, " is the fuzzy comprehensive evaluation operator symbol, also known as the synthesis operator. The comprehensive index of the scheme obtained through fuzzy comprehensive evaluation is is a one-dimensional vector, by comparison The optimal solution is obtained by taking the value of .

[0061] (g) Evaluation results Maximum membership method: The judgment results The corresponding solution is the optimal solution, that is, the final evaluation result is:

[0062] Weighted average method: Think Weight, the corresponding program set indicator elements The evaluation results are obtained by weighted average, namely:

[0063] Fuzzy comprehensive evaluation often uses ratings to process qualitative indicators and standardization to process quantitative indicators. When processing quantitative indicators, in order to eliminate differences in dimensions and units, the evaluation indicators are usually dimensionless, so that each quantitative indicator can be standardized and unified.

[0064] In summary, the methanol generator set-battery hybrid system mode switching control method described in this embodiment proposes a switching control method for different modes of the pusher propulsion system that takes into account the proportion of different pusher operating conditions. The proportion of time spent in different pusher operating conditions during actual navigation is used as a key weighting factor. This factor, along with the weights of the battery SOC, temperature, and power demand, is input into a fuzzy rule library for comprehensive evaluation. The weight distribution of battery SOC, battery temperature, and power is evaluated using the analytic hierarchy process, and the most suitable operating mode is selected based on the fuzzy comprehensive evaluation. For example, during the free navigation phase, power is primarily provided by the battery. However, if the data processing module predicts that a longer free navigation phase will follow, the control strategy will select the generator set operating mode to reduce repeated switching of operating modes. The control strategy will also be adjusted based on real-time detection feedback, continuously updating and adjusting the weights of each operating condition to continuously optimize navigation status.

[0065] Embodiment 4: This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the methanol generator set-battery hybrid system mode switching control method described in any one of the above embodiments is executed.

[0066] Embodiment 5. This embodiment provides a computer device, which includes a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes the methanol generator set-battery hybrid system mode switching control method described in any one of the above embodiments.

[0067] This embodiment provides a computer device, in which the hardware device of this part is a general model and is not shown in the form of a diagram. The system includes a processor and a memory, wherein the processor and the memory can be connected via a bus or other means. The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs, non-transient computer executable programs and modules, and corresponding program instructions / modules. The processor executes various functional applications and data processing of the processor by running the non-transient software programs, instructions and modules stored in the memory, so as to realize the methanol generator set-battery hybrid system mode switching control method and steps in the above method embodiment.

[0068] The foregoing description is merely an embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of the claims.

Claims

1. Methanol generator set-battery hybrid system mode switching control system, characterized in that: include: A working condition judgment module for judging the working condition of the ship; A data processing module for determining the proportion of different operating conditions based on historical navigation data; A control strategy module used to select the optimal operating mode based on battery SOC, battery temperature, power, and operating condition ratio as evaluation factors; A monitoring module that continuously monitors the ship's navigation conditions after changing the working mode, and feeds the monitoring data back to the working condition judgment module for further judgment.

2. The control method for implementing the mode switching control system of the methanol generator set-battery hybrid system according to claim 1 is characterized in that: The method is: S1: Get ship resistance , speed and the number of barges , judge the working condition of the ship; S2: According to the working conditions of the ship, analyze the proportion of the total sailing time occupied by different working conditions and determine the proportion of different working conditions; S3: Construct an operation mode switching strategy based on fuzzy comprehensive evaluation logic rules; S4: Taking battery SOC, battery temperature, power, and the proportion of different operating conditions as influencing factors, the constructed operating mode switching strategy is used to perform weight distribution, affiliation, and comprehensive evaluation of the influencing factors to obtain the optimal operating mode.

3. The methanol generator set-battery hybrid power system mode switching control method according to claim 2, characterized in that: The operating conditions include self-propelled conditions, full-load conditions and extreme conditions.

4. The methanol generator set-battery hybrid power system mode switching control method according to claim 3, characterized in that: S1 is specifically: like , , it is the self-propelled condition; like and , then it is full load condition; like or , then it is the extreme working condition. in, To trigger the minimum resistance of full load condition, , is the resistance of the pusher itself, is the resistance experienced by the barge itself; It is the upper limit of resistance under full load condition.

5. The methanol generator set-battery hybrid power system mode switching control method according to claim 2, characterized in that: The time proportion of different operating conditions of the pusher boat during actual navigation is taken as the key weight factor and input into the fuzzy rule base together with the weights of battery SOC, temperature and power demand for comprehensive evaluation.

6. The methanol generator set-battery hybrid power system mode switching control method according to claim 5, characterized in that: The weight of the working condition ratio is a dynamic weight.

7. The methanol generator set-battery hybrid power system mode switching control method according to claim 5, characterized in that: S4 is specifically: The analytic hierarchy process was used to determine the relative weights of each factor on the three operating modes and obtain the comprehensive weights; The fuzzy comprehensive evaluation method is used to comprehensively judge the comprehensive weights of multiple factors through the membership function to obtain the optimal operation mode.

8. The methanol generator set-battery hybrid power system mode switching control method according to claim 7, characterized in that: The operating modes include generator set working mode, pure battery working mode and methanol generator set-battery hybrid mode.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the methanol generator set-battery hybrid power system mode switching control method according to any one of claims 2 to 8.

10. A computer device, characterized in that: The device includes a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes the methanol generator set-battery hybrid power system mode switching control method according to any one of claims 2 to 8.

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