Intelligent flight control system of electric paraglider

Abstract

The invention discloses an intelligent flight control system of an electric paraglider, and belongs to the technical field of aviation sports equipment control. The system adopts a dual-core architecture in which a hand-held terminal and a central processing unit are interconnected through a CAN (Controller Area Network) bus. And the central processing unit runs a real-time operating system, and collects data of the GNSS / IMU module, the battery management system, the electronic speed regulator and the temperature sensor through a hybrid scheduling strategy. A micro-control unit of the handheld terminal fuses the data to obtain accurate flight state information, a rule engine is embedded, and system state monitoring and accelerator instruction safety verification are executed in parallel based on diagnosis rules and multi-layer safety logic. And finally, centralized display is carried out through the display screen, and the local storage module is utilized to completely record the data chain with the timestamp. According to the invention, comprehensive perception of the flight state, intelligent safety control and complete data traceability are realized, and the flight safety and reliability of the electric paraglider are significantly improved.

Description

Technical Field

[0001] This invention relates to the field of aviation sports equipment control technology, specifically to an intelligent flight control system for an electric paraglider. Background Technology

[0002] Powered paragliders, as personal aircraft, are undergoing a transition from fuel-powered to electric power. Electric paragliders offer advantages such as low operating costs and high reliability. However, current electric paraglider control systems on the market generally suffer from the following drawbacks: Fragmented information perception: Flight parameters (such as GPS position, battery voltage, motor speed) are displayed by multiple independent instruments, making it difficult for pilots to form a unified and comprehensive situational awareness.

[0003] Disconnect between control and safety: Throttle control is mostly based on simple command output and lacks intelligent safety verification based on the overall state of the aircraft (such as malfunctions and ground conditions), which poses a risk of misoperation.

[0004] Lack of data traceability: The system does not have complete "black box" data recording capabilities, making it impossible to conduct effective analysis after an accident occurs.

[0005] Poor system scalability: Functionality is fixed in the hardware, making it difficult to iterate functions through software upgrades.

[0006] Therefore, there is an urgent need in this field for a highly integrated, intelligent, and safe flight control system. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and provide an intelligent flight control system for electric manned paragliders that is highly integrated, intelligent, safe, and has complete data traceability capabilities.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An intelligent flight control system for an electric paraglider includes a handheld terminal and a central processing unit (CPU). The handheld terminal and the CPU communicate via a CAN bus. The CPU is connected to an external GNSS / IMU module, a battery management system, an electronic speed controller, and at least one temperature sensor via the CAN bus to acquire various types of data from the GNSS / IMU module, the battery management system, the electronic speed controller, and the temperature sensor. The handheld terminal includes a microcontroller unit, a display screen, a throttle control unit, and a local data storage module; Microcontroller Unit: Receives and fuses data from the central processing unit to generate fused flight status information; based on the received data and / or fused flight status information and predefined diagnostic rules, it performs system status monitoring and intelligent diagnosis to determine if the system is abnormal; receives throttle commands from the throttle control unit and verifies the throttle commands based on the received data and / or fused flight status information and preset multi-layer safety logic; if the throttle command passes the verification, it sends the throttle command as a control signal to the electronic speed controller for execution; if the throttle command fails the verification or the intelligent diagnosis determines that the system is abnormal, it restricts or refuses to execute the throttle command and generates a corresponding alarm event; drives the display screen to centrally display the fused flight status information and alarm events, and controls the local data storage module to record relevant data.

[0009] Furthermore, the throttle control unit includes a Hall effect sensor associated with the throttle control mechanism of the electric paraglider for generating throttle commands without contact.

[0010] Furthermore, the microcontroller outputs a control signal to the electronic speed controller through a throttle output circuit; the control signal is a dual-redundant signal including CAN bus digital signals and PWM analog signals.

[0011] Furthermore, when CAN bus communication is normal, the CAN bus digital signal is used first; when CAN bus communication fails, the PWM analog signal is switched to be used.

[0012] Furthermore, the throttle control unit includes a physical safety switch connected in series in the throttle output circuit, used to physically connect or disconnect the output path of the control signal.

[0013] Furthermore, the microcontroller performs multi-layered security logic verification by invoking predefined diagnostic rules. The multi-layered security logic includes at least one of the following: Ground safety logic: When the flight speed is zero and the physical safety switch is in the closed state, suppress the output of control signals; the flight speed is derived from multiple data and / or fused flight status information; Fault suppression logic: When the fault level reported by the battery management system or electronic speed controller is severe, the output of the control signal is limited or cut off; the fault level reported by the battery management system or electronic speed controller comes from multiple data sources. Envelope protection logic: Dynamically adjust the upper limit of the control signal output based on the current flight altitude and / or speed; the current flight altitude and / or speed are derived from multiple data streams and / or fused flight status information.

[0014] Furthermore, the microcontroller unit performs data fusion on the positioning data and inertial measurement data from the GNSS / IMU module by executing the extended Kalman filter algorithm to obtain the fused flight status information, specifically including the following steps: S1: Synchronize the inertial measurement data using the UTC time reference provided by the GNSS module; S2: Transform the latitude, longitude, and altitude coordinates in the positioning data to the local northeast-sky coordinate system to obtain the observation position and observation velocity; at the same time, transform the acceleration in the carrier coordinate system measured by the IMU module to the northeast-sky coordinate system, and subtract the gravitational acceleration component to obtain the motion acceleration; S3: In each calculation cycle of the extended Kalman filter, perform: S31: Prediction Step: Using the state estimate from the previous moment, the angular velocity measured by the IMU module, and the motion acceleration obtained in S2, predict the state vector and prediction covariance matrix for the current moment; the state vector must contain at least position, velocity, and attitude angle; S32: Update steps: When data from the GNSS module is received, the observation position and observation velocity are compared with the state vector predicted in S31, the Kalman gain is calculated, and the predicted state vector is corrected to obtain the posterior state estimate, i.e., the fused flight state information.

[0015] Furthermore, the microcontroller unit embeds a rule engine that processes multiple data streams and / or fused flight status information from the central processing unit in parallel. It performs real-time diagnosis of the multiple data streams and / or fused flight status information by calling multiple predefined diagnostic rules, and verifies throttle commands. At least some of the diagnostic rules depend on multiple parameters from different data streams and are correlated through logical operators. When the logical condition of any diagnostic rule is met, an alarm event containing alarm level and type information is generated.

[0016] Furthermore, the local data storage module continuously records data, alarm events, and throttle command operation records from the central processing unit using a data frame structure with time-series identifiers.

[0017] Furthermore, the central processing unit employs a microcontroller with multi-core processing capabilities and runs a real-time operating system to poll data from the battery management system and electronic speed controller via high-priority timed tasks, and passively receives data broadcast by the GNSS / IMU module via hardware interrupts.

[0018] Compared with the prior art, the present invention has the following beneficial effects: This invention adopts a dual-core distributed architecture of handheld terminal + central processing unit and CAN bus network, which realizes real-time and reliable interaction and centralized processing of system information, and has strong anti-interference ability.

[0019] This invention introduces a multi-layered safety logic verification based on multi-source data for throttle control, preventing misoperation and dangerous situations from the source of control and achieving inherent safety.

[0020] This invention provides pilots with a comprehensive, intuitive, and real-time flight situation by fusing multi-sensor data and displaying it centrally on a screen, thus significantly enhancing situational awareness.

[0021] The throttle unit of this invention adopts a Hall sensor and a dual-channel redundant output design of CAN / PWM, which can seamlessly switch when the main channel fails, greatly improving the reliability of power control.

[0022] The system of this invention has complete black box data recording function, and all data is stamped with high precision, providing a solid data foundation for flight analysis, fault tracing and performance optimization. Attached Figure Description

[0023] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0024] Terminology Explanation: GNSS stands for Global Navigation Satellite System.

[0025] IMU stands for Inertial Measurement Unit.

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0027] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0028] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; of course, they can also refer to a mechanical connection or an electrical connection; furthermore, they can refer to a direct connection, an indirect connection through an intermediate medium, or a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0029] like Figure 1 As shown, the present invention provides an intelligent flight control system for an electric paraglider, including a handheld terminal and a central processing unit. The handheld terminal and the central processing unit communicate with each other via a CAN bus. The central processing unit is connected to an external GNSS / IMU module, a battery management system, an electronic speed controller, and at least one temperature sensor via the CAN bus to acquire various types of data from the GNSS / IMU module, the battery management system, the electronic speed controller, and the temperature sensor. The handheld terminal includes a microcontroller unit, a display screen, a throttle control unit, and a local data storage module; Microcontroller unit: Receives and integrates data from the central processing unit to generate integrated flight status information; performs status monitoring and intelligent diagnosis of the system based on the received data and / or integrated flight status information to determine whether the system is abnormal; receives throttle commands from the throttle control unit and verifies the throttle commands based on the received data and / or integrated flight status information and preset multi-layer safety logic; if the throttle command passes the verification, it is sent as a control signal to the electronic speed controller for execution; if the throttle command fails the verification or the intelligent diagnosis determines that the system is abnormal, the throttle command is restricted or refused to be executed, and a corresponding alarm event is generated; drives the display screen to centrally display the integrated flight status information and alarm events, and controls the local data storage module (104) to record relevant data.

[0030] This invention, based on data generated by existing common modules of electric paragliders, such as GNSS / IMU modules, battery management systems, electronic speed controllers, and temperature sensors, aims to provide a higher-level, intelligent flight control system solution. The central processing unit (CPU) connects to the existing GNSS / IMU module, battery management system, electronic speed controller, and at least one temperature sensor on the electric paraglider via a CAN bus, acquiring various data from these components. Preferably, the CPU is located on the parachute pack or motor bracket of the electric paraglider. The GNSS (positioning) data and IMU (inertial measurement) data acquired from the GNSS / IMU module include, but are not limited to: latitude and longitude, altitude, ground velocity, and rate of climb from the GNSS module; and three-axis angular velocity and three-axis linear acceleration from the IMU module; preferably, it also includes roll angle, pitch angle, and yaw angle attitude information calculated and output by the module. Data acquired from the battery management system includes, but is not limited to: total battery voltage, total current, individual cell voltage, remaining capacity, health status, and temperature. This battery is a power battery pack composed of multiple cells connected in series and / or parallel, providing power to the entire electric paraglider propulsion system. This power battery pack generates multiple stable low-voltage DC currents through the power management system, providing unified power to the central processing unit, motor / electronic speed controller, and handheld terminal, ensuring the uniformity and purity of the system's power supply. Data acquired from the electronic speed controller includes, but is not limited to: real-time motor speed, internal temperature of the electronic speed controller, input current, and specific error codes generated by the electronic speed controller's self-diagnosis. This motor is the thrust motor of the electric paraglider. Data acquired from temperature sensors (e.g., motor temperature sensors) shows the real-time temperature of the motor windings or shell. The central processing unit has an external environmental sensor interface (such as UART, I2C, SPI, or analog ADC interface) for connecting to external temperature and humidity sensors that collect atmospheric temperature and humidity data of the flight environment. This data is used for system data recording, flight status tracing, and providing environmental parameter input to the system.

[0031] The central processing unit of this invention integrates various types of acquired data into data packets via a CAN bus and transmits them to the microcontroller unit of the handheld terminal. The microcontroller unit unpacks the data packets received via the CAN bus, parses out the various types of data contained therein according to a predefined communication protocol, performs data integrity verification (such as CRC check), and determines whether the data is within a reasonable physical range (e.g., the voltage is not negative). Invalid or erroneous data frames are discarded to ensure the reliability of the data used for subsequent processing.

[0032] The microcontroller unit (MCU) performs deep fusion of positioning and inertial measurement data from the GNSS / IMU module by executing an algorithm based on extended Kalman filtering to obtain accurate, smooth, and reliable flight status information. This method systematically solves the problem of time and space synchronization of multi-source data and effectively suppresses the inherent defects of various sensors. The MCU receives data packets from the central processing unit (CPU), which contain GNSS (positioning) data (latitude, longitude, altitude, velocity, and UTC timestamp) and IMU data (three-axis angular velocity, three-axis linear acceleration, and corresponding microcontroller local timestamps). Because GNSS data has a low update rate (e.g., 10Hz) and contains random noise, while IMU data has a high update rate (e.g., 100Hz) but suffers from accumulated errors, the two are not strictly aligned in time. To this end, data preprocessing and time synchronization are performed, namely S1: using the high-precision UTC timestamp provided by the GNSS module as the absolute time reference for the entire system; for IMU data arriving between two GNSS data points, a high-resolution timer inside the microcontroller unit is used to assign a precise microsecond-level timestamp consistent with the GNSS time reference through linear interpolation or higher-order interpolation algorithms, thus synchronizing the two types of data. Then, coordinate system I and data transformation are performed, namely S2: the latitude, longitude, and altitude coordinates in the positioning data are transformed to a local northeast-sky coordinate system with the flight start point or a certain reference point as the origin through a map projection algorithm to obtain the observation position and observation velocity; at the same time, the acceleration in the carrier coordinate system measured by the IMU module is transformed to the northeast-sky coordinate system, and the gravitational acceleration component is subtracted to obtain the motion acceleration. Finally, the core iterative process of the extended Kalman filter, namely S3, includes a prediction step and an update step. S31: Prediction step: Using the state estimate from the previous moment, the angular velocity measured by the IMU module, and the motion acceleration obtained in S2, predict the current state vector and prediction covariance matrix; the state vector includes at least position, velocity, and attitude angles. S32: Update step: When data from the GNSS module is received, the observed position and velocity are compared with the state vector predicted in S31, the Kalman gain is calculated, and the predicted state vector is corrected to obtain the posterior state estimate, i.e., the fused flight state information. This process runs continuously at high frequency, using IMU data (e.g., 100Hz) for continuous state prediction and GNSS data (e.g., 10Hz) as the observation benchmark for periodic correction, thereby effectively suppressing GNSS noise and jumps and compensating for the trajectory divergence inevitably caused by pure IMU integration. The final output is smooth, accurate, and low-latency flight trajectory, velocity, and attitude data, which drives the display screen in real time, providing pilots with comprehensive, stable, and reliable situational awareness in various forms such as graphical instruments, virtual horizons, and digital parameters.

[0033] The microcontroller unit (101) also embeds a rule engine, which processes multiple data streams and / or fused flight status information from the central processing unit (200) in parallel; it performs real-time diagnosis of the multiple data streams and / or fused flight status information by calling multiple predefined diagnostic rules, and verifies throttle commands; at least some of the diagnostic rules depend on multiple parameters from different data streams and are correlated through logical operators; when the logical condition of any diagnostic rule is met, an alarm event containing alarm level and type information is generated. This invention, through a set of multi-parameter, multi-level correlated diagnostic and alarm logic that goes beyond simple threshold judgment, faces and successfully solves the three major technical challenges of multi-parameter coupling, real-time diagnosis, and system scalability.

[0034] Specifically, during system initialization, a predefined, structured set of diagnostic rules is loaded into memory. Each diagnostic rule consists of three parts: 1. Unique Identifier (Rule ID): used to identify the rule. 2. Condition: a judgment condition consisting of a logical expression (using operators such as AND, OR, NOT). This expression depends on one or more data parameters. 3. Action: a set of instructions to be executed when the condition is met, the core of which is to generate a structured alarm event. The rule engine runs periodically at a high, fixed frequency (e.g., 20Hz). Its single processing cycle is as follows: The rule engine acquires all the data required for the current cycle in parallel, including multi-channel data and fused flight status information; it iterates and evaluates the conditions of all activated diagnostic rules in parallel, specifically reading the current values ​​of the parameters referenced in the condition part of each diagnostic rule and performing the corresponding logical operations, ultimately obtaining a Boolean result (True or False) for a rule; for rules with a Boolean result of True, its action part is immediately executed, and an alarm event is further generated. An alarm event includes at least: Event ID: associated with the rule ID; Timestamp: high-precision UTC time; Alarm level: such as "Alert," "Warning," or "Critical"; Alarm type / description: such as "Battery overheating and power reduction," or "Power system response anomaly"; Relevant data snapshot: the instantaneous value of the key parameters when the alarm is triggered. Alarms are categorized into "Alert," "Warning," and "Critical" levels, attracting the pilot's attention through different colors, sounds, and screen flashing patterns.

[0035] This invention performs dynamic correlation analysis on parameters from different sources (GNSS / IMU module, battery management system, electronic speed controller, and temperature sensor). For example, the determination of a "battery overheating and power reduction" alarm is not based on an isolated judgment of temperature > 80°C, but must simultaneously meet the power load condition of "discharge current > 80% of rated value," forming a multi-parameter coupled logic expression to distinguish between real risks and transient interference. To achieve real-time and efficient processing of this complex logic, this invention adopts a hierarchical diagnostic tree structure: the bottom layer performs rapid threshold screening for single parameters, the middle layer performs combined logic judgment of multiple parameters, and the top layer performs final adjudication and conflict resolution of alarm levels based on the state machine. In addition, a dynamic threshold adjustment mechanism is introduced, and some thresholds can be dynamically adjusted according to flight phase (such as takeoff, cruise, and landing) or environmental parameters (such as altitude), and delayed triggering and automatic recovery logic to prevent alarm overload is designed. Ultimately, the alarm information generated through this sophisticated process is categorized into different levels and output through differentiated visual and auditory channels, thereby achieving a fundamental shift from passive alarms to proactive intelligent diagnosis, significantly improving the system's security and reliability.

[0036] The core of the throttle control unit of this invention is a Hall effect sensor, which is operatively coupled to the throttle control mechanism of an electric paraglider in a non-contact manner. In a preferred embodiment, the throttle control mechanism is a rotatable throttle handle. A small permanent magnet is fixedly mounted on the rotation axis of the throttle handle. The Hall effect sensor is fixedly mounted on the body or internal circuit board of the handheld terminal, its spatial position corresponding to the magnet on the rotation axis. When the pilot rotates the throttle handle, the magnet rotates accordingly, causing a linear change in the magnetic field strength and / or direction between it and the fixed Hall effect sensor. The Hall effect sensor senses this magnetic field change non-contactly and outputs an analog voltage signal or digital PWM signal that is precisely proportional to the angle of the throttle handle. This signal is the original throttle command, which is directly transmitted to the microcontroller unit. This invention uses a Hall effect sensor instead of a traditional potentiometer, offering advantages such as non-contact operation, wear-free operation, high precision, and long lifespan, while outputting a stable and reliable throttle command.

[0037] The microcontroller unit (MCU) first samples and digitizes the throttle command. Subsequently, the throttle command is not directly output but must undergo multi-layered safety logic verification. After successful verification, the MCU synchronously generates two completely independent control signals: one is the primary channel signal, i.e., the CAN bus digital signal, which is sent to the electronic speed controller (ESC) via the CAN bus. This channel is the highly reliable primary control channel. The other is the backup channel signal, a PWM analog signal corresponding to the CAN bus digital signal. The ESC prioritizes receiving and responding to the CAN bus digital signal. This system (through the MCU or ESC) continuously monitors the CAN bus communication status. When a CAN communication failure (timeout, error, or loss) is detected, the system automatically or seamlessly switches to receiving the PWM analog signal, thereby ensuring the continuity of power control and greatly improving the system's fault tolerance.

[0038] The throttle control unit also includes a physical safety switch connected in series in the throttle output circuit, used to physically connect or disconnect the control signal output path. The throttle output circuit is a complete electronic signal path from the generation of the control signal by the microcontroller to its delivery to the electronic governor. The physical safety switch is a mechanical self-locking or toggle switch. When it is in the OFF position, it physically and simultaneously hardwires the CAN bus and PWM signal lines to the electronic governor, ensuring that the electronic governor cannot receive any valid throttle signal and completely preventing accidental ground starts.

[0039] The multi-layered security logic embedded in the microcontroller is a software-based intelligent decision-making layer based on multi-source information. It executes verifications of the multi-layered security logic by invoking predefined diagnostic rules. The multi-layered security logic includes at least one of the following: Ground safety logic: When the flight speed is zero and the physical safety switch is in the closed state, suppress the output of control signals; the flight speed is derived from multiple data and / or fused flight status information; The ground safety logic aims to completely prevent the risks associated with accidental ground activation. The system forcibly suppresses the output of control signals when both of the following conditions are met: 1. Zero flight speed: The system determines that the aircraft is stationary on land. The flight speed may be derived from: (a) multiplexed data: directly using the ground speed provided raw by the GNSS module from the central processing unit. (b) fused flight status information: prioritizing the use of a smoother and more accurate speed value processed by a data fusion algorithm.

[0040] 2. Physical safety switch is in the off position: This condition indicates that the pilot has no intention to start the operation and provides the most basic hardware safety confirmation.

[0041] When the above two conditions are met, the microcontroller will completely ignore the instructions from the throttle control unit at the software level, fundamentally suppressing any power output.

[0042] The fault suppression logic proactively intervenes to ensure safety when critical system components experience severe failures. It is triggered when the battery management system or electronic speed controller reports a severe fault level, limiting or cutting off the output of control signals. The fault level is directly derived from multiple data streams from the central processing unit. Examples of severe fault levels reported by the battery management system include severe battery imbalance, severe undervoltage / overvoltage, and severe internal short circuit. Examples of severe fault levels reported by the electronic speed controller include motor stall, hardware overcurrent, and communication loss.

[0043] For some degradeable faults (such as certain overheat alarms), the system will forcibly limit the maximum throttle output (e.g., not exceeding 50% power), allowing the pilot to return to base or land at a safe power level. For faults that may cause equipment damage or immediate danger (such as severe short circuits), the system will completely cut off the output of control signals, forcing the motors to stop.

[0044] The envelope protection logic aims to prevent unintentional dangerous maneuvers and dynamically safeguard flight safety boundaries. The system monitors flight status in real time and dynamically adjusts throttle response according to the preset envelope protection logic. For example, when the system detects a flight altitude < 20 meters, it automatically limits the maximum throttle output to no more than 80% to prevent uninstructed attitude changes caused by a sudden increase in thrust during the ground roll phase, ensuring a smooth and stable takeoff process and avoiding loss of controllable flight. When the flight speed < 30 km / h and the flight altitude > 50 meters, the maximum rate of climb is limited to prevent stall. When the flight speed > 90% of the maximum permissible speed, the throttle sensitivity is gradually reduced and the maximum power is limited to suppress the tendency to continue accelerating. Flight altitude and / or speed are derived from: (a) multi-channel data: the original altitude and ground speed provided by the GNSS module. (b) fused flight status information: the altitude and speed information obtained after data fusion are used preferentially, as they have higher accuracy and reliability.

[0045] The local data storage module of this invention is an indispensable "black box" of the system. It does not simply accumulate data, but continuously records the complete flight data chain in a customized format that is efficient, reliable, and easy to analyze afterward, providing an irreplaceable data foundation for flight analysis, fault tracing, and performance optimization. It continuously records data, alarm events, and throttle command operation records from the central processing unit (200) using a data frame structure with time-series identifiers. Data from the central processing unit includes raw data from the GNSS / IMU module, all parameters of the battery management system, electronic speed controller status data, temperature sensor readings, and all multi-channel data acquired via the CAN bus. Alarm events are generated by the rule engine and include complete alarm event objects containing alarm level, type, timestamp, and related data snapshots. Throttle command operation records include the value of the throttle command, the time point of the state change, and the state transition of the physical safety switch.

[0046] To achieve efficient, ordered, and interference-resistant storage, the system employs a custom data frame structure with timing identifiers. A new data file is created for each flight or each system power-on. A header is written at the beginning of the file, recording metadata such as the device serial number, firmware version, and start time. Following the header, all information is recorded in consecutive data frames. Each frame contains the following fields: Synchronization word: A specific sequence of bytes used to quickly locate the start of the frame in the data stream, preventing data corruption. High-precision timing identifier: A monotonically increasing timestamp in milliseconds or even microseconds from system startup. This timestamp is associated with the GNSS UTC time in the file header, providing a unified time reference for all data and is crucial for accurate traceability. Data type ID: An identifier indicating the data type carried by this frame (e.g., 0x01 for GNSS data, 0x02 for battery management system data, 0xF0 for alarm events, etc.). Data length: Indicates the length of the effective data payload. Effective data payload: The actual data content stored. Its format is predefined according to the data type ID, typically a compact binary format to save storage space. Cyclic Redundancy Check (CRC) code: Used to verify the integrity of the data in this frame during transmission and storage, ensuring that the data has not been tampered with or damaged.

[0047] The local data storage module preferably uses SD cards or eMMC flash memory as storage media and provides convenient physical data export capabilities via a USB interface. Exported data files can be parsed in two ways: direct file copy: users can directly copy the files to a computer and use dedicated host computer ground station software for graphical analysis, report generation, and curve playback. API interface communication: the host computer software can also communicate with the handheld terminal via commands to filter and read data records related to specific time periods or events.

[0048] The central processing unit (CPU) of this invention employs a microcontroller with multi-core processing capabilities (e.g., a chip based on an ARM Cortex-M7 or Cortex-M4 / M7 heterogeneous architecture) and runs a real-time operating system (e.g., FreeRTOS, ThreadX, or μC / OS). It polls data from the battery management system and electronic speed controller via high-priority timed tasks and passively receives data broadcast by the GNSS / IMU module via hardware interrupts. The CPU adopts a hybrid strategy combining active polling and passive interrupt reception, tailored to the data characteristics of different external modules. This achieves extremely low latency acquisition of high-speed data, with a response speed in the microsecond range, perfectly matching the high update rate characteristics of the GNSS / IMU module and ensuring the timeliness of navigation information.

[0049] The microcontroller unit of this invention preferably uses STMicroelectronics' STM32H7 series or similar high-performance microcontrollers. Specific models may include STM32H743, STM32H750, or other brand chips with similar performance.

[0050] In one embodiment of the present invention, the central processing unit (CPU) is a high-performance multi-core microcontroller (such as the STM32H7 series) running a real-time operating system such as FreeRTOS. A GNSS / IMU module, battery management system, electronic speed controller, and temperature sensor are connected via multiple CAN interfaces. The CPU's task scheduler creates a high-priority task to actively poll the data from the battery management system, electronic speed controller, and temperature sensor at a frequency of 20Hz. Simultaneously, a CAN filter is configured to receive 100Hz data broadcast by the GNSS / IMU module via hardware interrupts. All data is initially verified and stored in a circular buffer, then retrieved by a 10Hz data packaging task, assembled into a unified format data packet, and sent to the handheld terminal. For external temperature and humidity sensors, they are connected via the CPU's external environmental sensor interface. The CPU creates a dedicated task to communicate with the sensor through this interface protocol, periodically reading ambient temperature and humidity data, storing this data in the circular buffer, and finally sending it to the handheld terminal for display and recording.

[0051] After receiving the data packet, the microcontroller unit of the handheld terminal uses the Extended Kalman Filter (EKF) algorithm to deeply fuse the absolute positioning information of GNSS with the high-frequency inertial measurement data of the IMU, outputting smooth, accurate, and low-latency flight status information. First, GNSS data (latitude, longitude, altitude, ground velocity, and rate of ascent / descent) and IMU data (three-axis angular velocity and three-axis linear acceleration) are separated from the data packet. Then, using the UTC timestamp provided by the GNSS module in the data packet as a reference, the IMU data is interpolated and aligned using an internal high-precision timer to ensure that all data are time-consistent. Subsequently, the latitude, longitude, and altitude coordinates of the GNSS module are transformed to the local northeast-sky coordinate system to obtain the observation position and observation velocity; simultaneously, the acceleration measured by the IMU module in the carrier coordinate system is transformed to the northeast-sky coordinate system, and the gravitational acceleration component is subtracted to obtain the motion acceleration. Finally, within each calculation cycle of the EKF, the EKF algorithm is executed for data fusion. The EKF state vector is set to 9 dimensions, including position, velocity, attitude angle, and sensor bias. The algorithm iteratively performs prediction and update steps within each calculation cycle. In the prediction step, the state estimate from the previous moment, the angular velocity measured by the IMU module, and the motion acceleration obtained in S2 are used to predict the state vector and the prediction covariance matrix at the current moment. The state vector includes at least position, velocity, and attitude angle. In the update step, when data is received from the GNSS module, the observed position and observed velocity are compared with the state vector predicted in S31, the Kalman gain is calculated, and the predicted state vector is corrected to obtain the posterior state estimate. Finally, a smooth and accurate flight trajectory and attitude are output.

[0052] The merged data is rendered on the display screen in real time and visualized centrally in the form of virtual horizons, digital meters, bar charts, etc.

[0053] The throttle control unit uses a Hall sensor to collect throttle input, and a physical safety switch is connected in series in the throttle output circuit. After reading the throttle command, the microcontroller unit calls the embedded rule engine to perform multi-layered safety logic checks. The rule engine predefines several diagnostic rules, such as: Rule 1 (Ground Safety): IF (GNSS speed < 1 km / h) AND (physical safety switch = OFF) THEN suppress throttle output.

[0054] Rule 2 (Battery Overheating): IF (Battery temperature > 80°C) AND (Discharge current > 80% of rated value) THEN triggers the "Battery Overheating Power Reduction" warning and limits the maximum throttle output to 70%.

[0055] If all checks pass, the microcontroller sends a digital throttle command to the electronic governor via the CAN bus, while simultaneously generating a corresponding PWM analog signal as a backup. If the microcontroller detects a CAN bus communication timeout or error, it immediately switches to the PWM analog signal output to ensure uninterrupted power delivery.

[0056] Meanwhile, the local data storage module (such as an SD card) continuously records all data packets, alarm events, and throttle operation records from the central processing unit in a custom binary format. Each frame of data contains a synchronization header, a millisecond-level timestamp, a data type ID, a data payload, and a cyclic redundancy check code.

[0057] Finally, it should be noted that the above embodiments are merely preferred embodiments of the present invention used to illustrate the technical solutions of the present invention, and are not intended to limit the invention, nor are they intended to limit the patent scope of the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention. That is to say, any changes or refinements made to the main design concept and spirit of the present invention that are not of substantial significance, but whose technical problems are still consistent with the present invention, should be included within the protection scope of the present invention. In addition, the direct or indirect application of the technical solutions of the present invention to other related technical fields are similarly included within the patent protection scope of the present invention.

Claims

1. An intelligent flight control system for an electric parafoil, characterized in that, The handheld terminal and the central processor are in data communication through a CAN bus; the central processor is connected with an external GNSS / IMU module, a battery management system, an electronic governor and at least one temperature sensor through the CAN bus to acquire various data from the GNSS / IMU module, the battery management system, the electronic governor and the temperature sensor; The handheld terminal comprises a micro control unit, a display screen, a throttle control unit and a local data storage module; The micro control unit receives and fuses the data from the central processor to generate fused flight state information; based on the received data and / or fused flight state information and predefined diagnostic rules, the system is monitored and intelligently diagnosed to determine whether the system is abnormal; the throttle instruction from the throttle control unit is received and verified based on the received data and / or fused flight state information and preset multi-layer safety logic; if the throttle instruction passes the verification, the throttle instruction is sent to the electronic governor as a control signal for execution; if the throttle instruction fails the verification or the intelligent diagnosis determines that the system is abnormal, the throttle instruction is restricted or rejected for execution, and corresponding alarm events are generated; The display screen is driven to display the fused flight state information and alarm events, and the local data storage module is controlled to record relevant data.

2. An intelligent flight control system for a powered paraglider according to claim 1, wherein, The throttle control unit comprises a Hall effect sensor associated with a throttle control mechanism of the powered parachute, for generating a throttle instruction without contact.

3. The intelligent flight control system of a motorized paraglider according to claim 1, wherein, The micro control unit outputs a control signal to the electronic governor through a throttle output loop; the control signal is a dual-redundancy signal comprising a CAN bus digital signal and a PWM analog signal.

4. An intelligent flight control system for a powered paraglider according to claim 3, wherein, When the CAN bus communication is normal, the CAN bus digital signal is used preferentially; when the CAN bus communication fails, the PWM analog signal is switched to.

5. The intelligent flight control system of a motorized paraglider according to claim 3, wherein, The throttle control unit comprises a physical safety switch connected in series in the throttle output loop, for physically connecting or cutting off the output path of the control signal.

6. An intelligent flight control system for a powered paraglider according to claim 5, wherein, The micro control unit performs verification of the multi-layer safety logic by calling predefined diagnostic rules, the multi-layer safety logic comprising at least one of the following: Ground safety logic: when the flight speed is zero and the physical safety switch is in the off state, the output of the control signal is inhibited; the flight speed is derived from multiple data and / or fused flight state information; Fault inhibition logic: when the fault level reported by the battery management system or the electronic governor is serious, the output of the control signal is limited or cut off; the fault level reported by the battery management system or the electronic governor is derived from multiple data; Packet line protection logic: dynamically adjust the upper limit of the control signal output according to the current flight height and / or speed; The current flight height and / or speed are derived from multiple data and / or fused flight state information.

7. The intelligent flight control system of a motorized paraglider according to claim 1, wherein, The micro control unit fuses the positioning data and inertial measurement data from the GNSS / IMU module by performing an extended Kalman filtering algorithm to obtain fused flight state information, comprising the following steps: S1: time synchronizing the inertial measurement data with the UTC time reference provided by the GNSS module; S2: convert the longitude and latitude coordinates in the positioning data to the local East-North-Sky coordinate system to obtain the observation position and observation velocity; meanwhile, convert the acceleration measured by the IMU module in the carrier coordinate system to the East-North-Sky coordinate system, and deduct the gravity acceleration component to obtain the motion acceleration; S3: in each calculation period of the extended Kalman filter, perform: S31: prediction step: use the state estimation value at the last time, the angular velocity measured by the IMU module, and the motion acceleration obtained in S2 to predict the state vector and the predicted covariance matrix at the current time; the state vector at least includes position, velocity, and attitude angle; S32: update step: when the data of the GNSS module is received, compare the observation position and observation velocity with the state vector predicted in S31, calculate the Kalman gain, and modify the predicted state vector to obtain the posterior state estimation, i.e. the fused flight state information.

8. The intelligent flight control system of a motorized paraglider according to claim 1, wherein, The micro control unit is embedded with a rule engine, which processes multiple channels of data from the central processor and / or the fused flight state information in parallel; real-time diagnosis is performed on the multiple channels of data and / or the fused flight state information by calling multiple predefined diagnostic rules, and the throttle command is verified; at least part of the diagnostic rules depend on multiple parameters from different channels of data and are associated through logical operators; when the logical condition of any diagnostic rule is met, an alarm event containing alarm level and type information is generated.

9. The intelligent flight control system of a motorized paraglider according to claim 1, wherein, The local data storage module records the data from the central processor, alarm events, and operation records of the throttle command in a data frame structure with time sequence identification.

10. The intelligent flight control system of a motorized paraglider according to claim 1, wherein, The central processor uses a microcontroller with multi-core processing capability and runs a real-time operating system to poll the data of the battery management system and the electronic speed controller through high-priority timing tasks, and passively receives the data broadcast by the GNSS / IMU module through hardware interrupts.

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