Energy management method for fuel cell vehicle

By analyzing the efficiency and degradation of fuel cells and power batteries, a double-layer fuzzy controller is used to manage the energy of fuel cell vehicles, which solves the problems of frequent start-stop and shortened life of fuel cells in existing technologies and realizes the efficient use of fuel cells and power batteries.

CN120096394BActive Publication Date: 2025-09-09SHAANXI HEAVY DUTY AUTOMOBILE CO LTD
View PDF 4 Cites 0 Cited by

Patent Information

Application Number
CN202510601875.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-12
Publication Date
2025-09-09
Estimated Expiration
2045-05-12

AI Technical Summary

Technical Problem

Existing fuel cell vehicle energy management methods fail to accurately control the output power of the fuel cell, resulting in frequent starts and stops, reducing the life of the fuel cell, and do not take into account the service life and load-changing capabilities of the fuel cell and power battery.

Method used

By analyzing the efficiency and degradation of fuel cells and power batteries, calculating the equivalent hydrogen consumption, and using a double-layer fuzzy controller to manage the energy consumption and life of the entire vehicle, the fuel cell output power is optimized by combining the evaluation indicators of fuel cells and power batteries.

Benefits of technology

The service life of fuel cells and power batteries is improved, the impact of fuel cell power fluctuations on life is reduced, and the service life of the fuel cell system is extended.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN120096394B_ABST
    Figure CN120096394B_ABST
Patent Text Reader

Abstract

The present invention provides an energy management method for fuel cell vehicles, comprising: analyzing the fuel cell and power battery to obtain fuel cell efficiency, power battery efficiency, fuel cell degradation, power battery degradation, and power battery #imgabs0#, and then calculating equivalent hydrogen consumption; inputting the power battery #imgabs1# and the vehicle's required power into a fuzzy controller for data processing to obtain the fuel cell output power; and using the equivalent hydrogen consumption and the fuel cell degradation and power battery degradation levels as energy management strategy evaluation indicators to evaluate and manage the lifespan and energy consumption balance of the fuel cell and power battery. By increasing the fuel cell power variation limit, the method more closely matches the actual load-variable capacity of the fuel cell system, reducing the impact of fuel cell power fluctuations on its lifespan. When the fuel cell SOC is very low, the fuel cell can operate at minimum power rather than shutting down directly, reducing the number of starts and stops of the fuel cell system and extending the fuel cell lifespan.
Need to check novelty before this filing date? Find Prior Art

Description

Technical Field

[0001] The present invention relates to a fuel cell vehicle energy management method, and relates to the technical field of fuel cells. Background Art

[0002] Fuel cells convert the chemical energy of hydrogen and oxygen directly into electrical energy through an electrochemical reaction. At the anode, hydrogen is decomposed into hydrogen ions and electrons by a catalyst. The electrons flow through an external circuit to the cathode, where they combine with oxygen to form water. This process produces no harmful emissions, achieving near-zero emissions. Fuel cells are widely used in automobiles, offering advantages such as high efficiency, environmental friendliness, and long driving range. They are considered a key solution for future sustainable transportation. Managing the lifespan and energy balance of fuel cells is a crucial component of technological development.

[0003] The existing patent CN115476735A discloses a composite energy management method, device, equipment and storage medium. This invention patent determines whether the fuel cell system is turned on according to the preset switch control rules, and calculates the vehicle's required power and power battery under different working conditions. As the input signal of the fuel cell system; when it is determined that the fuel cell system is on, the fuzzy output power is obtained through fuzzy control calculation, and the output power is smoothed by a sliding average filter to obtain a smooth output power; when it is determined that the fuel cell system is off, the fuel cell system is controlled to shut down. Although the existing technology solves the problem that frequent and large fluctuations in the fuel cell load will reduce its durability and output efficiency, under certain working conditions, the large fluctuation range of the power battery charge and discharge leads to a shortened battery life and safety problems caused by overcharging and over-discharging. However, the following shortcomings still exist:

[0004] 1. The fuzzy controller only has the vehicle power requirement and power battery Two input signals make it impossible to accurately control the increase or decrease of the fuel cell output power;

[0005] 2. Using the fuel cell output power proportionality coefficient to directly calculate the fuel cell output power without considering the load-variable capability of the actual fuel cell engine output power;

[0006] 3. Using a switch controller to control the on or off of the fuel cell system causes the fuel cell system to start and stop frequently during use, thereby reducing the life of the fuel cell;

[0007] 4. The same fuzzy rule is used for both vehicle power demand ≥ 0 and vehicle power demand < 0, resulting in an inability to accurately control the increase or decrease of fuel cell output power during normal driving and energy recovery;

[0008] 5. The number of fuzzy subsets of vehicle power requirements is too large, making the fuzzy control method unsuitable for different types of driving conditions. Summary of the Invention

[0009] To solve the above technical problems, the present invention aims to provide a fuel cell vehicle energy management method to address the problem that existing strategies only consider the energy consumption of fuel cell vehicles, but do not consider the service life of fuel cells and power batteries. This method cannot effectively control the load range and the number of times the fuel cell system can be started during the vehicle's operation. The specific technical solution is as follows:

[0010] A fuel cell vehicle energy management method, comprising:

[0011] By analyzing the fuel cell and power battery, the fuel cell efficiency, power battery efficiency, fuel cell degradation, power battery degradation and power battery , and then calculate the equivalent hydrogen consumption;

[0012] The power battery and vehicle power requirements The data is input into the fuzzy controller for data processing to obtain the fuel cell output power;

[0013] The equivalent hydrogen consumption, fuel cell degradation degree and power battery degradation degree are used as energy management strategy evaluation indicators to evaluate and manage the two indicators of vehicle energy consumption and fuel cell and power battery life.

[0014] Preferably, the fuel cell efficiency is calculated by the following formula:

[0015] ;

[0016] Where, is the fuel cell efficiency, Output power for the fuel cell.

[0017] Furthermore, the power battery efficiency is calculated using the following formula:

[0018] ;

[0019] Where, For power battery charging efficiency, is the power battery discharge efficiency, The internal resistance of the power battery at each state of charge, is the internal discharge resistance of the power battery at each state of charge; Output power for the power battery, It is the open circuit voltage of the power battery.

[0020] Preferably, the vehicle requires power Pre-processing is performed before inputting into the fuzzy controller. If the vehicle requires power <The minimum output power of the fuel cell, the vehicle power is provided by the power battery; if the vehicle requires power continuous If the time is 0, the fuel cell is turned off and the fuel cell output power is 0;

[0021] If the vehicle requires continuous power If the time is not 0, a double-layer fuzzy controller is used; the vehicle power demand , power batteries The fuzzy coefficient is input into the first-layer fuzzy controller, and the fuel cell output power corresponding to the first-layer fuzzy controller is output according to the fuzzy rules; the fuel cell output power corresponding to the output of the first-layer fuzzy controller at the previous moment is input into the second fuzzy controller, and the fuzzy coefficient is output according to the fuzzy rules and used as the fuzzy coefficient of the first-layer fuzzy controller.

[0022] Furthermore, the equivalent hydrogen consumption is calculated as follows:

[0023] The hydrogen consumption of the fuel cell is calculated as follows:

[0024] ;

[0025] Where, is the number of fuel cells, is the molar mass of hydrogen, represents the number of electron reactions per mole of hydrogen. is the Faraday constant, is the fuel cell current;

[0026] The equivalent hydrogen consumption of the power battery is calculated as follows:

[0027] ;

[0028] Where, is the lower calorific value of hydrogen, take , is the average efficiency of the fuel cell, for Average converter efficiency, is the average charging efficiency of the power battery, is the average discharge efficiency of the power battery, The charging and discharging power of the power battery;

[0029] The additional hydrogen consumption due to fuel cell aging is defined as the hydrogen consumption corresponding to aging, which is expressed as follows:

[0030] ;

[0031] The hydrogen consumption of the whole vehicle is the sum of the above three, as shown below:

[0032] ;

[0033] Where, is the fuel cell engine power, Before fuel cell engine degradation Output power at power, For fuel cell engines Power voltage decay value.

[0034] Furthermore, the fuzzy rule for the fuel cell output power corresponding to the first layer fuzzy controller output according to the fuzzy rule is as follows: , the vehicle relies on the power battery to provide power, and the fuel cell is started when the vehicle requires a large amount of power. Power Battery , then the power battery and fuel cell work together and the fuel cell can charge the power battery. If the power battery The fuel cell provides the power required by the entire vehicle and charges the power battery; the fuzzy rule for outputting the fuzzy coefficient according to the fuzzy rule is that the difference between the fuel cell output power corresponding to the output of the second-layer fuzzy controller at the next moment and the fuel cell output power corresponding to the output of the first-layer fuzzy controller at the previous moment is within a preset range.

[0035] Preferably, the fuel cell model of the fuel cell receives the fuel cell output power signal, performs logic processing to obtain the fuel cell efficiency, fuel cell and fuel cell degradation.

[0036] Furthermore, the fuel cell efficiency is obtained by fitting a fuel cell power-efficiency curve using a fitting coefficient.

[0037] Furthermore, the fuel cell Expressed in the form of fuel cell stack voltage:

[0038] ;

[0039] Where, is the stack voltage; is the fuel cell current; is the number of fuel cells; is the operating temperature, is the Tafel constant, is the concentration constant; is the open circuit voltage at a specified temperature and pressure; is the total resistance; is the exchange current; is the limiting current; For working hours.

[0040] Furthermore, the fuel cell degradation is determined by the total degradation of the fuel cell voltage, specifically:

[0041] ;

[0042] Where, is the total decay of the power battery voltage, is the performance degradation coefficient caused by the low power area of ​​the fuel cell, The time proportion when the fuel cell engine power is 10%-30% of the rated power, is the performance degradation coefficient caused by the high power area of ​​the fuel cell, The time proportion when the fuel cell engine power is 80%-100% of the rated power, is the fuel cell engine degradation coefficient caused by fuel cell engine power load change, For working hours, is the fuel cell engine power, is the performance degradation coefficient caused by the number of starts and stops of the fuel cell engine, The number of times the fuel cell engine is started and stopped.

[0043] Preferably, the power battery model of the power battery receives the power battery output power signal, performs logic processing to obtain the power battery efficiency, power battery and power battery degradation.

[0044] Preferably, the power battery It is calculated through the power battery current. The specific calculation is as follows:

[0045] ;

[0046] Where, is the initial state of charge of the power battery, is the rated capacity of the power battery, is the total integration time, It is the charging and discharging current of the power battery;

[0047] The power battery charge and discharge current is obtained by calculating the power battery open circuit voltage, power battery output power, and power battery equivalent internal resistance as inputs to a power battery current calculation model.

[0048] Furthermore, the degradation of the power battery is represented by its performance degradation rate:

[0049] ;

[0050] in is the degradation coefficient, the ideal gas constant , is the operating temperature, is the battery activation energy, Refers to the power battery in the process The absolute value of the cumulative change.

[0051] By increasing the fuel cell power variation limit, the present invention can be closer to the actual fuel cell system's load-changing capability and reduce the impact of fuel cell power fluctuations on its lifespan. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a logic flow chart of a fuel cell vehicle energy management method of the present invention.

[0053] Figure 2 It is a logic block diagram of the fuel cell model of the present invention.

[0054] Figure 3 It is a logic block diagram of the power battery model of the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0056] like Figure 1 As shown, the present invention provides an energy management method for fuel cell vehicles based on the balance between life and energy consumption. It uses a fuzzy controller to design an energy management strategy to achieve the function of reducing equivalent hydrogen consumption and increasing the service life of fuel cells and power batteries. Specifically, it includes:

[0057] By analyzing the fuel cell and power battery, we can get the fuel cell efficiency, power battery efficiency, fuel cell degradation, power battery degradation, fuel cell and power batteries , and then calculate the equivalent hydrogen consumption; It refers to the state of nuclear power;

[0058] The power battery and vehicle power requirements The data is input into the fuzzy controller for data processing to obtain the fuel cell output power;

[0059] The energy management strategy uses equivalent hydrogen consumption, fuel cell degradation, and power battery degradation as evaluation indicators to evaluate and manage energy consumption balance and the life of fuel cells and power batteries. The two indicators, vehicle energy consumption and the life of fuel cells and power batteries, are mainly evaluated through the optimal cost of use throughout the entire life cycle. The cost of use throughout the entire life cycle includes fuel costs and the cost of replacing parts. The fuel cost reflects energy consumption, and the cost of replacing parts reflects the life of the fuel cell engine and power battery.

[0060] Preferably, the vehicle requires power Pre-processing is performed before inputting into the fuzzy controller. If the vehicle requires power <The minimum output power of the fuel cell is 30kw, which is the power required by the vehicle If it is regarded as 0, the vehicle power is provided by the power battery; if the vehicle requires power continuous If the time is 0, the fuel cell is turned off and the fuel cell output power is 0;

[0061] If the vehicle requires continuous power If the time is not 0, a double-layer fuzzy controller is used; the vehicle power demand , power batteries The fuzzy coefficient is input into the first-layer fuzzy controller, and the fuel cell output power corresponding to the first-layer fuzzy controller is output according to the fuzzy rules; the fuel cell output power corresponding to the output of the first-layer fuzzy controller at the previous moment is input into the second fuzzy controller, and the fuzzy coefficient is output according to the fuzzy rules and used as the fuzzy coefficient of the first-layer fuzzy controller.

[0062] Furthermore, the fuzzy rule for the fuel cell output power corresponding to the first layer fuzzy controller output according to the fuzzy rule is as follows: , the vehicle mainly relies on the power battery to provide power, and the fuel cell is started when the vehicle requires a large amount of power. Power Battery , the power battery and fuel cell work together and the fuel cell occasionally charges the power battery. The specific output values ​​of the two are continuously adjusted according to the hydrogen consumption. If the power battery , the fuel cell provides the power required by the entire vehicle and charges the power battery as quickly as possible; the fuzzy rule for outputting the fuzzy coefficient according to the fuzzy rule is that the difference between the fuel cell output power corresponding to the output of the second-layer fuzzy controller at the next moment and the fuel cell output power corresponding to the output of the first-layer fuzzy controller at the previous moment is within a preset range.

[0063] Specifically, the fuzzy rule for outputting the fuzzy coefficient according to the fuzzy rule is to ensure that the difference between the fuel cell output power output by the second fuzzy controller at the next moment and the fuel cell output power output by the first fuzzy controller at the previous moment is within For example, if the fuel cell output power input to the second fuzzy controller is , then the output coefficient is So the fuel cell output power output by the first layer fuzzy controller is around The fuel cell power fluctuation is controlled to reduce fuel cell degradation and increase its service life.

[0064] The input membership function of the first-layer fuzzy controller is as follows:

[0065] Input a "power battery ", ranging from a1 to c3, is divided into three fuzzy amounts, namely low [a1 0a2], medium [b1 b2 b3], and high [c1 c2 c3].

[0066] Input 2 "Vehicle Required Power ", ranging from d1 to d19, which is divided into 7 fuzzy quantities, namely one [d1 d2], two [d3 d4], three [d5 d6 d7], four [d8 d9 d10], five [d11 d12 d13], six [d14 d15 d16], and seven [d17d18 d19].

[0067] Input three "fuzzy coefficients" ranging from e1 to e18, which are divided into seven fuzzy quantities, namely one [e1 0 e2], two [0e3 e4], three [e5 e6 e7], four [e8 e9 e10], five [e11 e12 e13], six [e14 e15 e16], and seven [e17 e18e19].

[0068] Output "fuel cell output power", range f1-f20, which is divided into 7 fuzzy quantities, namely one [f1 f2f3], two [f4 f5 f6], three [f7 f8 f9], four [f10 f11 f12], five [f13 f14 f15], six [f16 f17f18], seven [f19 f20 f21].

[0069] The membership function of the second-layer fuzzy controller is as follows:

[0070] The input is "the fuel cell output power output by the first fuzzy controller at the previous moment", which ranges from h1 to h21. It is divided into 7 fuzzy quantities, namely 1[h1 h2 h3], 2[h4 h5 h6], 3[h7 h8 h9], 4[h10 h11 h12], 5[h13 h14 h15], 6[h16 h17 h18], and 7[h19 h20 h21].

[0071] The output is "fuzzy coefficient", ranging from g1 to g21, which is divided into 7 fuzzy quantities, namely 1[g1 g2 g3], 2[g4g5 g6], 3[g7 g8 g9], 4[g10 g11 g12], 5[g13 g14 g15], 6[g16 g17 g18], and 7[g19 g20g21].

[0072] Preferably, Figure 2 As shown, the fuel cell model of the fuel cell receives the fuel cell output power signal, performs logic processing to obtain the fuel cell efficiency, fuel cell SOC and fuel cell degradation status.

[0073] The fuel cell efficiency is calculated by the following formula:

[0074] ;

[0075] Where, is the fuel cell efficiency, Output power for the fuel cell.

[0076] Furthermore, the fuel cell efficiency is obtained by fitting a fuel cell power-efficiency curve using a fitting coefficient. The fuel cell efficiency is obtained by logically processing the fuel cell output power using a fuel cell efficiency model. This model facilitates subsequent calculations of hydrogen consumption and analysis of whether the fuel cell is operating in its high-efficiency range. This determination is primarily based on whether the fuel cell engine's operating efficiency is greater than 50%.

[0077] Furthermore, the performance of a fuel cell stack depends on the relationship between the output current and voltage of the fuel cell at different temperatures. The relationship between the voltage and current density of a fuel cell is called a polarization curve. The fuel cell SOC is expressed in the form of the fuel cell stack voltage:

[0078] ;

[0079] Where, is the stack voltage; is the fuel cell current; is the number of fuel cells; is the operating temperature, is the Tafel constant, is the concentration constant; is the open circuit voltage at a specified temperature and pressure; is the total resistance; is the exchange current; is the limiting current; is the working time. According to the formula, as the fuel cell usage time increases, the fuel cell curve will change, which is roughly manifested as a decrease in voltage at the same current.

[0080] Furthermore, the operational factors that affect fuel cell life are mainly divided into four categories: frequent start-stop, low-power operation, high-power operation, and transient load. Assuming that the contribution of each factor to voltage degradation is independent of each other, the fuel cell degradation is determined by the total degradation of the fuel cell voltage, specifically:

[0081] ;

[0082] Where, is the total decay of the power battery voltage, is the performance degradation coefficient caused by the low power area of ​​the fuel cell, The time proportion when the fuel cell engine power is 10%-30% of the rated power, is the performance degradation coefficient caused by the high power area of ​​the fuel cell, The time proportion when the fuel cell engine power is 80%-100% of the rated power, is the fuel cell engine degradation coefficient caused by fuel cell engine power load change, For working hours, is the fuel cell engine power, is the performance degradation coefficient caused by the number of starts and stops of the fuel cell engine, The number of times the fuel cell engine is started and stopped.

[0083] The model processes the input signal "fuel cell output power" to obtain the output signal "fuel cell voltage decay". It mainly includes four subsystems: the first subsystem is the idle time, which is used to calculate the fuel cell output power. <Minimum output power of fuel cell The second subsystem is the reload time, which is used to calculate > The third subsystem, Power Fluctuation, calculates and accumulates the power fluctuation value at each moment. The fourth subsystem, Start / Stop Count, counts the number of fuel cell starts and stops. The outputs of each subsystem are multiplied by the respective coefficients and then accumulated to obtain the fuel cell voltage decay value during vehicle operation. Idle and heavy load standards are calibration parameters set according to requirements, and power fluctuation refers to the rate of power change at each moment.

[0084] like Figure 3 As shown, the power battery model of the power battery receives the power battery output power signal, performs logical processing to obtain the power battery efficiency, power battery and power battery degradation.

[0085] The power battery efficiency is calculated using the following formula:

[0086] ;

[0087] Where, For power battery charging efficiency, is the power battery discharge efficiency, The internal resistance of the power battery at each state of charge, is the internal discharge resistance of the power battery at each state of charge; Output power for the power battery, It is the open circuit voltage of the power battery.

[0088] The power battery efficiency model provides the power battery charge and discharge efficiency for the subsequent power battery equivalent hydrogen consumption calculation. The input signal is "power battery output power" and the output signal "power battery" is obtained through processing. ", "Power battery charge and discharge efficiency". The power battery current calculation model takes the input signals of "power battery open circuit voltage", "power battery output power", and "power battery equivalent internal resistance" as input signals, and the output signal is "power battery charge and discharge current". The above parameters are all provided by the power battery manufacturer. It is calculated through the power battery current. The specific calculation is as follows:

[0089] ;

[0090] Where, is the initial state of charge of the power battery, is the rated capacity of the power battery, is the total integration time, It is the charging and discharging current of the power battery;

[0091] The power battery charge and discharge current is obtained by calculating the power battery open circuit voltage, power battery output power, and power battery equivalent internal resistance as inputs to a power battery current calculation model.

[0092] Preferably, the performance degradation of a lithium battery system is defined as the percentage of capacity loss compared to the original value after a period of operation. This depends on the activation energy of the battery, the number of cycles, the operating temperature, and the operating time. The degradation of the power battery is represented by its performance decay rate:

[0093] ;

[0094] in is the degradation coefficient, the ideal gas constant , is the operating temperature, is the battery activation energy, Refers to the power battery in the process The absolute value of the cumulative change.

[0095] The equivalent hydrogen consumption is calculated as follows:

[0096] The hydrogen consumption of the fuel cell is calculated as follows:

[0097] ;

[0098] Where, is the number of fuel cells, is the molar mass of hydrogen, represents the number of electron reactions per mole of hydrogen. is the Faraday constant, is the fuel cell current;

[0099] During battery discharge, The fuel cell system needs to replenish energy to maintain That is, at a certain future moment, the fuel cell will increase its output power by charging the battery to compensate for the battery discharge, thus ensuring Maintaining balance. This compensatory charging occurs under predictive conditions, so the operating efficiency of the fuel cell and power battery is uncertain and is usually assumed to be an average value. Similarly, during battery charging, due to the forward-looking nature of the energy consumption process, the efficiency of the relevant components is also considered to be an average value. Based on the above principles, the equivalent hydrogen consumption of the power battery is calculated as follows:

[0100] ;

[0101] Where, is the lower calorific value of hydrogen, take , is the average efficiency of the fuel cell, for Average converter efficiency, is the average charging efficiency of the power battery, is the average discharge efficiency of the power battery, The charging and discharging power of the power battery;

[0102] As the fuel cell voltage decreases, the fuel cell current needs to increase to maintain the same power output, which will lead to an increase in instantaneous hydrogen consumption. The additional hydrogen consumption caused by fuel cell aging is defined as aging-related hydrogen consumption, which is expressed as follows:

[0103] ;

[0104] The hydrogen consumption of the whole vehicle is the sum of the above three, as shown below:

[0105] ;

[0106] Where, is the fuel cell engine power, Before fuel cell engine degradation Output power at power, For fuel cell engines Power voltage decay value.

[0107] The present invention can be closer to the actual fuel cell system's load capacity by increasing the fuel cell power variation limit, reducing the impact of fuel cell power fluctuations on its life; When the fuel cell is running at minimum power rather than shutting down, it can reduce the number of starts and stops of the fuel cell system and extend the life of the fuel cell. This solves the problem that existing strategies only consider the energy consumption of fuel cell vehicles, but do not consider the service life of fuel cells and power batteries, and cannot effectively control the load range and the number of startups that can be achieved under load changes when the vehicle is in operation.

[0108] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A fuel cell vehicle energy management method, characterized in that: include: By analyzing the fuel cell and power battery, the fuel cell efficiency, power battery efficiency, fuel cell degradation, power battery degradation and power battery , and then calculate the equivalent hydrogen consumption; The power battery and vehicle power requirements The data is input into the fuzzy controller for data processing to obtain the fuel cell output power; Equivalent hydrogen consumption and fuel cell and power battery degradation levels are used as energy management strategy evaluation indicators to evaluate and manage vehicle energy consumption and the lifespan of fuel cells and power batteries. The required power of the vehicle Pre-processing is performed before inputting into the fuzzy controller. If the vehicle requires power <The minimum output power of the fuel cell, the vehicle power is provided by the power battery; if the vehicle requires power continuous If the time is 0, the fuel cell is turned off and the fuel cell output power is 0; If the vehicle requires continuous power If the time is not 0, a double-layer fuzzy controller is used; the vehicle power demand , power batteries The fuzzy coefficient is input into the first-layer fuzzy controller, and the fuel cell output power corresponding to the first-layer fuzzy controller is output according to the fuzzy rule; the fuel cell output power corresponding to the first-layer fuzzy controller at the previous moment is input into the second fuzzy controller, and the fuzzy coefficient is output according to the fuzzy rule and used as the fuzzy coefficient of the first-layer fuzzy controller; The fuzzy rule for the fuel cell output power corresponding to the first layer fuzzy controller output according to the fuzzy rule is as follows: , the vehicle is powered by the power battery. Power Battery , then the power battery and fuel cell work together and the fuel cell can charge the power battery. If the power battery The fuel cell provides the power required by the entire vehicle and charges the power battery; the fuzzy rule for outputting the fuzzy coefficient according to the fuzzy rule is that the difference between the fuel cell output power corresponding to the output of the second-layer fuzzy controller at the next moment and the fuel cell output power corresponding to the output of the first-layer fuzzy controller at the previous moment is within a preset range.

2. A fuel cell vehicle energy management method according to claim 1, characterized in that: The fuel cell efficiency is calculated by the following formula: ; Where, is the fuel cell efficiency, Output power for the fuel cell.

3. A fuel cell vehicle energy management method according to claim 2, characterized in that: The power battery efficiency is calculated by the following formula: ; Where, For power battery charging efficiency, is the power battery discharge efficiency, The internal resistance of the power battery at each state of charge, is the internal discharge resistance of the power battery at each state of charge; Output power for the power battery, It is the open circuit voltage of the power battery.

4. A fuel cell vehicle energy management method according to claim 3, characterized in that: The equivalent hydrogen consumption is calculated as follows: The hydrogen consumption of the fuel cell is calculated as follows: ; Where, is the number of fuel cells, is the molar mass of hydrogen, represents the number of electron reactions per mole of hydrogen. is the Faraday constant, is the fuel cell current; The equivalent hydrogen consumption of the power battery is calculated as follows: ; Where, is the lower calorific value of hydrogen, take , is the average efficiency of the fuel cell, for Average converter efficiency, is the average charging efficiency of the power battery, is the average discharge efficiency of the power battery, The charging and discharging power of the power battery; The additional hydrogen consumption due to fuel cell aging is defined as the hydrogen consumption corresponding to aging, which is expressed as follows: ; The hydrogen consumption of the whole vehicle is the sum of the above three, as shown below: ; Where, is the fuel cell engine power, Before fuel cell engine degradation Output power at power, For fuel cell engines Power voltage decay value.

5. The fuel cell vehicle energy management method according to claim 1, characterized in that: The fuel cell model of the fuel cell receives the fuel cell output power signal and performs logic processing to obtain the fuel cell efficiency, fuel cell and fuel cell degradation.

6. A fuel cell vehicle energy management method according to claim 5, characterized in that: The fuel cell efficiency is obtained by fitting the fuel cell power-efficiency curve using a fitting coefficient.

7. A fuel cell vehicle energy management method according to claim 5, characterized in that: The fuel cell Expressed in the form of fuel cell stack voltage: ; Where, is the stack voltage; is the fuel cell current; is the number of fuel cells; is the operating temperature, is the Tafel constant, is the concentration constant; is the open circuit voltage at a specified temperature and pressure; is the total resistance; is the exchange current; is the limiting current; For working hours.

8. The fuel cell vehicle energy management method according to claim 5, characterized in that: The fuel cell degradation is determined by the overall degradation of the fuel cell voltage, specifically: ; Where, is the total decay of the power battery voltage, is the performance degradation coefficient caused by the low power area of ​​the fuel cell, The time proportion when the fuel cell engine power is 10%-30% of the rated power, is the performance degradation coefficient caused by the high power area of ​​the fuel cell, The time proportion when the fuel cell engine power is 80%-100% of the rated power, is the fuel cell engine degradation coefficient caused by fuel cell engine power load change, For working hours, is the fuel cell engine power, is the performance degradation coefficient caused by the number of starts and stops of the fuel cell engine, The number of times the fuel cell engine is started and stopped.

9. The fuel cell vehicle energy management method according to claim 1, characterized in that: The power battery model of the power battery receives the power battery output power signal, performs logic processing and obtains the power battery efficiency, power battery and power battery degradation.

10. The fuel cell vehicle energy management method according to claim 1, characterized in that: The power battery It is calculated through the power battery current. The specific calculation is as follows: ; Where, is the initial state of charge of the power battery, is the rated capacity of the power battery, is the total integration time, It is the charging and discharging current of the power battery; The power battery charge and discharge current is obtained by calculating the power battery open circuit voltage, power battery output power, and power battery equivalent internal resistance as inputs to a power battery current calculation model.

11. The fuel cell vehicle energy management method according to claim 9, characterized in that: The power battery degradation is represented by its performance degradation rate: ; in is the degradation coefficient, the ideal gas constant , is the operating temperature, is the battery activation energy, Refers to the power battery in the process The absolute value of the cumulative change.

Citation Information

Patent Citations

  • Calculation method for optimal working state control strategy of fuel cell vehicle

    CN112918330A

  • Fuel cell vehicle energy management method and system based on seagull optimization algorithm

    CN114906014A

  • Fuel cell automobile energy management method and device based on snake optimization algorithm

    CN116714483A

  • An energy management strategy and system for a multi-stack fuel cell hybrid system for hydrogen electric vehicles

    CN118082630B