Tractor ploughing hybrid power system control method fusing fuel cell health state

Abstract

The invention provides a tractor ploughing hybrid power system control method fusing the health state of a fuel cell, and the method comprises the steps: receiving data collected by a sensor through a vehicle control unit, and building a total demand power model during the ploughing operation of a tractor; carrying out on-line adaptive estimation on the health state of the fuel cell; judging the health state of the fuel cell based on the health coefficient of the fuel cell; calculating an energy gap; and controlling the working mode switching of the tractor. Performance degradation of the fuel cell under the severe ploughing working condition can be effectively slowed down, the service life of the fuel cell is prolonged while the operation dynamic property is guaranteed, and the economical efficiency and adaptability of the system are improved.

Description

Technical Field

[0001] This invention belongs to the field of new energy agricultural vehicle control technology, and particularly relates to a control method for a tractor plowing hybrid power system that integrates the health status of fuel cells. Background Technology

[0002] With the trend towards low-carbon development in agricultural machinery, fuel cell hybrid tractors have gradually become a research hotspot. Fuel cell hybrid tractors operate in harsh environments during plowing and other agricultural tasks, with significant load fluctuations and considerably higher vibration and dust levels than road vehicles, which can easily lead to fuel cell performance degradation and shortened lifespan. To ensure operational power, energy management strategies are needed to coordinate the power distribution between the fuel cell and the battery.

[0003] In existing research, fuel cell agricultural machinery energy management strategies mostly focus on power coordination and optimization among multiple energy sources. For example, existing technology 1 (Xu Wenxiang, Zhu Yejun, Xiao Maohua, Liu Mengnan, YeLiling, Yang Yanpeng, Liu Ze. Energy-saving and stability-enhancing control for unmanned distributed drive electric plant protection vehicle based on active torque distribution[J]. Artificial Intelligence in Agriculture, 2026,16: 495–513.) coordinates the power output of fuel cells, power batteries, and other power sources through a strategy of maximizing energy efficiency; existing technology 2 (Li Xianzhe, Xu Liyou, Liu Mengnan, Yan Xianghai, Zhang Mingzhu. Research on torque cooperative control of distributed drive system for fuel cell electric tractor[J]. Computers and Electronics in Agriculture, 2024,219: 108811.) utilizes the frequency characteristics of load power to perform power shunting in order to improve the operational stability of fuel cells under fluctuating loads. However, these methods are generally based on the assumption that the fuel cell output capacity remains constant, failing to adequately consider the decrease in available power and weakened dynamic response caused by the degradation of the fuel cell's State of Health (SOH) under complex real-world operating conditions. After fuel cell degradation, traditional control still allocates power according to the rated capacity, which can easily lead to insufficient power or subject the fuel cell to dynamic loads exceeding its actual capacity, accelerating aging. Therefore, there is an urgent need for a control method that can incorporate the real-time health status of the fuel cell and adaptively allocate power based on its actual available capacity. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a control method for a tractor-plowing hybrid power system that integrates the health status of the fuel cell, enabling adaptive power allocation based on the real-time health status of the fuel cell and its actual available capacity.

[0005] The present invention achieves the above-mentioned technical objectives through the following technical means.

[0006] A control method for a tractor-plowing hybrid power system that incorporates fuel cell health status includes the following processes: Step 1: The vehicle controller receives data collected by various sensors on the tractor and data input on the tractor terminal setting interface to establish a total power demand model for the tractor during plowing operations; Step 2: The vehicle controller performs online adaptive estimation of the fuel cell's health status to obtain the fuel cell's current comprehensive health status; Step 3: The vehicle controller calculates the fuel cell health coefficient based on the current overall health status of the fuel cell, and then determines the health status of the fuel cell. Step 4: When the current available power limit of the fuel cell cannot meet the total power demand of the tractor, the resulting energy gap is made up by the power battery; Step 5: The vehicle controller switches the tractor's operating mode based on the fuel cell health status assessment results.

[0007] Furthermore, in step 1, the total power demand model for tractor plowing operations is as follows:

[0008]

[0009]

[0010]

[0011] in, This represents the total power demand of the current tractor. The power required for the tractor to overcome traction resistance. The PTO rotational power required to drive the plowshare is For total traction resistance, For the mechanical efficiency of the transmission system. For soil specific resistance, The specific torque coefficient of the rotary plow. For soil density, The rotor radius is... The angular velocity of the PTO axis. For PTO transmission efficiency; The depth of plowing; The width of a single-furrow plowshare; The number of plowshares; This refers to the operating speed of the tractor.

[0012] Furthermore, the specific process of step 2 is as follows: Step 2.1: The vehicle controller collects the output voltage, output current, temperature, and rate of change of the load-requested power of the fuel cell in real time; Step 2.2: The vehicle controller sequentially calculates health indicators based on ohmic internal resistance. Health indicators based on dynamic response Health indicators based on output voltage ; Step 2.3: The vehicle controller calculates the tractor's current real-time load rate and load change rate:

[0013]

[0014] in, For real-time load rate, This represents the maximum usable output power of the fuel cell under the current SOH constraint. This refers to the maximum permissible discharge power of the power battery. For real-time load change rate, For discrete-time indexing, For the vehicle controller in the first The real-time load rate calculated within each control cycle This represents the real-time load rate from the previous control cycle. To control the time interval of the cycle; When the real-time load change rate When it is large, increase weight To enhance the model's sensitivity to transient performance degradation; when the real-time load rate When the level is high and the change is stable, increase them respectively. and weight , To reflect the impact of long-term heavy load on performance degradation; when the real-time load rate When the system is at a lower level or under rapid transition or light load conditions, increase The health assessment relies on the Ohmic internal resistance index; where the weights satisfy the following conditions: ; The current overall health status of the fuel cell is as follows:

[0015] in, This represents the current overall health status of the fuel cell.

[0016] Furthermore, the specific process of step 2.2 is as follows: The vehicle controller periodically injects a high-frequency, small-amplitude alternating current signal into the fuel cell stack. The amplitude of the AC voltage response is measured by a high-bandwidth differential voltage acquisition module installed at the fuel cell stack. The vehicle controller extracts the voltage response component with the same frequency as the injected AC current through a built-in bandpass filter and digital phase-locked amplification algorithm, thereby obtaining the AC voltage response amplitude. The vehicle controller utilizes the current control capability of the fuel cell DC-DC converter to superimpose a preset small-amplitude sinusoidal disturbance current onto the steady-state output current of the fuel cell, resulting in the actual output current of the fuel cell stack being:

[0017] in, This represents the actual output current of the fuel cell stack. For time variables, This refers to the steady-state output current of the fuel cell. The amplitude of the alternating current disturbance. The angular frequency of the AC disturbance signal; Based on the extracted AC voltage response amplitude and AC disturbance current amplitude, calculate the current ohmic internal resistance of the fuel cell. :

[0018] Then, health indicators based on ohmic internal resistance are calculated. ; The vehicle controller monitors the natural step change of the load current in real time. When the step amplitude exceeds a set threshold, it records the voltage response curve and extracts the voltage response time constant through first-order system fitting. Then, health indicators based on dynamic response are calculated. ; When the system operates under steady-state conditions near the rated current, the vehicle controller collects the average output voltage. and average output current The output voltage at the rated current of the fuel cell under current conditions is obtained through standardized correction, and then a health index based on the output voltage is calculated. .

[0019] Furthermore, the health index based on ohmic internal resistance for:

[0020] middle, This is the ohmic internal resistance at the end of the fuel cell's lifespan. The ohmic internal resistance of the fuel cell in its initial state; The health indicators based on dynamic response for:

[0021] in, This is the time constant at the end of the fuel cell's lifespan. The response time constant under the initial state; The health index based on output voltage for:

[0022] in, This represents the output voltage at the rated current of the fuel cell under its current condition. This is the output voltage at the rated current in the initial state of the fuel cell.

[0023] Furthermore, in step 3, hour This indicates that fuel cells are at their peak. hour This indicates that the fuel cell is in a mild degradation phase. hour This indicates that the fuel cell is in a moderate decline phase. hour This indicates that the fuel cell is in a period of severe degradation. hour This indicates that the fuel cell is in its failure period; This indicates the fuel cell health coefficient; when the fuel cell in a hybrid tractor degrades, the current maximum sustainable output power of the fuel cell also decreases. To delay the degradation of the fuel cell, an upper limit is set on the current available power of the fuel cell.

[0024] The present invention has the following beneficial effects: This invention introduces an adaptive weighted algorithm to comprehensively estimate the state of power (SOH) of a fuel cell using three easily obtainable online characteristic parameters: ohmic internal resistance, dynamic response, and voltage decay. This is no longer a fixed estimation algorithm, but rather one that intelligently adjusts according to the workload, fully leveraging the strengths of each indicator under different operating conditions and avoiding the limitations of a single indicator. Specifically optimized for the characteristics of tractor plowing operations, this invention can adaptively allocate power based on the real-time health status of the fuel cell and its actual available capacity. The estimation accuracy is continuously optimized as the operation progresses, enabling intelligent operation and better adaptability in complex agricultural scenarios.

[0025] This invention is designed for agricultural working conditions. It proposes a three-index model based on ohmic internal resistance, dynamic response, and voltage. It also creatively uses fuzzy logic to dynamically adjust the weights of each index according to the real-time load rate and load change rate, thereby achieving more accurate and robust online SOH estimation.

[0026] This invention combines SOH with a power limiting closed loop, directly and dynamically applying the estimated SOH to the calculation formula of the maximum available power of the fuel cell, while simultaneously considering steady-state limits and dynamic ramp rate limits. This invention establishes a hierarchical mode switching control strategy. Based on discrete health states, it presets multiple operating modes from "full function" to "protection / limp", forming a complete adaptive energy management framework with the protection of fuel cell health as its core. Attached Figure Description

[0027] Figure 1 This is a block diagram of the control logic of the tractor-plowing hybrid power system integrating fuel cell health status as described in this invention. Detailed Implementation

[0028] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but the scope of protection of the present invention is not limited thereto.

[0029] The control method for a tractor-plowing hybrid power system integrating fuel cell health status as described in this invention is as follows: Figure 1 As shown, the specific process includes the following: Step 1: The tractor performs plowing operations. During this process, the tractor's operating speed is acquired in real time via a magnetoelectric speed sensor installed on the gearbox output shaft or an onboard GNSS module (i.e., Global Navigation Satellite System). The plowing depth is measured in real time by an angle sensor installed on the lifting arm of the tractor's three-point suspension or a stroke sensor installed on the hydraulic lifting cylinder of the plow. The width of the single-furrow plowshare is automatically read by the tractor's attachment identification system or entered by the driver in the terminal settings interface. The number of plowshares can be automatically identified by the plow attachment identification module or by entering the number of plowshares into the terminal settings interface before operation. The collected information is then transmitted to the tractor's vehicle control unit (VCU). After receiving the data, the vehicle controller establishes the total power demand model for tractor plowing operations as shown below, which includes the power required for the tractor to overcome traction resistance and the rotational power of the power take-off (PTO) shaft required to drive the plow:

[0030]

[0031]

[0032]

[0033] in, This represents the total power demand of the current tractor. The power required for the tractor to overcome traction resistance. The PTO rotational power required to drive the plowshare is For total traction resistance, For the mechanical efficiency of the transmission system. Soil specific drag represents the resistance experienced per unit cultivated cross-sectional area. The specific torque coefficient of the rotary plow. For soil density, The rotor radius is... The angular velocity of the PTO axis. For PTO transmission efficiency.

[0034] Step 2: The vehicle controller performs online adaptive estimation of the fuel cell's health status. Step 2.1: The vehicle controller collects the output voltage, output current, temperature, and rate of change of the load-requested power of the fuel cell in real time; Step 2.2: The vehicle controller periodically injects a high-frequency, small-amplitude AC current signal into the fuel cell stack. The AC voltage response amplitude is measured by a high-bandwidth differential voltage acquisition module installed at the fuel cell stack. The vehicle controller extracts the voltage response component with the same frequency as the injected AC current through a built-in bandpass filter and digital phase-locked amplification algorithm, thereby obtaining the AC voltage response amplitude. The vehicle controller utilizes the current control capability of the fuel cell DC-DC converter to superimpose a preset small-amplitude sinusoidal disturbance current onto the steady-state output current of the fuel cell, resulting in the actual output current of the fuel cell stack being:

[0035] in, This represents the actual output current of the fuel cell stack. This is a time variable used to describe the instantaneous output current change of the fuel cell stack during a disturbance period. This refers to the steady-state output current of the fuel cell. The amplitude of the alternating current disturbance. This is the angular frequency of the AC disturbance signal.

[0036] Based on the extracted AC voltage response amplitude and AC disturbance current amplitude, calculate the current ohmic internal resistance of the fuel cell:

[0037] in, For fuel cells The ohmic internal resistance value at time t. The amplitude of the AC voltage response. This represents the amplitude of the alternating current disturbance.

[0038] Then, the health index based on ohmic internal resistance is obtained according to the following formula. :

[0039] in, As a health indicator based on ohmic internal resistance, This is the ohmic internal resistance at the end of the fuel cell's lifespan. This represents the ohmic internal resistance of the fuel cell in its initial state.

[0040] The tractor's overall controller monitors the natural step changes of the load current in real time. When the step amplitude exceeds a set threshold, it records the voltage response curve and extracts the voltage response time constant through first-order system fitting. Then, the health index based on dynamic response is calculated according to the following formula. :

[0041] in, As a health indicator based on dynamic response, This is the time constant at the end of the fuel cell's lifespan. is the response time constant under the initial state.

[0042] When the system operates under steady-state conditions near the rated current, the vehicle controller collects the average output voltage. and average output current The output voltage at the rated current of the fuel cell under current conditions is obtained through standardized correction, and then the health index based on the output voltage is calculated according to the following formula. :

[0043] in, As a health indicator based on output voltage, This represents the output voltage at the rated current of the fuel cell under its current condition. This is the output voltage at the rated current in the initial state of the fuel cell.

[0044] Step 2.3: The vehicle controller calculates the tractor's current real-time load rate and load change rate: in, For real-time load rate, This represents the maximum usable output power of the fuel cell under the current SOH constraint. This refers to the maximum permissible discharge power of the power battery.

[0045] Real-time load rate The membership functions include three fuzzy subsets: low load, medium load, and high load. Its membership functions are in... The axes are distributed in trapezoidal and triangular shapes, with left-shoulder membership functions used for low loads. High membership degree within a small range; triangular membership function is used for medium loads. The middle interval has the highest membership degree; high load uses a right-shoulder membership function. Larger intervals have higher membership degrees. The three membership functions mentioned above... There is some overlap on the axes to achieve continuous division of load states; The formula for calculating the real-time load change rate is:

[0046] in, For real-time load change rate, For discrete-time index, indicating the first... One control cycle, For the vehicle controller in the first The real-time load rate calculated within each control cycle This represents the real-time load rate from the previous control cycle. The time interval for controlling the cycle is set by the system sampling cycle.

[0047] Real-time load change rate The membership functions include three fuzzy subsets: gradual, moderate, and abrupt. Gradual changes use left-shoulder membership functions, moderate changes use triangular membership functions, and abrupt changes use right-shoulder membership functions, respectively describing different states of load change rate from stable and slightly fluctuating to rapid abrupt changes. The three membership functions are partially overlapping on the φ axis to ensure the continuity of fuzzy inference input and to reflect the intensity of load fluctuations.

[0048] when A larger value indicates a significant change in the tractor's operating load, such as encountering hard soil or rocks; when A lower load factor indicates that the system is in a light-load or driving state; a higher load factor and a stable change indicate that the tractor is in deep plowing or stable heavy-load operation.

[0049] Define real-time load rate Membership degree is used to represent The degree of matching belonging to the low-load, medium-load, or high-load fuzzy subset, with a value ranging from 0 to 1, and the load change rate. The membership degree is used to represent the degree of matching of a variable to a slowly varying, moderately varying, or drastically varying fuzzy subset, and its value ranges from 0 to 1. A higher membership degree indicates that the variable is closer to the operating conditions defined by that fuzzy subset. The vehicle controller then... and The membership degree was determined using a fuzzy logic lookup table method to identify three types of health indicators. , , The adaptive weighting coefficients are determined using the following method: When the real-time load change rate When the value is large, improve the dynamic response health indicators. weight To enhance the model's sensitivity to transient performance degradation; when the real-time load rate When the ohmic internal resistance is high and changes steadily, it improves the health index. and rated point voltage index weight , This is to reflect the impact of long-term heavy load on performance degradation; when the real-time load rate R is low or the system is in a rapid transition or light load state, effective dynamic response and rated point data cannot be obtained, mainly improving... Health estimation is performed based on the ohmic internal resistance index, and the final adaptive weights must satisfy the following:

[0050] Current overall health status of fuel cells The weighted formula yields:

[0051] Step 3: When the tractor is plowing, the state of health (SOH) of the fuel cell is first determined, and the evaluation parameter for the fuel cell's health status is set as the fuel cell health coefficient. The specific evaluation is as follows: hour This indicates that fuel cells are at their peak. hour This indicates that the fuel cell is in a mild degradation phase. hour This indicates that the fuel cell is in a moderate decline phase. hour This indicates that the fuel cell is in a period of severe degradation. hour This indicates that the fuel cell is in its failure period; Indicates the health coefficient of the fuel cell; When the fuel cell in a hybrid tractor degrades, the maximum sustainable output power of the fuel cell also decreases. To mitigate this degradation, a current available power limit is set for the fuel cell. .

[0052] Step 4: When the current available power limit of the fuel cell cannot meet the total power demand of the tractor, the resulting energy gap is made up by the power battery; whereby the energy gap is:

[0053]

[0054] in, The energy gap between the total power demand of tractors and the current available power limit of fuel cells. This represents the current maximum available power of the fuel cell. The initial rated power of the fuel cell ( hour), The fuel cell output power of the previous control cycle. This represents the maximum allowable power change rate of the fuel cell under its current health condition. To control the cycle.

[0055] Step 5: The hybrid tractor obtains information through the vehicle controller. Then, switch the tractor's operating mode: If the sum of the current available power limit of the fuel cell and the output power of the power battery is still insufficient to meet the total power demand of the tractor, then enter mode M0, that is, temporarily unlock the output power of the fuel cell to the maximum available power of the fuel cell. If the sum of the current available power limit of the fuel cell and the maximum allowable discharge power of the power battery is still less than the total power demand of the tractor, then proceed to the next step of switching the working mode: When the fuel cell is in full power output mode M1, it enters mode M1, meaning the fuel cell outputs its rated power at full capacity. It can be briefly overloaded to the rated power, and the power battery responds quickly, allowing the power to climb faster to keep up with the load; When the power output of the fuel cell is limited to the upper limit of the available power (90% of the rated power), the power battery response is smooth, the power change rate is limited, and dynamic stress is reduced. When the fuel cell is in degraded operation, the output is limited to a lower available power limit (80% of the rated power). The power battery aims for stability and operates at a constant power point as much as possible to avoid any drastic changes. When the power supply is in a certain state, it enters mode M4, which strictly protects the output of a very low constant power (60% of the rated power) or is used only for charging the power battery. The power battery avoids dynamic response and will not respond to rapid load changes under any circumstances. When the fuel cell outputs a very low constant power or acts only as a charger, the battery becomes the sole power source. The system may only retain its core mobility function to ensure that the driver can reach the repair site.

[0056] In the above process, in modes M0 to M5, it is required that when the total power demand of the tractor during plowing operations is less than the sum of the maximum available power of the current battery system and fuel cell system, the rate of increase of the total power demand of the tractor during plowing operations is less than the rate of increase of the current maximum power of the fuel cell.

[0057] In modes M0 to M5, the SOC of the tractor power battery is ultimately maintained at a high level to ensure its ability to compensate for power gaps, while effectively suppressing the rate of decline in the state of health (SOH) of the fuel cell.

[0058] The embodiments described above are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Any obvious improvements, substitutions or modifications that can be made by those skilled in the art without departing from the essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A control method for a tractor-plowing hybrid power system integrating fuel cell health status, characterized in that, The process includes the following: Step 1: The vehicle controller receives data collected by various sensors on the tractor and data input on the tractor terminal setting interface to establish a total power demand model for the tractor during plowing operations; Step 2: The vehicle controller performs online adaptive estimation of the fuel cell's health status to obtain the fuel cell's current comprehensive health status; Step 3: The vehicle controller calculates the fuel cell health coefficient based on the current overall health status of the fuel cell, and then determines the health status of the fuel cell. Step 4: When the current available power limit of the fuel cell cannot meet the total power demand of the tractor, the resulting energy gap is made up by the power battery; Step 5: The vehicle controller switches the tractor's operating mode based on the fuel cell health status assessment results.

2. The control method for a tractor-plowing hybrid power system integrating fuel cell health status according to claim 1, characterized in that, In step 1, the total power demand model for tractor plowing operations is as follows: ； ； ； ； in, This represents the total power demand of the current tractor. The power required for the tractor to overcome traction resistance. The PTO rotational power required to drive the plowshare is For total traction resistance, For the mechanical efficiency of the transmission system. For soil specific resistance, The specific torque coefficient of the rotary plow. For soil density, The rotor radius is... The angular velocity of the PTO axis. For PTO transmission efficiency; The depth of plowing; The width of a single-furrow plowshare; The number of plowshares; This refers to the operating speed of the tractor.

3. The control method for a tractor-plowing hybrid power system integrating fuel cell health status according to claim 1, characterized in that, The specific process of step 2 is as follows: Step 2.1: The vehicle controller collects the output voltage, output current, temperature, and rate of change of the load-requested power of the fuel cell in real time; Step 2.2: The vehicle controller sequentially calculates health indicators based on ohmic internal resistance. Health indicators based on dynamic response Health indicators based on output voltage ; Step 2.3: The vehicle controller calculates the tractor's current real-time load rate and load change rate: ； ； in, For real-time load rate, This represents the total power demand of the current tractor. This represents the maximum usable output power of the fuel cell under the current SOH constraint. This refers to the maximum permissible discharge power of the power battery. For real-time load change rate, For discrete-time indexing, For the vehicle controller in the first The real-time load rate calculated within each control cycle This represents the real-time load rate from the previous control cycle. To control the time interval of the cycle; When the real-time load change rate When it is large, increase weight To enhance the model's sensitivity to transient performance degradation; when the real-time load rate When the level is high and the change is stable, increase them respectively. and weight , To reflect the impact of long-term heavy load on performance degradation; when the real-time load rate When the system is at a lower level or under rapid transition or light load conditions, increase The health assessment relies on the Ohmic internal resistance index; where the weights satisfy the following conditions: ; The current overall health status of the fuel cell is as follows: ； in, This represents the current overall health status of the fuel cell.

4. The control method for a tractor-plowing hybrid power system integrating fuel cell health status according to claim 3, characterized in that, The specific process of step 2.2 is as follows: The vehicle controller periodically injects a high-frequency, small-amplitude alternating current signal into the fuel cell stack. The amplitude of the AC voltage response is measured by a high-bandwidth differential voltage acquisition module installed at the fuel cell stack. The vehicle controller extracts the voltage response component with the same frequency as the injected AC current through a built-in bandpass filter and digital phase-locked amplification algorithm, thereby obtaining the AC voltage response amplitude. The vehicle controller utilizes the current control capability of the fuel cell DC-DC converter to superimpose a preset small-amplitude sinusoidal disturbance current onto the steady-state output current of the fuel cell, resulting in the actual output current of the fuel cell stack being: ； in, This represents the actual output current of the fuel cell stack. For time variables, This refers to the steady-state output current of the fuel cell. The amplitude of the alternating current disturbance. The angular frequency of the AC disturbance signal; Based on the extracted AC voltage response amplitude and AC disturbance current amplitude, calculate the current ohmic internal resistance of the fuel cell. : ； Then, health indicators based on ohmic internal resistance are calculated. ; The vehicle controller monitors the natural step change of the load current in real time. When the step amplitude exceeds a set threshold, it records the voltage response curve and extracts the voltage response time constant through first-order system fitting. Then, health indicators based on dynamic response are calculated. ; When the system operates under steady-state conditions near the rated current, the vehicle controller collects the average output voltage. and average output current The output voltage at the rated current of the fuel cell under current conditions is obtained through standardized correction, and then a health index based on the output voltage is calculated. .

5. The control method for a tractor-plowing hybrid power system integrating fuel cell health status according to claim 4, characterized in that, The health index based on ohmic resistance for: ； middle, This is the ohmic internal resistance at the end of the fuel cell's lifespan. The ohmic internal resistance of the fuel cell in its initial state; The health indicators based on dynamic response for: ； in, This is the time constant at the end of the fuel cell's lifespan. The response time constant under the initial state; The health index based on output voltage for: ； in, This represents the output voltage at the rated current of the fuel cell under its current condition. This is the output voltage at the rated current in the initial state of the fuel cell.

6. The control method for a tractor-plowing hybrid power system integrating fuel cell health status according to claim 3, characterized in that, In step 3 hour This indicates that fuel cells are at their peak. hour This indicates that the fuel cell is in a mild degradation phase. hour This indicates that the fuel cell is in a moderate decline phase. hour This indicates that the fuel cell is in a period of severe degradation. hour This indicates that the fuel cell is in its failure period; This indicates the fuel cell health coefficient; when the fuel cell in a hybrid tractor degrades, the current maximum sustainable output power of the fuel cell also decreases. To delay the degradation of the fuel cell, an upper limit is set on the current available power of the fuel cell.

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