Fuel Cell Energy Management Optimization Methods

Abstract

This invention discloses a fuel cell energy management optimization method, comprising the following steps: 1) The fuel cell energy management system maximizes the utilization of fuel cell energy by adjusting and optimizing system parameters; 2) Modeling the fuel cell energy management system, including the stack, battery management system, and DC / DC converter; 3) Simulating and analyzing the fuel cell energy management system, considering the system's operating state, load requirements, and environmental conditions; 4) Optimizing and analyzing the simulation results to obtain the optimal parameter configuration and control strategy; 4-1) Optimization analysis of the fuel cell energy management system; 4-2) Adjustment analysis of the fuel cell energy management strategy; 4-3) Adjustment analysis of the fuel cell energy management system.

Description

Technical Field

[0001] This invention relates to fuel cells and fuel cell power management technology, specifically, a fuel cell energy management optimization method. Background Technology

[0002] Current fuel cell energy management systems typically employ relatively simple control methods, failing to fully consider the impact of different operating conditions on the overall system performance. This results in the system's actual performance potentially not reaching its optimal level under complex and variable operating conditions.

[0003] At the same time, there are still areas that need improvement:

[0004] Insufficient monitoring and optimization: Existing technologies have shortcomings in real-time monitoring and system response under different operating conditions. The lack of efficient monitoring methods and rapid optimization methods based on real-time data limits the system's performance under dynamic operating conditions.

[0005] Energy allocation optimization problem: Some systems face certain optimization challenges in energy allocation under different operating conditions. Existing technologies have not fully considered the impact of different operating conditions on energy allocation, resulting in the system failing to achieve optimal performance under various operating conditions.

[0006] Therefore, it is necessary to provide a fuel cell energy management optimization method to solve the above problems. Summary of the Invention

[0007] The purpose of this invention is to provide a method for optimizing energy management of fuel cells.

[0008] The present invention achieves the above objectives through the following technical solution:

[0009] A method for optimizing fuel cell energy management includes the following steps:

[0010] 1) The fuel cell energy management system maximizes the utilization of fuel cell energy by adjusting and optimizing system parameters;

[0011] 2) Model the aforementioned fuel cell energy management system, including the fuel cell stack, battery management system, and DC / DC converter;

[0012] 3) Conduct simulation analysis on the fuel cell energy management system, considering the system's operating status, load requirements, and environmental conditions;

[0013] 4) Optimize and analyze the simulation results to obtain the best parameter configuration and control strategy.

[0014] 4-1) Optimization analysis of the battery energy management system;

[0015] 4-2) Analysis of adjustments to fuel cell energy management strategies;

[0016] 4-3) Adjustment analysis of fuel cell energy management system.

[0017] Furthermore, the parameters of the fuel cell energy management system include:

[0018] Battery stack voltage, current, and temperature; battery management system control strategies, including battery charge / discharge control and power distribution strategies; DC / DC efficiency and power loss.

[0019] Furthermore, the modeling of the fuel cell energy management system includes:

[0020] The physical characteristics of the fuel cell stack are modeled, including hydrogen supply, oxygen supply, and chemical reaction processes; the control strategies of the battery management system are modeled, including battery charge and discharge control algorithms and power distribution algorithms; and the efficiency and power loss of the DC / DC converter are modeled.

[0021] Furthermore, the simulation analysis of the fuel cell energy management system includes:

[0022] Considering the dynamic response and steady-state performance of the fuel cell stack, the changes in battery voltage, current and temperature under different operating conditions are simulated; considering the changes in load demand and the influence of environmental conditions, the performance of the fuel cell system in actual operation is simulated.

[0023] Further optimization analysis of the fuel cell energy management system includes:

[0024] The simulation results are evaluated to analyze the energy utilization rate, system efficiency, and response speed of the fuel cell stack. Based on the evaluation results, the parameter configuration and control strategy are adjusted to optimize the performance of the fuel cell energy management system. The results of various optimizations are compared horizontally to select the best optimization parameters and control strategy.

[0025] Further adjustments and analyses of the fuel cell energy management system include:

[0026] Set the stack parameters: Set the operating temperature range of the air-cooled fuel cell stack to 60°C to 80°C to ensure the stack operates at a suitable temperature. Set the rated voltage of the stack to 48 V, with an open-circuit voltage of approximately 40 V to meet the system's voltage requirements. Set the stack output power limit to 500 W, and adjust the power distribution strategy according to actual load demands and stack performance.

[0027] Adjust the battery management system control strategy: Employ battery charge / discharge control algorithms to ensure high efficiency and safety during battery charging and discharging. Suppress current ripple by reducing ripple in the battery output current through current control and filtering techniques, thereby reducing energy loss and improving system stability.

[0028] Adjusting DC / DC parameters: For DC / DC converters using a boost topology, assuming a conversion efficiency between 90% and 95%, adjustments are made based on the stack voltage and load requirements. Considering power losses during energy conversion, a loss factor for the DC / DC converter is set for optimization analysis of the energy management system.

[0029] Furthermore, this also includes an assessment of the fuel cell energy management system;

[0030] The evaluation metrics for fuel cell energy management systems include:

[0031] Energy utilization rate assessment: Plot the energy utilization rate curves of the battery stack under different operating conditions, and analyze the efficiency of battery energy utilization under different load requirements and temperature conditions;

[0032] System efficiency assessment: Through simulation analysis, the efficiency of the entire fuel cell energy management system in actual operation is obtained, including the efficiency loss of the battery management system, DC / DC, etc.

[0033] Response speed assessment: Analyze the response speed, charging speed and discharging speed of the fuel cell stack when load demand changes, to ensure that the system can meet load demand in a timely manner;

[0034] Ripple suppression evaluation: Check the effect of current ripple suppression control. By comparing the curves and data before and after ripple, evaluate the quality of ripple suppression effect.

[0035] System stability and reliability assessment: The stability and reliability of the system are assessed under different environmental conditions by evaluating the temperature changes and current response of the fuel cell stack and converter.

[0036] Compared with existing technologies, this invention establishes a fuel cell energy management system model, including a fuel cell stack, a battery management system, and a DC / DC converter, and sets corresponding parameters and control strategies. Simulation analysis is then performed, considering the system's operating conditions, load requirements, and environmental conditions. The model simulates the fuel cell stack's response and steady-state performance, evaluates the system's energy utilization rate, efficiency, and response speed, conducts optimization analysis, adjusts parameter configurations and control strategies, and performs simulation analysis again. Multiple optimization results are compared horizontally to derive the optimal optimization parameters and control strategies, thereby achieving the optimal performance of the fuel cell energy management system. Attached Figure Description

[0037] Figure 1This is a schematic diagram of the process of the present invention. Detailed Implementation

[0038] Implementation example:

[0039] See Figure 1 This embodiment demonstrates a fuel cell energy management optimization method, including the following steps:

[0040] 1) The fuel cell energy management system maximizes the utilization of fuel cell energy by adjusting and optimizing system parameters;

[0041] 2) Model the aforementioned fuel cell energy management system, including the fuel cell stack, battery management system, and DC / DC converter;

[0042] 3) Conduct simulation analysis on the fuel cell energy management system, considering the system's operating status, load requirements, and environmental conditions;

[0043] 4) Optimize and analyze the simulation results to obtain the best parameter configuration and control strategy.

[0044] 4-1) Optimization analysis of the battery energy management system;

[0045] 4-2) Analysis of adjustments to fuel cell energy management strategies;

[0046] 4-3) Adjustment analysis of fuel cell energy management system.

[0047] The parameters of the fuel cell energy management system include:

[0048] Battery stack voltage, current, and temperature; battery management system control strategies, including battery charge / discharge control and power distribution strategies; DC / DC efficiency and power loss.

[0049] Modeling of the fuel cell energy management system includes:

[0050] The physical characteristics of the fuel cell stack are modeled, including hydrogen supply, oxygen supply, and chemical reaction processes; the control strategies of the battery management system are modeled, including battery charge and discharge control algorithms and power distribution algorithms; and the efficiency and power loss of the DC / DC converter are modeled.

[0051] The simulation analysis of the fuel cell energy management system includes:

[0052] Considering the dynamic response and steady-state performance of the fuel cell stack, the changes in battery voltage, current and temperature under different operating conditions are simulated; considering the changes in load demand and the influence of environmental conditions, the performance of the fuel cell system in actual operation is simulated.

[0053] The optimization analysis of the fuel cell energy management system includes:

[0054] The simulation results are evaluated to analyze the energy utilization rate, system efficiency, and response speed of the fuel cell stack. Based on the evaluation results, the parameter configuration and control strategy are adjusted to optimize the performance of the fuel cell energy management system. The results of various optimizations are compared horizontally to select the best optimization parameters and control strategy.

[0055] The adjustment analysis of the fuel cell energy management system includes:

[0056] Set the stack parameters: Set the operating temperature range of the air-cooled fuel cell stack to 60°C to 80°C to ensure the stack operates at a suitable temperature. Set the rated voltage of the stack to 48 V, with an open-circuit voltage of approximately 40 V to meet the system's voltage requirements. Set the stack output power limit to 500 W, and adjust the power distribution strategy according to actual load demands and stack performance.

[0057] Adjust the battery management system control strategy: Employ battery charge / discharge control algorithms to ensure high efficiency and safety during battery charging and discharging. Suppress current ripple by reducing ripple in the battery output current through current control and filtering techniques, thereby reducing energy loss and improving system stability.

[0058] Adjusting DC / DC parameters: For DC / DC converters using a boost topology, assuming a conversion efficiency between 90% and 95%, adjustments are made based on the stack voltage and load requirements. Considering power losses during energy conversion, a loss factor for the DC / DC converter is set for optimization analysis of the energy management system.

[0059] This also includes assessments of fuel cell energy management systems;

[0060] The evaluation metrics for fuel cell energy management systems include:

[0061] Energy utilization rate assessment: Plot the energy utilization rate curves of the battery stack under different operating conditions, and analyze the efficiency of battery energy utilization under different load requirements and temperature conditions;

[0062] System efficiency assessment: Through simulation analysis, the efficiency of the entire fuel cell energy management system in actual operation is obtained, including the efficiency loss of the battery management system, DC / DC, etc.

[0063] Response speed assessment: Analyze the response speed, charging speed and discharging speed of the fuel cell stack when load demand changes, to ensure that the system can meet load demand in a timely manner;

[0064] Ripple suppression evaluation: Check the effect of current ripple suppression control. By comparing the curves and data before and after ripple, evaluate the quality of ripple suppression effect.

[0065] System stability and reliability assessment: The stability and reliability of the system are assessed under different environmental conditions by evaluating the temperature changes and current response of the fuel cell stack and converter.

[0066] Compared with existing technologies, this invention establishes a fuel cell energy management system model, including a fuel cell stack, a battery management system, and a DC / DC converter, and sets corresponding parameters and control strategies. Simulation analysis is performed, considering the system's operating conditions, load requirements, and environmental conditions. The response and steady-state performance of the fuel cell stack are simulated, and the system's energy utilization rate, efficiency, and response speed are evaluated. Optimization analysis is conducted, parameter configurations and control strategies are adjusted, and simulation analysis is performed again. Multiple optimization results are compared horizontally to derive the optimal optimization parameters and control strategies, thereby achieving the optimal performance of the fuel cell energy management system.

[0067] The above descriptions are merely some embodiments of the present invention. Those skilled in the art can make various modifications and improvements without departing from the inventive concept of the present invention, and these all fall within the scope of protection of the present invention.

Claims

1. A method for optimizing energy management of a fuel cell, characterized in that: Includes the following steps: 1) The fuel cell energy management system maximizes the utilization of fuel cell energy by adjusting and optimizing system parameters; 2) Model the aforementioned fuel cell energy management system, including the fuel cell stack, battery management system, and DC / DC converter; 3) Conduct simulation analysis on the fuel cell energy management system, considering the system's operating status, load requirements, and environmental conditions; 4) Optimize and analyze the simulation results to obtain the optimal parameter configuration and control strategy. The optimization analysis in step 4) specifically includes: 4-1) Optimization analysis of fuel cell energy management system; 4-2) Analysis of adjustments to fuel cell energy management strategies; 4-3) Adjustment analysis of the fuel cell energy management system; The parameters of the fuel cell energy management system include: Battery stack voltage, current, and temperature; battery management system control strategies, including battery charge / discharge control and power distribution strategies; DC / DC efficiency and power loss; Modeling of the fuel cell energy management system includes: The physical characteristics of the fuel cell stack are modeled, including hydrogen supply, oxygen supply, and chemical reaction processes; the control strategies of the battery management system are modeled, including battery charge and discharge control algorithms and power distribution algorithms; and the efficiency and power loss of the DC / DC converter are modeled.

2. The fuel cell energy management optimization method according to claim 1, characterized in that: The simulation analysis of the fuel cell energy management system includes: Considering the dynamic response and steady-state performance of the fuel cell stack, the changes in battery voltage, current and temperature under different operating conditions are simulated; considering the changes in load demand and the influence of environmental conditions, the performance of the fuel cell system in actual operation is simulated.

3. The fuel cell energy management optimization method according to claim 2, characterized in that: The optimization analysis of the fuel cell energy management system includes: The simulation results are evaluated to analyze the energy utilization rate, system efficiency, and response speed of the fuel cell stack. Based on the evaluation results, the parameter configuration and control strategy are adjusted to optimize the performance of the fuel cell energy management system. The results of various optimizations are compared horizontally to select the best optimization parameters and control strategy.

4. The fuel cell energy management optimization method according to claim 3, characterized in that: The adjustment analysis of the fuel cell energy management system includes: Set the stack parameters: Set the operating temperature range of the air-cooled fuel cell stack to 60°C to 80°C to ensure that the stack operates at a suitable temperature; set the rated voltage of the stack to 48 V and the open-circuit voltage to 40 V to meet the voltage requirements of the system; set the stack output power limit to 500 W, and adjust the power distribution strategy according to the actual load demand and stack performance. Adjust the battery management system control strategy: Employ battery charge and discharge control algorithms to ensure high efficiency and safety during battery charge and discharge; suppress current ripple by reducing ripple in the battery output current through current control and filtering techniques to reduce energy loss and improve system stability; Adjusting DC / DC parameters: For DC / DC converters using boost topology, assuming a conversion efficiency between 90% and 95%, adjust the parameters based on the stack voltage and load requirements; considering power losses during energy conversion, set the DC / DC loss factor for optimization analysis of the energy management system.

5. The fuel cell energy management optimization method according to claim 4, characterized in that: This also includes assessments of fuel cell energy management systems; The evaluation metrics for fuel cell energy management systems include: Energy utilization rate assessment: Plot the energy utilization rate curves of the battery stack under different operating conditions, and analyze the efficiency of battery energy utilization under different load requirements and temperature conditions; System efficiency assessment: Through simulation analysis, the efficiency of the entire fuel cell energy management system in actual operation is obtained, including the efficiency loss of the battery management system and DC / DC converter; Response speed assessment: Analyze the response speed, charging speed and discharging speed of the fuel cell stack when load demand changes, to ensure that the system can meet load demand in a timely manner; Ripple suppression evaluation: Check the effect of current ripple suppression control. By comparing the curves and data before and after ripple, evaluate the quality of ripple suppression effect. System stability and reliability assessment: The stability and reliability of the system are assessed under different environmental conditions by evaluating the temperature changes and current response of the fuel cell stack and converter.

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