A method and system for controlling the speed of a high-speed motor module of a drone

Abstract

The application relates to the technical field of unmanned aerial vehicle control, in particular to a method and system for controlling the rotating speed of a high-speed motor module of an unmanned aerial vehicle; the method comprises the following steps: acquiring current attitude information, instantaneous voltage information of a power supply circuit, current operation information and a current flight control scheme of the unmanned aerial vehicle; obtaining attitude abnormal information of the unmanned aerial vehicle by using the current attitude information, the instantaneous voltage information and each current operation information; determining a flight adjustment scheme of the unmanned aerial vehicle based on the attitude abnormal information of the unmanned aerial vehicle; adjusting and processing the current flight control scheme by using the flight adjustment scheme of the unmanned aerial vehicle to obtain an adjusted flight control scheme; and adjusting and processing the high-speed motor module of the unmanned aerial vehicle by using the adjusted flight control scheme, so as to complete the flight control of the unmanned aerial vehicle. The application aims to solve the problem that the rotating speed of the high-speed motor module cannot be effectively controlled during the flight of the unmanned aerial vehicle, resulting in the attitude instability of the unmanned aerial vehicle.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) control technology, specifically to a method and system for controlling the rotational speed of a high-speed motor module in a UAV. Background Technology

[0002] When performing various missions, drones encounter complex environments during flight, such as changes in airflow or adjustments to their own load. To counteract external disturbances, the drone's flight control system sends drastic deceleration commands to some high-speed motor modules. When these high-speed motor modules are forced to decelerate rapidly, they generate reverse electrical energy due to regenerative braking, which is instantly fed back to the drone's shared power line, creating a strong voltage spike. Since all high-speed motor modules on the drone are connected to the same power line, the voltage spike generated by the decelerating high-speed motor module is simultaneously applied to other high-speed motor modules executing stabilization commands. This causes unstable fluctuations in motor speed, affecting thrust output and making it difficult to maintain stable flight attitude, potentially even hindering mission completion.

[0003] For a high-speed motor module executing an acceleration command, the received flight control command is to increase its rotational speed. However, the operating voltage unexpectedly spikes due to a power line voltage increase. Since motor speed is positively correlated with input voltage, this voltage spike causes a sudden, uninstructed speed overshoot in the high-speed motor module, instead of a smooth increase in speed. This uncontrolled acceleration generates excessive counter-corrective force, failing to stabilize the attitude and instead causing the drone to tilt violently and excessively in the opposite direction. Upon detecting this more severe counter-attitude deviation, the flight control system issues even more extreme counter-control commands, creating a vicious cycle of oscillations. The inability to effectively control the high-speed motor module's rotational speed leads to violent swaying in the air, unstable attitude, and ultimately, an uncontrolled crash. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for controlling the speed of a high-speed motor module in a drone, which solves the problem that it is difficult to effectively control the speed of the high-speed motor module during drone flight, and that the motor speed overshoot leads to the drone's attitude instability.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for controlling the rotational speed of a high-speed motor module in a UAV, comprising: Acquire the current attitude information of the UAV during flight, the instantaneous voltage information of the power line, the current operating information of each high-speed motor module in the UAV, and the current flight control scheme of the UAV; Using the current attitude information, instantaneous voltage information, and each current operating information, the current abnormal state of the UAV is identified and processed to obtain the attitude abnormality information of the UAV; wherein, the attitude abnormality information includes attitude abnormality information generated by power feedback, normal attitude adjustment, or external disturbance. Based on the abnormal attitude information of the UAV, a flight adjustment plan for the UAV is determined; Using the flight adjustment scheme of the UAV, the current flight control scheme is adjusted to obtain the adjusted flight control scheme; The adjusted flight control scheme is used to modify the high-speed motor module of the UAV in order to achieve flight control of the UAV.

[0006] Furthermore, the steps of identifying and processing the current abnormal state of the UAV using the current attitude information, instantaneous voltage information, and each current operational information to obtain the UAV's attitude abnormality information include: Based on the current attitude information, determine the urgency of the current attitude anomaly and the probability of each motor speed anomaly. Based on the instantaneous voltage information and each current operating information, the voltage spike characteristics of the instantaneous voltage information and the operating state characteristics of each motor are determined; wherein, the operating state characteristics include the current speed, operating time and operating frequency; By utilizing the urgency level, probability value, voltage spike characteristics, and operating status characteristics of each motor in the current attitude, the current abnormal state of the UAV is identified and processed to obtain the attitude abnormality information of the UAV.

[0007] Furthermore, based on the current attitude information, the steps of determining the urgency of the current attitude anomaly and the probability of each motor speed occurring abnormally include: The current attitude information is processed to extract the current power supply voltage and the speed overshoot information of each motor. The current power supply voltage and the speed overshoot information of each motor are corrected to obtain the corrected current power supply voltage and the speed overshoot information of each motor. Based on the corrected current power supply voltage and the speed overshoot information of each motor, the urgency of the current attitude abnormality and the probability value of each motor speed abnormality are determined.

[0008] Furthermore, based on the corrected current power supply voltage and the speed overshoot information of each motor, the steps of determining the urgency of the current attitude anomaly and the probability value of each motor speed anomaly include: Using the corrected current power supply voltage and the speed overshoot information of each motor, the current attitude of the UAV is subjected to anomaly assessment processing to obtain the anomaly assessment value of the current attitude information. The abnormal assessment value of the current posture information is matched with a preset urgency level model to obtain the abnormal urgency level of the current posture. Using the anomaly assessment value of the current attitude information, the abnormal state of each motor speed is predicted, and the probability value of each motor speed occurring abnormally is obtained.

[0009] Furthermore, based on the instantaneous voltage information and each current operating information, the steps of determining the voltage spike characteristics of the instantaneous voltage information and the operating state characteristics of each motor include: The instantaneous voltage information is subjected to voltage spike detection processing to determine the voltage spike characteristics of the instantaneous voltage information; Using the instantaneous voltage information, state feature extraction processing is performed on each current operating information to obtain the operating state features of each motor.

[0010] Furthermore, the steps for determining the flight adjustment scheme for the UAV based on the attitude anomaly information of the UAV include: The attitude anomaly information of the UAV is processed for information identification to obtain the attitude anomaly state type and attitude anomaly level; Based on the type of attitude anomaly, an adjustment scheme model for the UAV is determined; The abnormality level of the attitude anomaly is matched with the UAV's adjustment scheme model to obtain the UAV's flight adjustment scheme.

[0011] Furthermore, the steps of performing information identification processing on the attitude anomaly information of the UAV to obtain the attitude anomaly state type and attitude anomaly level include: The attitude anomaly information of the UAV is processed to identify the anomaly type, and the attitude anomaly state type is obtained; Based on the state type of the posture anomaly, determine the anomaly level index and the weight of the anomaly level index. By using the aforementioned anomaly level index and its weight, anomaly level analysis is performed on the attitude anomaly information of the UAV to obtain the anomaly level of the attitude anomaly.

[0012] Furthermore, the steps of adjusting the current flight control scheme using the UAV's flight adjustment scheme to obtain the adjusted flight control scheme include: Using the flight adjustment scheme of the UAV, the current flight control scheme is initially adjusted to obtain a preliminary adjustment scheme; Using the aforementioned preliminary adjustment scheme, the high-speed motor module of the UAV is simulated and adjusted to determine the energy feedback value and intensity of each motor during deceleration. Using the energy feedback value and the intensity of the energy feedback, the preliminary adjustment scheme is modified to obtain the adjusted flight control scheme.

[0013] Furthermore, using the aforementioned preliminary adjustment scheme, the steps of simulating and adjusting the high-speed motor module of the UAV to determine the energy feedback value and intensity of each motor during deceleration include: Using the aforementioned preliminary adjustment scheme, the high-speed motor module of the UAV is simulated and adjusted to determine the instantaneous temperature, internal resistance, and state of charge information of the energy storage battery in the UAV. Based on the instantaneous temperature, internal resistance, and state of charge information of the energy storage battery, the battery health, the initial value of energy feedback for each motor during deceleration, and the initial intensity of energy feedback are determined. Using the battery health status, the initial value and initial intensity of the energy feedback for each motor during deceleration are adjusted to obtain the energy feedback value and intensity for each motor during deceleration.

[0014] The present invention also provides a high-speed motor module speed control system for unmanned aerial vehicles (UAVs), the system comprising: The information acquisition module is used to acquire the current attitude information of the UAV during flight, the instantaneous voltage information of the power line, the current operating information of each high-speed motor module in the UAV, and the current flight control scheme of the UAV. The information recognition module is used to identify and process the current abnormal state of the UAV using the current attitude information, instantaneous voltage information and each current operation information to obtain the attitude abnormal information of the UAV; wherein, the attitude abnormal information includes attitude abnormal information caused by power feedback, normal attitude adjustment or external disturbance. The scheme determination module is used to determine the flight adjustment scheme of the UAV based on the attitude anomaly information of the UAV; The scheme adjustment module is used to adjust the current flight control scheme using the flight adjustment scheme of the UAV, so as to obtain the adjusted flight control scheme; The flight control module is used to adjust the high-speed motor module of the UAV using the adjusted flight control scheme in order to complete the flight control of the UAV.

[0015] Compared with the prior art, the UAV high-speed motor module speed control method and system of the present invention have the following advantages: This invention acquires the current attitude information of the UAV, the instantaneous voltage information of the power supply line, the current operating information of the high-speed motor module, and the current flight control scheme. It then uses this information to identify and process the UAV's current abnormal state, obtaining attitude anomaly information. This attitude anomaly information encompasses various factors that cause attitude instability, such as power feedback, normal attitude adjustments, or external disturbances. By determining a flight adjustment scheme based on the attitude anomaly information and adjusting the current flight control scheme, the adjusted scheme is ultimately used to control the high-speed motor module. This allows for real-time and comprehensive perception of the UAV's operating status and environmental changes, accurate identification of attitude anomalies caused by factors such as power feedback, and targeted generation and correction of flight control schemes. This avoids vicious oscillation cycles when facing voltage spikes and speed overshoots, thereby significantly improving the UAV's flight stability, safety, and mission success rate. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0017] Figure 1 This is a flowchart of a method for controlling the speed of a high-speed motor module in an unmanned aerial vehicle (UAV) according to the present invention.

[0018] Figure 2 This is a flowchart of step S200 in the method for controlling the speed of a high-speed motor module of an unmanned aerial vehicle (UAV) according to the present invention.

[0019] Figure 3 This is a flowchart of step S300 in the method for controlling the speed of a high-speed motor module of an unmanned aerial vehicle (UAV) according to the present invention.

[0020] Figure 4 This is a structural block diagram of a high-speed motor module speed control system for unmanned aerial vehicles (UAVs) according to the present invention.

[0021] In the diagram: 410, Information Acquisition Module; 420, Information Identification Module; 430, Scheme Determination Module; 440, Scheme Adjustment Module; 450, Flight Control Module.

[0022] The implementation and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] The following drawings disclose several embodiments of the present invention. For clarity, many practical details will be described in the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, in some embodiments of the invention, these practical details are not essential. Furthermore, for the sake of simplicity, some conventional structures and components will be shown in the drawings in a simple schematic manner.

[0024] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0025] Furthermore, in this invention, the use of terms such as "first" and "second" is for descriptive purposes only and does not specifically refer to any order or sequence, nor is it intended to limit the invention. They are merely used to distinguish components or operations described using the same technical terms, and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but only if they are feasible for those skilled in the art. If a combination of technical solutions is contradictory or impossible to implement, such a combination should be considered nonexistent and not within the scope of protection claimed by this invention.

[0026] To further understand the content, features, and effects of this invention, the following embodiments are provided, and detailed descriptions are given below in conjunction with the accompanying drawings: Please see Figure 1 This invention provides a method for controlling the rotational speed of a high-speed motor module in a drone, comprising the following steps: S100: Acquire the UAV's current attitude information, instantaneous voltage information of the power supply line, current operating information of each high-speed motor module in the UAV, and the UAV's current flight control scheme during flight. The high-speed motor module refers to the integrated unit of the motors and their associated drive and control units on the UAV that provide lift or thrust; their rotational speed directly affects the UAV's flight attitude and trajectory. Current attitude information refers to the UAV's spatial position and attitude data at a given moment, such as roll angle, pitch angle, yaw angle, and angular velocity. Instantaneous voltage information refers to the voltage value detected in real time on the UAV's power supply line, reflecting the stability of the power supply. Current operating information refers to the real-time operating status data of each high-speed motor module, such as current speed, current, and temperature. The current flight control scheme refers to the flight commands and control strategies currently being executed by the UAV. Specifically, current attitude information can be collected in real time by sensors such as the UAV's built-in inertial measurement unit (IMU) or global positioning system (GPS), and the data is fused and processed by the flight control system. Instantaneous voltage information can be monitored in real time by setting up high-precision voltage sensors on the power supply line. The current operating information of each high-speed motor module, such as speed, current, and temperature, can be measured by sensors inside the motor driver or by external additional sensors, and the data is transmitted to the flight control system. The current flight control scheme is then generated and executed by the UAV flight control system based on preset tasks or operator instructions.

[0027] S200. Using the current attitude information, instantaneous voltage information, and each current operating information, the current abnormal state of the UAV is identified and processed to obtain the UAV's attitude abnormality information. This attitude abnormality information includes information generated by power feedback, normal attitude adjustment, or external disturbances. Attitude abnormality information refers to the abnormal situations identified through analysis that cause instability in the UAV's attitude. These may include power feedback during motor deceleration, normal attitude adjustment commands issued by the flight controller, or disturbances from the external environment (such as gusts of wind). Specifically, attitude abnormality information can include information generated by power feedback, normal attitude adjustment, or external disturbances. For example, by analyzing attitude sensor data, it can be determined whether the UAV is experiencing unexpected tilting or shaking. Simultaneously, by combining the instantaneous voltage information of the power line, voltage spikes or drops can be detected, indicating the occurrence of power feedback. Furthermore, by analyzing the operating information of each high-speed motor module, it can be determined whether there are abnormal fluctuations in rotational speed. This allows for the identification of the UAV's current abnormal state and the differentiation of its source as power feedback, normal attitude adjustment, or external disturbances. For example, if a rapid deceleration of the motor is accompanied by a voltage spike, it may be identified as an attitude anomaly caused by power feedback. When the flight control system issues an attitude adjustment command, but the attitude change exceeds the expected range, it is identified as an anomaly during normal attitude adjustment. When the attitude suddenly changes drastically without any obvious internal cause, it is identified as an external disturbance.

[0028] S300. Based on the attitude anomaly information of the UAV, determine a flight adjustment plan for the UAV. The flight adjustment plan refers to a strategy generated to correct the UAV's flight state based on the identified attitude anomaly information. Specifically, if the attitude anomaly is identified as being caused by power feedback, the flight adjustment plan may include limiting the deceleration rate of the relevant motor modules, or directing the feedback power into an energy storage device through an energy management system. If the attitude anomaly is caused by external disturbances, the flight adjustment plan may include increasing motor thrust to counteract the disturbance, or adjusting the UAV's flight path to avoid the disturbance area. If the attitude anomaly occurs during normal attitude adjustment, fine-tuning the control parameters may be necessary to optimize the adjustment effect.

[0029] S400. Using the UAV's flight adjustment scheme, the current flight control scheme is adjusted to obtain an adjusted flight control scheme. The adjusted flight control scheme refers to the final control commands modified from the original flight control scheme by incorporating the flight adjustment scheme. Specifically, the flight adjustment scheme can be superimposed on the current flight control scheme as a correction command, or new flight commands can be recalculated and generated based on the flight adjustment scheme. The adjusted flight control scheme will include precise control commands for actuators such as motor speed and control surface deflection to correct abnormal UAV attitudes.

[0030] The S500 utilizes an adjusted flight control scheme to modify the high-speed motor modules of the UAV, thereby enabling flight control. Specifically, the adjusted flight control scheme is directly sent to the drivers of each high-speed motor module. The drivers then precisely control the motor speed and output thrust according to the instructions. This allows the UAV to effectively cope with various abnormal situations, maintain flight stability, and successfully complete its predetermined mission.

[0031] In this embodiment, by acquiring the UAV's attitude information, instantaneous voltage information of the power supply line, and current operating information of each high-speed motor module, and combining this with the current flight control scheme, the current abnormal state of the UAV can be identified and processed to obtain attitude anomaly information. Based on the attitude anomaly information, corresponding flight adjustment schemes can be determined and implemented, thereby adjusting the current flight control scheme and ultimately achieving precise control of the UAV's high-speed motor modules. By introducing the instantaneous voltage information of the power supply line and the current operating information of each high-speed motor module, attitude anomalies caused by power feedback, normal attitude adjustment, or external disturbances can be identified earlier and more accurately, thus enabling the identification of non-command speed overshoot caused by voltage spikes. Through the fusion and identification of multi-dimensional information, the source and nature of anomalies can be distinguished, thereby avoiding blindly performing reverse control. For example, when a power supply voltage spike is detected during rapid motor deceleration, the anomaly caused by power feedback can be identified, and a flight adjustment scheme can be determined accordingly, such as limiting the deceleration rate or performing energy management, rather than simply issuing a more extreme reverse deceleration command. Through targeted adjustments, interference from voltage spikes to other motor modules can be effectively avoided, thereby suppressing speed overshoot and vicious oscillations. Therefore, this invention can significantly improve the flight stability, safety and control accuracy of UAVs in complex environments, and effectively avoid the risk of loss of control and crash.

[0032] For some of the embodiments described above in this application, please refer to Figure 2 Step S200: The step of identifying and processing the current abnormal state of the UAV using the current attitude information, instantaneous voltage information, and each current operation information to obtain the attitude abnormality information of the UAV includes: S210. Based on the current attitude information, determine the urgency of the current attitude anomaly and the probability of each motor speed anomaly. Specifically, when identifying and processing the current abnormal state of the UAV, firstly, based on the UAV's current attitude information, the urgency of the current attitude anomaly and the probability of each motor speed anomaly can be determined. The current attitude information may include data such as the UAV's pitch angle, roll angle, yaw angle, angular velocity, and acceleration. By analyzing the attitude data, the degree and urgency of the UAV's attitude deviating from the normal range can be assessed. Simultaneously, by combining historical data and prediction models, the probability of each motor speed anomaly can be estimated.

[0033] S220. Based on the instantaneous voltage information and each current operating information, determine the voltage spike characteristics of the instantaneous voltage information and the operating state characteristics of each motor; wherein, the operating state characteristics include the current speed, operating time, and operating frequency. Specifically, the voltage spike characteristics of the instantaneous voltage information refer to the abnormal rise or fall of voltage in the power supply line within a short period of time, usually related to power feedback or sudden changes in motor load. The operating state characteristics of each motor are key parameters reflecting the current operating status of the motor, specifically including the current speed, operating time, and operating frequency. The current speed indicates the actual rotational speed of the motor; the operating time records the duration of continuous operation of the motor in a specific state; and the operating frequency reflects the frequency of the motor drive signal. This helps to comprehensively understand the real-time operating status of the motor and its potential abnormal performance.

[0034] S230. Using the urgency level, probability value, voltage spike characteristics, and operating status characteristics of each motor of the current attitude, the current abnormal state of the UAV is identified and processed to obtain the attitude abnormality information of the UAV.

[0035] Specifically, consider a scenario where a drone encounters a strong gust of wind during flight, causing a drastic deviation in its attitude. At this point, the system acquires the drone's current attitude information (e.g., rapid changes in roll and pitch angles), instantaneous voltage information from the power supply lines (which may fluctuate due to changes in motor load), and current operating information from each high-speed motor module (e.g., a sudden increase or decrease in the speed of a particular motor). Upon receiving this information, the system first analyzes the attitude sensor data based on the current attitude information to determine that the urgency of the current attitude anomaly is high. Based on the attitude change trend and motor response, it predicts a high probability of abnormal speeds in some motors. Simultaneously, voltage spike detection processing is performed on the instantaneous voltage information, revealing slight voltage fluctuations that do not reach the level of severe spikes. Next, the operating status characteristics of each motor are extracted, revealing that one motor experienced a brief overshoot in speed during the attitude deviation, but quickly recovered. By combining this information, utilizing the urgency and probability of the current attitude anomaly, voltage spike characteristics, and the operating status characteristics of each motor, it is identified that the current abnormal state of the UAV is mainly caused by external disturbances (strong winds), accompanied by slight motor speed overshoot, rather than severe power feedback or motor failure. Therefore, the obtained attitude anomaly information clearly indicates the type and urgency of the anomaly, providing precise input for the subsequent solution determination module to formulate targeted flight adjustment plans, such as prioritizing attitude recovery rather than immediately and drastically adjusting motor power to avoid unnecessary power feedback.

[0036] This invention effectively avoids insufficient identification accuracy by refining the identification process of abnormal UAV states into multi-dimensional data analysis. Specifically, by determining the urgency of the anomaly and the probability of abnormal motor speed based on current attitude information, the stability of the UAV's attitude and the health of the motor operation can be assessed from both macroscopic and microscopic levels. Simultaneously, by analyzing the voltage spike characteristics of instantaneous voltage information and the operating status characteristics of each motor, the real-time dynamics of the power system and motor modules can be deeply explored, especially when power feedback or external disturbances occur, these characteristics can provide crucial diagnostic evidence. Due to the comprehensive utilization and cross-validation of multi-source heterogeneous information, the nature and cause of the UAV's current abnormal state can be identified more accurately, such as distinguishing between attitude fluctuations caused by power feedback, attitude deviations caused by external wind disturbances, or abnormal speeds caused by motor malfunctions. This layered and multi-dimensional identification mechanism lays a solid foundation for subsequently developing precise flight adjustment plans.

[0037] In some embodiments of this application described above, the steps of determining the urgency of the current attitude anomaly and the probability of each motor speed anomaly based on the current attitude information include: The current attitude information is processed to extract the current power supply voltage and the overshoot information of each motor. This step involves parsing and extracting key information related to power supply voltage and motor speed overshoot from the raw attitude data acquired by the UAV sensors. For example, voltage signals related to power fluctuations and overshoot signals related to instantaneous changes in motor speed can be identified from the attitude sensor data. The purpose is to transform the raw attitude data, which may contain multi-dimensional information, into more targeted power supply voltage and motor speed overshoot data for assessing abnormal states. The current power supply voltage is the voltage value of the UAV power supply system at a specific moment, reflecting the power supply status of the UAV's power system. The speed overshoot information of each motor refers to the instantaneous peak value or fluctuation amplitude when the motor speed changes rapidly (e.g., during attitude adjustment or when subjected to external disturbances), exceeding the target or stable value and then falling back. This information is a key indicator for assessing UAV attitude anomalies and motor operating status.

[0038] The current power supply voltage and the speed overshoot information of each motor are corrected to obtain the corrected current power supply voltage and speed overshoot information of each motor. This step involves denoising, filtering, calibration, or compensation of the extracted raw power supply voltage and speed overshoot data. For example, algorithms such as Kalman filtering and moving average filtering can be used to remove sensor noise, or the voltage and speed overshoot values ​​can be corrected according to a preset calibration curve to eliminate sensor errors or environmental influences. The purpose is to improve the accuracy and reliability of these key data, providing high-quality input for subsequent anomaly assessment.

[0039] Based on the corrected current power supply voltage and the speed overshoot information of each motor, the urgency level of the current attitude anomaly and the probability value of each motor speed anomaly are determined. This step refers to using precisely processed data to more accurately assess the degree of anomaly and its urgency of the UAV's current attitude, and predict the likelihood of each motor speed anomaly. For example, a mathematical model or machine learning algorithm can be established, using the corrected voltage and speed overshoot data as input, to output quantified anomaly urgency and probability values.

[0040] Specifically, during flight, the drone's attitude sensors detect slight attitude fluctuations. First, the raw current attitude information is processed to extract instantaneous power supply voltage data and the speed overshoot data of the four motors (e.g., motor 1, motor 2, motor 3, and motor 4). For example, by analyzing the high-frequency components in the attitude data, instantaneous motor speed overshoot can be identified, and the instantaneous voltage can be obtained from telemetry data from the power management unit. Next, the extracted power supply voltage data and the speed overshoot data of each motor are corrected. Specifically, the power supply voltage data can be corrected by comparing it with a known standard voltage and applying a calibration coefficient, while a low-pass filter is used to remove high-frequency noise; the motor speed overshoot data can be smoothed by comparing it with the motor model's predicted value and incorporating historical data to eliminate sensor drift or instantaneous interference. For example, if the original speed overshoot data of motor 1 is 1200 RPM, after correction, it may be corrected to 1180 RPM, more accurately reflecting the actual situation. Finally, based on the corrected current power supply voltage and the speed overshoot information of each motor, a preset evaluation model (e.g., a model based on fuzzy logic or a neural network) is used to calculate the urgency level of the current attitude anomaly (e.g., a score of 3, indicating moderate urgency) and the probability value of each motor speed anomaly (e.g., 0.15 for motor 1, 0.05 for motor 2, 0.08 for motor 3, and 0.06 for motor 4). The corrected data input makes the anomaly evaluation results more accurate and reliable, avoiding misjudgments caused by errors in the original data.

[0041] This invention extracts and processes raw current attitude information, decomposing complex attitude data into more physically meaningful components such as the current power supply voltage and the speed overshoot information of each motor. This makes the analysis of abnormal states more focused and effective. By correcting the extracted information, sensor noise, environmental interference, or system errors can be effectively eliminated, ensuring the accuracy and reliability of the data used for judgment. Due to the refined data processing method, subsequent determinations of the urgency of the current attitude anomaly and the probability of abnormal speeds of each motor based on the corrected data achieve higher accuracy and robustness, avoiding misjudgments caused by problems with the quality of the raw data.

[0042] In some embodiments of this application described above, the steps of determining the urgency of the current attitude anomaly and the probability of an anomaly occurring speed of each motor based on the corrected current power supply voltage and the speed overshoot information of each motor include: Using the corrected current power supply voltage and the speed overshoot information of each motor, an anomaly assessment is performed on the current attitude of the UAV to obtain an anomaly assessment value for the current attitude information. This step refers to comprehensively judging the degree of deviation and potential risks of the UAV attitude by analyzing the corrected current power supply voltage and the speed overshoot information of each motor. For example, a multi-parameter fusion algorithm can be used to weight and calculate data such as voltage fluctuations, instantaneous changes in speed, and overshoot amplitude, thereby quantifying the anomaly assessment value of the current attitude information. The anomaly assessment value reflects the severity of the UAV attitude deviating from the normal range.

[0043] The anomaly assessment value of the current posture information is matched with a preset urgency model to obtain the anomaly urgency level of the current posture. The preset urgency model is a multi-level classification model, for example, dividing the anomaly assessment value into multiple levels such as minor anomaly, moderate anomaly, and severe anomaly, with each level corresponding to a different urgency threshold. By matching the anomaly assessment value of the current posture information with this model, the anomaly urgency level of the current posture can be quickly and accurately determined.

[0044] Using the anomaly assessment values ​​of the current attitude information, the abnormal state of each motor speed is predicted, yielding the probability value of each motor speed anomaly. Specifically, by analyzing the frequency and pattern of abnormal motor speeds under specific anomaly assessment values, a prediction model is established to obtain the probability value of each motor speed anomaly. This probability value can provide a more refined decision-making basis for subsequent flight adjustment plans.

[0045] This invention first performs anomaly assessment processing on the corrected current power supply voltage and the speed overshoot information of each motor. This transforms complex raw data into a unified anomaly assessment value, thereby quantifying the degree of anomaly in the current attitude of the UAV. This allows for subsequent matching of the anomaly assessment value with a preset urgency model, directly and effectively determining the urgency level of the current attitude anomaly. Simultaneously, based on this anomaly assessment value, it predicts the abnormal state of each motor's speed, anticipating potential speed anomalies and providing corresponding probability values. This provides forward-looking data support for subsequent refined control.

[0046] In some embodiments of this application described above, the steps of determining the voltage spike characteristics of the instantaneous voltage information and the operating state characteristics of each motor based on the instantaneous voltage information and each current operating information include: The instantaneous voltage information is processed for voltage spike detection to determine the characteristics of voltage spikes. Voltage spike detection refers to real-time monitoring and analysis of the instantaneous voltage information of the power line to identify any abnormal voltage transients or spikes. This is achieved by setting voltage thresholds, monitoring voltage change rates, or employing digital signal processing techniques (such as wavelet transform and Fourier transform). The aim is to accurately capture voltage anomalies caused by motor commutation, power feedback, or other electrical interference, which are important indicators of unstable motor operation.

[0047] Using the instantaneous voltage information, state feature extraction processing is performed on each current operating information to obtain the operating state features of each motor. Specifically, the operating state features include the current speed, operating time, and operating frequency. For example, the speed data of each motor can be collected in real time by sensors, its cumulative operating time can be recorded, and its current operating frequency can be calculated. The purpose is to comprehensively understand the real-time operating status of each motor module, providing detailed data support for subsequent abnormal state identification.

[0048] This invention utilizes specialized voltage spike detection processing on instantaneous voltage information to effectively separate key voltage anomaly features from complex power signals, avoiding misinterpretation of normal voltage fluctuations as abnormal conditions. Simultaneously, by combining instantaneous voltage information with state feature extraction processing of the current operating information of each high-speed motor module, it can more comprehensively and accurately obtain the actual operating status of the motor, including core parameters such as its current speed, operating time, and operating frequency. This not only senses changes in the external power environment but also provides in-depth insights into the dynamic behavior of the motor itself, thus offering a more refined and reliable data foundation for subsequent identification of the drone's current abnormal state.

[0049] For some of the embodiments described above in this application, please refer to Figure 3 Step S300: The step of determining the flight adjustment scheme of the UAV based on the attitude anomaly information of the UAV includes: S310. The attitude anomaly information of the UAV is processed for information identification to obtain the state type and anomaly level of the attitude anomaly. Specifically, the root cause of the attitude anomaly is analyzed using multiple sensor data and algorithms, thereby classifying it into a specific state type, such as attitude anomaly caused by power feedback, attitude fluctuation caused by normal flight attitude adjustment, or attitude deviation caused by external disturbances such as gusts and collisions. At the same time, by evaluating the magnitude, duration, and potential impact on flight stability of the attitude deviation, the anomaly level of the attitude anomaly can be determined, for example, divided into different levels such as slight, moderate, or critical.

[0050] S320. Based on the state type of the attitude anomaly, determine the adjustment scheme model for the UAV. This step refers to pre-establishing or dynamically selecting corresponding control strategies or algorithm sets for different types of attitude anomalies. For example, for anomalies caused by power feedback, it may be necessary to focus on fine control of motor speed and power management; for external disturbances, a stronger anti-interference control strategy may be needed. These adjustment scheme models can be a series of preset control parameters, algorithm modules, or decision trees.

[0051] S330. Match the anomaly level of the attitude anomaly with the UAV's adjustment scheme model to obtain the UAV's flight adjustment scheme. This step refers to optimizing parameters or selecting strategies for the selected adjustment scheme model based on the determined anomaly level. For example, for the same type of attitude anomaly, if its anomaly level is high, the matched flight adjustment scheme may take more rapid and powerful corrective measures; if the anomaly level is low, it may take a gentler and more gradual adjustment approach. Through matching, it can be ensured that the final flight adjustment scheme is both targeted at the anomaly type and adaptable to the severity of the anomaly.

[0052] Specifically, consider a scenario where a drone encounters a strong crosswind during flight, causing a significant deviation in its attitude. First, the drone's current attitude information is processed. By analyzing real-time data from attitude sensors, the abnormal attitude is identified as being caused by an external disturbance, and the level of the disturbance is assessed as emergency based on the magnitude and speed of the deviation. Second, based on the identified type of external disturbance, a suitable anti-interference control model is determined from a pre-defined adjustment scheme library. This model may include a fast-response attitude-maintaining algorithm and high-gain controller parameters. Finally, the emergency level of the disturbance is matched with the anti-interference control model. Due to the emergency situation, the matching result generates a high-intensity flight adjustment scheme, such as rapidly increasing or decreasing the rotation speed of the motor modules to generate a strong counterforce, quickly counteracting the crosswind's effects and allowing the drone to rapidly return to its preset flight attitude. In this way, the drone can specifically respond to external disturbances, avoiding the problems of slow response or insufficient correction that may occur when using a general adjustment scheme.

[0053] This invention introduces detailed information identification and processing of attitude anomaly information, decomposing attitude anomalies into specific state types and quantified anomaly levels, thereby avoiding potential problems with vagueness when determining flight adjustment schemes. A clear understanding of the type and severity of the anomaly allows for more targeted adjustment schemes. Specifically, by determining the adjustment scheme model based on the state type of the attitude anomaly, it ensures that the selected control strategy fundamentally matches the nature of the anomaly, avoiding ineffective or inefficient one-size-fits-all adjustments. Furthermore, by matching the anomaly level with the adjustment scheme model, the adjustment scheme is refined, ensuring that the intensity and timing of adjustments are adapted to the severity of the anomaly. This enables UAVs to generate more accurate, efficient, and safe flight adjustment schemes when facing various attitude anomalies.

[0054] In some embodiments of this application described above, the steps of performing information identification processing on the attitude anomaly information of the UAV to obtain the attitude anomaly state type and the attitude anomaly level include: The attitude anomaly information of the UAV is processed to identify the anomaly type, thus obtaining the attitude anomaly state type. Specifically, by analyzing the characteristics of the attitude anomaly information, it is classified into predefined anomaly types. For example, the attitude anomaly information may contain components caused by power feedback, normal attitude adjustment, or external disturbances. These components can be analyzed using pattern recognition algorithms, machine learning models, or rule-based expert systems. The purpose of this step is to accurately identify the root cause or nature of the attitude deviation, such as determining whether it is mainly caused by motor speed overshoot, sudden gusts of wind, or commanded maneuvers.

[0055] Based on the state type of the attitude anomaly, anomaly severity indicators and their weights are determined. Specifically, different anomaly types may require different metrics to assess their severity. For example, if the anomaly type is identified as primarily caused by external disturbances (such as strong crosswinds), indicators such as attitude angle deviation, rate of change of angular velocity, and duration of deviation can be considered. If the anomaly is related to power feedback, indicators such as voltage spikes, motor current fluctuations, and battery temperature may be more relevant. The weights assigned to these indicators reflect their relative importance in assessing the overall severity of a specific anomaly type. These indicators and weights can be pre-configured in a database or dynamically adjusted based on historical data and the real-time operating context.

[0056] By utilizing the aforementioned anomaly level indicators and their weights, anomaly level analysis is performed on the attitude anomaly information of the UAV to obtain the anomaly level of the attitude anomaly. Specifically, the analysis process involves applying weighted indicators to the current attitude anomaly data to obtain a comprehensive anomaly score, or classifying anomalies into discrete levels (e.g., low, medium, high, and critical). The purpose of this step is to provide a quantitative or qualitative measure of the severity of the attitude anomaly, which is crucial for the formulation of subsequent flight adjustment plans.

[0057] Specifically, when a drone suddenly detects an attitude anomaly during flight, the first step is to identify the type of the received attitude anomaly information. For example, by analyzing the time-series characteristics of data such as attitude angle, angular velocity, motor speed, and power supply voltage, and combining this with a pre-defined pattern recognition algorithm, the type of the current attitude anomaly is identified as a momentary attitude deviation caused by an external disturbance, rather than a sustained attitude instability caused by a motor fault or a voltage spike caused by power feedback. Once the anomaly type is determined to be a momentary attitude deviation caused by an external disturbance, the corresponding anomaly level indicators and their weights are dynamically determined based on this type. For example, for external disturbances, indicators that might be selected include: attitude angle deviation magnitude, attitude angular velocity change rate, and deviation duration. Simultaneously, weights are assigned to these indicators; for example, the attitude angle deviation magnitude weight is 0.5, the attitude angular velocity change rate weight is 0.3, and the deviation duration weight is 0.2. Subsequently, using the determined indicators and weights, an anomaly level analysis is performed on the current attitude anomaly information. For example, if the attitude angle deviation magnitude is 5 degrees, the attitude angular velocity change rate is 10 degrees / second, and the deviation duration is 0.5 seconds, a comprehensive anomaly level score can be obtained. The score is then compared with a preset level threshold to classify the current attitude anomaly as a medium-level anomaly. In this way, it is possible to avoid misjudging instantaneous deviations caused by external disturbances as high-risk motor failures, thereby avoiding excessive or inappropriate flight adjustments and ensuring that the UAV can maintain efficient and safe operation in complex environments.

[0058] This invention, through meticulous anomaly type identification processing of UAV attitude anomaly information, can first clarify the root cause or nature of attitude anomalies. For different anomaly types, it can specifically determine the anomaly level indicators and their weights that best reflect their severity. For example, for attitude anomalies caused by external disturbances, the focus may be more on deviations in attitude angular velocity and acceleration; while for attitude anomalies caused by electrical feedback, the focus may be more on indicators such as voltage spikes and motor speed overshoot. The method of dynamically adjusting the evaluation indicators and weights according to the anomaly type makes subsequent anomaly level analysis more accurate and objective. By comprehensively using these customized indicators and weights to analyze attitude anomaly information, it can avoid misjudgments or inadequate assessments that may be caused by traditional single evaluation standards, thereby ensuring accurate quantification or classification of the severity of attitude anomalies.

[0059] In some embodiments of this application described above, the step of adjusting the current flight control scheme using the UAV's flight adjustment scheme to obtain an adjusted flight control scheme includes: Using the UAV's flight adjustment scheme, the current flight control scheme is initially adjusted to obtain a preliminary adjustment scheme. Specifically, the preliminary adjustment process refers to making initial fundamental modifications to the current flight control scheme based on the UAV's flight adjustment scheme to generate a control scheme that can initially meet the flight adjustment requirements. This preliminary adjustment scheme aims to respond quickly to flight adjustment commands, but it has not yet considered all potential dynamic electrical effects in detail.

[0060] Using the aforementioned preliminary adjustment scheme, the high-speed motor module of the UAV is simulated and adjusted to determine the energy feedback value and intensity of each motor during deceleration. This step involves simulating the motor behavior during deceleration by establishing electrical and mechanical models of the UAV motor module based on the preliminary adjustment scheme. During this simulation, the electrical energy fed back to the power system by each motor during deceleration (energy feedback value) and the instantaneous impact of this feedback energy on the power system (energy feedback intensity) can be accurately calculated. The energy feedback value can be understood as the amount of electricity provided by the motor as a generator to the power system under specific deceleration conditions, typically expressed as the integral of energy units (e.g., joules) or power units (e.g., watts) over a specific time period. The intensity of the energy feedback reflects the instantaneous amplitude and rate of change of the energy feedback, such as the instantaneous voltage increase or current change rate.

[0061] Using the energy feedback value and its intensity, the initial adjustment scheme is refined to obtain the adjusted flight control scheme. Specifically, the scheme refinement process involves using the simulated energy feedback value and its intensity to fine-tune the initial adjustment scheme. The purpose of the refinement is to effectively manage and suppress the negative impacts of energy feedback while ensuring flight control performance. This can be achieved by adjusting the motor deceleration curve, introducing energy absorption or feedback management strategies, etc., to obtain an adjusted flight control scheme that meets both flight adjustment requirements and ensures stable operation of the power system.

[0062] Specifically, the UAV is performing a flight mission involving a rapid descent followed by level flight. First, based on the current attitude information and flight adjustment plan, a preliminary flight control scheme is generated, instructing the motors to rapidly decelerate to achieve descent. Next, this preliminary adjustment scheme is used to simulate and adjust the UAV's high-speed motor module. In the simulation environment, using motor and power system models, the precise amount of electrical energy each motor will feed back to the power line during rapid deceleration (energy feedback value) and the resulting instantaneous voltage spike (energy feedback intensity) are determined. For example, simulation results show that a certain motor will generate 200W of instantaneous feedback power during deceleration, potentially causing the power supply voltage to momentarily rise above a safe threshold. Based on the simulation results, the preliminary adjustment scheme is revised. The revised scheme may adjust the motor's deceleration curve to make the deceleration process smoother, or introduce activation commands for energy absorption circuits to absorb some of the feedback energy during deceleration. Thus, the final adjusted flight control scheme, during execution, achieves both rapid descent and attitude adjustment for the UAV while effectively suppressing voltage spikes caused by energy feedback, ensuring stable operation of the power system and accurate flight control.

[0063] This invention enables rapid response to flight adjustment needs by making preliminary adjustments to the current flight control scheme. Secondly, the key lies in using this preliminary adjustment scheme to simulate and adjust the high-speed motor module, thereby accurately determining the electrical energy feedback value and intensity generated by each motor during deceleration. This simulation process can predict potential electrical shocks before actual execution. Finally, based on the predicted electrical energy feedback information, the preliminary adjustment scheme is revised, so that the final adjusted flight control scheme not only achieves the expected flight attitude adjustment but also proactively manages and mitigates the potential negative impacts of electrical energy feedback on the power system. For example, by optimizing the deceleration strategy to smooth electrical energy feedback and avoid instantaneous voltage spikes, it ensures the stability of the UAV's electrical system and the accuracy of flight control during high-speed motor module deceleration.

[0064] In some embodiments of this application described above, the step of simulating and adjusting the high-speed motor module of the UAV using the preliminary adjustment scheme to determine the energy feedback value and intensity of each motor during deceleration includes: Using the aforementioned preliminary adjustment scheme, the high-speed motor module of the UAV is simulated and adjusted to determine the instantaneous temperature, internal resistance, and state of charge (SOC) information of the energy storage battery within the UAV. Specifically, the instantaneous temperature of the energy storage battery can be acquired in real time using a temperature sensor built into the battery pack; the internal resistance can be measured and estimated online or offline using the current-voltage response method or AC impedance spectroscopy; and the SOC information can be accurately estimated using algorithms such as coulomb counting, open-circuit voltage method, or Kalman filtering. These information are key parameters for assessing the current operating state and health status of the battery.

[0065] Based on the instantaneous temperature, internal resistance, and state of charge information of the energy storage battery, the battery health, the initial value of energy feedback for each motor during deceleration, and the initial intensity of energy feedback are determined. Specifically, battery health is a comprehensive indicator reflecting the degree of performance degradation of the battery relative to its initial state, such as capacity decay and increased internal resistance. This health can be calculated or evaluated using a preset battery model, machine learning algorithms, or lookup tables, combined with the aforementioned instantaneous parameters. Simultaneously, based on the preliminary adjustment plan and the instantaneous state of the battery, the initial value of energy feedback for each motor during deceleration and the initial intensity of energy feedback can be preliminarily determined. These initial values ​​and intensities are estimates based on ideal or average battery conditions.

[0066] Using the battery health status, the initial value and intensity of the energy feedback for each motor during deceleration are adjusted to obtain the energy feedback value and intensity for each motor during deceleration. Specifically, when the battery health is low, the energy feedback value and intensity may be appropriately reduced to avoid excessive impact or overcharging of the battery; conversely, when the battery health is good and there is sufficient margin, the energy feedback value and intensity can be optimized to maximize energy recovery efficiency. Through these adjustments, more accurate and safer energy feedback values ​​and intensities for each motor during deceleration are ultimately obtained.

[0067] Specifically, the drone needs to decelerate rapidly during flight, at which point the high-speed motor module generates electrical feedback. First, sensors obtain the instantaneous temperature of the energy storage battery as 45°C, internal resistance as 50mΩ, and state of charge as 80%. Based on real-time data and a pre-set battery health assessment model, the current battery health is determined to be 75%. Simultaneously, according to the preliminary adjustment plan, it is estimated that under ideal conditions, each motor should generate an initial electrical feedback of 10A and an initial intensity of 12V during deceleration. However, considering that the current battery health is 75% (lower than 100% for a new battery), this health level is used to correct the initial feedback value and intensity. For example, a correction factor might be set, such that when the health is below 80%, for every 5% decrease in health, the feedback value and intensity decrease by 5%. In this embodiment, the health is 75%, lower than 80%, therefore the feedback value and intensity will decrease by 5% accordingly. Ultimately, the adjusted electrical feedback value might be 9.5A, and the electrical feedback intensity would be 11.4V. In this way, the energy feedback process can effectively recover energy while avoiding excessive burden on the battery in its current state, thereby ensuring battery safety and extending its service life.

[0068] This invention incorporates instantaneous temperature, internal resistance, and state of charge information of the energy storage battery, and determines the battery's health, thereby enabling fine-tuning of the energy feedback value and intensity. Since the actual operating state and health of the energy storage battery directly affect its charge-discharge performance and lifespan, estimating energy feedback solely based on motor operating parameters cannot adequately adapt to real-time battery changes. By monitoring key battery parameters in real time and converting them into battery health information, the energy feedback strategy can dynamically adapt to the battery's actual capacity and optimal operating state. Therefore, when the motor decelerates and generates energy feedback, the intensity and value of the feedback can be adjusted according to the battery's actual health condition, avoiding risks such as overcharging and overheating due to poor battery condition. Simultaneously, it ensures that energy can be recovered to the maximum extent when the battery is in good health, improving the overall system's energy utilization efficiency and safety.

[0069] Based on any of the above embodiments, a method for controlling the speed of a high-speed motor module in a UAV is provided. Figure 4 The present invention also provides a high-speed motor module speed control system for unmanned aerial vehicles (UAVs), which includes an information acquisition module 410, an information identification module 420, a scheme determination module 430, a scheme adjustment module 440, and a flight control module 450.

[0070] The information acquisition module 410 is used to acquire the current attitude information of the UAV during flight, the instantaneous voltage information of the power line, the current operating information of each high-speed motor module in the UAV, and the current flight control scheme of the UAV.

[0071] The information recognition module 420 is used to identify and process the current abnormal state of the UAV using the current attitude information, instantaneous voltage information and each current operation information to obtain the attitude abnormal information of the UAV; wherein, the attitude abnormal information includes attitude abnormal information caused by power feedback, normal attitude adjustment or external disturbance.

[0072] The scheme determination module 430 is used to determine the flight adjustment scheme of the UAV based on the attitude anomaly information of the UAV.

[0073] The scheme adjustment module 440 is used to adjust the current flight control scheme using the flight adjustment scheme of the UAV, so as to obtain the adjusted flight control scheme.

[0074] The flight control module 450 is used to adjust the high-speed motor module of the UAV using the adjusted flight control scheme in order to complete the flight control of the UAV.

[0075] In this embodiment, the information acquisition module 410 comprehensively collects the UAV's operational data, the information identification module 420 intelligently analyzes and distinguishes the sources of anomalies, and then the scheme determination module 430 generates targeted adjustment strategies. Subsequently, the scheme adjustment module 440 optimizes the existing flight control scheme, and finally the flight control module 450 precisely executes the adjustment commands, thereby effectively avoiding motor speed overshoot and vicious oscillations caused by power feedback, normal attitude adjustment, or external disturbances, significantly improving the flight stability and safety of the UAV.

[0076] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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. Such 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, and they should all be covered within the scope of the present invention specification.

Claims

1. A method for controlling the rotational speed of a high-speed motor module in a drone, characterized in that, include: Acquire the current attitude information of the UAV during flight, the instantaneous voltage information of the power line, the current operating information of each high-speed motor module in the UAV, and the current flight control scheme of the UAV; Using the current attitude information, instantaneous voltage information, and each current operating information, the current abnormal state of the UAV is identified and processed to obtain the attitude abnormality information of the UAV; wherein, the attitude abnormality information includes attitude abnormality information generated by power feedback, normal attitude adjustment, or external disturbance. Based on the abnormal attitude information of the UAV, a flight adjustment plan for the UAV is determined; Using the flight adjustment scheme of the UAV, the current flight control scheme is adjusted to obtain the adjusted flight control scheme; The adjusted flight control scheme is used to modify the high-speed motor module of the UAV in order to achieve flight control of the UAV.

2. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 1, characterized in that, The steps for identifying and processing the current abnormal state of the UAV using the current attitude information, instantaneous voltage information, and each current operational information to obtain the UAV's attitude abnormality information include: Based on the current attitude information, determine the urgency of the current attitude anomaly and the probability of each motor speed anomaly. Based on the instantaneous voltage information and each current operating information, the voltage spike characteristics of the instantaneous voltage information and the operating state characteristics of each motor are determined; wherein, the operating state characteristics include the current speed, operating time and operating frequency; By utilizing the urgency level, probability value, voltage spike characteristics, and operating status characteristics of each motor in the current attitude, the current abnormal state of the UAV is identified and processed to obtain the attitude abnormality information of the UAV.

3. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 2, characterized in that, Based on the current attitude information, the steps for determining the urgency level of the current attitude anomaly and the probability value of each motor speed anomaly include: The current attitude information is processed to extract the current power supply voltage and the speed overshoot information of each motor. The current power supply voltage and the speed overshoot information of each motor are corrected to obtain the corrected current power supply voltage and the speed overshoot information of each motor. Based on the corrected current power supply voltage and the speed overshoot information of each motor, the urgency of the current attitude abnormality and the probability value of each motor speed abnormality are determined.

4. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 3, characterized in that, Based on the corrected current power supply voltage and the speed overshoot information of each motor, the steps for determining the urgency of the current attitude anomaly and the probability of each motor speed anomaly include: Using the corrected current power supply voltage and the speed overshoot information of each motor, the current attitude of the UAV is subjected to anomaly assessment processing to obtain the anomaly assessment value of the current attitude information. The abnormal assessment value of the current posture information is matched with a preset urgency level model to obtain the abnormal urgency level of the current posture. Using the anomaly assessment value of the current attitude information, the abnormal state of each motor speed is predicted, and the probability value of each motor speed occurring abnormally is obtained.

5. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 3, characterized in that, Based on the instantaneous voltage information and each current operating information, the steps for determining the voltage spike characteristics of the instantaneous voltage information and the operating state characteristics of each motor include: The instantaneous voltage information is subjected to voltage spike detection processing to determine the voltage spike characteristics of the instantaneous voltage information; Using the instantaneous voltage information, state feature extraction processing is performed on each current operating information to obtain the operating state features of each motor.

6. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 1, characterized in that, Based on the abnormal attitude information of the UAV, the steps for determining the flight adjustment scheme of the UAV include: The attitude anomaly information of the UAV is processed for information identification to obtain the attitude anomaly state type and attitude anomaly level; Based on the type of attitude anomaly, an adjustment scheme model for the UAV is determined; The abnormality level of the attitude anomaly is matched with the UAV's adjustment scheme model to obtain the UAV's flight adjustment scheme.

7. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 6, characterized in that, The steps for performing information identification processing on the attitude anomaly information of the UAV to obtain the attitude anomaly state type and attitude anomaly level include: The attitude anomaly information of the UAV is processed to identify the anomaly type, and the attitude anomaly state type is obtained; Based on the state type of the posture anomaly, determine the anomaly level index and the weight of the anomaly level index. By using the aforementioned anomaly level index and its weight, anomaly level analysis is performed on the attitude anomaly information of the UAV to obtain the anomaly level of the attitude anomaly.

8. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 1, characterized in that, The steps for adjusting the current flight control scheme using the UAV's flight adjustment scheme to obtain the adjusted flight control scheme include: Using the flight adjustment scheme of the UAV, the current flight control scheme is initially adjusted to obtain a preliminary adjustment scheme; Using the aforementioned preliminary adjustment scheme, the high-speed motor module of the UAV is simulated and adjusted to determine the energy feedback value and intensity of each motor during deceleration. Using the energy feedback value and the intensity of the energy feedback, the preliminary adjustment scheme is modified to obtain the adjusted flight control scheme.

9. The method for controlling the rotational speed of a high-speed motor module in a UAV according to claim 8, characterized in that, Using the aforementioned preliminary adjustment scheme, the steps for simulating and adjusting the high-speed motor module of the UAV to determine the energy feedback value and intensity of each motor during deceleration include: Using the aforementioned preliminary adjustment scheme, the high-speed motor module of the UAV is simulated and adjusted to determine the instantaneous temperature, internal resistance, and state of charge information of the energy storage battery in the UAV. Based on the instantaneous temperature, internal resistance, and state of charge information of the energy storage battery, the battery health, the initial value of energy feedback for each motor during deceleration, and the initial intensity of energy feedback are determined. Using the battery health status, the initial value and initial intensity of the energy feedback for each motor during deceleration are adjusted to obtain the energy feedback value and intensity for each motor during deceleration.

10. A high-speed motor module speed control system for unmanned aerial vehicles (UAVs), characterized in that, The system includes: The information acquisition module is used to acquire the current attitude information of the UAV during flight, the instantaneous voltage information of the power line, the current operating information of each high-speed motor module in the UAV, and the current flight control scheme of the UAV. The information recognition module is used to identify and process the current abnormal state of the UAV using the current attitude information, instantaneous voltage information and each current operation information to obtain the attitude abnormal information of the UAV; wherein, the attitude abnormal information includes attitude abnormal information caused by power feedback, normal attitude adjustment or external disturbance. The scheme determination module is used to determine the flight adjustment scheme of the UAV based on the attitude anomaly information of the UAV; The scheme adjustment module is used to adjust the current flight control scheme using the flight adjustment scheme of the UAV, so as to obtain the adjusted flight control scheme; The flight control module is used to adjust the high-speed motor module of the UAV using the adjusted flight control scheme in order to complete the flight control of the UAV.

Images