Energy Management Method for a Hybrid Power System Based on a Proton Exchange Membrane Fuel Cell

Abstract

The present invention provides an energy management method for a hybrid power system based on a proton exchange membrane fuel cell, which relates to the technical field of energy management. The specific steps include: obtaining key parameters during the operation of the fuel cell, calculating an environmental impact index, an electric energy evaluation index, and a power response index based on the key parameters; constructing a comprehensive evaluation model according to the environmental impact index, the electric energy evaluation index, and the power response index to generate a comprehensive energy management index; comparing the comprehensive energy management index with a preset threshold, and formulating a real-time energy allocation strategy according to the comparison result, and applying a genetic algorithm to further optimize the energy allocation strategy. The present invention realizes multi-dimensional analysis and evaluation of system performance. The constructed comprehensive evaluation model enables the energy management strategy to comprehensively consider environmental factors and energy use efficiency, ensuring the best performance of the system under different loads.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management, and particularly to an energy management method for a hybrid power system based on a proton exchange membrane fuel cell. Background Technique

[0002] A proton exchange membrane fuel cell (PEMFC) is an efficient and clean electric energy conversion device, which is widely used in fields such as transportation, stationary power supplies, and portable devices. Its core advantage lies in being able to use hydrogen as fuel and directly generate electric energy through an electrochemical reaction, and the emissions of this reaction are only water. However, in practical applications, PEMFC still faces many technical challenges, especially in terms of energy management and system response performance. Under dynamic load conditions, the output power of the fuel cell needs to be quickly adjusted to meet the demand changes, so as to ensure the performance and stability of the system. However, traditional energy management strategies often lack real-time performance and flexibility, and cannot effectively cope with the system instability caused by load fluctuations, resulting in a reduction in the battery working efficiency and possible energy waste.

[0003] In addition, most current energy management methods are based on static models and fail to effectively consider the influence of environmental factors and various operating states on system performance. For example, environmental variables such as temperature, humidity, and gas flow have a significant impact on the working efficiency of fuel cells, but existing technologies usually lack real-time monitoring and comprehensive analysis of these parameters. Therefore, in practical applications, the system cannot achieve a rapid response to environmental changes, resulting in a reduction in the electric energy use efficiency and an increase in environmental impact. At the same time, existing methods also have deficiencies in power response, especially when facing instantaneous load changes, the system cannot adjust the power distribution in a timely manner. These deficiencies not only affect the overall performance and service life of fuel cells, but also restrict their promotion and application in a wider range of application fields. Therefore, it is urgent to develop new energy management methods to achieve efficient coordination and optimization of fuel cells and other energy storage devices, thereby improving the comprehensive performance of the system.

[0004] The above information disclosed in the background technique section is only used to strengthen the understanding of the background of the present disclosure, so it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide an energy management method for a hybrid power system based on a proton exchange membrane fuel cell to solve the problems raised in the above background technique.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] An energy management method for a hybrid power system based on a proton exchange membrane fuel cell, the specific steps include:

[0008] Step 1: Monitor and analyze the operating state of the fuel cell to obtain key parameters. The key parameters include temperature, humidity, current, voltage, gas flow rate, and the actual response time of the system. Calculate the load power based on the current and voltage data.

[0009] Step 2: Calculate the environmental impact index based on the dimensionless temperature, humidity, and gas flow rate data; calculate the electrical energy evaluation index based on the dimensionless load power data; calculate the power response index based on the dimensionless load power and actual response time.

[0010] Step 3: Construct a comprehensive evaluation model according to the environmental impact index, electrical energy evaluation index, and power response index of the battery to be evaluated. Generate the weights within the comprehensive evaluation model through the analytic hierarchy process, and use the comprehensive evaluation model to generate the comprehensive energy management index.

[0011] Step 4: Compare the comprehensive energy management index with a preset threshold, and formulate a real-time energy allocation strategy based on the comparison result. Apply the genetic algorithm to further optimize the energy allocation strategy.

[0012] Furthermore, implement a time synchronization mechanism to ensure that the data of all the following sensors are collected under the same timestamp:

[0013] Use an NTC thermistor to obtain the operating temperature of the PEMFC, denoted as ;

[0014] Use a humidity sensor to obtain the humidity of the PEMFC operating environment, denoted as ;

[0015] Use a current sensor to monitor the current flowing through the fuel cell and the load, denoted as ;

[0016] Use a voltage sensor to monitor the voltage of the fuel cell and the load, denoted as ;

[0017] Install a flow meter between the gas source and the fuel cell stack to collect gas flow rate data, denoted as ;

[0018] The actual response time of the system, that is, the time delay required for the system to adjust its state when the system receives a new load change signal. The specific logic for obtaining the actual response time is as follows:

[0019] When the system receives a new load change signal, record this moment , after the system responds, monitor the time when the current and voltage data reach a stable state : ; Among them, is the actual response time;

[0020] The load power is calculated using the following formula: where is the load power at the current moment, is the voltage value at the current moment, is the current value at the current moment, is the power factor at the current moment, is the total harmonic distortion;

[0021] is obtained by: sampling the voltage signal using a digital instrument with a sampling frequency 10 times the highest frequency of the signal and satisfying the Nyquist sampling theorem. For the collected time-domain signal, it is converted to a frequency-domain signal using the fast Fourier transform to obtain the amplitudes of each harmonic component. For each harmonic, its effective value is calculated according to the following formula: ; where is the effective value of the harmonic, is the time required for the signal to complete one full waveform, is the signal value at the moment within one full waveform time, is the time variable within one full waveform time;

[0022] Using the above formula for calculating the effective value of the harmonic, calculate the effective value of the fundamental wave and the effective value of the a-th harmonic, where a represents the harmonic index. Among them, , represents the total number of the fundamental wave and harmonics, and substitute the calculation results into the following calculation formula: ; where is the total harmonic distortion, is the effective value of the fundamental wave, that is, the effective value of the first harmonic, is the effective value of the a-th harmonic, .

[0023] Furthermore, calculate the environmental impact index according to the following formula: ; where is the environmental impact index, is the current temperature, is the temperature threshold, is the current humidity, is the humidity threshold, is the current gas flow data, is the gas flow threshold, is the denominator adjustment constant. When or or When it is zero, the corresponding denominator adjustment constant is 1. or or When it is not zero, the corresponding denominator adjustment constant is 0. is the preset proportional coefficient;

[0024] The electric energy evaluation index is calculated according to the following formula: ;in, is the electric energy assessment index, is the load power, is the efficiency factor, is the input power, i.e. the total input power of the fuel cell;

[0025] The calculation formula is: ;in, It indicates the highest efficiency that the system can achieve under ideal conditions. is the current gas flow data, Indicates the gas flow data under ideal conditions;

[0026] The power response index is calculated according to the following formula: ;in, is the power response index, is the load power, is the expected power, is the maximum output power, is the actual response time, The maximum response time designed for the system, is the scaling factor used to adjust the effect of the power difference on the power response index, It is an adjustment factor used to balance the impact of response time on the power response index.

[0027] Furthermore, a comprehensive evaluation model is constructed based on the environmental impact index, electric energy evaluation index and power response index of the system to be evaluated. The model expression is as follows: ;in, is the comprehensive energy management index, is the environmental impact index, is the electric energy assessment index, is the power response index, is the proportionality coefficient.

[0028] Furthermore, the specific logic of generating the weights in the comprehensive evaluation model through the hierarchical analysis method is as follows:

[0029] Mark the three indicators of the environmental impact index, the electric energy evaluation index, and the power response index, determine the relative importance values between each pair through the nine-scale method, and construct a judgment matrix. Among them, mark the index of the environmental impact index as 1, the index of the electric energy evaluation index as 2, and the index of the power response index as 3. The constructed judgment matrix is: ; where, both represent the index of the index, and , represents that the index with is more important than the index with index , and ;

[0030] Divide each element value in the judgment matrix by the sum of its column to obtain the normalized judgment matrix. Calculate the mean value of each row element value in the normalized judgment matrix, and take the mean value of the first row element value as the weight of the environmental impact index, the mean value of the second row element value as the weight of the electric energy evaluation index, and the mean value of the third row element value as the weight of the power response index. Under the constraint that the sum of the scaled values is equal to 1, scale the three weights proportionally, and take the scaled weights as the proportional coefficients of the corresponding indices.

[0031] Furthermore, compare the comprehensive energy management index with the preset threshold:

[0032] If , continue to adopt the current energy allocation strategy, set the main energy source in the system as the fuel cell, and give priority to using the fuel cell;

[0033] If , use the supercapacitor to quickly respond to load changes;

[0034] where, is the comprehensive energy management index, is the preset index evaluation threshold;

[0035] Apply the genetic algorithm to further optimize the energy allocation strategy. The specific logic is as follows:

[0036] Set a sample set containing n individuals, where each individual represents an energy allocation strategy, indicating the power allocation ratio between the fuel cell and the supercapacitor under different load conditions. For each individual, calculate its corresponding environmental impact index, electrical energy evaluation index, and power response index, and use the maximum and minimum values of the environmental impact index, electrical energy evaluation index, and power response index in the sample set as constraints. Randomly generate an initial population, input the individuals into the comprehensive evaluation model to obtain the corresponding comprehensive energy management index, sort the individuals in descending order according to the comprehensive energy management index, select the individuals at the forefront of the ranking as parents and perform crossover and mutation operations to obtain new individuals. After integrating the newly generated individuals and the individuals serving as parents as a new population, repeat the selection, crossover, and mutation operations until the predetermined number of iterations is reached. Select the individual with the largest comprehensive energy management index as the optimal parameter combination, and adjust the current energy allocation strategy according to the power allocation ratio in the optimal parameter combination.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0038] The present invention obtains the operating state of the system by real-time monitoring of key parameters such as temperature, humidity, current, and voltage, and calculates the environmental impact index, electrical energy evaluation index, and power response index based on dimensionless processing, so as to realize the multi-dimensional analysis and evaluation of the system performance. The constructed comprehensive evaluation model enables the energy management strategy to comprehensively consider environmental factors and energy use efficiency, ensuring the best performance of the system under different loads. At the same time, the genetic algorithm is applied to optimize the energy allocation strategy, enabling the system to flexibly adapt to instantaneous load changes and improving the response speed and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0040] Figure 2 It is a schematic diagram of the genetic algorithm of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0041] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the following further details the present invention with reference to specific embodiments.

[0042] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those with ordinary skills in the field to which the present invention pertains. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "comprising" or "including" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0043] Embodiment

[0044] Please refer to Figure 1 , the present invention provides a technical solution:

[0045] An energy management method for a hybrid power system based on a proton exchange membrane fuel cell, the specific steps include:

[0046] Step 1: Monitor and analyze the operating state of the fuel cell to obtain key parameters, where the key parameters include temperature, humidity, current, voltage, gas flow rate and the actual response time of the system, and calculate the load power through the current and voltage data;

[0047] In this embodiment, an implementation time synchronization mechanism is adopted to ensure that the data of all the following sensors are collected under the same timestamp:

[0048] Use an NTC thermistor to obtain the operating temperature of the PEMFC, denoted as ;

[0049] Use a humidity sensor to obtain the humidity of the operating environment of the PEMFC, denoted as ;

[0050] Use a current sensor to monitor the current flowing through the fuel cell and the load, denoted as ;

[0051] Use a voltage sensor to monitor the voltage of the fuel cell and the load, denoted as ;

[0052] Install a flowmeter between the gas source and the fuel cell stack to collect gas flow rate data, denoted as ;

[0053] The actual response time of the system, i.e., the time delay required for the system to adjust its state after receiving a new load change signal. The specific logic for obtaining the actual response time is as follows:

[0054] When the system receives a new load change signal, record the time , after the system responds, monitor the time when the current and voltage data reach a stable state : Among them, is the actual response time;

[0055] Use the following formula to calculate the load power: Among them, is the load power at the current moment, is the voltage value at the current moment, is the current value at the current moment, is the power factor at the current moment, is the total harmonic distortion;

[0056] The acquisition method of is as follows: Use a digital instrument to sample the voltage signal, the sampling frequency is 10 times the highest frequency of the signal and satisfies the Nyquist sampling theorem. For the collected time-domain signal, use the fast Fourier transform to convert it into a frequency-domain signal to obtain the amplitudes of each harmonic component. For each harmonic, calculate its effective value according to the following formula: ; among them, is the effective value of the harmonic, is the time required for the signal to complete one full waveform, is the signal value at the moment within one full waveform time,

[0057] Use the above harmonic effective value calculation formula to calculate the effective value of the fundamental wave and the effective value of the a-th harmonic, where a represents the index of the harmonic. Among them, , represents the total number of the fundamental wave and harmonics, and substitute the calculation results into the following calculation formula: ; among them, is the total harmonic distortion, is the effective value of the fundamental wave, i.e., the effective value of the first harmonic, is the effective value of the a-th harmonic, .

[0058] Step 1 comprehensively monitors and analyzes the operating state of the fuel cell to obtain key parameters, and calculates the load power using these data. This real-time monitoring mechanism ensures the accuracy and timeliness of the data, providing a solid foundation for subsequent energy management decisions. Compared with existing technologies, this method not only improves the comprehensiveness and accuracy of data collection but also can quickly respond under complex dynamic load conditions, avoiding system instability and energy waste problems caused by data lag in traditional methods.

[0059] In the patent solution, implementing Step 1 can significantly enhance the effectiveness of the overall solution. Through real-time monitoring and data analysis, it ensures the optimal performance and energy usage efficiency of the system under different operating conditions. This provides reliable data support for the comprehensive evaluation model, making subsequent energy distribution strategies and optimization adjustments more scientific and reasonable, thus promoting the flexibility and efficiency of fuel cells and their hybrid power systems in practical applications. Such improvements not only enhance the economy of the system but also lay a foundation for the popularization and application of renewable energy technologies.

[0060] Step 2: Calculate the environmental impact index based on the dimensionless temperature, humidity, and gas flow data; calculate the electric energy evaluation index based on the dimensionless load power data, and calculate the power response index based on the dimensionless load power and actual response time;

[0061] In this embodiment, the environmental impact index is calculated according to the following formula: ; where, is the environmental impact index, is the current temperature, is the temperature threshold, is the current humidity, is the humidity threshold, is the current gas flow data, is the gas flow threshold, is the denominator adjustment constant. When or or is zero, the corresponding denominator adjustment constant is 1. When or or is not zero, the corresponding denominator adjustment constant is 0, is a preset proportionality coefficient used to adjust the scale and sensitivity of the environmental impact index , . The specific value of

[0062] is determined based on industry standards, historical data, and laboratory tests. When it increases, it means that the current temperature deviation increases and the environmental stability decreases. Therefore decreases; when increases, it means that the current humidity variation increases and the environmental stability decreases. Therefore decreases; when increases, it means that the current gas flow data deviates more from the threshold value. Therefore decreases accordingly; that is to say, , , and the environmental impact index show a negative correlation. The calculation of is to evaluate the suitability of the fuel cell system under specific environmental conditions. By considering the differences between the current temperature, humidity, and gas flow and the preset threshold values, can reflect the degree of influence of the environment on the fuel cell performance. When increases, it indicates that the current environmental conditions are more suitable for the fuel cell, which may mean that the system can operate efficiently under these conditions; when

[0063] According to the following formula, calculate the electrical energy evaluation index: ; where is the electrical energy evaluation index, is the load power, is the efficiency factor, is the input power, that is, the total input power of the fuel cell;

[0064] The efficiency factor is calculated by the formula: ; where represents the highest efficiency that the system can achieve under ideal conditions, is the current gas flow data, represents the gas flow data under ideal conditions; and The specific values of are obtained according to the technical manual.

[0065] When the load power increases, it means that more input power is converted into load power. At this time, the electrical energy utilization efficiency increases and the electrical energy evaluation index decreases; when the load power decreases, it means that the input power fails to be effectively converted into load power, resulting in a decrease in the electrical energy utilization efficiency. Therefore increases; the electrical energy evaluation index Used to quantify the electrical energy usage efficiency of a fuel cell system. By comparing the load power with the input power, it can intuitively reflect the energy utilization situation of the system during actual operation; when When the value decreases, it indicates that the electrical energy usage efficiency of the system is improving, which may mean that the fuel cell has better performance under the current environmental conditions, with reduced energy losses. This is a positive signal indicating that the system is operating more efficiently; while when When the value increases, it shows that the electrical energy usage efficiency of the system has decreased.

[0066] According to the following formula, calculate the power response index: ; where, is the power response index, is the load power, is the expected power, is the maximum output power, is the actual response time, is the maximum response time designed for the system, is the scaling factor used to adjust the influence of the power difference on the power response index, is the adjustment factor used to balance the influence of the response time on the power response index, and This is because the influence of the power difference on the power response is greater than that of the response time. In many systems, especially in power and energy management, the influence of load changes on system performance is often more direct and important.

[0067] When increases, increases, meaning that the system can handle larger power demands. At this time, increases; when the actual response time decreases, it means that the system responds faster to load changes. At this time, the value increases; that is to say, is positively correlated with , is negatively correlated with . Calculating the power response index can help evaluate and optimize the response ability of the power system to load changes. When the value increases, it indicates that the system responds faster to load changes and can better meet the actual power demands; when the value decreases, it indicates that the system's response ability is insufficient and it cannot quickly adapt to load changes.

[0068] Step 2 calculates the environmental impact index, power evaluation index, and power response index by processing the dimensionless temperature, humidity, gas flow rate, and load power data. The key advantage of this process is that it can convert performance indicators with different dimensions into dimensionless values, facilitating comparison and comprehensive evaluation. This method effectively reduces the evaluation deviation caused by different data magnitudes, improving the accuracy and reliability of the overall evaluation. Compared with the existing technology, Step 2 not only simplifies the complex parameter calculation process but also better reflects the performance changes of the fuel cell system under dynamic load conditions, ensuring the scientific nature of the energy management strategy.

[0069] In the patent solution, adopting Step 2 can significantly enhance the evaluation ability of the overall solution, providing basic data for the comprehensive evaluation model. The implementation of this process promotes the effectiveness of subsequent steps, enabling the energy management strategy to more accurately reflect the actual operating conditions, thereby optimizing energy distribution and improving system operating efficiency. Through real-time environmental impact and energy use efficiency evaluation, this step provides forward-looking support for system decision-making, enabling the hybrid power system to achieve optimal performance and resource utilization in a complex working environment.

[0070] Step 3: Construct a comprehensive evaluation model based on the environmental impact index, power evaluation index, and power response index of the battery to be evaluated, generate the weights within the comprehensive evaluation model through the analytic hierarchy process, and use the comprehensive evaluation model to generate the comprehensive energy management index;

[0071] In this embodiment, a comprehensive evaluation model is constructed according to the environmental impact index, power evaluation index, and power response index of the system to be evaluated, and the model expression is as follows: ; where is the comprehensive energy management index, is the environmental impact index, is the power evaluation index, is the power response index, is the proportionality coefficient.

[0072] When the environmental impact index increases, it indicates that the current environmental conditions are more suitable, and the comprehensive energy management index increases; when the power evaluation index increases, it means that the input power fails to be effectively converted into load power, resulting in a decrease in power use efficiency. Therefore, the comprehensive energy management index decreases; when the power response index increases, it indicates that the system responds faster when the load changes and can better meet the actual power demand, and the comprehensive energy management index increases, that is, it shows that , and Show a positive correlation and show a negative correlation

[0073] The specific logic for generating the weights within the comprehensive evaluation model through the Analytic Hierarchy Process is as follows:

[0074] Label the three indicators of the environmental impact index, power evaluation index, and power response index. Determine the numerical values of the relative importance between each pair through the nine-scale method, and construct a judgment matrix. Among them, label the index of the environmental impact index as 1, the index of the power evaluation index as 2, and the index of the power response index as 3. The constructed judgment matrix is: ; where both represent the index of the index, and , represents that the index with index is more important than the index with index , and ;

[0075] Divide each element value in the judgment matrix by the sum of its column to obtain the normalized judgment matrix. Calculate the mean value of each row element value in the normalized judgment matrix. Take the mean value of the first row element value as the weight of the environmental impact index, the mean value of the second row element value as the weight of the power evaluation index, and the mean value of the third row element value as the weight of the power response index. Under the constraint that the sum of the scaled values is equal to 1, scale the three weights proportionally, and take the scaled weights as the proportionality coefficients of the corresponding indexes.

[0076] In step 3, by constructing a comprehensive evaluation model, integrate the environmental impact index, power evaluation index, and power response index to generate a comprehensive energy management index . The key advantage of this process is that it provides a systematic method to comprehensively evaluate the overall performance of the fuel cell system, thereby making more scientific and reasonable energy management decisions under complex operating conditions. Compared with the existing technology, this step not only improves the comprehensiveness and accuracy of the evaluation, but also clarifies the weight relationship of each index through the Analytic Hierarchy Process, making the decision-making process more transparent and logical.

[0077] In the patent solution, adopting step 3 can effectively improve the decision-making ability and flexibility of the overall solution. By establishing a comprehensive evaluation model, the system can evaluate and adjust the energy management strategy in real time in the face of different operating conditions and environmental impacts. This dynamic adjustment ability ensures the efficient operation of the system, greatly reduces energy waste, and improves the overall energy utilization rate. Ultimately, the implementation of this step promotes the optimization of the hybrid power system, enabling it to achieve higher economic efficiency and environmental friendliness in practical applications, and also provides strong support for future technological development.

[0078] Step 4: Compare the comprehensive energy management index with a preset threshold, and formulate a real-time energy allocation strategy according to the comparison result. Apply the genetic algorithm to further optimize the energy allocation strategy;

[0079] In this embodiment, the comprehensive energy management index is compared with the preset threshold:

[0080] If , continue to adopt the current energy allocation strategy, set the main energy source in the system as the fuel cell, and give priority to using the fuel cell;

[0081] If , use the supercapacitor to quickly respond to load changes;

[0082] Wherein, is the comprehensive energy management index, is the preset index evaluation threshold;

[0083] Apply the genetic algorithm to further optimize the energy allocation strategy. The specific logic is as follows:

[0084] Set a sample set containing n individuals, each individual represents an energy allocation strategy, indicating the power allocation ratio of the fuel cell and the supercapacitor under different load conditions. For each individual, calculate its corresponding environmental impact index, power evaluation index and power response index, and use the maximum and minimum values of the environmental impact index, power evaluation index and power response index in the sample set as constraints. Randomly generate an initial population, input the individuals into the comprehensive evaluation model to obtain the corresponding comprehensive energy management index, sort the individuals in descending order according to the comprehensive energy management index, select the individuals at the forefront of the ranking as parents and perform crossover and mutation operations to obtain new individuals. After integrating the newly generated individuals and the individuals as parents to form a new population, repeat the selection, crossover and mutation operations until the predetermined number of iterations is reached. The preset number of iterations in this scheme is 200 times. This number of iterations can ensure that the algorithm has enough opportunities to find the optimal solution while avoiding waste of computing resources caused by excessive iterations. Select the individual with the largest comprehensive energy management index as the optimal parameter combination, and adjust the current energy allocation strategy according to the power allocation ratio in the optimal parameter combination.

[0085] The core advantage of Step 4 is that by comparing the comprehensive energy management index with the preset threshold Compare and formulate a real-time energy allocation strategy. This method can respond promptly to the operating state of the system, ensuring the flexibility and efficiency of the system under different load change conditions. Compared with the existing technologies, adopting this step can achieve more intelligent energy management, avoiding the problem of unreasonable energy allocation caused by data delay or inaccurate prediction in traditional methods, thereby improving the overall reliability and response speed of the system.

[0086] In the patent solution, adopting Step 4 can significantly enhance the dynamic adjustment ability of the overall solution. By monitoring and adjusting the energy allocation strategy in real time, the system can quickly switch the main energy source according to the actual operating conditions, thus maintaining the stability and efficiency of the system when the load changes. This flexibility not only optimizes the energy utilization rate but also reduces the operating cost, providing a more competitive solution for the hybrid power system of proton exchange membrane fuel cells and promoting the popularization and development of renewable energy technologies in practical applications. The genetic algorithm adopted in Step 4 is an optimization algorithm based on natural selection and genetic mechanisms, which can effectively find near-optimal solutions in a complex search space. In the energy allocation strategy, the genetic algorithm helps the system quickly find the optimal power allocation ratio by simulating the evolution process, thereby improving the efficiency and effectiveness of energy management.

[0087] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0088] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0089] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0090] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application.

Claims

1. A hybrid power system energy management method based on proton exchange membrane fuel cells, characterized in that: The specific steps include: Step 1: Monitor and analyze the operating status of the fuel cell to obtain key parameters, including temperature, humidity, current, voltage, gas flow rate and actual response time of the system, and calculate the load power through current and voltage data; Step 2: Calculate the environmental impact index based on the dimensionless processed temperature, humidity and gas flow data, calculate the electric energy evaluation index based on the dimensionless processed load power data, and calculate the power response index based on the dimensionless processed load power and actual response time; Step 3: Construct a comprehensive evaluation model based on the environmental impact index, electric energy evaluation index and power response index of the battery to be evaluated, generate the weights in the comprehensive evaluation model through the hierarchical analysis method, and use the comprehensive evaluation model to generate a comprehensive energy management index; Step 4: Compare the comprehensive energy management index with the preset threshold, and formulate a real-time energy allocation strategy based on the comparison result, and apply the genetic algorithm to further optimize the energy allocation strategy; Implement a time synchronization mechanism to ensure that data from all the following sensors are collected at the same timestamp: The PEMFC operating temperature is obtained using an NTC thermistor, denoted as ; Use the humidity sensor to obtain the humidity of the PEMFC working environment, denoted as ; Use a current sensor to monitor the current flowing through the fuel cell and the load, recorded as ; Use a voltage sensor to monitor the voltage of the fuel cell and the load, denoted as ; The flow meter is installed between the gas source and the fuel cell stack to collect gas flow data, which is recorded as ; The actual response time of the system is the time delay required for the system to adjust its state after receiving a new load change signal. The specific logic for obtaining the actual response time is: When the system receives a new load change signal, record the time , after the system responds, monitor the time it takes for the current and voltage data to reach a stable state : ； in, is the actual response time; Use the following formula to calculate the load power: ； in, is the load power at the current moment, is the voltage value at the current moment, is the current value at the current moment, is the power factor at the current moment, is the total harmonic distortion; The acquisition method is as follows: use a digital instrument to sample the voltage signal, the sampling frequency is 10 times the highest frequency of the signal, and satisfies the Nyquist sampling theorem. For the collected time domain signal, use fast Fourier transform to convert it into a frequency domain signal to obtain the amplitude of each harmonic component. For each harmonic, calculate its effective value according to the following formula: ； in, is the effective value of the harmonic, The time required for the signal to complete a complete waveform. The time for a complete waveform The signal value at time is the time variable within a complete waveform time; Use the above harmonic effective value calculation formula to calculate the effective value of the fundamental wave and the effective value of the ath harmonic, where a represents the index of the harmonic, where , represents the total number of fundamental waves and harmonics, and substitute the calculated results into the following Calculation formula: ； in, is the total harmonic distortion, is the effective value of the fundamental wave, that is, the effective value of the first harmonic, is the effective value of the ath harmonic, ; The environmental impact index is calculated according to the following formula: ； in, is the environmental impact index, is the current temperature, is the temperature threshold, is the current humidity, is the humidity threshold, is the current gas flow data, is the gas flow threshold, is the denominator adjustment constant, when or or When it is zero, the corresponding denominator adjustment constant is 1. or or When it is not zero, the corresponding denominator adjustment constant is 0. is the preset proportional coefficient; The electric energy evaluation index is calculated according to the following formula: ； in, is the electric energy assessment index, is the load power, is the efficiency factor, is the input power, i.e. the total input power of the fuel cell; The calculation formula is: ； in, It indicates the highest efficiency that the system can achieve under ideal conditions. is the current gas flow data, Indicates the gas flow data under ideal conditions; The power response index is calculated according to the following formula: ； in, is the power response index, is the load power, is the expected power, is the maximum output power, is the actual response time, The maximum response time designed for the system, is the scaling factor used to adjust the effect of the power difference on the power response index, is the adjustment factor used to balance the effect of response time on the power response index; A comprehensive evaluation model is constructed based on the environmental impact index, electric energy evaluation index and power response index of the system to be evaluated. The model expression is as follows: ； in, is the comprehensive energy management index, is the environmental impact index, is the electric energy assessment index, is the power response index, is the proportionality coefficient; Compare the overall energy management index with the preset threshold: like , continue to use the current energy allocation strategy, set the main energy source in the system to fuel cells, and give priority to the use of fuel cells; like , using supercapacitors to quickly respond to load changes; in, is the comprehensive energy management index, Evaluation thresholds for preset indices; Genetic algorithm is used to further optimize the energy allocation strategy. The specific logic is as follows: A sample set containing n individuals is set, each individual represents an energy allocation strategy, indicating the power allocation ratio of fuel cells and supercapacitors under different load conditions. For each individual, its corresponding environmental impact index, electric energy evaluation index and power response index are calculated, and the maximum and minimum values ​​of the environmental impact index, electric energy evaluation index and power response index in the sample set are used as constraints. The initial population is randomly generated, and the individuals are input into the comprehensive evaluation model to obtain the corresponding comprehensive energy management index. The individuals are sorted from large to small according to the comprehensive energy management index, and the individuals at the front of the sorting are selected as the parent generation and crossover and mutation operations are performed to obtain new individuals. After the newly generated individuals and the individuals as the parent generation are integrated as a new population, the selection, crossover and mutation operations are repeated until the predetermined number of iterations is reached, and the individual with the largest comprehensive energy management index is selected as the optimal parameter combination. The current energy allocation strategy is adjusted according to the power allocation ratio in the optimal parameter combination.

2. The energy management method of a hybrid power system based on a proton exchange membrane fuel cell according to claim 1, characterized in that: The specific logic of generating weights in the comprehensive evaluation model through the hierarchical analysis method is: The three indicators of environmental impact index, electric energy evaluation index and power response index are marked, and the relative importance values ​​between them are determined by the nine-scale method to construct a judgment matrix, in which the index of the environmental impact index is marked as 1, the index of the electric energy evaluation index is marked as 2, and the index of the power response index is marked as 3. The constructed judgment matrix is: ； in, denotes the index of the index, and , Indicates that the index is The index relative to the index is The index importance of ; Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain a normalized normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the environmental impact index, the mean of the element values ​​in the second row is used as the weight of the electric energy evaluation index, and the mean of the element values ​​in the third row is used as the weight of the power response index. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled in equal proportions, and the scaled weights are used as the proportional coefficients of the corresponding indexes.

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