A fuel cell engine control method and device based on inertial measurement sensor

Abstract

The present invention provides a fuel cell engine control method and device based on an inertial measurement sensor, belonging to the field of fuel cell technology. This method addresses the problem of poor control accuracy caused by prior art failure to consider the impact of the vehicle's operating state on the fuel cell engine's state. The method comprises: S1. Deploying an inertial measurement sensor on a vehicle equipped with a fuel cell engine; S2. Starting the fuel cell engine and acquiring data collected by the inertial measurement sensor while the vehicle is operating to determine the vehicle's real-time operating status indicator; S3. Acquiring the fuel cell engine's current state and control signal, and optimizing the control signal based on the vehicle's real-time operating status indicator and the engine's current state; S4. Controlling the fuel cell engine's operating state at the next moment based on the optimized control signal. By optimizing the control of the fuel cell engine using signals collected by the vehicle's inertial measurement sensor, control accuracy and speed are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fuel cells, and in particular to a fuel cell engine control method and device based on an inertial measurement sensor. Background Art

[0002] With the development of autonomous driving technology, driverless vehicles are becoming more and more common.

[0003] Inertial measurement sensors (IMUs) are commonly installed in current traditional vehicles to monitor the vehicle's position information offline and the vehicle's real-time status during operation, such as acceleration and deceleration, uphill and downhill driving, and turning.

[0004] When used in autonomous vehicles, fuel cell engines offer advantages such as high power generation efficiency, low environmental pollution, high specific energy, and low noise. However, these engines are sensitive to the vehicle's operating state, and varying vehicle operating conditions can have a certain degree of impact on system operation. Currently, there is no effective control solution for adjusting fuel cell engines based on real-time signals from inertial measurement sensors on the vehicle. Summary of the Invention

[0005] In view of the above analysis, the embodiments of the present invention aim to provide a fuel cell engine control method and device based on an inertial measurement sensor to solve the problem that the prior art does not consider the impact of the vehicle operating state on the fuel cell engine state, resulting in poor control accuracy.

[0006] In one aspect, an embodiment of the present invention provides a fuel cell engine control method based on an inertial measurement sensor, comprising the following steps:

[0007] S1. Deploy an inertial measurement sensor on a vehicle equipped with a fuel cell engine;

[0008] S2 starts the fuel cell engine, obtains data collected by the inertial measurement sensor in the vehicle running state, and obtains the real-time operating status indicator of the vehicle;

[0009] S3 obtains the current state and control signal of the fuel cell engine, and optimizes the coupling of the control signal based on the real-time operating status of the vehicle in combination with the current state of the engine;

[0010] S4. Control the operating state of the fuel cell engine at the next moment according to the control signal after coupling optimization.

[0011] The above technical solution has the following beneficial effects: It proposes an optimized fuel cell engine control method that monitors the vehicle's real-time operating status by analyzing data from the vehicle's inertial measurement unit (IMU). This signal is then used to optimize the coupling of the fuel cell engine's control signals for more effective control, eliminating the impact of different vehicle operating conditions on the fuel cell engine, such as acceleration and deceleration, uphill and downhill driving, and cornering. Compared to existing control solutions, this method significantly improves the control accuracy and speed of the fuel cell engine, thereby effectively enhancing the user experience.

[0012] Based on a further improvement of the above method, in step S2, the data collected by the inertial measurement sensor includes at least one of the vehicle's three-axis attitude angle, angular rate, and acceleration; and

[0013] The real-time operating status indicator of the vehicle includes at least one of the vehicle's inclination, acceleration / deceleration, and load weight information.

[0014] Furthermore, in step S3, the current state of the fuel cell engine includes at least one of the flow rate, temperature, and pressure of the hydrogen gas and air entering the stack, and the stack temperature.

[0015] Further, the step S2 is refined as follows:

[0016] S21. Start the fuel cell engine and run the vehicle;

[0017] S22. When the vehicle is in operation, start the inertial measurement sensor and identify whether the inertial measurement sensor is working properly. If so, execute the next step; otherwise, turn off the inertial measurement sensor;

[0018] S23. Regularly obtain the CAN signal collected by the inertial measurement sensor, extract the vehicle's three-axis attitude angle, angular rate, acceleration contained in the signal, and obtain the vehicle's position coordinates and ambient temperature;

[0019] S24. Based on the above-mentioned three-axis attitude angle, angular rate, and acceleration of the whole vehicle, combined with the position coordinates and ambient temperature of the vehicle, the vehicle's inclination, acceleration and deceleration, and load weight information are obtained.

[0020] Further, the step S3 is refined as follows:

[0021] S31 obtains indicators representing the current state of the fuel cell engine, including the flow rate, temperature, pressure of hydrogen and air into the stack, and the stack temperature;

[0022] S32 obtains the fuel cell engine control signal, including the air compressor control signal, the hydrogen injection device control signal, the control valve control signal, and obtains the amplitude, frequency and duty cycle of each of the control signals;

[0023] S33. The vehicle's inclination, acceleration and deceleration, load weight information, indicators characterizing the current state of the fuel cell engine, and the amplitude, frequency, and duty cycle of each control signal are input into a pre-trained deep learning network to obtain the amplitude, frequency, and duty cycle of each control signal after coupling optimization.

[0024] Furthermore, the fuel cell engine control method based on the inertial measurement sensor further includes the following steps:

[0025] S5. Based on the current state of the fuel cell engine combined with the coupled optimized control signal, predict the state of the fuel cell engine at the next moment;

[0026] S6. Determine whether the state of the above-mentioned fuel cell engine at the next moment is within a preset range. If so, control the operating state of the fuel cell engine at the next moment according to the control signal after coupling optimization; otherwise, control the operating state of the fuel cell engine at the next moment according to the control signal before coupling optimization.

[0027] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0028] 1. The vehicle's real-time operating status is derived from signals collected by inertial measurement sensors throughout the vehicle. Data collected by inertial measurement sensors is unaffected by factors such as weather conditions, lighting, snow, or obscured landmarks. The data is more reliable because it does not require any connection or data exchange with any equipment outside the vehicle body, thus providing a more accurate indicator of the vehicle's real-time operating status.

[0029] 2. The vehicle's inclination, acceleration, deceleration, and load weight information are obtained through signals collected by the inertial measurement sensors on the entire vehicle, and then used to control the operating status of the fuel cell engine. This can effectively eliminate the impact of the vehicle's inclination, acceleration, deceleration, and load weight information on the operating status of the fuel cell engine, thereby improving the control accuracy of the fuel cell engine. It is suitable for various types of automatic unmanned vehicles and various climatic conditions.

[0030] 3. By predicting the state of the fuel cell engine at the next moment, the control strategy can be further optimized to prevent the fuel cell engine state from exceeding the preset range due to changes in the control strategy, thereby improving control safety.

[0031] On the other hand, an embodiment of the present invention provides a fuel cell engine control device based on an inertial measurement sensor, comprising an inertial measurement sensor, a controller and a fuel cell engine; wherein,

[0032] The controller is configured to start the fuel cell engine, obtain data collected by an inertial measurement sensor while the vehicle is in operation, and derive a real-time operating status indicator for the vehicle; obtain a current state of the fuel cell engine and a control signal, and perform coupling optimization on the control signal based on the real-time operating status indicator of the vehicle and the current state of the engine; and control the operating state of the fuel cell engine at a subsequent moment based on the coupled optimized control signal.

[0033] Based on the above device, the controller is improved and further comprises:

[0034] The data acquisition unit is used to obtain the vehicle's three-axis attitude angle, angular rate, and acceleration collected by the inertial measurement sensor, as well as the current state of the fuel cell engine, and send them to the data processing and control unit;

[0035] The data processing and control unit is used to start the fuel cell engine and, when the vehicle is in operation, derive the vehicle's real-time operating status indicator based on the received three-axis attitude angle, angular rate, and acceleration of the vehicle; obtain the current state and control signal of the fuel cell engine, and perform coupling optimization on the control signal based on the above-mentioned real-time operating status indicator of the vehicle combined with the current state of the engine; and control the operating state of the fuel cell engine's air compressor, hydrogen injection equipment, and various control valves at the next moment based on the coupled optimized control signal.

[0036] Furthermore, the data acquisition unit further comprises:

[0037] The data analysis module is used to receive the CAN signal collected by the inertial measurement sensor and extract the vehicle's three-axis attitude angle, angular rate, and acceleration from the CAN signal;

[0038] Gas flow sensors are installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the flow rates of hydrogen and air entering the stack;

[0039] Gas temperature sensors are installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the temperatures of the hydrogen and air entering the stack;

[0040] Gas pressure sensors are installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the pressure of the hydrogen and air entering the stack;

[0041] A liquid temperature sensor is installed on the inner wall of the coolant outlet pipe of the fuel cell stack in the fuel cell engine to obtain the temperature of the fuel cell stack;

[0042] The ambient temperature sensor is installed around the fuel cell engine in the vehicle compartment and is used to obtain the temperature of the environment in which the fuel cell engine is located.

[0043] Furthermore, the controller is also used to predict the state of the fuel cell engine at the next moment based on the current state of the fuel cell engine combined with the control signal after coupling optimization; and to determine whether the state of the above-mentioned fuel cell engine at the next moment is within a preset range. If so, the operating state of the fuel cell engine at the next moment is controlled according to the control signal after coupling optimization; otherwise, the operating state of the fuel cell engine at the next moment is controlled according to the control signal before coupling optimization.

[0044] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the disclosure, nor is it intended to limit the scope of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure with reference to the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0046] Figure 1 A schematic diagram showing the steps of the fuel cell engine control method according to embodiment 1 is shown;

[0047] Figure 2 A schematic diagram showing the principle of the fuel cell engine control method of Example 2 is shown. DETAILED DESCRIPTION

[0048] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0049] As used herein, the term "including" and its variations represent open inclusion, i.e., "including but not limited to." Unless otherwise stated, the term "or" means "and / or." The term "based on" means "based at least in part on." The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment." The term "another embodiment" means "at least one additional embodiment." The terms "first," "second," etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0050] In order to more clearly introduce the content of the present invention, the key terms involved in the present invention are first described below.

[0051] An inertial measurement unit (IMU) is a device that measures an object's three-axis attitude angle, angular rate, and acceleration. Typically, an IMU consists of three single-axis accelerometers and three single-axis gyroscopes. The accelerometers detect the object's three-axis acceleration signals within the carrier's coordinate system, while the gyroscopes detect the carrier's angular velocity signals relative to the navigation coordinate system. The angular velocity and acceleration of an object in three-dimensional space are measured and used to calculate the object's attitude.

[0052] Example 1

[0053] One embodiment of the present invention discloses a fuel cell engine control method based on an inertial measurement sensor, such as Figure 1 As shown, the following steps are included:

[0054] S1. Install an inertial measurement unit (IMU) on a vehicle equipped with a fuel cell engine;

[0055] S2. Start the fuel cell engine and obtain data collected by the inertial measurement sensor while the vehicle is in operation (ie, the vehicle is in motion) to obtain a real-time operating status indicator of the vehicle;

[0056] S3 obtains the current state and control signal of the fuel cell engine, and optimizes the coupling of the control signal based on the real-time operating status of the vehicle in combination with the current state of the engine;

[0057] S4. Control the operating state of the fuel cell engine at the next moment according to the control signal after coupling optimization.

[0058] Optionally, in step S2, the real-time operating status indicator of the vehicle may include a change in vehicle position in addition to the indicator described in Example 2.

[0059] Optionally, in step S3, the current state of the fuel cell engine may include the flow rate, pressure, temperature of the gas entering the stack and the stack temperature as described in Example 2, as well as the flow rate, pressure, and temperature of the gas leaving the stack.

[0060] Optionally, in step S3, the control signal of the fuel cell engine may include at least one of an output voltage signal, an output current signal, a stack outlet pressure signal, a stack outlet temperature signal, a conductivity signal, an air compressor output pressure signal, an air flow signal, and a hydrogen flow signal in addition to the control signal described in Example 2.

[0061] Optionally, in step S3, the coupling optimization method may adopt the deep learning network described in Example 2, or a laboratory-calibrated coupling optimization model. The coefficients of the model can be obtained by data reverse deduction, which can be understood by those skilled in the art.

[0062] Compared to existing technologies, this embodiment proposes an optimized fuel cell engine control method. This method monitors the vehicle's real-time operating status by analyzing signals collected by the vehicle's inertial measurement sensors. This signal is then used to optimize the coupling of the fuel cell engine's control signals, enabling more effective control and eliminating the impact of varying vehicle operating conditions on the fuel cell engine, such as acceleration and deceleration, hill climbing, and cornering. Compared to existing control schemes, this significantly improves the fuel cell engine's control accuracy and speed, thereby effectively enhancing the user experience.

[0063] Example 2

[0064] An improvement is made based on the method of Example 1. In step S2, the data collected by the inertial measurement sensor includes at least one of the vehicle's three-axis attitude angle, angular rate, and acceleration.

[0065] The real-time operating status indicator of the vehicle includes at least one of the vehicle's inclination, acceleration / deceleration, and load weight information.

[0066] Preferably, in step S3, the current state of the fuel cell engine includes at least one of the flow rate, temperature, and pressure of the hydrogen gas and air entering the stack, and the stack temperature.

[0067] Preferably, the step S2 further comprises:

[0068] S21. Start the fuel cell engine and run the vehicle;

[0069] S22. While the vehicle is in operation, start the inertial measurement sensor and determine whether the inertial measurement sensor is functioning properly (whether data is being collected). If so, determine that the inertial measurement sensor is functioning properly and proceed to the next step. Otherwise, determine that the inertial measurement sensor is faulty and disable the inertial measurement sensor.

[0070] S23. Regularly acquire the CAN signal collected by the inertial measurement sensor, extract the vehicle's three-axis attitude angle, angular rate, and acceleration contained in the signal, and simultaneously obtain the vehicle's position coordinates (via the inertial measurement sensor or onboard GPS module), ambient temperature (from an ambient temperature sensor installed in the vehicle), and ambient humidity (from an ambient humidity sensor installed in the vehicle);

[0071] S24. Input the vehicle's three-axis attitude angles, angular rates, and accelerations, as well as the vehicle's position coordinates, ambient temperature, and humidity, into the trained neural network to derive information about the vehicle's inclination, acceleration, deceleration, and payload weight. Training data can be obtained through laboratory calibration, as will be understood by those skilled in the art.

[0072] Preferably, step S3 further comprises:

[0073] S31. Obtain indicators (parameters) representing the current state of the fuel cell engine, including flow, temperature, and pressure of hydrogen and air entering the stack, as well as the stack temperature;

[0074] S32. Obtain control signals for the fuel cell engine, including the control signals for the air compressor, the hydrogen injection equipment, and the control signals for the control valves (the stack air control valve, the stack hydrogen control valve, the stack hydrogen-side pressure regulating valve, the stack air-side pressure regulating valve, etc.), and derive the amplitude, frequency, and duty cycle of each of the control signals;

[0075] S33. The vehicle's inclination, acceleration and deceleration, load weight information, indicators characterizing the current state of the fuel cell engine, and the amplitude, frequency, and duty cycle of each control signal are input into a pre-trained deep learning network to obtain the amplitude, frequency, and duty cycle of each control signal after coupling optimization.

[0076] Optionally, the deep learning network may be at least one of ResNet, Inception, and DenseNet.

[0077] Preferably, the fuel cell engine control method may further include the following steps:

[0078] S5. Predict the state of the fuel cell engine at the next moment based on the current state of the fuel cell engine and the control signal after coupling optimization.

[0079] S6. Determine whether the state of the above-mentioned fuel cell engine at the next moment is within a preset range. If so, control the operating state of the fuel cell engine (or engine components, i.e., the air compressor, hydrogen injection equipment, and various control valves) at the next moment according to the control signal after coupling optimization. Otherwise, control the operating state of the fuel cell engine at the next moment according to the control signal before coupling optimization.

[0080] It should be noted that the above steps S5 to S6 are applicable to the regulation of the fuel cell engine as a whole and each component, to prevent the operating state of the whole or each component from exceeding the set range.

[0081] The basic principle of the above method is as follows Figure 2 As shown, but not limited to Figure 2 The content described.

[0082] Compared with the prior art, the fuel cell engine control method of this embodiment has the following beneficial effects:

[0083] 1. The vehicle's real-time operating status is derived from signals collected by inertial measurement sensors throughout the vehicle. Data collected by inertial measurement sensors is unaffected by factors such as weather conditions, lighting, snow, or obscured landmarks. The data is more reliable because it does not require any connection or data exchange with any equipment outside the vehicle body, thus providing a more accurate indicator of the vehicle's real-time operating status.

[0084] 2. The vehicle's inclination, acceleration, deceleration, and load weight information are obtained through signals collected by the inertial measurement sensors on the entire vehicle, and then used to control the operating status of the fuel cell engine. This can effectively eliminate the impact of the vehicle's inclination, acceleration, deceleration, and load weight information on the operating status of the fuel cell engine, thereby improving the control accuracy of the fuel cell engine. It is suitable for various types of automatic unmanned vehicles and various climatic conditions.

[0085] 3. By predicting the state of the fuel cell engine at the next moment, the control strategy can be further optimized to prevent the fuel cell engine state from exceeding the preset range due to changes in the control strategy, thereby improving control safety.

[0086] Example 3

[0087] Another embodiment of the present invention further provides a fuel cell engine control device corresponding to the method of embodiment 1 or 2, which includes an inertial measurement sensor, a controller, and a fuel cell engine connected in sequence.

[0088] The controller is configured to start the fuel cell engine, obtain data collected by an inertial measurement sensor while the vehicle is in operation, and derive a real-time operating status indicator for the vehicle; obtain a current state of the fuel cell engine and a control signal, and perform coupling optimization on the control signal based on the real-time operating status indicator of the vehicle and the current state of the engine; and control the operating state of the fuel cell engine at a subsequent moment based on the coupled optimized control signal.

[0089] The output end of the controller is connected to the control end of each control component in the fuel cell engine.

[0090] Compared to existing technologies, this embodiment proposes an optimized fuel cell engine control device. This device monitors the vehicle's real-time operating status by analyzing signals collected by the vehicle's inertial measurement sensors. This signal is then used to optimize the coupling of the fuel cell engine's control signals, enabling more effective control and eliminating the impact of varying vehicle operating conditions on the fuel cell engine, such as acceleration and deceleration, hill climbing, and cornering. Compared to existing control solutions, this significantly improves the fuel cell engine's control accuracy and speed, thereby effectively enhancing the user experience.

[0091] Example 4

[0092] An improvement is made based on the device of Example 3, where the controller further includes a data acquisition unit and a data processing and control unit connected in sequence.

[0093] The data acquisition unit is used to obtain the three-axis attitude angle, angular rate, and acceleration of the vehicle collected by the inertial measurement sensor, as well as the current state of the fuel cell engine, and send them to the data processing and control unit.

[0094] The data processing and control unit is used to start the fuel cell engine and, when the vehicle is in operation, derive the vehicle's real-time operating status indicator based on the received three-axis attitude angle, angular rate, and acceleration of the vehicle; obtain the current state and control signal of the fuel cell engine, and perform coupling optimization on the control signal based on the above-mentioned real-time operating status indicator of the vehicle combined with the current state of the engine; and control the operating state of the fuel cell engine's air compressor, hydrogen injection equipment, and various control valves at the next moment based on the coupled optimized control signal.

[0095] Preferably, the data acquisition unit further includes a data analysis module, a gas flow sensor, a gas temperature sensor, a gas temperature sensor, a gas pressure sensor, a liquid temperature sensor, an ambient temperature sensor, and an ambient humidity sensor.

[0096] The data analysis module is used to receive the CAN signal collected by the inertial measurement sensor and extract the three-axis attitude angle, angular rate and acceleration of the whole vehicle from the CAN signal.

[0097] Gas flow sensors are respectively installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the flow rates of hydrogen and air entering the stack.

[0098] Gas temperature sensors are installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the temperatures of the hydrogen and air entering the stack.

[0099] Gas pressure sensors are respectively installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the pressure of the hydrogen and air entering the stack.

[0100] The liquid temperature sensor is installed on the inner wall of the coolant outlet pipe of the fuel cell stack in the fuel cell engine and is used to obtain the temperature of the fuel cell stack.

[0101] The ambient temperature sensor is installed around the fuel cell engine in the vehicle compartment and is used to obtain the temperature of the environment in which the fuel cell engine is located.

[0102] The environmental humidity sensor is installed around the fuel cell engine in the vehicle compartment and is used to obtain the humidity of the environment in which the fuel cell engine is located.

[0103] The procedures executed by the data processing and control unit refer to the methods described in Examples 1 and 2.

[0104] Preferably, the controller (data processing and control unit) is also used to predict the state of the fuel cell engine at the next moment based on the current state of the fuel cell engine combined with the control signal after coupling optimization; and to determine whether the state of the above-mentioned fuel cell engine at the next moment is within a preset range. If so, the operating state of the fuel cell engine at the next moment is controlled according to the control signal after coupling optimization; otherwise, the operating state of the fuel cell engine at the next moment is controlled according to the control signal before coupling optimization.

[0105] Preferably, the data processing and control unit is provided with a display module, wherein the display screen of the display module displays the real-time operating status indicators of the vehicle and the current status of the fuel cell engine.

[0106] Compared with the prior art, the device of this embodiment has the following beneficial effects:

[0107] 1. The vehicle's real-time operating status is derived from signals collected by inertial measurement sensors throughout the vehicle. Data collected by inertial measurement sensors is unaffected by factors such as weather conditions, lighting, snow, or obscured landmarks. The data is more reliable because it does not require any connection or data exchange with any equipment outside the vehicle body, thus providing a more accurate indicator of the vehicle's real-time operating status.

[0108] 2. The vehicle's inclination, acceleration, deceleration, and load weight information are obtained through signals collected by the inertial measurement sensors on the entire vehicle, and then used to control the operating status of the fuel cell engine. This can effectively eliminate the impact of the vehicle's inclination, acceleration, deceleration, and load weight information on the operating status of the fuel cell engine, thereby improving the control accuracy of the fuel cell engine. It is suitable for various types of automatic unmanned vehicles and various climatic conditions.

[0109] 3. By predicting the state of the fuel cell engine at the next moment, the control strategy can be further optimized to prevent the fuel cell engine state from exceeding the preset range due to changes in the control strategy, thereby improving control safety.

[0110] While various embodiments of the present disclosure have been described above, the foregoing description is intended to be illustrative, non-exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or improvements over the prior art, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A fuel cell engine control method based on an inertial measurement sensor, characterized in that: include: S1. Deploy an inertial measurement sensor on a vehicle equipped with a fuel cell engine; S2. Start the fuel cell engine and obtain data collected by the inertial measurement sensor while the vehicle is in operation to obtain real-time operating status indicators of the vehicle, including: S21. Start the fuel cell engine and run the vehicle; S22. When the vehicle is in operation, start the inertial measurement sensor and identify whether the inertial measurement sensor is working properly. If so, execute the next step; otherwise, turn off the inertial measurement sensor; S23. Regularly obtain the CAN signal collected by the inertial measurement sensor, extract the vehicle's three-axis attitude angle, angular rate, acceleration contained in the signal, and obtain the vehicle's position coordinates and ambient temperature; S24. Based on the above three-axis attitude angle, angular rate, acceleration of the vehicle combined with the vehicle's position coordinates and ambient temperature, the vehicle's inclination, acceleration, and load weight information are obtained; S3. Obtaining the current state and control signal of the fuel cell engine, and performing coupling optimization on the control signal based on the real-time operating state indicator of the vehicle and the current state of the engine, including: S31 obtains indicators representing the current state of the fuel cell engine, including the flow rate, temperature, pressure of hydrogen and air into the stack, and the stack temperature; S32 obtains the fuel cell engine control signal, including the air compressor control signal, the hydrogen injection device control signal, the control valve control signal, and obtains the amplitude, frequency and duty cycle of each of the control signals; S33. The vehicle's inclination, acceleration and deceleration, loaded weight information, and indicators representing the current state of the fuel cell engine and the amplitude, frequency, and duty cycle of each control signal are input into a pre-trained deep learning network to obtain the amplitude, frequency, and duty cycle of each control signal after coupling optimization; S4. Control the operating state of the fuel cell engine at the next moment according to the control signal after coupling optimization.

2. The fuel cell engine control method based on inertial measurement sensor according to claim 1, characterized in that: The following steps are also included: S5. Based on the current state of the fuel cell engine combined with the coupled optimized control signal, predict the state of the fuel cell engine at the next moment; S6. Determine whether the state of the above-mentioned fuel cell engine at the next moment is within a preset range. If so, control the operating state of the fuel cell engine at the next moment according to the control signal after coupling optimization; otherwise, control the operating state of the fuel cell engine at the next moment according to the control signal before coupling optimization.

3. A fuel cell engine control device based on an inertial measurement sensor, characterized in that: The fuel cell engine control method based on an inertial measurement sensor as described in any one of claims 1 to 2 comprises an inertial measurement sensor, a controller and a fuel cell engine; wherein, The controller is configured to start the fuel cell engine, obtain data collected by an inertial measurement sensor while the vehicle is in operation, and derive a real-time operating status indicator for the vehicle; obtain a current state of the fuel cell engine and a control signal, and perform coupling optimization on the control signal based on the real-time operating status indicator of the vehicle and the current state of the engine; and control the operating state of the fuel cell engine at a subsequent moment based on the coupled optimized control signal.

4. The fuel cell engine control device based on inertial measurement sensor according to claim 3, characterized in that: The controller further comprises: The data acquisition unit is used to obtain the vehicle's three-axis attitude angle, angular rate, and acceleration collected by the inertial measurement sensor, as well as the current state of the fuel cell engine, and send them to the data processing and control unit; The data processing and control unit is used to start the fuel cell engine and, when the vehicle is in operation, derive the vehicle's real-time operating status indicator based on the received three-axis attitude angle, angular rate, and acceleration of the vehicle; obtain the current state and control signal of the fuel cell engine, and perform coupling optimization on the control signal based on the above-mentioned real-time operating status indicator of the vehicle combined with the current state of the engine; and control the operating state of the fuel cell engine's air compressor, hydrogen injection equipment, and various control valves at the next moment based on the coupled optimized control signal.

5. The fuel cell engine control device based on inertial measurement sensor according to claim 4, characterized in that: The data acquisition unit further comprises: The data analysis module is used to receive the CAN signal collected by the inertial measurement sensor and extract the vehicle's three-axis attitude angle, angular rate, and acceleration from the CAN signal; Gas flow sensors are installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the flow rates of hydrogen and air entering the stack; Gas temperature sensors are installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the temperatures of the hydrogen and air entering the stack; Gas pressure sensors are installed on the inner walls of the hydrogen inlet and air inlet pipes of the fuel cell engine stack to obtain the pressure of the hydrogen and air entering the stack; A liquid temperature sensor is installed on the inner wall of the coolant outlet pipe of the fuel cell stack in the fuel cell engine to obtain the temperature of the fuel cell stack; The ambient temperature sensor is installed around the fuel cell engine in the vehicle compartment and is used to obtain the temperature of the environment in which the fuel cell engine is located.

6. The fuel cell engine control device based on an inertial measurement sensor according to any one of claims 3 to 5, characterized in that: The controller is further configured to predict the state of the fuel cell engine at the next moment based on the current state of the fuel cell engine in combination with the control signal after coupling optimization; and to determine whether the state of the fuel cell engine at the next moment is within a preset range. If so, the operating state of the fuel cell engine at the next moment is controlled according to the control signal after coupling optimization; otherwise, the operating state of the fuel cell engine at the next moment is controlled according to the control signal before coupling optimization.

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