Parameter determination method, device and electronic equipment for fuel cell

Abstract

This disclosure relates to a method, apparatus, and electronic device for determining parameters of a fuel cell, relating to the field of vehicles. The method includes: acquiring multiple operating data points of a vehicle; determining energy flow data corresponding to each operating data point, thereby obtaining multiple energy flow data points; wherein the energy flow data points include one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, total vehicle energy consumption, and vehicle operating differential time; and determining the vehicle's efficiency parameters under the multiple operating data points and / or the multiple energy flow data points. This method enables rapid analysis of fuel cell data from multiple vehicles, reducing the manpower and resources required for fuel cell vehicle data analysis and providing corresponding data analysis support for the development of fuel cell vehicles.

Description

Technical Field

[0001] This disclosure relates to the field of vehicles, and more specifically, to a method, apparatus, and electronic device for determining parameters of a fuel cell. Background Technology

[0002] Currently, hydrogen fuel cell vehicles are in a stage of rapid development. However, the current calculation methods for parameters such as system efficiency, hydrogen consumption per 100 kilometers, electricity consumption per 100 kilometers, and changes in energy flow of fuel cells can only be performed offline based on data, which wastes a lot of human and material resources and makes it difficult to provide corresponding data analysis for the development of fuel cell vehicles. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides a method, apparatus and electronic device for determining parameters of a fuel cell.

[0004] According to a first aspect of the present disclosure, a method for determining parameters of a fuel cell is provided, the method comprising:

[0005] Acquire multiple operational data points of the vehicle;

[0006] Based on each of the multiple operating data, the energy flow data corresponding to each operating data is determined, resulting in multiple energy flow data; wherein, the energy flow data includes one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, vehicle energy consumption, and vehicle operating differential time;

[0007] The efficiency parameters of the vehicle under the multiple operating data are determined based on the multiple operating data and / or the multiple energy flow data.

[0008] Optionally, the efficiency parameters include:

[0009] One or more of the following: fuel cell system efficiency, hydrogen utilization rate, average hydrogen-to-electric conversion rate of fuel cell stack, average hydrogen-to-electric conversion rate of fuel cell system, electricity consumption per 100 kilometers, and hydrogen consumption per 100 kilometers.

[0010] Optionally, each of the plurality of operating data includes: fuel cell power demand; when the efficiency parameter is the fuel cell system efficiency, determining the vehicle's efficiency parameter under the plurality of operating data based on the plurality of operating data and / or the plurality of energy flow data includes:

[0011] The target power is determined by the power demand of the fuel cell;

[0012] The efficiency of the vehicle's fuel cell system is determined based on the target power, the plurality of operating data, and the plurality of energy flow data.

[0013] Optionally, determining the target power based on the fuel cell's power demand includes:

[0014] The target power is determined based on the number of times each fuel cell's required power appears in the plurality of energy flow data.

[0015] Optionally, each of the plurality of operating data includes: the average single-cell voltage of the fuel cell, and determining the fuel cell system efficiency of the vehicle based on the target power, the plurality of operating data, and the plurality of energy flow data includes:

[0016] The difference between the fuel cell system output power and the target power for each of the multiple energy flow data is used to determine at least one energy flow data and at least one operating data corresponding to the target power;

[0017] The fuel cell stack efficiency of the vehicle at the target power is determined based on the average single cell voltage of the fuel cell in at least one of the operating data.

[0018] The proportion of fuel cell system accessory energy consumption of the vehicle at the target power is determined based on the fuel cell system output energy and fuel cell stack output energy in the at least one energy flow data.

[0019] The fuel cell system efficiency of the vehicle at the target power is determined based on the fuel cell stack efficiency and the proportion of energy consumption of the fuel cell system accessories.

[0020] Optionally, determining the proportion of fuel cell system accessory energy consumption of the vehicle at the target power based on the fuel cell system output energy and fuel cell stack output energy from the at least one energy flow data includes:

[0021] The energy consumption ratio of the fuel cell system accessories in the vehicle at the target power is determined by the following formula:

[0022]

[0023] Wherein, K1 represents the proportion of fuel cell system accessory energy consumption of the vehicle at the target power;

[0024] I represents the quantity of the at least one energy flow data;

[0025] x i This represents the fuel cell stack output energy of the i-th energy flow data in the at least one energy flow data;

[0026] y i This represents the fuel cell system output energy of the i-th energy flow data in the at least one energy flow data.

[0027] Optionally, each of the plurality of operational data further includes: cumulative operational mileage, and the method further includes:

[0028] When the efficiency parameter is the hydrogen utilization rate, the hydrogen utilization rate of the vehicle in the plurality of operating data is determined based on the actual hydrogen consumption and theoretical hydrogen consumption in the plurality of energy flow data.

[0029] When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell stack, the average hydrogen-to-electric conversion rate of the vehicle's fuel cell stack in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell stack in the multiple energy flow data.

[0030] When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell system, the average hydrogen-to-electric conversion rate of the vehicle's fuel cell system in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell system in the multiple energy flow data.

[0031] When the efficiency parameter is the energy consumption per 100 kilometers, the energy consumption per 100 kilometers of the vehicle in the multiple operating data is determined based on the cumulative operating mileage in the multiple operating data and the energy consumption of the whole vehicle in the energy flow data corresponding to each operating data.

[0032] When the efficiency parameter is the hydrogen consumption per 100 kilometers, the hydrogen consumption per 100 kilometers of the vehicle in the multiple operating data is determined based on the electricity consumption per 100 kilometers, the actual hydrogen consumption in the multiple energy flow data, and the output energy of the fuel cell system.

[0033] Optionally, the method further includes:

[0034] Based on the filtering criteria, obtain multiple operating data, energy flow data, and efficiency parameters of at least one vehicle from the big data platform;

[0035] Multiple operating data, energy flow data, and efficiency parameters of the at least one vehicle are visualized.

[0036] According to a second aspect of the present disclosure, a parameter determination apparatus for a fuel cell is provided, applied to a big data platform, the apparatus comprising:

[0037] The acquisition module is used to acquire multiple operational data of the vehicle;

[0038] The data processing module is used to determine the energy flow data corresponding to each of the multiple operating data to obtain multiple energy flow data; wherein, the energy flow data includes one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, vehicle energy consumption, and vehicle operating differential time.

[0039] The determination module is used to determine the efficiency parameters of the vehicle under the plurality of operating data based on the plurality of operating data and / or the plurality of energy flow data.

[0040] According to a third aspect of the present disclosure, an electronic device is provided, comprising:

[0041] A memory on which computer programs are stored;

[0042] A processor is configured to execute the computer program in the memory to implement the steps of the parameter determination method for a fuel cell provided in the first aspect of this disclosure.

[0043] The above technical solution acquires multiple operational data points from the vehicle. Based on each operational data point, energy flow data is determined, resulting in multiple energy flow data sets. These energy flow data sets include one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, total vehicle energy consumption, and vehicle operating differential time. Based on these multiple operational data points and / or the multiple energy flow data sets, the vehicle's efficiency parameters under these multiple operational data points are determined. This method enables rapid analysis of fuel cell data from multiple vehicles, reducing the manpower and resources required for fuel cell vehicle data analysis and providing corresponding data analysis support for the development of fuel cell vehicles.

[0044] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0045] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0046] Figure 1 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment.

[0047] Figure 2 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment.

[0048] Figure 3 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment.

[0049] Figure 4 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment.

[0050] Figure 5 This is a block diagram illustrating a parameter determination device 500 for a fuel cell according to an exemplary embodiment.

[0051] Figure 6 This is a block diagram illustrating an electronic device 600 according to an exemplary embodiment. Detailed Implementation

[0052] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0053] It should be noted that all actions involving the acquisition of signals, information, or data in this disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with authorization from the owner of the relevant device.

[0054] Figure 1 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment, such as... Figure 1 As shown, when applied to a big data platform, this method includes the following steps:

[0055] In step S11, multiple operational data of the vehicle are acquired.

[0056] For example, in the embodiments described in this disclosure, the vehicle is a hydrogen fuel cell vehicle, using hydrogen as its primary energy source. The fuel cell converts hydrogen and oxygen into electrical energy, which drives an electric motor to propel the vehicle. A big data platform is a system integrating technologies and services that can process, store, analyze, and manage large amounts of data. It supports data collection, cleaning, integration, analysis, and visualization. Therefore, within this big data platform, the operational data of each vehicle connected to the platform can be collected, cleaned, integrated, analyzed, and visualized. It is understandable that the status of a vehicle's fuel cell, energy flow data, and efficiency parameters (fuel cell system efficiency, hydrogen utilization rate, average hydrogen-to-electric conversion rate of the fuel cell stack, average hydrogen-to-electric conversion rate of the fuel cell system, energy consumption per 100 kilometers, hydrogen consumption per 100 kilometers, etc.) may vary significantly due to different external environments within different time intervals. Therefore, these multiple operating data can be multiple operating data of the vehicle within a specified time interval; for example, the specified time can be 1 month, 1 quarter, 1 year, etc. For example, at the end of each quarter, the big data platform can trigger the acquisition of multiple operating data of the vehicle in that quarter, and clean, integrate, analyze, and visualize the multiple operating data of the vehicle, and can also store the cleaned, integrated, analyzed, and visualized operating data and results in the big data platform. Furthermore, this disclosure allows multiple operational data points for each vehicle to be stored in a database associated with a big data platform. For example, each operational data point for a vehicle may include one or more of the following: fuel cell stack output voltage, fuel cell stack output current, fuel cell system output voltage, fuel cell system output current, total power battery current, total power battery voltage, data time, maximum hydrogen pressure, hydrogen system temperature, power battery status, cumulative mileage, drive motor speed, drive motor torque, average single-cell voltage of fuel cell, and fuel cell power demand. These multiple operational data points can be stored in a database associated with the big data platform. Each data table in this database can store multiple operational data points for different vehicles. The row values ​​of the data tables can be used to represent one operational data point, and the column values ​​can be used to represent one or more parameters.

[0057] Optionally, after acquiring the multiple operating data, the method further includes deleting null values ​​and abnormal 0 values ​​from the multiple operating data, and deleting operating data in which the power battery is in a charging state.

[0058] In step S12, energy flow data corresponding to each operating data is determined based on each of the multiple operating data, resulting in multiple energy flow data; wherein, the energy flow data includes one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, vehicle energy consumption, and vehicle operating differential time.

[0059] For example, the multiple operational data are arranged in order from earliest to latest according to the data time (which can be the time when the vehicle reports each operational data to the big data platform, or the time when the big data platform stores the data).

[0060] In summary, the energy flow data corresponding to each operational data point is determined, and this energy flow data can include:

[0061] Vehicle operation differential time: The data time of each operation data is converted into a timestamp, and the difference between the timestamp of each operation data and the timestamp of the operation data immediately preceding it is used as the vehicle operation differential time.

[0062] Fuel cell stack output power = fuel cell stack output voltage × fuel cell stack output current;

[0063] Fuel cell system output power = fuel cell system output voltage × fuel cell system output current;

[0064] Power battery output power = total power battery current × total power battery voltage;

[0065] Total vehicle power consumption = Fuel cell system output power + Power battery output power;

[0066] Drive motor power consumption = drive motor speed × drive motor torque ÷ 9550;

[0067] Power consumed by vehicle accessories = Power consumed by the whole vehicle - Power consumed by the drive motor;

[0068] Fuel cell system accessory power = fuel cell stack output power - fuel cell system output power;

[0069] Hydrogen storage capacity of the hydrogen system: The hydrogen storage capacity of the hydrogen system is determined based on the maximum hydrogen pressure and the temperature of the hydrogen system.

[0070] Hydrogen addition amount: When the difference between the hydrogen storage amount of the hydrogen system and the preceding operating data is greater than or equal to a specified difference, it can be determined that the hydrogen system has been added, and the difference is taken as the hydrogen addition amount; when the difference is less than the specified difference, it can be determined that the hydrogen system has not been added, and the hydrogen addition amount for that operating data is 0.

[0071] Theoretical hydrogen consumption: determined by the output current of the fuel cell stack and the differential time of vehicle operation;

[0072] For example, through formula M represents the theoretical hydrogen consumption; I represents the output current of the fuel cell stack; t represents the vehicle's differential operating time; n represents the number of individual fuel cells.

[0073] Fuel cell stack output energy = fuel cell stack output power × vehicle operating differential time;

[0074] Fuel cell system output energy = fuel cell system output power × vehicle operating differential time;

[0075] Power battery output energy = power battery power × vehicle operating differential time;

[0076] Drive motor energy = drive motor power × vehicle operating differential time;

[0077] Vehicle energy consumption = Vehicle power consumption × Vehicle operating differential time;

[0078] Energy consumed by vehicle accessories = Power consumed by vehicle accessories × Vehicle operating differential time;

[0079] Fuel cell system accessory energy = fuel cell system accessory power column data × vehicle operating differential time;

[0080] It is understood that the above energy flow data is not the only type of energy flow data for vehicles, and the calculation of other energy flow data will not be elaborated in this disclosure.

[0081] Therefore, the energy flow data corresponding to each operational data point can be determined through the relevant parameters in the operational data. Thus, this energy flow data can be calculated on the big data platform based on the operational data reported by the vehicle, or it can be calculated by the vehicle's onboard system before reporting each operational data point and its corresponding energy flow data to the big data platform. This disclosure does not impose any restrictions on this. Furthermore, if the operational data and corresponding energy flow data are stored in a database, multiple operational data points and energy flow data points for each vehicle can be stored in the same data table or in different data tables. This disclosure does not impose any restrictions on this.

[0082] In step S13, the efficiency parameters of the vehicle under the multiple operating data and / or the multiple energy flow data are determined based on the multiple operating data.

[0083] Optionally, the efficiency parameter includes one or more of the following: fuel cell system efficiency, hydrogen utilization rate, average hydrogen-to-electric conversion rate of fuel cell stack, average hydrogen-to-electric conversion rate of fuel cell system, energy consumption per 100 kilometers, and hydrogen consumption per 100 kilometers.

[0084] For example, based on the multiple operating data and / or the multiple energy flow data, the efficiency parameters of the vehicle under the multiple operating data can be determined. The efficiency parameters may include at least one or more of the following: fuel cell system efficiency, hydrogen utilization rate, average hydrogen-to-electric conversion rate of fuel cell stack, average hydrogen-to-electric conversion rate of fuel cell system, energy consumption per 100 kilometers, and hydrogen consumption per 100 kilometers. Thus, the vehicle status can be monitored based on the operating data, the energy flow data, and the efficiency parameters. In addition, the operating data, energy flow data, and efficiency parameters of multiple vehicles can be analyzed in a unified manner, thereby providing corresponding data support for the development of fuel cell vehicles.

[0085] The above technical solution acquires multiple operational data points from the vehicle. Based on each operational data point, energy flow data is determined, resulting in multiple energy flow data sets. These energy flow data sets include one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, total vehicle energy consumption, and vehicle operating differential time. Based on these multiple operational data points and / or the multiple energy flow data sets, the vehicle's efficiency parameters under these multiple operational data points are determined. This method enables rapid analysis of fuel cell data from multiple vehicles, reducing the manpower and resources required for fuel cell vehicle data analysis and providing corresponding data analysis support for the development of fuel cell vehicles.

[0086] Figure 2 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment, such as... Figure 2 As shown, each of the multiple operating data includes: fuel cell power demand. When the efficiency parameter is the efficiency of the fuel cell system, step S13 includes the following steps:

[0087] In step S131, the target power is determined based on the fuel cell's power demand.

[0088] For example, the fuel cell power demand is the power output of the fuel cell when it needs to meet the vehicle's power requirements. However, the actual output power of the fuel cell system is not necessarily equal to the fuel cell power demand. The efficiency of a fuel cell system refers to its ability to convert chemical energy into electrical energy, and this ability may differ at different output power levels. Therefore, the fuel cell system efficiency of the vehicle may vary under different fuel cell power demand conditions. In summary, one or more target power values ​​can be determined from the fuel cell power demand values ​​in the multiple energy flow data, and the fuel cell system efficiency of the vehicle at different target power values ​​can be determined based on the target power, the multiple operating data values, and the multiple energy flow data values.

[0089] Optionally, the target power is determined based on the number of times each fuel cell power demand appears in the multiple energy flow data.

[0090] For example, the target power can be the fuel cell demand power that appears most frequently in multiple energy flow data sets; or it can be the fuel cell demand power that appears more than or equal to a specified number of times in multiple energy flow data sets, and there can be one or more target powers; or it can be the mode of the target power of the fuel cell system in multiple energy flow data sets; or it can be determined by other means. Furthermore, the target power can also be a preset value in the big data platform, and this disclosure does not limit the method for determining the target power.

[0091] In step S132, the efficiency of the vehicle's fuel cell system is determined based on the target power, the plurality of operating data, and the plurality of energy flow data.

[0092] Figure 3 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment, such as... Figure 3 As shown, each of the multiple operating data includes: average single-cell voltage of the fuel cell. Step S132 includes the following steps:

[0093] In step S1321, at least one energy flow data and at least one operating data corresponding to the target power are determined by the difference between the fuel cell system output power of each energy flow data and the target power.

[0094] For example, when determining the efficiency of the fuel cell system corresponding to the target power, at least one energy flow data corresponding to the target power can be determined from the difference between the output power of the fuel cell system and the target power for each energy flow data. For instance, if the difference between the output power of the fuel cell system and the target power for any energy flow data is less than a specified threshold, then that energy flow data can be determined as an energy flow data corresponding to the target power. Through this method, at least one energy flow data corresponding to the target power can be determined. Furthermore, in step S12, each operating data corresponds to one energy flow data; therefore, by determining at least one energy data, at least one operating data corresponding to the target power can be determined.

[0095] Optionally, after determining the at least one energy flow data and the at least one operating data, the at least one energy flow data and the at least one operating data can be filtered. For example, energy flow data corresponding to discontinuous values ​​of fuel cell system output power can be filtered out from the plurality of energy flow data, and operating data corresponding to the filtered energy flow data can be filtered out from the at least one operating data. Discontinuous values ​​of fuel cell system output power refer to the absence of immediately preceding and immediately following energy flow data in the at least one energy flow data. Alternatively, multiple consecutive energy flow data can be selected from the at least one energy flow data as the at least one energy flow data.

[0096] In step S1322, the fuel cell stack efficiency of the vehicle at the target power is determined based on the average single cell voltage of the fuel cell in the at least one operating data.

[0097] Alternatively, the fuel cell stack efficiency can be determined using the following formula:

[0098]

[0099] Wherein, K2 represents the fuel cell stack efficiency of the vehicle at the target power;

[0100] I represents the quantity of at least one running data;

[0101] z i This represents the average single-cell voltage of the fuel cell in the i-th operating data among at least one operating data set;

[0102] This represents the average value of the average single-cell voltage of the fuel cell in at least one operating data point;

[0103] U represents the theoretical voltage value of the lower calorific value of hydrogen.

[0104] In step S1323, the proportion of fuel cell system accessory energy consumption of the vehicle at the target power is determined based on the fuel cell system output energy and fuel cell stack output energy in the at least one energy flow data.

[0105] Optionally, the proportion of fuel cell system accessory energy consumption for the vehicle at the target power can be determined using the following formula:

[0106]

[0107] K3 represents the percentage of fuel cell system accessory energy consumption for the vehicle at the target power.

[0108] I represents the quantity of at least one energy flow data;

[0109] x i This represents the fuel cell stack output energy of the i-th energy flow data in at least one energy flow data;

[0110] y i This represents the fuel cell system output energy of the i-th energy flow data in at least one energy flow data.

[0111] In step S1324, the fuel cell system efficiency of the vehicle at the target power is determined based on the fuel cell stack efficiency and the proportion of energy consumption of the fuel cell system accessories.

[0112] For example, the fuel cell system efficiency of the vehicle at the target power can be determined by multiplying the fuel cell stack efficiency and the energy consumption of the fuel cell system accessories.

[0113] Optionally, each of the plurality of operational data includes: cumulative operational mileage, and the method further includes:

[0114] When the efficiency parameter is the hydrogen utilization rate, the hydrogen utilization rate of the vehicle in the multiple operating data is determined based on the actual hydrogen consumption and theoretical hydrogen consumption in the multiple energy flow data.

[0115] When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell stack, the average hydrogen-to-electric conversion rate of the fuel cell stack of the vehicle in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell stack in the multiple energy flow data.

[0116] When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell system, the average hydrogen-to-electric conversion rate of the vehicle's fuel cell system in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell system in the multiple energy flow data.

[0117] When the efficiency parameter is the energy consumption per 100 kilometers, the energy consumption per 100 kilometers of the vehicle in the multiple operating data is determined based on the cumulative operating mileage in the multiple operating data and the energy consumption of the whole vehicle in the energy flow data corresponding to each operating data.

[0118] When the efficiency parameter is the hydrogen consumption per 100 kilometers, the hydrogen consumption per 100 kilometers of the vehicle is determined based on the electricity consumption per 100 kilometers, the actual hydrogen consumption in the multiple energy flow data, and the output energy of the fuel cell system.

[0119] For example, the hydrogen utilization rate, average hydrogen-to-electric conversion rate of the fuel cell stack, average hydrogen-to-electric conversion rate of the fuel cell stack, energy consumption per 100 kilometers, and hydrogen consumption per 100 kilometers of the vehicle can be determined respectively using the following formulas:

[0120]

[0121]

[0122] Among these, V represents the actual hydrogen consumption of the vehicle in these multiple operating data points;

[0123] K4 represents the hydrogen utilization rate of the vehicle among these multiple operating data points;

[0124] M represents the number of these multiple energy flow data;

[0125] v m This represents the theoretical hydrogen consumption of the m-th energy flow data among the multiple energy flow data;

[0126] Q max This represents the maximum cumulative mileage among the multiple operational data points;

[0127] Q min This represents the minimum cumulative mileage among the multiple operational data points;

[0128] q m This represents the amount of hydrogen added to the m-th energy flow data among the multiple energy flow data;

[0129] K5 represents the average hydrogen-to-electric conversion efficiency of the vehicle's fuel cell stack across these multiple operational data points;

[0130] x m This represents the fuel cell stack output energy of the m-th energy flow data among the multiple energy flow data;

[0131] K6 represents the average hydrogen-to-electric conversion rate of the vehicle's fuel cell system across these multiple operational data points;

[0132] y m This represents the output energy of the fuel cell system for the m-th energy flow data among the multiple energy flow data;

[0133] The K7's energy consumption per 100 kilometers is among these multiple operating data points;

[0134] J m This represents the total energy consumption of the vehicle in the m-th energy flow data among the multiple energy flow data;

[0135] K max This represents the maximum cumulative mileage among the multiple operational data points;

[0136] K min This represents the minimum cumulative mileage among the multiple operational data points.

[0137] K8 indicates the vehicle's hydrogen consumption per 100 kilometers among these multiple operating data points.

[0138] Optionally, each of the plurality of operational data may further include: vehicle speed;

[0139] For example, the energy consumed by the vehicle while parking can be determined by the sum of the total vehicle energy in the energy flow data corresponding to at least one operating data point when the vehicle speed is 0 in multiple operating data points.

[0140] At this point, the total energy consumption of the vehicle during operation in these multiple operating data points = total energy consumption of the vehicle - energy consumption while parked;

[0141] Therefore, the energy consumption per 100 kilometers of vehicle operation can be determined using the following formula:

[0142]

[0143] Among these, the K9's multiple operational data points include the vehicle's energy consumption per 100 kilometers during operation;

[0144] Q R This indicates the energy consumed by the entire vehicle during operation;

[0145] K max This represents the maximum cumulative mileage among the multiple operational data points;

[0146] K min This represents the minimum cumulative mileage among the multiple operational data points.

[0147] The hydrogen consumption per 100 kilometers during vehicle operation can be determined using the following formula:

[0148]

[0149] Among them, K 10 The hydrogen consumption per 100 kilometers during vehicle operation is included in these multiple operational data points;

[0150] The K9's energy consumption per 100 kilometers during vehicle operation is among these multiple operational data points;

[0151] V. The actual hydrogen consumption of the vehicle in these multiple operating data;

[0152] y m This represents the output energy of the fuel cell system for the m-th energy flow data among the multiple energy flow data.

[0153] Optionally, the big data platform can store multiple operating data for each vehicle associated with the big data platform, and automatically determine the energy flow data and efficiency parameters corresponding to the multiple operating data of each vehicle through the method described in the embodiments of this disclosure when a specified time is reached (such as the end of each month, the end of each quarter, etc.). The determined energy flow data and efficiency parameters of each vehicle can be stored in the big data platform, and the data of at least one vehicle can be automatically visualized on the visualization interface of the big data platform through data visualization analysis methods such as line charts, scatter plots, bubble charts, and tables. It is understood that this disclosure does not limit the way the data is displayed.

[0154] Figure 4 This is a flowchart illustrating a method for determining parameters of a fuel cell according to an exemplary embodiment, such as... Figure 4 As shown, the method also includes the following steps:

[0155] In step S14, multiple operating data, energy flow data and efficiency parameters of at least one vehicle are obtained from the big data platform according to the filtering conditions.

[0156] In step S15, multiple operating data, energy flow data and efficiency parameters of the at least one vehicle are visualized.

[0157] For example, the big data platform may include a visualization interface for analyzing and displaying the operating data, energy flow data, and efficiency parameters of one or more vehicles, allowing staff to intuitively observe changes in vehicle data. Furthermore, the visualization interface can display data based on user-input filtering conditions, which may include one or more of the following: vehicle identification number, vehicle announcement number, quarter, month, data to be displayed, and time interval. This disclosure does not limit the filtering conditions. Additionally, if the big data platform does not store the energy flow data and efficiency parameters of a vehicle's fuel cell within the time interval specified in the filtering conditions, the energy flow data and efficiency parameters of the vehicle can be calculated using the method described in the embodiments of this disclosure, and then visualized after calculation.

[0158] For example, the energy consumption per 100 kilometers of all vehicles with the same announcement number in a certain quarter can be used as the vertical axis and the identification code of each vehicle as the horizontal axis, and displayed in the form of a scatter plot on the visualization platform. This can quickly and effectively present the distribution of energy consumption per 100 kilometers of vehicles with the same announcement number in the same quarter.

[0159] The above technical solution acquires multiple operational data points from the vehicle. Based on each operational data point, energy flow data is determined, resulting in multiple energy flow data sets. These energy flow data sets include one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, total vehicle energy consumption, and vehicle operating differential time. Based on these multiple operational data points and / or the multiple energy flow data sets, the vehicle's efficiency parameters under these multiple operational data points are determined. This method enables rapid analysis of fuel cell data from multiple vehicles, reducing the manpower and resources required for fuel cell vehicle data analysis and providing corresponding data analysis support for the development of fuel cell vehicles.

[0160] Figure 5 This is a block diagram illustrating a parameter determination device 500 for a fuel cell according to an exemplary embodiment. Figure 5 As shown, the device is applied to a big data platform and includes: an acquisition module 510, a data processing module 520, and a determination module 530.

[0161] The acquisition module 510 is used to acquire multiple operating data of the vehicle;

[0162] The data processing module 520 determines the energy flow data corresponding to each of the multiple operating data based on each operating data, thereby obtaining multiple energy flow data; wherein, the energy flow data includes one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, vehicle energy consumption, and vehicle operating differential time.

[0163] The determining module 530 is used to determine the efficiency parameters of the vehicle under the plurality of operating data based on the plurality of operating data and / or the plurality of energy flow data.

[0164] Optionally, the efficiency parameter includes:

[0165] One or more of the following: fuel cell system efficiency, hydrogen utilization rate, average hydrogen-to-electric conversion rate of fuel cell stack, average hydrogen-to-electric conversion rate of fuel cell system, electricity consumption per 100 kilometers, and hydrogen consumption per 100 kilometers.

[0166] Optionally, each of the plurality of operating data includes: fuel cell power demand; the determining module 530 includes: a first determining submodule and a second determining submodule.

[0167] The first determining submodule is used to determine the target power based on the fuel cell's required power.

[0168] The second determining submodule is used to determine the fuel cell system efficiency of the vehicle based on the target power, the plurality of operating data and the plurality of energy flow data.

[0169] Optionally, the first determining submodule is also configured to determine the target power based on the number of times each fuel cell power demand appears in the plurality of energy flow data.

[0170] Optionally, each of the plurality of operating data includes: the average single-cell voltage of the fuel cell. The second determining submodule is also used for:

[0171] The difference between the fuel cell system output power and the target power for each of the multiple energy flow data is used to determine at least one energy flow data and at least one operating data corresponding to the target power;

[0172] The fuel cell stack efficiency of the vehicle at the target power is determined based on the average single cell voltage of the fuel cell in at least one of the operating data.

[0173] The proportion of fuel cell system accessory energy consumption of the vehicle at the target power is determined based on the fuel cell system output energy and fuel cell stack output energy in at least one energy flow data.

[0174] The efficiency of the fuel cell system of the vehicle at the target power is determined based on the efficiency of the fuel cell stack and the proportion of energy consumption of the fuel cell system accessories.

[0175] Optionally, the second determining submodule is further configured to determine the proportion of fuel cell system accessory energy consumption of the vehicle at the target power using the following formula:

[0176]

[0177] Wherein, K1 represents the proportion of fuel cell system accessory energy consumption of the vehicle at the target power;

[0178] I represents the quantity of at least one energy flow data;

[0179] x i This represents the fuel cell stack output energy of the i-th energy flow data in at least one energy flow data;

[0180] y iThis represents the fuel cell system output energy of the i-th energy flow data in at least one energy flow data.

[0181] Optionally, the determining module 530 is also used for:

[0182] When the efficiency parameter is the hydrogen utilization rate, the hydrogen utilization rate of the vehicle in the multiple operating data is determined based on the actual hydrogen consumption and theoretical hydrogen consumption in the multiple energy flow data.

[0183] When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell stack, the average hydrogen-to-electric conversion rate of the fuel cell stack of the vehicle in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell stack in the multiple energy flow data.

[0184] When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell system, the average hydrogen-to-electric conversion rate of the vehicle's fuel cell system in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell system in the multiple energy flow data.

[0185] When the efficiency parameter is the energy consumption per 100 kilometers, the energy consumption per 100 kilometers of the vehicle in the multiple operating data is determined based on the cumulative operating mileage in the multiple operating data and the energy consumption of the whole vehicle in the energy flow data corresponding to each operating data.

[0186] When the efficiency parameter is the hydrogen consumption per 100 kilometers, the hydrogen consumption per 100 kilometers of the vehicle is determined based on the electricity consumption per 100 kilometers, the actual hydrogen consumption in the multiple energy flow data, and the output energy of the fuel cell system.

[0187] Optionally, the device 500 also includes a display module;

[0188] This display module is used for:

[0189] Based on the filtering criteria, obtain multiple operating data, energy flow data, and efficiency parameters of at least one vehicle from the big data platform;

[0190] Multiple operational data, energy flow data, and efficiency parameters of at least one vehicle are visualized.

[0191] The above technical solution acquires multiple operational data points from the vehicle. Based on each operational data point, energy flow data is determined, resulting in multiple energy flow data sets. These energy flow data sets include one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, total vehicle energy consumption, and vehicle operating differential time. Based on these multiple operational data points and / or the multiple energy flow data sets, the vehicle's efficiency parameters under these multiple operational data points are determined. This method enables rapid analysis of fuel cell data from multiple vehicles, reducing the manpower and resources required for fuel cell vehicle data analysis and providing corresponding data analysis support for the development of fuel cell vehicles.

[0192] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0193] Figure 6 This is a block diagram illustrating an electronic device 600 according to an exemplary embodiment. For example, the electronic device 600 may be provided as a server, such as a big data platform. (Refer to...) Figure 6 The electronic device 600 includes a processor 622, which may be one or more, and a memory 632 for storing computer programs executable by the processor 622. The computer programs stored in the memory 632 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 622 may be configured to execute the computer program to perform the aforementioned method for determining the parameters of the fuel cell.

[0194] Additionally, the electronic device 600 may also include a power supply component 626 and a communication component 650. The power supply component 626 can be configured to perform power management of the electronic device 600, and the communication component 650 can be configured to enable communication of the electronic device 600, such as wired or wireless communication. Furthermore, the electronic device 600 may also include an input / output (I / O) interface 658. The electronic device 600 can operate on an operating system stored in memory 632.

[0195] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the above-described fuel cell parameter determination method. For example, the non-transitory computer-readable storage medium may be the memory 632 including the program instructions, which may be executed by the processor 622 of the electronic device 600 to complete the above-described fuel cell parameter determination method.

[0196] In another exemplary embodiment, a computer program product is also provided, comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described method for determining parameters of a fuel cell when executed by the programmable device.

[0197] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0198] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0199] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A method of determining parameters of a fuel cell, characterized by, Applied to big data platforms, the method includes: Acquire multiple operational data points of the vehicle; Based on each of the multiple operating data, the energy flow data corresponding to each operating data is determined, resulting in multiple energy flow data; wherein, the energy flow data includes one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, vehicle energy consumption, and vehicle operating differential time; The efficiency parameters of the vehicle under the multiple operating data are determined based on the multiple operating data and / or the multiple energy flow data. Each of the plurality of operating data includes: fuel cell power demand and average single-cell voltage of the fuel cell; when the efficiency parameter is the fuel cell system efficiency, determining the vehicle's efficiency parameter under the plurality of operating data based on the plurality of operating data and / or the plurality of energy flow data includes: The target power is determined by the power demand of the fuel cell; The difference between the fuel cell system output power and the target power for each of the multiple energy flow data is used to determine at least one energy flow data and at least one operating data corresponding to the target power; The fuel cell stack efficiency of the vehicle at the target power is determined based on the average single cell voltage of the fuel cell in at least one of the operating data. The proportion of fuel cell system accessory energy consumption of the vehicle at the target power is determined based on the fuel cell system output energy and fuel cell stack output energy in the at least one energy flow data. The fuel cell system efficiency of the vehicle at the target power is determined based on the fuel cell stack efficiency and the proportion of energy consumption of the fuel cell system accessories.

2. The method of claim 1, wherein, Determining the target power based on the fuel cell's power demand includes: The target power is determined based on the number of times each fuel cell's required power appears in the plurality of energy flow data.

3. The method of claim 1, wherein, Determining the proportion of fuel cell system accessory energy consumption of the vehicle at the target power based on the fuel cell system output energy and fuel cell stack output energy from the at least one energy flow data includes: The energy consumption ratio of the fuel cell system accessories in the vehicle at the target power is determined by the following formula: wherein, represents the fuel cell system accessory energy consumption ratio of the vehicle at the target power; a number representing the at least one energy flow data; representing a fuel cell stack output energy of the at least one energy flow data flow data; representing an output energy of the fuel cell system for the at least one energy flow data flow data.

4. The method of claim 1, wherein, Each of the plurality of operational data further includes: cumulative operational mileage, and the method further includes: When the efficiency parameter is hydrogen utilization rate, the hydrogen utilization rate of the vehicle in the multiple operating data is determined based on the actual hydrogen consumption and theoretical hydrogen consumption in the multiple energy flow data. When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell stack, the average hydrogen-to-electric conversion rate of the vehicle's fuel cell stack in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell stack in the multiple energy flow data. When the efficiency parameter is the average hydrogen-to-electric conversion rate of the fuel cell system, the average hydrogen-to-electric conversion rate of the vehicle's fuel cell system in the multiple operating data is determined based on the actual hydrogen consumption and the output energy of the fuel cell system in the multiple energy flow data. When the efficiency parameter is the energy consumption per 100 kilometers, the energy consumption per 100 kilometers of the vehicle in the multiple operating data is determined based on the cumulative operating mileage in the multiple operating data and the energy consumption of the whole vehicle in the energy flow data corresponding to each operating data. When the efficiency parameter is hydrogen consumption per 100 kilometers, the hydrogen consumption per 100 kilometers of the vehicle in the multiple operating data is determined based on the electricity consumption per 100 kilometers, the actual hydrogen consumption in the multiple energy flow data, and the output energy of the fuel cell system.

5. The method according to any one of claims 1 to 4, characterized in that, The method further includes: Based on the filtering criteria, obtain multiple operating data, energy flow data, and efficiency parameters of at least one vehicle from the big data platform; Multiple operating data, energy flow data, and efficiency parameters of the at least one vehicle are visualized.

6. A parameter determination device for a fuel cell, characterized in that, The device, applied to a big data platform, includes: The acquisition module is used to acquire multiple operational data of the vehicle; The data processing module is used to determine the energy flow data corresponding to each of the multiple operating data to obtain multiple energy flow data; wherein, the energy flow data includes one or more of the following: fuel cell system output power, fuel cell stack output power, fuel cell system output energy, fuel cell stack output energy, actual hydrogen consumption, theoretical hydrogen consumption, vehicle energy consumption, and vehicle operating differential time. The determining module is used to determine the efficiency parameters of the vehicle under the multiple operating data based on the multiple operating data and / or the multiple energy flow data; Each of the plurality of operating data includes: fuel cell power demand and average single-cell voltage of the fuel cell; when the efficiency parameter is the fuel cell system efficiency, determining the vehicle's efficiency parameter under the plurality of operating data based on the plurality of operating data and / or the plurality of energy flow data includes: The target power is determined by the power demand of the fuel cell; The difference between the fuel cell system output power and the target power for each of the multiple energy flow data is used to determine at least one energy flow data and at least one operating data corresponding to the target power; The fuel cell stack efficiency of the vehicle at the target power is determined based on the average single cell voltage of the fuel cell in at least one of the operating data. The proportion of fuel cell system accessory energy consumption of the vehicle at the target power is determined based on the fuel cell system output energy and fuel cell stack output energy in the at least one energy flow data. The fuel cell system efficiency of the vehicle at the target power is determined based on the fuel cell stack efficiency and the proportion of energy consumption of the fuel cell system accessories.

7. An electronic device, comprising: include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1 to 5.

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