Fuel cell temperature control method and system

Abstract

The invention discloses a fuel cell temperature control method and system, and relates to the technical field of temperature control, the current fuel cell temperature is obtained in real time, the current to-be-driven route information of a target vehicle is obtained, and the flow speed of cooling liquid of a fuel cell of the target vehicle and the rotating speed of a fan are jointly adjusted; cooling the fuel cell based on the adjusted flow velocity of the cooling liquid and the fan rotating speed, and evaluating whether cooling is qualified or not; if the cooling is qualified, continuously cooling the fuel cell based on the adjusted flow speed of the cooling liquid of the target vehicle fuel cell and the fan rotating speed; if the cooling is not qualified, directly starting the maximum flow speed of the cooling liquid and the maximum rotating speed of the fan to control the temperature of the fuel cell; in the running process of the automobile, when cooling is needed, the flow speed of the cooling liquid and the air speed of the fan can be selected for cooling according to actual conditions, further damage to the fuel cell is reduced, meanwhile, the risk of fire disasters of the automobile is reduced, and hidden dangers in the running process are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control, and in particular to a fuel cell temperature control method and system thereof. Background Art

[0002] In the automotive field, fuel cell temperature control primarily involves effectively regulating the fuel cell's operating temperature to ensure it operates at optimal conditions and provides stable power output, ensuring safe driving and minimizing vehicle losses. Because fuel cells generate heat during power generation, excessively high temperatures can reduce efficiency or damage the cells. Therefore, cooling systems (such as liquid cooling and fans) are required to maintain an appropriate temperature range. Temperature control also extends the fuel cell's lifespan and improves overall energy efficiency.

[0003] However, when the car is driving and it is detected that the fuel cell temperature needs to be cooled, since cooling the car fuel cell temperature is a relatively long process, if the cooling method with the maximum coolant flow rate and the maximum fan speed is directly selected, it may cause thermal shock and damage the battery components. Secondly, the drastic changes in the cooling system may increase energy consumption, reduce the overall efficiency of the vehicle, and cause premature wear or failure of vehicle components. However, if the temperature is not cooled in time, there may be a further risk of fire in the car, deepening the hidden dangers during driving. Summary of the Invention

[0004] The purpose of the present invention is to solve the above-mentioned problems and provide a fuel cell temperature control method and system.

[0005] In a first aspect of the present invention, a fuel cell temperature control method is first proposed, the method comprising: Obtaining the current fuel cell temperature and the current route information of the target vehicle in real time, and adjusting the flow rate of the coolant and the fan speed of the target vehicle's fuel cell according to the current fuel cell temperature and the current route information; Cooling the fuel cell based on the adjusted coolant flow rate and fan speed, obtaining cooling evaluation information during the cooling process, and evaluating whether the cooling is qualified based on the cooling evaluation information; If the cooling is qualified, continue to cool the fuel cell based on the adjusted flow rate of the coolant and the fan speed of the fuel cell of the target vehicle; If the temperature reduction is unsatisfactory, the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell.

[0006] Optionally, the step of adjusting the coolant flow rate and fan speed of the fuel cell of the target vehicle according to the current fuel cell temperature and the current route information to be traveled is: Obtain the total distance of the route to be traveled and the average moving speed of the route to be traveled of the target vehicle, and divide them into different fuzzy sets based on the current fuel cell temperature, the total distance of the route to be traveled, and the average moving speed of the route to be traveled as input items of the fuzzy logic; The coolant flow rate and fan speed of the target vehicle's fuel cell are used as output items of fuzzy logic and divided into different fuzzy sets; Formulate fuzzy rules to describe the effects of the current fuel cell temperature, the total distance of the route to be traveled, and the average moving speed of the route to be traveled on the coolant flow rate and fan speed of the target vehicle's fuel cell; According to the fuzzy inference results, the flow rate of the coolant and the fan speed of the fuel cell of the target vehicle are output.

[0007] Optionally, the steps of cooling the fuel cell based on the adjusted coolant flow rate and fan speed, obtaining cooling evaluation information during the cooling process, and evaluating whether the cooling is qualified according to the cooling evaluation information are as follows: The cooling evaluation information includes a cooling uniformity coefficient, a cooling temperature effect coefficient, and a battery power stability coefficient. A cooling evaluation coefficient is obtained based on the cooling uniformity coefficient, the cooling temperature effect coefficient, and the battery power stability coefficient, and the cooling evaluation coefficient is compared with a preset cooling evaluation coefficient threshold. Whether the cooling is qualified is determined based on the comparison result.

[0008] Optionally, the steps for calculating the cooling uniformity coefficient are: Install temperature sensors at different locations of the fuel cell to obtain the temperatures at different locations of the fuel cell and obtain a set of fuel cell temperatures; Calculate the absolute difference between any two temperatures in the temperature set as the temperature difference, and construct an n×n temperature difference matrix, where each element represents the temperature difference between one temperature and another temperature; Sum all off-diagonal elements in the temperature difference matrix and divide by the number of all elements to get the average temperature difference; and calculate the standard deviation based on each temperature difference in the temperature difference matrix and the average temperature difference; Determine the maximum temperature difference and the minimum temperature difference in the temperature difference matrix, and calculate the cooling uniformity coefficient by combining the standard deviation and the average temperature difference. The calculation formula is: , where is the cooling uniformity coefficient, and The value range is 0-1. is the mean temperature difference, is the standard deviation, and are the minimum and maximum temperature differences, respectively.

[0009] Optionally, the steps for calculating the cooling temperature effect coefficient are: Temperature sensors are installed at different locations of the fuel cell to obtain the temperature before and current temperature of the fuel cell at different locations to obtain a temperature sequence; each element in the temperature sequence includes the temperature before and current temperature of a location. Calculate the difference between the temperature before cooling and the current temperature at each location as the effective cooling value, calculate the average of the effective cooling values, and obtain the total effective cooling value of the fuel cell; The total effective cooling value of the fuel cell is divided by the cooling time to obtain the cooling rate. The cooling rate is compared with the preset cooling rate range. If the cooling rate is within the preset cooling rate range, the cooling temperature effect coefficient is recorded as 1, otherwise it is recorded as 0.

[0010] Optionally, the steps for calculating the battery power stability coefficient are: Acquire the real-time discharge power signal of the fuel cell during the cooling process, perform Fourier transform on the discharge power signal, convert the discharge power signal into frequency, and obtain a frequency spectrum; Set a power threshold, record the area of ​​the frequency spectrum that is not less than the power threshold as the high-frequency area, and the area less than the power threshold as the low-frequency area. Calculate the energy of the low-frequency area and the total energy of the frequency spectrum, and divide the energy of the low-frequency area by the total energy of the frequency spectrum to obtain the stable battery power value; The battery power stability value is set to a preset standard battery power stability value to obtain a battery power stability coefficient.

[0011] Optionally, the step of obtaining the cooling evaluation coefficient according to the cooling uniformity coefficient, the cooling temperature effect coefficient, and the battery power stability coefficient is: The cooling uniformity coefficient, cooling temperature effect coefficient, and battery power stability coefficient are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as inputs of the machine learning model. The machine learning model uses each set of comprehensive feature vectors to predict the cooling evaluation coefficient labels as the prediction target, and minimizes the sum of the prediction errors of all cooling evaluation coefficient labels as the training target. The machine learning model is trained until the sum of the prediction errors reaches convergence, and the model training is stopped. The cooling evaluation coefficient is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0012] Optionally, the step of comparing the cooling evaluation coefficient with a preset cooling evaluation coefficient threshold and determining whether the cooling is qualified according to the comparison result is: The cooling evaluation coefficient is compared with a preset cooling evaluation coefficient threshold. If the cooling evaluation coefficient is less than the preset cooling evaluation coefficient threshold, it indicates that the cooling is unqualified. At this time, an alarm signal is issued to remind the driver, and the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell; If the temperature reduction evaluation coefficient is not less than the preset temperature reduction evaluation coefficient threshold, it indicates that the temperature reduction is qualified, and the fuel cell temperature is continued to be controlled based on the adjusted coolant flow rate and fan speed of the target vehicle fuel cell.

[0013] In a second aspect of the present invention, a fuel cell temperature control method system is provided, the system comprising: Adjustment module: obtains the current fuel cell temperature and the current route information of the target vehicle in real time, and adjusts the coolant flow rate and fan speed of the target vehicle's fuel cell according to the current fuel cell temperature and the current route information; Evaluation module: Cools the fuel cell based on the adjusted coolant flow rate and fan speed, obtains cooling evaluation information during the cooling process, and evaluates whether the cooling is qualified based on the cooling evaluation information; A first cooling control module: if the cooling is qualified, continuing to cool the fuel cell based on the adjusted flow rate of the coolant and the fan speed of the fuel cell of the target vehicle; The second cooling control module: If the cooling is unsatisfactory, the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell.

[0014] Beneficial effects of the present invention: The present invention proposes a fuel cell temperature control method and system thereof, which obtains the current fuel cell temperature and the current route information of the target vehicle in real time, and adjusts the coolant flow rate and fan speed of the target vehicle fuel cell according to the current fuel cell temperature and the current route information; cools the fuel cell based on the adjusted coolant flow rate and fan speed, obtains cooling evaluation information during the cooling process, and evaluates whether the cooling is qualified according to the cooling evaluation information; if the cooling is qualified, continues to cool the fuel cell based on the adjusted coolant flow rate and fan speed of the target vehicle fuel cell; if the cooling is unqualified, directly turns on the maximum coolant flow rate and the maximum fan speed to control the temperature of the fuel cell; in this way, when the car is driving, when it is detected that the fuel cell temperature needs to be cooled, the coolant flow rate and fan speed can be selected for cooling according to the actual situation, thereby reducing further damage to the fuel cell, reducing the risk of fire in the car, and alleviating hidden dangers during driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below with reference to the accompanying drawings.

[0016] Figure 1 is a flow chart of a fuel cell temperature control method; Figure 2 This is a framework diagram of a fuel cell temperature control method system. DETAILED DESCRIPTION

[0017] 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.

[0018] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0019] The embodiment of the present invention provides a fuel cell temperature control method. Figure 1 , Figure 1 A flow chart of a fuel cell temperature control method provided in an embodiment of the present invention. The method includes the following steps: Obtaining the current fuel cell temperature and the current route information of the target vehicle in real time, and adjusting the flow rate of the coolant and the fan speed of the target vehicle's fuel cell according to the current fuel cell temperature and the current route information; Cooling the fuel cell based on the adjusted coolant flow rate and fan speed, obtaining cooling evaluation information during the cooling process, and evaluating whether the cooling is qualified based on the cooling evaluation information; If the cooling is qualified, continue to cool the fuel cell based on the adjusted flow rate of the coolant and the fan speed of the fuel cell of the target vehicle; If the temperature reduction is unsatisfactory, the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell.

[0020] Based on a fuel cell temperature control method provided by an embodiment of the present invention, when a car is driving and it is detected that the fuel cell temperature needs to be cooled, the coolant flow rate and fan speed can be selected for cooling according to the actual situation, thereby reducing further damage to the fuel cell, reducing the risk of fire in the car, and alleviating hidden dangers during driving.

[0021] In one embodiment, the steps of adjusting the coolant flow rate and fan speed of the fuel cell of the target vehicle according to the current fuel cell temperature and the current travel route information are as follows: Obtain the total distance of the route to be traveled and the average moving speed of the route to be traveled of the target vehicle, and divide them into different fuzzy sets based on the current fuel cell temperature, the total distance of the route to be traveled, and the average moving speed of the route to be traveled as input items of the fuzzy logic; The coolant flow rate and fan speed of the target vehicle's fuel cell are used as output items of fuzzy logic and divided into different fuzzy sets; Formulate fuzzy rules to describe the effects of the current fuel cell temperature, the total distance of the route to be traveled, and the average moving speed of the route to be traveled on the coolant flow rate and fan speed of the target vehicle's fuel cell; According to the fuzzy inference results, the flow rate of the coolant and the fan speed of the fuel cell of the target vehicle are output.

[0022] It should be noted that to obtain vehicle route information: In practical applications, it is first necessary to obtain two key parameters of the route: Total distance (for example: 10 km, 50 km, 100 km, etc.), average moving speed (for example: 20 km / h, 50 km / h, 80 km / h, etc.); this information will help the system determine the workload and heat accumulation that the fuel cell will bear during driving.

[0023] 2. Fuzzy logic input definition: The input is broken down into three variables. Each variable is divided into different fuzzy sets based on its actual value, and each set is assigned a fuzzy linguistic value (such as "low," "medium," or "high"). These inputs serve as the basis for subsequent reasoning.

[0024] For example: Fuel cell temperature: Low temperature: <40°C; Normal temperature: 40°C-70°C; High temperature: 70°C; Total distance of the route to be traveled: Short distance: <30 km; Medium distance: 30 km-80 km; Long distance: 80 km; Average moving speed of the route to be traveled: low speed: <30km / h; medium speed: 30km / h-60km / h; high speed: 60km / h; 3. Fuzzy Logic Output Definition The output items are coolant flow rate and fan speed. Each output item needs to be divided into different fuzzy sets so that it can be adjusted during the reasoning process.

[0025] 3.1 Coolant flow rate (F_coolant) Low flow rate: 1L / min-5L / min Medium flow rate: 5L / min-10L / min High flow rate: 10L / min; 3.2 Fan speed (F_fan) Low speed: 1000rpm-2000rpm; Medium speed: 2000rpm-4000rpm; High speed: 4000rpm4; To link inputs and outputs, fuzzy rules were developed based on common usage scenarios. These rules describe how different combinations of fuel cell temperature, driving distance, and speed affect the selection of coolant flow rate and fan speed.

[0026] 4.1 Fuzzy Rule Example: If the fuel cell temperature is high, the distance is long, and the speed is high, then the coolant flow rate is high and the fan speed is high. If the fuel cell temperature is high, the distance is short, and the speed is low, then the coolant flow rate is medium and the fan speed is medium. If the fuel cell temperature is normal, the distance is medium, and the speed is medium, then the coolant flow rate is medium and the fan speed is medium. If the fuel cell temperature is low, the distance is long, and the speed is low, then the coolant flow rate is low and the fan speed is low.

[0027] 5. Fuzzy Reasoning and Output Fuzzy reasoning is to derive the final coolant flow rate and fan speed by deriving fuzzy rules between the input items (fuel cell temperature, total distance of the route to be traveled, and average moving speed) and the output items (coolant flow rate and fan speed).

[0028] 5.1 Fuzzy Reasoning Process: Fuzzification of Input Items: Based on the real-time information of fuel cell temperature, driving distance, and speed, each is converted into a corresponding fuzzy set. For example, if the current temperature is 75°C, the driving distance is 50 km, and the speed is 45 km / h, then: Fuel cell temperature = high temperature driving distance = medium speed = medium speed Rule matching and reasoning: According to these fuzzy set matching rules, the fuzzy values ​​of the coolant flow rate and fan speed are obtained through the inference system. For example, according to the first rule, when the temperature is high, the distance is medium, and the speed is medium, the coolant flow rate is "high" and the fan speed is "high". Defuzzification: Convert the fuzzy reasoning results into specific values. Assuming that the fuzzy reasoning results are "high flow rate" and "high speed", the specific coolant flow rate and fan speed can be obtained through the defuzzification algorithm (such as the weighted average method). For example: coolant flow rate: 9L / min (the weighted average between medium flow rate and high flow rate) fan speed: 3800rpm (the weighted average between medium speed and high speed); 5.2 Calculation Example: Current fuel cell temperature: 75°C → High temperature Total distance to be driven: 50 km → Medium distance Average moving speed: 45 km / h → Medium speed Based on fuzzy rule reasoning, it is concluded that: Coolant flow rate: 9 L / min Fan speed: 3800 rpm These two values ​​will be used as control parameters to adjust the fuel cell temperature of the target vehicle.

[0029] It's important to note that in this fuzzy logic-based fuel cell temperature control method, data acquisition encompasses multiple vehicle sensors and systems. First, the vehicle's navigation system and GPS obtain the total distance and average speed of the target vehicle's route, providing dynamic data on the route and speed. Next, the fuel cell's real-time temperature is monitored by built-in temperature sensors (such as thermocouples or RTD sensors) and fed back to the control system. Coolant flow rate and fan speed are monitored in real time by flow sensors and fan speed sensors, respectively, to ensure the cooling system effectively adjusts to temperature fluctuations. All this data is collected and processed by the vehicle's electronic control unit (ECU) and fed into a fuzzy logic inference engine. Based on the input data, the inference engine automatically adjusts the coolant flow rate and fan speed according to the defined fuzzy rules to ensure the fuel cell remains within a safe and effective operating temperature range, thereby improving overall system efficiency and safety. This approach enables intelligent temperature control in various driving environments.

[0030] In one implementation, this fuzzy logic temperature control method precisely adjusts the coolant flow rate and fan speed to operate the fuel cell within a safe and efficient temperature range based on actual driving conditions and real-time temperature changes. At the same time, it does not directly select the maximum coolant flow rate and fan speed for cooling, thereby reducing the probability of thermal shock and damage to battery components. Secondly, it also reduces energy consumption, reduces the overall efficiency of the vehicle, and reduces premature wear or failure of vehicle components.

[0031] In one embodiment, the steps of cooling the fuel cell based on the adjusted coolant flow rate and fan speed, obtaining cooling evaluation information during the cooling process, and evaluating whether the cooling is qualified according to the cooling evaluation information are as follows: The cooling evaluation information includes a cooling uniformity coefficient, a cooling temperature effect coefficient, and a battery power stability coefficient. A cooling evaluation coefficient is obtained based on the cooling uniformity coefficient, the cooling temperature effect coefficient, and the battery power stability coefficient, and the cooling evaluation coefficient is compared with a preset cooling evaluation coefficient threshold. Whether the cooling is qualified is determined based on the comparison result.

[0032] In one embodiment, the steps for calculating the cooling uniformity coefficient are: Install temperature sensors at different locations of the fuel cell to obtain the temperatures at different locations of the fuel cell and obtain a set of fuel cell temperatures; Calculate the absolute difference between any two temperatures in the temperature set as the temperature difference, and construct an n×n temperature difference matrix, where each element represents the temperature difference between one temperature and another temperature; Sum all off-diagonal elements in the temperature difference matrix and divide by the number of all elements to get the average temperature difference; and calculate the standard deviation based on each temperature difference in the temperature difference matrix and the average temperature difference; Determine the maximum temperature difference and the minimum temperature difference in the temperature difference matrix, and calculate the cooling uniformity coefficient by combining the standard deviation and the average temperature difference. The calculation formula is: , where is the cooling uniformity coefficient, and The value range is 0-1. is the mean temperature difference, is the standard deviation, and are the minimum and maximum temperature differences, respectively.

[0033] It should be noted that the data acquisition method involved in the above calculation process mainly relies on sensors and real-time monitoring systems. Specifically, temperature data is obtained by installing temperature sensors at various key locations of the fuel cell. These sensors monitor temperature changes within the battery in real time and transmit the data to the control system. The coolant flow rate and fan speed are measured in real time using flow meters and speed sensors to ensure that the cooling effect during the adjustment process is accurately monitored. At the same time, battery power data can be obtained through the battery management system (BMS) to monitor battery power output and stability in real time. This real-time data provides the basic support for calculating the cooling uniformity coefficient, battery power stability coefficient, and cooling temperature effect coefficient.

[0034] It should be noted that the TCU is a metric that measures the uniformity of temperature distribution across the fuel cell. It calculates the temperature differences between different locations on the fuel cell, reflecting the degree of temperature variation across different regions during the cooling process. A higher TCU indicates smaller temperature differences between different regions and a more uniform temperature distribution, indicating that the cooling system is more effectively balancing the temperature across the entire cell, preventing localized overheating or overcooling. A higher TCU indicates more uniform heat transfer during the cooling process, resulting in more effective cooling system regulation, effectively reducing the risk of fires caused by overheating and thus improving battery system safety. Maintaining good temperature uniformity during driving helps prevent localized overheating of the battery cells, thereby mitigating safety hazards caused by hot spots. Therefore, optimizing the coolant flow rate and fan speed to ensure a high TCU not only reduces battery failures due to overheating but also effectively reduces the risk of serious problems such as fires caused by uneven temperatures, thereby improving overall vehicle safety.

[0035] In one embodiment, the steps for calculating the cooling temperature effect coefficient are: Temperature sensors are installed at different locations of the fuel cell to obtain the temperature before and current temperature of the fuel cell at different locations to obtain a temperature sequence; each element in the temperature sequence includes the temperature before and current temperature of a location. Calculate the difference between the temperature before cooling and the current temperature at each location as the effective cooling value, calculate the average of the effective cooling values, and obtain the total effective cooling value of the fuel cell; The total effective cooling value of the fuel cell is divided by the cooling time to obtain the cooling rate. The cooling rate is compared with the preset cooling rate range. If the cooling rate is within the preset cooling rate range, the cooling temperature effect coefficient is recorded as 1, otherwise it is recorded as 0.

[0036] It should be noted that the preset cooling speed range is set by professionals based on actual conditions and is not specifically limited or elaborated on.

[0037] It should be noted that the cooling temperature effect coefficient is an important indicator for measuring the efficiency and effectiveness of fuel cell cooling. It calculates the change in fuel cell temperature per unit time (i.e., the cooling rate) and compares it with a preset cooling rate range to assess whether the cooling process meets the predetermined standards. Specifically, a larger cooling temperature effect coefficient means that the fuel cell temperature drops faster during the cooling process, and this rate remains within an appropriate range, indicating that the cooling system's adjustments (such as coolant flow rate and fan speed) are effective and can reduce the battery temperature from a high temperature to a safe range in a relatively short period of time, ensuring that the battery is always in a stable operating state. This coefficient reflects the effectiveness of the cooling system, ensuring that the battery's cooling process can quickly and effectively eliminate excessive temperatures and prevent local overheating and heat accumulation.

[0038] When the cooling temperature effect coefficient is large and meets the preset standards, it means that the fuel cell can quickly adjust its temperature and maintain thermal balance during the cooling process, thereby effectively preventing the battery from overheating. Overheating is a major cause of thermal runaway, performance degradation, and even fire in fuel cells. If the cooling effect is unsatisfactory (for example, the cooling rate is too slow or uneven), it may cause certain areas of the battery to overheat, which in turn may cause abnormal chemical reactions within the battery, increasing the risk of short circuits, overheating, and even fire. Therefore, maintaining a high cooling temperature effect coefficient not only helps ensure that the fuel cell operates within a high efficiency and safety range, but also significantly reduces the safety risks caused by excessive temperatures.

[0039] Furthermore, maintaining an appropriate cooling temperature coefficient is crucial for long-term battery life and performance. Slow or unstable cooling can lead to excessive thermal cycling and temperature fluctuations in the battery, which in turn can affect the battery's health, potentially accelerating the aging or damage of internal components and reducing the battery's overall efficiency. By optimizing the cooling system's regulation to ensure the cooling temperature coefficient remains within a reasonable range, battery damage or performance degradation due to overheating can be minimized. For vehicles, ensuring that batteries remain within a safe temperature range not only extends their service life but also reduces the likelihood of battery failure during driving, lowering the risk of serious accidents such as fires and explosions caused by battery failure. Therefore, effectively cooling the fuel cell based on adjusted coolant flow rate and fan speed not only optimizes the battery's operating temperature and reduces potential safety hazards, but also provides more reliable vehicle operation, ensuring stability and safety under various driving conditions.

[0040] In one embodiment, the steps for calculating the battery power stability coefficient are: Acquire the real-time discharge power signal of the fuel cell during the cooling process, perform Fourier transform on the discharge power signal, convert the discharge power signal into frequency, and obtain a frequency spectrum; Set a power threshold, record the area of ​​the frequency spectrum that is not less than the power threshold as the high-frequency area, and the area less than the power threshold as the low-frequency area. Calculate the energy of the low-frequency area and the total energy of the frequency spectrum, and divide the energy of the low-frequency area by the total energy of the frequency spectrum to obtain the stable battery power value; The battery power stability value is set to a preset standard battery power stability value to obtain a battery power stability coefficient.

[0041] It should be noted that the power threshold and the preset standard battery power stability value are set by professionals based on actual conditions and are not specifically limited or elaborated on.

[0042] It's important to note that the data involved in calculating the battery power stability factor is primarily acquired through real-time monitoring and data acquisition systems. Specifically, the fuel cell's discharge power signal is monitored in real time by the battery management system (BMS). This data reflects the battery's power output and its fluctuations. The power signal is typically measured using current and voltage sensors, from which the discharge power is calculated. Real-time discharge power data is then transmitted to the control system.

[0043] It should be noted that the battery power stability factor (BPF) is a key indicator for measuring the stability of a fuel cell's power output during the cooling process. It reflects the degree of power fluctuation in the fuel cell. It is calculated by analyzing the frequency spectrum of the battery's discharge power signal and calculating the ratio of the energy in the low-frequency region to the total energy. A higher BPF indicates more stable power output and lower power fluctuations, indicating effective cooling system regulation during the cooling process, maintaining a relatively stable battery operating state. Large fluctuations in battery power during the cooling process may be due to temperature imbalance, inadequate cooling, or overheating. This can lead to unstable chemical reactions within the battery, increasing the risk of overheating and failure. Therefore, a higher BPF indicates that the coolant flow rate and fan speed are effectively regulated, ensuring temperature balance within the battery and preventing localized overheating. This, in turn, reduces safety risks such as overheating, thermal runaway, and fires caused by overheating. Furthermore, the battery power stability coefficient is large, which not only helps to avoid excessive temperature fluctuations during the cooling process, but also reduces performance loss and system instability caused by uneven temperature, thereby reducing the probability of battery failure during driving, ensuring the safe operation of the vehicle and preventing the aggravation of hidden dangers during driving.

[0044] In one embodiment, the steps of obtaining the cooling evaluation coefficient according to the cooling uniformity coefficient, the cooling temperature effect coefficient, and the battery power stability coefficient are as follows: The cooling uniformity coefficient, cooling temperature effect coefficient, and battery power stability coefficient are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as inputs of the machine learning model. The machine learning model uses each set of comprehensive feature vectors to predict the cooling evaluation coefficient labels as the prediction target, and minimizes the sum of the prediction errors of all cooling evaluation coefficient labels as the training target. The machine learning model is trained until the sum of the prediction errors reaches convergence, and the model training is stopped. The cooling evaluation coefficient is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0045] In one embodiment, the step of comparing the cooling evaluation coefficient with a preset cooling evaluation coefficient threshold and determining whether the cooling is qualified according to the comparison result is as follows: The cooling evaluation coefficient is compared with a preset cooling evaluation coefficient threshold. If the cooling evaluation coefficient is less than the preset cooling evaluation coefficient threshold, it indicates that the cooling is unqualified. At this time, an alarm signal is issued to remind the driver, and the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell; If the temperature reduction evaluation coefficient is not less than the preset temperature reduction evaluation coefficient threshold, it indicates that the temperature reduction is qualified, and the fuel cell temperature is continued to be controlled based on the adjusted coolant flow rate and fan speed of the target vehicle fuel cell.

[0046] It should be noted that the preset cooling evaluation coefficient threshold is set by professionals based on actual conditions and is not specifically limited or elaborated.

[0047] In one implementation, after the cooling evaluation coefficient is calculated, the system compares it with a preset cooling evaluation coefficient threshold to determine whether the cooling process is satisfactory. The cooling evaluation coefficient reflects the effectiveness of the cooling process. If the calculated cooling evaluation coefficient is less than the preset threshold, it indicates a problem with the cooling process and that the effect has not met the expected standard. This may result in the fuel cell temperature not being effectively reduced to a safe range. In this case, the system automatically triggers an alarm signal, reminding the driver to pay close attention to the battery status to avoid safety issues such as overheating. Simultaneously, the system immediately activates the maximum coolant flow rate and maximum fan speed, using more aggressive cooling measures to quickly reduce the battery temperature and prevent battery failure or safety hazards caused by excessive temperatures. Conversely, if the cooling evaluation coefficient is not less than the preset threshold, indicating that the cooling effect has met the standard and the fuel cell temperature has stabilized within the safe range, the system will continue to maintain the current coolant flow rate and fan speed for continuous temperature control to ensure long-term stable battery operation and avoid battery performance loss or overcooling due to excessive cooling. This automated assessment and control can effectively reduce battery failures, extend battery life, and ensure battery safety during driving.

[0048] Based on the same inventive concept, the present invention also provides a fuel cell temperature control method and system. Figure 2 , Figure 2 A framework diagram of a fuel cell temperature control method system provided by an embodiment of the present invention, the system comprising: Adjustment module: obtains the current fuel cell temperature and the current route information of the target vehicle in real time, and adjusts the coolant flow rate and fan speed of the target vehicle's fuel cell according to the current fuel cell temperature and the current route information; Evaluation module: Cools the fuel cell based on the adjusted coolant flow rate and fan speed, obtains cooling evaluation information during the cooling process, and evaluates whether the cooling is qualified based on the cooling evaluation information; A first cooling control module: if the cooling is qualified, continuing to cool the fuel cell based on the adjusted flow rate of the coolant and the fan speed of the fuel cell of the target vehicle; The second cooling control module: If the cooling is unsatisfactory, the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell.

[0049] Based on a fuel cell temperature control method system provided by an embodiment of the present invention, when a car is driving and it is detected that the fuel cell temperature needs to be cooled, the coolant flow rate and fan speed can be selected for cooling according to the actual situation, thereby reducing further damage to the fuel cell, reducing the risk of fire in the car, and alleviating hidden dangers during driving.

[0050] The above is a detailed description of an embodiment of the present invention. However, the content is only a preferred embodiment of the present invention and should not be used to artificially limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A fuel cell temperature control method, characterized in that: The following steps are involved: Obtaining the current fuel cell temperature and the current route information of the target vehicle in real time, and adjusting the flow rate of the coolant and the fan speed of the target vehicle's fuel cell according to the current fuel cell temperature and the current route information; Cooling the fuel cell based on the adjusted coolant flow rate and fan speed, obtaining cooling evaluation information during the cooling process, and evaluating whether the cooling is qualified based on the cooling evaluation information; If the cooling is qualified, continue to cool the fuel cell based on the adjusted flow rate of the coolant and the fan speed of the fuel cell of the target vehicle; If the temperature reduction is unsatisfactory, the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell.

2. A fuel cell temperature control method according to claim 1, characterized in that: The steps of adjusting the coolant flow rate and fan speed of the fuel cell of the target vehicle according to the current fuel cell temperature and the current route information to be traveled are as follows: Obtain the total distance of the route to be traveled and the average moving speed of the route to be traveled of the target vehicle, and divide them into different fuzzy sets based on the current fuel cell temperature, the total distance of the route to be traveled, and the average moving speed of the route to be traveled as input items of the fuzzy logic; The coolant flow rate and fan speed of the target vehicle's fuel cell are used as output items of fuzzy logic and divided into different fuzzy sets; Formulate fuzzy rules to describe the effects of the current fuel cell temperature, the total distance of the route to be traveled, and the average moving speed of the route to be traveled on the coolant flow rate and fan speed of the target vehicle's fuel cell; According to the fuzzy inference results, the flow rate of the coolant and the fan speed of the fuel cell of the target vehicle are output.

3. A fuel cell temperature control method according to claim 1, characterized in that: The steps of cooling the fuel cell based on the adjusted coolant flow rate and fan speed, obtaining cooling evaluation information during the cooling process, and evaluating whether the cooling is qualified according to the cooling evaluation information are as follows: The cooling evaluation information includes a cooling uniformity coefficient, a cooling temperature effect coefficient, and a battery power stability coefficient. A cooling evaluation coefficient is obtained based on the cooling uniformity coefficient, the cooling temperature effect coefficient, and the battery power stability coefficient, and the cooling evaluation coefficient is compared with a preset cooling evaluation coefficient threshold. Whether the cooling is qualified is determined based on the comparison result.

4. A fuel cell temperature control method according to claim 3, characterized in that: The calculation steps of the cooling uniformity coefficient are as follows: Install temperature sensors at different locations of the fuel cell to obtain the temperatures at different locations of the fuel cell and obtain a set of fuel cell temperatures; Calculate the absolute difference between any two temperatures in the temperature set as the temperature difference, and construct an n×n temperature difference matrix, where each element represents the temperature difference between one temperature and another temperature; Sum all off-diagonal elements in the temperature difference matrix and divide by the number of all elements to get the average temperature difference; and calculate the standard deviation based on each temperature difference in the temperature difference matrix and the average temperature difference; Determine the maximum temperature difference and the minimum temperature difference in the temperature difference matrix, and calculate the cooling uniformity coefficient by combining the standard deviation and the average temperature difference. The calculation formula is: , where is the cooling uniformity coefficient, and The value range is 0-1. is the mean temperature difference, is the standard deviation, and are the minimum and maximum temperature differences, respectively.

5. A fuel cell temperature control method according to claim 4, characterized in that: The calculation steps of the cooling temperature effect coefficient are as follows: Temperature sensors are installed at different locations of the fuel cell to obtain the temperature before and current temperature of the fuel cell at different locations to obtain a temperature sequence; each element in the temperature sequence includes the temperature before and current temperature of a location. Calculate the difference between the temperature before cooling and the current temperature at each location as the effective cooling value, calculate the average of the effective cooling values, and obtain the total effective cooling value of the fuel cell; The total effective cooling value of the fuel cell is divided by the cooling time to obtain the cooling rate. The cooling rate is compared with the preset cooling rate range. If the cooling rate is within the preset cooling rate range, the cooling temperature effect coefficient is recorded as 1, otherwise it is recorded as 0.

6. A fuel cell temperature control method according to claim 3, characterized in that: The calculation steps of the battery power stability coefficient are: Acquire the real-time discharge power signal of the fuel cell during the cooling process, perform Fourier transform on the discharge power signal, convert the discharge power signal into frequency, and obtain a frequency spectrum; Set a power threshold, record the area of ​​the frequency spectrum that is not less than the power threshold as the high-frequency area, and the area less than the power threshold as the low-frequency area. Calculate the energy of the low-frequency area and the total energy of the frequency spectrum, and divide the energy of the low-frequency area by the total energy of the frequency spectrum to obtain the stable battery power value; The battery power stability value is set to a preset standard battery power stability value to obtain a battery power stability coefficient.

7. A fuel cell temperature control method according to claim 3, characterized in that: The steps to obtain the cooling evaluation coefficient based on the cooling uniformity coefficient, cooling temperature effect coefficient, and battery power stability coefficient are as follows: The cooling uniformity coefficient, cooling temperature effect coefficient, and battery power stability coefficient are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as inputs of the machine learning model. The machine learning model uses each set of comprehensive feature vectors to predict the cooling evaluation coefficient labels as the prediction target, and minimizes the sum of the prediction errors of all cooling evaluation coefficient labels as the training target. The machine learning model is trained until the sum of the prediction errors reaches convergence, and the model training is stopped. The cooling evaluation coefficient is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

8. A fuel cell temperature control method according to claim 3, characterized in that: The steps of comparing the cooling evaluation coefficient with a preset cooling evaluation coefficient threshold and determining whether the cooling is qualified according to the comparison result are as follows: The cooling evaluation coefficient is compared with a preset cooling evaluation coefficient threshold. If the cooling evaluation coefficient is less than the preset cooling evaluation coefficient threshold, it indicates that the cooling is unqualified. At this time, an alarm signal is issued to remind the driver, and the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell; If the temperature reduction evaluation coefficient is not less than the preset temperature reduction evaluation coefficient threshold, it indicates that the temperature reduction is qualified, and the fuel cell temperature is continued to be controlled based on the adjusted coolant flow rate and fan speed of the target vehicle fuel cell.

9. A fuel cell temperature control system, used to implement a fuel cell temperature control method according to any one of claims 1 to 8, characterized in that: The system comprises: Adjustment module: obtains the current fuel cell temperature and the current route information of the target vehicle in real time, and adjusts the coolant flow rate and fan speed of the target vehicle's fuel cell according to the current fuel cell temperature and the current route information; Evaluation module: Cools the fuel cell based on the adjusted coolant flow rate and fan speed, obtains cooling evaluation information during the cooling process, and evaluates whether the cooling is qualified based on the cooling evaluation information; A first cooling control module: if the cooling is qualified, continuing to cool the fuel cell based on the adjusted flow rate of the coolant and the fan speed of the fuel cell of the target vehicle; The second cooling control module: If the cooling is unsatisfactory, the maximum flow rate of the coolant and the maximum speed of the fan are directly turned on to control the temperature of the fuel cell.

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