Fuel Cell Doctor System

Abstract

The present application relates to a fuel cell doctor system, comprising: a vehicle-mounted processing unit configured to execute a simple control strategy, the simple control strategy including: calculating a real-time value of a determination feature related to an abnormal condition of a fuel cell based on real-time values of a parameter set received and using a pre-stored simplified algorithm based on the parameter set; determining the abnormal condition of the fuel cell according to the real-time value of the determination feature; and selecting a pre-stored countermeasure corresponding to the abnormal condition of the fuel cell; a non-vehicle-mounted processing unit configured to optimize the simple control strategy, the optimization operation including: periodically running all complex algorithms pre-stored in the non-vehicle-mounted processing unit based on historical data pre-stored in the non-vehicle-mounted processing unit; comparing and analyzing the results obtained by the complex algorithms and the results calculated by the vehicle-mounted processing unit; and updating the simple control strategy.

Description

Technical Field

[0001] The present application relates to a fuel cell doctor system. Background Art

[0002] Compared with traditional internal combustion engine vehicles, fuel cell vehicles have received increasing attention due to their advantages of high energy conversion efficiency and zero pollution emissions. The fuel cell system is the energy source that provides power for fuel cell vehicles. The fuel cell system generally includes a fuel cell, a cooling circuit, a heating circuit, a battery management circuit, various sensors, a battery box, a high-voltage circuit, and signal lines for connecting them. This system is a very complex system, and various faults may occur. The causes of many complex faults are often relatively vague and random, and some faults may be caused by a combination of many reasons.

[0003] Due to the complexity of faults and their causes, the diagnosis of fuel cell system faults usually requires very complex and many non-linear calculations or estimations. It is very difficult for in-vehicle computing units with limited storage and computing capabilities to achieve this, while remote computing units with powerful storage and computing capabilities are difficult to achieve the timeliness of diagnosing and controlling fuel cell systems. Delayed diagnosis and control may cause very serious consequences.

[0004] It is hoped that the above technical problems can be solved. Summary of the Invention

[0005] The purpose of the present application is to solve one or more of the above technical problems.

[0006] This purpose is achieved by a fuel cell doctor system for diagnosing and controlling a fuel cell system for a vehicle. The fuel cell doctor system includes: a detection unit for detecting or measuring the real-time value of a parameter, an in-vehicle processing unit and a non-vehicle processing unit communicatively connected to the detection unit,

[0007] wherein the real-time value of the parameter detected by the detection unit is sent to the in-vehicle processing unit and the non-vehicle processing unit in real time,

[0008] wherein the in-vehicle processing unit is configured to execute a simple control strategy, and the simple control strategy includes:

[0009] Based on the real-time value of a parameter set received, calculating the real-time value of a determination feature related to the abnormal condition of the fuel cell by using a pre-stored simplified algorithm based on the parameter set, where the parameter set consists of at least one of the parameters whose real-time values are detected by the detection unit;

[0010] Determining the abnormal condition of the fuel cell according to the real-time value of the above determination feature; and

[0011] Select a pre - stored countermeasure corresponding to the abnormal condition of the fuel cell, and

[0012] wherein the off - vehicle processing unit is configured to optimize the simple control strategy, and the optimization operation includes:

[0013] Periodically run all complex algorithms pre - stored in the off - vehicle processing unit based on historical data pre - stored in the off - vehicle processing unit;

[0014] Compare and analyze the results obtained by the complex algorithms and the results calculated by the on - vehicle processing unit;

[0015] Update the simple control strategy.

[0016] In one embodiment, the real - time information includes numerical parameter information and / or status parameters.

[0017] In one embodiment, each abnormal condition can be characterized by one or more determination features, and each determination feature can be obtained by using a simple algorithm corresponding to one or more parameter sets based on one or more parameter sets.

[0018] In one embodiment, the parameter sets, the simple algorithms, the determination features, the abnormal conditions, and the countermeasures corresponding to each abnormal condition are all included in the simple control strategy and pre - stored in the on - vehicle processing unit.

[0019] In one embodiment, the on - vehicle processing unit is configured to obtain the real - time value of the determination feature for determining various aspects of the abnormal condition of the fuel cell system based on the real - time values of multiple parameter sets and the pre - stored simplified algorithms corresponding to the multiple parameter sets.

[0020] In one embodiment, the abnormal condition is manifested as the real - time value of the calculated determination feature exceeding the allowable range.

[0021] In one embodiment, the fuel cell doctor system further includes an execution unit communicatively connected to the on - vehicle processing unit, and the execution unit is configured to receive the selected countermeasure from the on - vehicle processing unit and execute it.

[0022] In one embodiment, the historical data includes at least one of the following: all historical data from the detection unit; various calculation data from the on - vehicle processing unit; inherent parameter data of the fuel cell system; inherent parameter data of the vehicle equipped with this fuel cell system; statistical data of other fuel cell systems of different types or models from this fuel cell system; statistical data of fuel cell systems from other vehicles.

[0023] In one embodiment, the off-vehicle processing unit includes one or both of a cloud server and a remote computing center.

[0024] In one embodiment, the off-vehicle processing unit is communicatively connected to the on-vehicle processing unit, so that the simple control strategy in the on-vehicle processing unit can be updated with the updated simple control strategy.

[0025] On the one hand, the fuel cell doctor system of the present application uses the on-vehicle processing unit to complete the rapid diagnosis of the fuel cell system through a simple flow calculation method based on a simple analysis and calculation of real-time measurement results, and uses a pre-stored rapid control strategy to achieve real-time control of the fuel cell. On the other hand, the off-vehicle processing unit uses big data operations on periodically updated historical data to obtain macroscopic and comprehensive information of the fuel cell system, and then optimizes the control strategy of the fuel cell system. The optimized control strategy can be used to update the pre-stored rapid control strategy in the on-vehicle processing unit, can be used to configure a new generation of vehicles, and can be used as valuable materials for technicians to conduct further research. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a block diagram of the fuel cell doctor system according to the present application.

[0027] Figure 2 is a schematic diagram showing the principle of the fuel cell doctor system of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] Embodiments of the present invention will be further described in detail below with reference to the drawings. The embodiments herein are only used to illustrate the basic principle of the present invention and are not intended to limit the scope of the present invention.

[0029] As Figure 1 shown in the block diagram of, the fuel cell doctor system generally includes a detection unit 10 and an on-vehicle processing unit 20 and an off-vehicle processing unit 30 communicatively connected to the detection unit 10.

[0030] The term "on-vehicle" means that an object is installed or arranged on a vehicle equipped with a fuel cell system; the term "off-vehicle" means that an object is installed or arranged away from a vehicle equipped with a fuel cell. The detection unit 10 and the on-vehicle processing unit 20 are arranged on the vehicle, and the off-vehicle processing unit 30 is not arranged on the vehicle.

[0031] The fuel cell doctor system of the present application first uses its detection unit 10 to perform real-time measurement or detection of parameters of the fuel cell system of the vehicle. Then, on the one hand, the on-vehicle processing unit 20 of the fuel cell doctor system completes the rapid diagnosis of the fuel cell system through a simple flow calculation method based on a simple analysis and calculation of the real-time measurement results, and realizes the real-time control of the fuel cell by using the pre-stored rapid control strategy. On the other hand, the non-on-vehicle processing unit 30 of the fuel cell doctor system obtains the macroscopic and comprehensive information of the fuel cell system through complex big data operations such as batch processing and iteration of various aspects of regularly updated data (historical data and recently updated data), and then optimizes the control strategy of the fuel cell system. The optimized control strategy can be used to update the rapid control strategy pre-stored in the on-vehicle processing unit, can be used to configure a new generation of vehicles, and can be used as valuable materials for technicians to conduct further research.

[0032] The detection unit 10 of the fuel cell doctor system includes a battery sensor group 12 for measuring or detecting real-time information about the fuel cell system of the vehicle (including performance parameter information such as current, voltage, single-cell voltage, water content of the membrane, operating temperature, etc.; or state information such as the temperature, humidity, pressure, and flow rate of the fuel cell intake (hydrogen, air), the temperature, pressure, and flow rate of the coolant entering the stack, etc.). Optionally, the detection unit 10 may further include a vehicle sensor group 14 for measuring or detecting real-time information about the vehicle itself (including parameter information such as vehicle speed and driving mileage, or state information such as driving state or stationary state, whether the pedal is depressed, etc.); and an environmental sensor group 16 for measuring or detecting real-time information about the vehicle's surrounding environment or weather (including parameter information such as outside temperature and air pressure, or state information such as rain, snow, fog, etc.).

[0033] In some embodiments, the battery sensor group 12 may include, but is not limited to, voltage, temperature, and current sensors for determining the voltage, temperature, and current of the battery in the fuel cell system; a hygrometer for measuring the moisture in the battery...

[0034] In some embodiments, the vehicle sensor group 14 may include, but is not limited to, a state sensor for determining whether the vehicle is in a driving state or a stationary state; a speed sensor and / or an acceleration sensor for measuring the current driving speed of the vehicle...

[0035] In some embodiments, the environmental sensor group 16 may include at least one of the following: a humidity / temperature sensor for determining the humidity / temperature of the environment where the vehicle is located; a detector for measuring the environmental air index; a GPS system for measuring the coordinates / altitude of the location where the vehicle is located...

[0036] The parameters that the detection unit 10 of the fuel cell doctor system can detect or measure may include numerical parameters, state parameters, and any other possible parameters, which are represented by C1, C2, C3... Cn in Figure 2 . It should be understood that at a specific moment, the detection unit 10 may only obtain the real-time values of one or some of these parameters.

[0037] As described above, the purpose of this application is first to quickly determine the existence of abnormal conditions of the fuel cell based on the real-time values of the parameters obtained by the detection unit 10 at a specific moment and to take corresponding countermeasures in a timely manner corresponding to the determined faults. This operation is implemented by the in-vehicle processing unit 20 with limited storage capacity, computing, and analysis capabilities using pre-stored relatively simple determination methods, relatively simple calculation formulas, or algorithms for each fault (collectively referred to as "simple algorithms" in this article).

[0038] The fuel cell of the vehicle may have various possible abnormal conditions (or also referred to as "faults"), which need to be discovered and corresponding countermeasures taken in a timely manner. In Figure 2 , it is represented by A, Figure 2 . Four abnormal conditions A1 - A4 are listed in , and these abnormal conditions may be that the fuel cell temperature is too high, the fuel cell moisture is too high, the short circuit between both ends of the battery, etc. Of course, A1 - A4 are only examples, and according to the preset, the number of abnormal conditions can be changed.

[0039] Each abnormal condition A can be determined by one or more determination features F. The determination feature F can be in the form of a numerical feature, a state feature, or any other feature. For example, when the determination feature F exceeds the allowable value or allowable range, it indicates that the fuel cell has the corresponding abnormal condition. As an example, the abnormal condition A1 can be determined by the determination feature F1 exceeding the allowable setting of F1, or by the determination feature F2 exceeding the allowable setting of F2, or by the determination feature F3 exceeding the allowable setting of F3; the abnormal condition A2 can be determined by the determination feature F2 exceeding another allowable setting of F2, or by the determination feature F5 exceeding the allowable setting of F5; the abnormal condition A3 can be determined by the determination feature F4 exceeding the allowable setting of F4; the abnormal condition A5 can be determined by the determination feature F5 exceeding another allowable setting of F5. Thus, the same abnormal condition can be determined by one or more determination features, and different determination features can be used to determine different abnormal conditions, for example, when using different allowable settings.

[0040] Each determination feature F can be obtained by using a simple algorithm D based on a certain parameter set B. For example Figure 2As shown, the determination feature F1 can be obtained by using the simple algorithm D1 based on the parameter set B1; the determination feature F2 can be obtained by using the simple algorithm D2 based on the parameter set B2, or can also be obtained by using the simple algorithm D3 based on the parameter set B3, and so on. That is to say, the determination features used to judge abnormal conditions can be obtained based on one or more simple algorithms using specific parameter sets.

[0041] As an example, the determination feature for judging excessive moisture (abnormal condition A) in a fuel cell - the moisture content (F) can be obtained by using the simple algorithm: in - stack water content = total water input + generated water - water content output (simple algorithm D) based on the state parameters (humidity, temperature, flow rate, and pressure of the inlet and outlet gases of the anode and cathode) and performance parameters (operating current, voltage) (parameter set B including the above - mentioned parameter C), and can also be obtained by looking up the table (simple algorithm D) after obtaining the impedance value by comparing with the preset map of the correspondence between the electrochemical impedance value and the membrane humidity (parameter set B including the above - mentioned parameter C).

[0042] The parameter set B is a set of parameters that the detection unit 10 can measure. For example, the parameter set B1 based on which the simple algorithm D1 is based includes parameters C1, C2, and C4, and the parameter set B3 based on which the simple algorithms D3 and D4 are based includes parameters C1, C5, and C8. That is to say, by using the same parameter set B and adopting different simple algorithms D, the real - time values of different determination features F can be obtained, and based on the obtained determination feature F, the abnormal conditions A existing in the fuel cell can be determined.

[0043] In this way, at a certain specific moment, when the detection unit 10 detects the real - time parameter values of parameters C1, C2, C4, C7, and C10, it transmits these real - time parameter values to the vehicle - mounted processing unit 20 in real time. The vehicle - mounted processing unit 20 receives the parameter values of the above - mentioned parameters, that is, it obtains the real - time values or updated values of all the parameters in the parameter sets B1, B2, and B4. Then, the vehicle - mounted processing unit 20 calculates all the simple algorithms D1, D2, and D5 based on the parameter sets B1, B2, and B4, and calculates the real - time values of the determination features F1, F2, and F4. Then, the vehicle - mounted processing unit 20 determines whether there are abnormal conditions A1, A2, and A3 in the fuel cell system according to the calculated real - time values of the determination features F1, F2, and F4. Finally, the vehicle - mounted processing unit 20 selects the countermeasures P1, P2, P3, and P4 corresponding to the existing abnormal conditions A1, A2, and A3 (if all three abnormal conditions exist). The vehicle - mounted processing unit 20 is also configured to communicate the selected countermeasures to the communication execution unit 40 for execution. Figure 2 The quantities of parameter C, parameter set B, simple algorithm D, determination feature F, abnormal condition A, and countermeasure P in the above are only examples and have no restrictive effect.

[0044] As described above, once the detection unit 10 detects or measures the real-time value of one or some parameters at any moment T, it does not have to wait for all other parameters to be updated, but transmits them to the vehicle-mounted processing unit 20 in real time. After receiving the real-time value of one or some parameters from the detection unit 10, the vehicle-mounted processing unit 20 also does not have to wait to receive the real-time values of other parameters (in this article, the terms "updated value" and "real-time value" have the same meaning), but determines the parameter set composed of these parameters with updated values, runs all the simple algorithms based on these parameter sets, obtains the real-time value of the corresponding determination feature through these simple algorithms, then determines the abnormal conditions existing in the fuel cell, and selects necessary countermeasures to implement.

[0045] The corresponding relationships among the above parameter set B, simple algorithm D, determination feature F, abnormal condition A, and countermeasure P are pre-stored in the vehicle-mounted control unit 20 as a simple control strategy. All operations related to diagnosis and real-time control after the vehicle-mounted control unit 20 receives the real-time value of the parameter from the detection unit 10 are completed by the vehicle-mounted control unit 20.

[0046] This "stream computing" processing method of the vehicle-mounted processing unit 20 makes the diagnosis of the abnormal conditions of the fuel cell faster and more timely, avoids delaying the opportunity to take countermeasures, ensures the quickness and timeliness of the diagnosis of the abnormal conditions of the fuel cell system and the taking of countermeasures (i.e., control), and can maximize the service life of the fuel cell and the safety factor of the vehicle using this fuel cell.

[0047] However, since the diagnosis and determination of the abnormal conditions of the fuel cell are very complex, in order to adapt to the uncertainties brought about by the performance differences of the same fuel cell at different stages, the differences between individual fuel cells, the differences between vehicles equipped with fuel cells, etc., and in order to achieve more accurate diagnosis and determination, the simple control strategy needs to be continuously improved. For this reason, the purpose of this application is also to use the non-vehicle-mounted processing unit 30 to improve or optimize the simple control strategy of the fuel cell system.

[0048] The non-vehicle-mounted processing unit 30 is arranged away from the vehicle equipped with the fuel cell system. In some embodiments, the non-vehicle-mounted processing unit 30 can be a cloud server, can be a remote computing center or a remote service center communicatively connected through various possible communication methods including cloud communication, or can include both of the above. The non-vehicle-mounted processing unit 30 can achieve large-capacity storage and high-speed and complex computing operations. When needed, the non-vehicle-mounted processing unit 30 can expand its storage capacity and enhanced computing and analysis capabilities.

[0049] The off-vehicle processing unit 30 may include an off-vehicle processor with a large-capacity storage capability and a powerful data processing capability, and may also include an analyzer that analyzes based on the calculation results of the off-vehicle processor and thereby forms an optimized control strategy.

[0050] The off-vehicle processing unit 30 may be configured to store at least one or all of the following: historical data of all parameters from the detection unit 10, which may be the real-time values of one or some parameters sent in real time successively when detected by the detection unit 10; various calculation data from the on-vehicle processing unit 20; inherent parameter data of the fuel cell system; inherent parameter data of the vehicle equipped with this fuel cell system; statistical data of other fuel cell systems of different types or models from this fuel cell system; statistical data of fuel cell systems from other vehicles, etc. Optionally, the off-vehicle processing unit 30 also stores various versions of the simple control strategy for reference during analysis.

[0051] The off-vehicle processing unit 30 also stores various more comprehensive and more accurate complex algorithms related to various abnormal conditions of the fuel cell system. This algorithm is more complex than the aforementioned simple algorithm executed by the on-vehicle processing unit 20, has a larger calculation amount, uses more parameters, and obtains more accurate results.

[0052] The off-vehicle processing unit 30 first performs comprehensive calculations based on various data and various complex algorithms regularly, and analyzes the calculation results regularly. In one embodiment, the comprehensive calculation is automatically performed by the off-vehicle processing unit 30, and the analysis step of the calculation results is semi-automatically performed with human participation.

[0053] The analysis step performed by the off-vehicle processing unit 30 may include analyzing the abnormal condition results by comparing and analyzing the abnormal condition results calculated by the off-vehicle processing unit 30 with the abnormal condition results diagnosed by the vehicle processing unit 20. The analysis step may also include analyzing the countermeasures corresponding to the abnormal conditions in the simple control strategy. The analysis step may also include optimizing and updating the simple control strategy according to the above analysis results.

[0054] The off-vehicle processing unit 30 may also be configured to communicate the updated simple control strategy to the on-vehicle processing unit 20 for updating automatically or under the control of an operator.

[0055] On the one hand, the fuel cell doctor system of the present application uses an in-vehicle processing unit to complete the rapid diagnosis of the fuel cell system through a simple flow calculation method based on the simple analysis and calculation of real-time measurement results, and uses the pre-stored rapid control strategy to achieve real-time control of the fuel cell. On the other hand, it uses a non-vehicle processing unit to obtain the macroscopic and comprehensive information of the fuel cell system through big data operations on regularly updated historical data, and then optimizes the control strategy of the fuel cell system. The optimized control strategy can be used to update the pre-stored rapid control strategy in the in-vehicle processing unit, can be used to configure a new generation of vehicles, and can be used as valuable information for technicians to conduct further research.

Claims

1. A fuel cell doctor system for the diagnosis and control of a fuel cell system for a vehicle, characterized in that Comprising: A detection unit for detecting or measuring the real-time value of a parameter, a vehicle-mounted processing unit and a non-vehicle-mounted processing unit communicatively connected to the detection unit, wherein the real-time value of the parameter detected by the detection unit is sent in real time to the vehicle-mounted processing unit and the non-vehicle-mounted processing unit, wherein the vehicle-mounted processing unit is configured to execute a simple control strategy, and the simple control strategy includes: Based on the real-time values of a set of parameters received, calculating in real time the real-time value of a determination feature related to an abnormal condition of the fuel cell by using a pre-stored simplified algorithm based on the set of parameters, the set of parameters consisting of at least one of the parameters whose real-time values are detected by the detection unit; Determining the abnormal condition of the fuel cell according to the real-time value of the above determination feature; and Selecting a pre-stored countermeasure corresponding to the abnormal condition of the fuel cell, and wherein the non-vehicle-mounted processing unit is configured to optimize the simple control strategy, and the optimization includes: Periodically running all the complex algorithms pre-stored in the non-vehicle-mounted processing unit based on the historical data pre-stored in the non-vehicle-mounted processing unit; Comparing and analyzing the results obtained by the complex algorithms and the results calculated by the vehicle-mounted processing unit; Updating the simple control strategy.

2. The fuel cell doctor system according to claim 1, wherein, The parameters to be detected or measured include numerical parameters and / or state parameters.

3. The fuel cell doctor system according to claim 1, wherein, Each abnormal condition can be characterized by one or more determination features, and each determination feature can be obtained by using a simple algorithm corresponding to a set of parameters based on one or more sets of parameters.

4. The fuel cell doctor system according to claim 3, wherein The set of parameters, the simple algorithm, the determination feature, the abnormal condition and the countermeasures corresponding to each abnormal condition are all included in the simple control strategy and pre-stored in the vehicle-mounted processing unit.

5. The fuel cell doctor system according to any one of claims 1-4, wherein, The vehicle-mounted processing unit is configured to obtain in real time the real-time value of a determination feature for determining various abnormal conditions of the fuel cell system based on the real-time values of multiple sets of parameters and the pre-stored simplified algorithms corresponding to the multiple sets of parameters.

6. The fuel cell doctor system according to claim 5, wherein The abnormal condition is manifested as the real-time value of the calculated determination feature exceeding the allowable range.

7. The fuel cell doctor system according to any one of claims 1-4, further comprising an execution unit communicatively connected to the vehicle-mounted processing unit, the execution unit being configured to receive and execute the selected countermeasure from the vehicle-mounted processing unit.

8. The fuel cell doctor system according to any one of claims 1-4, wherein, The historical data includes at least one of the following: all historical data from the detection unit; various calculation data from the vehicle-mounted processing unit; inherent parameter data of the fuel cell system; inherent parameter data of the vehicle loaded with this fuel cell system; statistical data of other fuel cell systems of different types or models from this fuel cell system; statistical data of fuel cell systems from other vehicles.

9. The fuel cell doctor system according to any one of claims 1-4, wherein, The non-vehicle-mounted processing unit includes one or both of a cloud server and a remote computing center.

10. The fuel cell doctor system according to any one of claims 1-4, wherein, The non-vehicle-mounted processing unit and the vehicle-mounted processing unit are communicatively connected so that the simple control strategy in the vehicle-mounted processing unit can be updated with the updated simple control strategy.

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