A control method, device and equipment of an electric propulsion system with a propeller and a storage medium

Abstract

The application discloses a control method, device and equipment of an electric propulsion system with a propeller and a computer readable storage medium, and establishes a system digital model to obtain driver surface airflow data and a driver surface convection heat transfer coefficient through a propeller digital model, propeller rotating speed, air physical property parameters, aircraft speed, driving system structure and driver heat transfer surface characteristics; determines driver operation loss heat according to the driver operation data and pre-stored hardware parameter data; determines driver temperature data according to the driver operation loss heat, the driver surface airflow velocity data, the driver surface convection heat transfer coefficient, the environmental temperature data and a preset driver thermal resistance network model; and controls the unmanned aerial vehicle motor driver according to the driver temperature data. The application calculates the driver surface airflow velocity and the convection heat transfer coefficient, and then obtains the temperature data of the driver, so that temperature judgment is avoided from being inaccurate, and the unmanned aerial vehicle is prevented from losing control.

Description

Technical Field

[0001] This invention relates to the field of motor control system monitoring, and in particular to a control method, apparatus, equipment, and computer-readable storage medium for an electric propulsion system with a propeller. Background Technology

[0002] Electric aircraft use batteries, electric drive systems, and propellers to provide propulsion. The electric drive system includes a motor and a drive unit. A typical UAV electric drive system structure is as follows: Figure 2 As shown, the propeller rotation generates a backward airflow, which in turn cools the motor and the driver. For the driver, the speed of the external airflow directly affects the cooling effect of the driver and the heat dissipation of the power module, which in turn directly affects the output power capability of the driver, including the output power and the output duration. Typically, a temperature sensor is installed on the driver power board to monitor the driver temperature. When the driver temperature is detected to be too high, it will be derated in time to ensure the reliable operation of the driver and the system.

[0003] However, during the flight of an electric drone, the failure of the driver system's measuring devices (such as temperature sensors) will cause the control system to misjudge the drone's current flight status, resulting in improper control. Therefore, how to provide a highly reliable drone motor driver monitoring and control method is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide a control method, apparatus, device, and computer-readable storage medium for an electric propulsion system with a propeller, in order to solve the problem in the prior art that the temperature measurement of the motor driver may be inaccurate, resulting in improper control.

[0005] To solve the above-mentioned technical problems, the present invention provides a control method for an electric propulsion system with a propeller, comprising:

[0006] Acquire propeller speed data, UAV speed data, ambient temperature data, and drive operation data;

[0007] The propeller rotation speed data is input into a preset propeller system digital model to obtain the propeller airflow velocity.

[0008] The airflow velocity data on the surface of the actuator is determined based on the propeller airflow velocity and the UAV speed.

[0009] The convective heat transfer coefficient of the driver surface is determined based on the airflow velocity data on the driver surface, the pre-stored air property parameters, and the preset driver heat transfer surface characteristic model.

[0010] The heat loss during driver operation is determined based on the driver's operating data and pre-stored hardware parameter data.

[0011] The driver temperature data is determined based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and the preset driver thermal resistance network model.

[0012] The drone motor driver is controlled based on the driver temperature data.

[0013] Optionally, in the control method of the propeller-driven electric propulsion system, before controlling the UAV motor driver based on the driver temperature data, the method further includes:

[0014] Acquire sensor temperature data;

[0015] Accordingly, controlling the UAV motor driver based on the driver temperature data includes:

[0016] The drone motor driver is controlled based on the driver temperature data and the sensor temperature data.

[0017] Optionally, in the control method of the propeller-driven electric propulsion system, controlling the UAV motor driver based on the driver temperature data and the sensor temperature data includes:

[0018] Determine the difference between the driver temperature data and the sensor temperature data;

[0019] Determine the relationship between the difference and the lower and higher threshold values, respectively;

[0020] When the difference is greater than the low-order difference and less than the high-order difference, the drone motor driver is controlled to enter the derating operation mode;

[0021] When the difference is greater than the high-level difference, the drone motor driver is controlled to enter limp mode and land and stop.

[0022] Optionally, in the control method of the propeller-driven electric propulsion system, at least one of the convective heat transfer coefficient of the drive surface, the heat loss during drive operation, and the drive temperature data is data obtained through a cloud server or a local multi-core processor.

[0023] A control device for an electric propulsion system with a propeller, comprising:

[0024] The acquisition module is used to acquire propeller speed data, UAV speed data, ambient temperature data, and drive operation data.

[0025] The propeller module is used to input the propeller rotation speed data into a preset propeller system digital model to obtain the propeller airflow velocity.

[0026] An airflow velocity module is used to determine the airflow velocity data on the surface of the actuator based on the airflow velocity of the propeller and the speed of the UAV.

[0027] The heat transfer coefficient determination module is used to determine the convective heat transfer coefficient of the driver surface based on the airflow velocity data on the driver surface, pre-stored air property parameters, and a preset driver heat transfer surface characteristic model.

[0028] A heat loss module is used to determine the heat loss of the driver during operation based on the driver's operating data and pre-stored hardware parameter data.

[0029] The temperature calculation module is used to determine the driver temperature data based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and a preset driver thermal resistance network model.

[0030] The control module is used to control the UAV motor driver based on the driver temperature data.

[0031] Optionally, in the control device of the aforementioned propeller-equipped electric propulsion system, the control module further includes:

[0032] The sensor temperature unit is used to acquire sensor temperature data;

[0033] The comparison control unit is used to control the UAV motor driver based on the driver temperature data and the sensor temperature data.

[0034] Optionally, in the control device of the aforementioned propeller-equipped electric propulsion system, the control module further includes:

[0035] The difference unit is used to determine the difference between the driver temperature data and the sensor temperature data;

[0036] A threshold determination unit is used to determine the relationship between the difference and the lower threshold and the higher threshold, respectively.

[0037] The derating unit is used to control the UAV motor driver to enter the derating operation mode when the difference is greater than the low-order difference and less than the high-order difference.

[0038] The limp unit is used to control the UAV motor driver to enter limp mode and land and stop when the difference is greater than the high-level difference.

[0039] A control device for an electric propulsion system with a propeller, comprising:

[0040] Memory, used to store computer programs;

[0041] A processor, used to execute the computer program to implement the steps of the control method for an electric propulsion system with a propeller as described above.

[0042] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of a control method for an electric propulsion system with a propeller as described above.

[0043] The control method for an electric propulsion system with a propeller provided by this invention involves acquiring propeller rotation speed data, UAV speed data, ambient temperature data, and actuator operating data; inputting the propeller rotation speed data into a preset propeller system digital model to obtain the propeller airflow velocity; determining the actuator surface airflow velocity data based on the propeller airflow velocity and the UAV speed; determining the actuator surface convective heat transfer coefficient based on the actuator surface airflow velocity data, pre-stored air property parameters, and a preset actuator heat transfer surface characteristic model; determining the actuator operating heat loss based on the actuator operating data and pre-stored hardware parameter data; determining the actuator temperature data based on the actuator operating heat loss, the actuator surface airflow velocity data, the actuator surface convective heat transfer coefficient, the ambient temperature data, and a preset actuator thermal resistance network model; and controlling the UAV motor actuator based on the actuator temperature data.

[0044] This invention calculates the fluid velocity (i.e., airflow velocity data) and convective heat transfer coefficient on the actuator surface without adding new sensors. Combining this with the actuator's operating parameters and hardware parameters, it calculates the actuator's heat generation (i.e., heat loss during operation) and thermal resistance network model. Adding the ambient temperature yields the actuator's temperature data. This method avoids inaccurate temperature judgments that could lead to loss of control of the UAV. This invention also provides a control device, equipment, and computer-readable storage medium for a propeller-driven electric propulsion system with the aforementioned advantages. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 A flowchart illustrating a specific embodiment of the control method for an electric propulsion system with a propeller provided by the present invention;

[0047] Figure 2 This is a schematic diagram illustrating the connection relationship between a drone motor driver and external devices in the prior art.

[0048] Figure 3 A flowchart illustrating another specific embodiment of the control method for an electric propulsion system with a propeller provided by the present invention;

[0049] Figure 4 A flowchart illustrating another specific embodiment of the control method for an electric propulsion system with a propeller provided by the present invention;

[0050] Figure 5 This is a schematic diagram of a specific embodiment of the control device for an electric propulsion system with a propeller provided by the present invention. Detailed Implementation

[0051] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] The core of this invention is to provide a control method for an electric propulsion system with a propeller, and a flowchart of one specific embodiment is shown below. Figure 1 As shown, this is referred to as Specific Implementation Method One, which includes:

[0053] S101: Acquires propeller speed data, UAV speed data, ambient temperature data, and drive operation data.

[0054] S102: Input the propeller rotation speed data into the preset propeller system digital model to obtain the propeller airflow velocity.

[0055] The digital model of the propeller system can be a preset CFD model (computational fluid dynamics model) or a simple rotational speed-airflow velocity correspondence model. The choice can be made according to actual needs, and this invention does not limit it.

[0056] S103: Determine the airflow velocity data on the surface of the actuator based on the propeller airflow velocity and the UAV speed.

[0057] In one specific implementation, the sum of the propeller airflow velocity and the UAV speed is determined as the airflow velocity on the actuator surface.

[0058] S104: Determine the convective heat transfer coefficient of the driver surface based on the airflow velocity data on the driver surface, the pre-stored air property parameters, and the preset driver heat transfer surface characteristic model.

[0059] The air physical properties include the ambient gas thermal conductivity and the ambient gas dynamic viscosity coefficient.

[0060] Of course, the convective heat transfer coefficient of the driver surface can also be empirical data determined based on some of the above data, and the specific method of obtaining it is not limited in this invention.

[0061] S105: Determine the heat loss of the driver during operation based on the driver operation data and pre-stored hardware parameter data.

[0062] In addition, the driver operating data includes driver operating current data and driver operating voltage data; the hardware parameter data includes driver structural parameters, driver power parameters, driver device loss model and control switching frequency.

[0063] S106: Determine the driver temperature data based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and the preset driver thermal resistance network model.

[0064] Once the thermal resistance network model of the driver is known, it can be determined how much heat from the driver's power board can be transferred to the surface of the driver. This can then be combined with the convective heat transfer formula (1) for the surface of the driver housing.

[0065] Q=A*α*(T W -T air (1)

[0066] The actual heat Q that can be dissipated through air convection can then be obtained, where α is the convective heat transfer coefficient of the actuator surface, A is the characteristic dimension data of the airflow contact surface, and T... W T is the surface temperature of the driver housing. air The ambient gas temperature (of course, since drones generally fly at high altitudes, the ambient gas is usually air).

[0067] S107: Control the UAV motor driver based on the driver temperature data.

[0068] In one specific implementation, at least one of the following is obtained through a cloud server or a local multi-core processor: the convective heat transfer coefficient of the driver surface, the heat loss during driver operation, the thermal resistance network model of the driver, and the driver temperature data.

[0069] In other words, the control method for an electric propulsion system with a propeller provided by this invention, after collecting relevant data, can process the data using a multi-core processor on the UAV itself or send it to a cloud server for processing, and then return the processed results to the UAV. The multiple cores of the multi-core processor each perform different functions, such as a communication core for external communication, a monitor for monitoring various data in the acquisition circuit, and a control core for controlling the motor driver. Using a multi-core processor can greatly improve the system's operational stability.

[0070] The control method for an electric propulsion system with a propeller provided by this invention involves acquiring propeller rotation speed data, UAV speed data, ambient temperature data, and actuator operating data; inputting the propeller rotation speed data into a preset propeller system digital model to obtain the propeller airflow velocity; determining the actuator surface airflow velocity data based on the propeller airflow velocity and the UAV speed; determining the actuator surface convective heat transfer coefficient based on the actuator surface airflow velocity data, pre-stored air property parameters, and a preset actuator heat transfer surface characteristic model; determining the actuator operating heat loss based on the actuator operating data and pre-stored hardware parameter data; determining the actuator temperature data based on the actuator operating heat loss, the actuator surface airflow velocity data, the actuator surface convective heat transfer coefficient, the ambient temperature data, and a preset actuator thermal resistance network model; and controlling the UAV motor actuator based on the actuator temperature data. This invention calculates the fluid velocity and convective heat transfer coefficient on the surface of the actuator without adding new sensors. It then calculates the heat generated by the actuator (i.e., the heat loss during operation) and the thermal resistance network model of the actuator by combining the parameters of the actuator during operation and the hardware parameters of the actuator itself. Adding the ambient temperature, the temperature data of the actuator can be obtained. The temperature data of the actuator calculated by the above method avoids the possibility of inaccurate temperature judgment and loss of control of the drone.

[0071] Based on Implementation Method 1, further improvements are made to enhance the operational stability of the UAV motor, resulting in Implementation Method 2, the flowchart of which is shown below. Figure 3 As shown, it includes:

[0072] S201: Acquire propeller speed data, UAV speed data, ambient temperature data, and drive operation data.

[0073] S202: Input the propeller rotation speed data into the preset propeller system digital model to obtain the propeller airflow velocity.

[0074] S203: Determine the airflow velocity data on the surface of the actuator based on the propeller airflow velocity and the UAV speed.

[0075] S204: Determine the convective heat transfer coefficient of the driver surface based on the airflow velocity data on the driver surface, the pre-stored air property parameters, and the preset driver heat transfer surface characteristic model.

[0076] S205: Determine the heat loss of the driver during operation based on the driver operation data and pre-stored hardware parameter data.

[0077] S206: Determine the driver temperature data based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and the preset driver thermal resistance network model.

[0078] S207: Acquire sensor temperature data.

[0079] Of course, theoretically, step S207 only needs to be done before step S208, and there is no strict order relationship with other steps. It can be adjusted according to the actual situation.

[0080] S208: Control the UAV motor driver based on the driver temperature data and the sensor temperature data.

[0081] The electric drive system is a core component of electric aircraft, classified as a Class A component in electric aircraft systems according to reliability standards, requiring extremely high reliability and failure rate. To rigorously achieve this, in addition to significantly improving the reliability and failure rate of individual components during the design of the motor and drive, it is crucial to monitor the system's operational information during operation by measuring key parameters such as current, voltage, speed, and temperature. The measurement system comprises various measurement units, and ensuring the reliability of each unit is also a key technology in electric aircraft drive systems.

[0082] This specific implementation method targets electric unmanned aerial vehicles (UAVs), proposing a method for calculating the temperature of the UAV motor driver based on a digital model of the propeller system, a digital model of the driver, and operating environment parameters. It also proposes comparing the calculated results with measurement results to determine the system's operating status. If the diagnostic measurement results are abnormal—that is, if the difference between the sensor-measured temperature data and the driver temperature data calculated from the data is too large—appropriate power reduction measures or emergency shutdown can be taken to prevent further risk escalation.

[0083] Based on Implementation Method 1, the control method of the UAV motor is further refined to obtain Implementation Method 3, the flowchart of which is shown below. Figure 4 As shown, it includes:

[0084] S301: Acquires propeller speed data, UAV speed data, ambient temperature data, and drive operation data.

[0085] S302: Input the propeller rotation speed data into the preset propeller system digital model to obtain the propeller airflow velocity.

[0086] S303: Determine the airflow velocity data on the surface of the actuator based on the propeller airflow velocity and the UAV speed.

[0087] S304: Determine the convective heat transfer coefficient of the driver surface based on the airflow velocity data on the driver surface, the pre-stored air property parameters, and the preset driver heat transfer surface characteristic model.

[0088] S305: Determine the heat loss of the driver during operation based on the driver operation data and pre-stored hardware parameter data.

[0089] S306: Determine the driver temperature data based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and the preset driver thermal resistance network model.

[0090] S307: Acquire sensor temperature data.

[0091] S308: Determine the difference between the driver temperature data and the sensor temperature data.

[0092] S309: Determine the relationship between the difference and the lower and higher threshold values, respectively.

[0093] S310: When the difference is greater than the low-order difference and less than the high-order difference, control the UAV motor driver to enter the derating operation mode;

[0094] S311: When the difference is greater than the high-level difference, control the UAV motor driver to enter limp mode and land and stop.

[0095] Of course, the above steps S311 and S310 are only the processing methods for two different situations after the judgment in step S309, and do not involve the order of priority.

[0096] In this specific embodiment, based on Specific Embodiment Two, the situation where there is a large difference between the driver temperature data and the sensor temperature data is further divided into two types. Specifically, firstly, when there is a difference between the two but within a certain range (i.e., the situation corresponding to step S310), the derating mode is entered to avoid increasing power and amplifying the risk of harm. Secondly, when the difference between the two is too large (the situation corresponding to S311), the probability of an accident is extremely high. Therefore, the limp mode is immediately entered, and the drone begins to land and stop so that staff can inspect it. This specific embodiment provides a method for graded handling of potential faults, reducing the possibility of high-altitude accidents involving drones.

[0097] The control device for the propeller-driven electric propulsion system provided in the embodiments of the present invention will be described below. The control device for the propeller-driven electric propulsion system described below can be referred to in correspondence with the control method for the propeller-driven electric propulsion system described above.

[0098] Figure 5 The structural block diagram of the control device for the propeller-driven electric propulsion system provided in this embodiment of the invention is referred to as Specific Embodiment Four, and is described in reference to... Figure 5 The control device for an electric propulsion system with a propeller may include:

[0099] The acquisition module 100 is used to acquire propeller speed data, UAV speed data, ambient temperature data, and drive operation data.

[0100] The propeller module 200 is used to input the propeller rotation speed data into a preset propeller system digital model to obtain the propeller airflow velocity.

[0101] The airflow velocity module 300 is used to determine the airflow velocity data on the surface of the actuator based on the airflow velocity of the propeller and the speed of the UAV.

[0102] The heat transfer coefficient determination module 400 is used to determine the convective heat transfer coefficient of the driver surface based on the airflow velocity data on the driver surface, the pre-stored air property parameters and the preset driver heat transfer surface characteristic model.

[0103] The heat loss module 500 is used to determine the heat loss of the driver during operation based on the driver operation data and pre-stored hardware parameter data.

[0104] The temperature calculation module 600 is used to determine the driver temperature data based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and a preset driver thermal resistance network model.

[0105] The control module 700 is used to control the UAV motor driver based on the driver temperature data.

[0106] In a preferred embodiment, the control module 700 further includes:

[0107] The sensor temperature unit is used to acquire sensor temperature data;

[0108] The comparison control unit is used to control the UAV motor driver based on the driver temperature data and the sensor temperature data.

[0109] In a preferred embodiment, the control module 700 includes:

[0110] The difference unit is used to determine the difference between the driver temperature data and the sensor temperature data;

[0111] A threshold determination unit is used to determine the relationship between the difference and the lower threshold and the higher threshold, respectively.

[0112] The derating unit is used to control the UAV motor driver to enter the derating operation mode when the difference is greater than the low-order difference and less than the high-order difference.

[0113] The limp unit is used to control the UAV motor driver to enter limp mode and land and stop when the difference is greater than the high-level difference.

[0114] The control method for an electric propulsion system with a propeller provided by this invention includes: an acquisition module 100 for acquiring propeller speed data, UAV speed data, ambient temperature data, and driver operation data; a propeller module 200 for inputting the propeller speed data into a preset propeller system digital model to obtain the propeller airflow velocity; an airflow velocity module 300 for determining the airflow velocity data on the driver surface based on the propeller airflow velocity and the UAV speed; a heat transfer coefficient determination module 400 for determining the convective heat transfer coefficient of the driver surface based on the driver surface airflow velocity data, pre-stored air property parameters, and a preset driver heat transfer surface characteristic model; a heat loss module 500 for determining the heat loss during driver operation based on the driver operation data and pre-stored hardware parameter data; a temperature calculation module 600 for determining the driver temperature data based on the driver operation heat loss, the driver surface airflow velocity data, the driver surface convective heat transfer coefficient, the ambient temperature data, and a preset driver thermal resistance network model; and a control module 700 for controlling the UAV motor driver based on the driver temperature data. This invention calculates the convective heat transfer coefficient of the driver surface without adding new sensors. Combining the driver's operating parameters and hardware parameters with the driver's operating data, it calculates the driver's heat generation (i.e., the heat loss during driver operation) and the driver's thermal resistance network model. It calculates the heat loss from the power card to the driver surface, as well as the heat loss due to the high-speed gas flowing over the surface. The remaining heat is then added to the ambient temperature to obtain the driver's temperature data. The driver temperature data calculated by the above method has high accuracy and good operational stability, avoiding inaccurate temperature judgments that could cause the UAV to lose control.

[0115] The control device for the propeller-driven electric propulsion system in this embodiment is used to implement the aforementioned control method for the propeller-driven electric propulsion system. Therefore, the specific implementation of the control device for the propeller-driven electric propulsion system can be found in the embodiment section of the control method for the propeller-driven electric propulsion system described above. For example, the acquisition module 100, propeller module 200, airflow velocity module 300, heat transfer coefficient determination module 400, heat loss module 500, temperature calculation module 600, and control module 700 are respectively used to implement steps S101, S102, S103, S104, S105, S106, and S107 in the aforementioned control method for the propeller-driven electric propulsion system. Therefore, its specific implementation can be referred to the description of the corresponding embodiments, which will not be repeated here.

[0116] A control device for an electric propulsion system with a propeller, comprising:

[0117] Memory, used to store computer programs;

[0118] A processor is configured to execute the computer program to implement the steps of the control method for a propeller-driven electric propulsion system as described above. The control method for a propeller-driven electric propulsion system provided by this invention involves: acquiring propeller speed data, UAV speed data, ambient temperature data, and driver operation data; inputting the propeller speed data into a preset propeller system digital model to obtain the propeller airflow velocity; determining the driver surface airflow velocity data based on the propeller airflow velocity and the UAV speed; determining the driver surface convective heat transfer coefficient based on the driver surface airflow velocity data, pre-stored air property parameters, and a preset driver heat transfer surface characteristic model; determining the driver operation heat loss based on the driver operation data and pre-stored hardware parameter data; determining the driver temperature data based on the driver operation heat loss, the driver surface airflow velocity data, the driver surface convective heat transfer coefficient, the ambient temperature data, and a preset driver thermal resistance network model; and controlling the UAV motor driver based on the driver temperature data. This invention calculates the fluid velocity and surface convective heat transfer coefficient on the actuator surface without adding new sensors. It then combines the actuator's operating parameters and hardware parameters to calculate the actuator's heat generation (i.e., the heat loss during actuator operation) and the actuator's thermal resistance network model. Adding the ambient temperature yields the actuator's temperature data. The actuator temperature data calculated using the above method avoids inaccurate temperature judgments that could cause the drone to lose control.

[0119] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the control method for a propeller-driven electric propulsion system as described above. The control method for a propeller-driven electric propulsion system provided by this invention involves: acquiring propeller rotation speed data, UAV speed data, ambient temperature data, and actuator operating data; inputting the propeller rotation speed data into a preset propeller system digital model to obtain the propeller airflow velocity; determining actuator surface airflow velocity data based on the propeller airflow velocity and the UAV speed; determining the actuator surface convective heat transfer coefficient based on the actuator surface airflow velocity data, pre-stored air property parameters, and a preset actuator heat transfer surface characteristic model; determining actuator operating heat loss based on the actuator operating data and pre-stored hardware parameter data; determining actuator temperature data based on the actuator operating heat loss, the actuator surface airflow velocity data, the actuator surface convective heat transfer coefficient, the ambient temperature data, and a preset actuator thermal resistance network model; and controlling the UAV motor actuator based on the actuator temperature data. This invention calculates the convective heat transfer coefficient of the driver surface without adding new sensors. It combines the driver's operating parameters and hardware parameters to calculate the driver's heat generation (i.e., the heat loss during driver operation) and the driver's thermal resistance network model. Adding the ambient temperature, the driver's temperature data can be obtained. The driver temperature data calculated by the above method can avoid inaccurate temperature judgment and the possibility of the UAV losing control.

[0120] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0121] It should be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0122] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0123] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0124] The control method, apparatus, device, and computer-readable storage medium for the propeller-driven electric propulsion system provided by this invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of this invention. It should be noted that those skilled in the art can make various improvements and modifications to this invention without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this invention.

Claims

1. A control method for an electric propulsion system with a propeller, characterized in that, include: Acquire propeller speed data, UAV speed data, ambient temperature data, and drive operation data; The driver operating data includes driver operating current data and driver operating voltage data; The propeller rotation speed data is input into a preset propeller system digital model to obtain the propeller airflow velocity. The sum of the propeller airflow velocity and the UAV speed is determined as the airflow velocity data on the actuator surface; Based on the airflow velocity data on the actuator surface, pre-stored air property parameters, and a preset actuator heat transfer surface characteristic model, the convective heat transfer coefficient of the actuator surface is determined; the air property parameters include the ambient gas thermal conductivity and the ambient gas dynamic viscosity coefficient. The heat loss of the driver during operation is determined based on the driver's operating data and pre-stored hardware parameter data; the hardware parameter data includes driver structural parameters, driver power parameters, driver device loss model, and control switching frequency. The driver temperature data is determined based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and the preset driver thermal resistance network model. The drone motor driver is controlled based on the driver temperature data.

2. The control method for an electric propulsion system with a propeller as described in claim 1, characterized in that, Before controlling the drone motor driver based on the driver temperature data, the method further includes: Acquire sensor temperature data; Accordingly, controlling the UAV motor driver based on the driver temperature data includes: The drone motor driver is controlled based on the driver temperature data and the sensor temperature data.

3. The control method for an electric propulsion system with a propeller as described in claim 2, characterized in that, The step of controlling the UAV motor driver based on the driver temperature data and the sensor temperature data includes: Determine the difference between the driver temperature data and the sensor temperature data; Determine the relationship between the difference and the lower and higher threshold values, respectively; When the difference is greater than the low threshold and less than the high threshold, the drone motor driver is controlled to enter the derated operation mode. When the difference is greater than the high threshold, the drone motor driver is controlled to enter limp mode and land and stop.

4. The control method for an electric propulsion system with a propeller as described in claim 1, characterized in that, At least one of the following data is obtained through a cloud server or a local multi-core processor: the convective heat transfer coefficient of the driver surface, the heat loss during driver operation, and the driver temperature data.

5. A control device for an electric propulsion system with a propeller, characterized in that, include: The acquisition module is used to acquire propeller speed data, UAV speed data, ambient temperature data, and drive operation data. The driver operating data includes driver operating current data and driver operating voltage data; The propeller module is used to input the propeller rotation speed data into a preset propeller system digital model to obtain the propeller airflow velocity. An airflow velocity module is used to determine the sum of the propeller airflow velocity and the UAV speed as the airflow velocity data on the actuator surface; The heat transfer coefficient determination module is used to determine the convective heat transfer coefficient of the driver surface based on the airflow velocity data on the driver surface, pre-stored air property parameters, and a preset driver heat transfer surface characteristic model; the air property parameters include the ambient gas thermal conductivity and the ambient gas dynamic viscosity coefficient. The heat loss module is used to determine the heat loss of the driver during operation based on the driver's operating data and pre-stored hardware parameter data; the hardware parameter data includes driver structural parameters, driver power parameters, driver device loss model, and control switching frequency. The temperature calculation module is used to determine the driver temperature data based on the heat loss during driver operation, the airflow velocity data on the driver surface, the convective heat transfer coefficient on the driver surface, the ambient temperature data, and a preset driver thermal resistance network model. The control module is used to control the UAV motor driver based on the driver temperature data.

6. The control device for an electric propulsion system with a propeller as described in claim 5, characterized in that, The control module further includes: The sensor temperature unit is used to acquire sensor temperature data; The comparison control unit is used to control the UAV motor driver based on the driver temperature data and the sensor temperature data.

7. The control device for an electric propulsion system with a propeller as described in claim 6, characterized in that, The control module further includes: The difference unit is used to determine the difference between the driver temperature data and the sensor temperature data; A threshold determination unit is used to determine the relationship between the difference and the lower threshold and the higher threshold, respectively. The derating unit is used to control the UAV motor driver to enter the derating operation mode when the difference is greater than the low threshold and less than the high threshold. The limp unit is used to control the UAV motor driver to enter limp mode and land and stop when the difference is greater than the high threshold.

8. A control device for an electric propulsion system with a propeller, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the control method for an electric propulsion system with a propeller as described in any one of claims 1 to 4.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the control method for an electric propulsion system with a propeller as described in any one of claims 1 to 4.

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