Intelligent battery photovoltaic endurance system of unmanned aerial vehicle

Abstract

The invention relates to the technical field of unmanned aerial vehicle endurance, and discloses an intelligent battery photovoltaic endurance system of an unmanned aerial vehicle, which comprises a flexible photovoltaic cell panel, an intelligent battery management system, an energy storage device, a flight controller and the like. The method comprises the following specific steps: S1, a photovoltaic cell panel conversion process and adjustment; s2, electric quantity management and charging process adjustment; and S3, task execution and state monitoring. In the control process of the intelligent battery photovoltaic endurance system of the unmanned aerial vehicle provided by the invention, two specific innovation aspects are provided: on a photovoltaic solar panel, a battery model is established based on an MPPT algorithm and by using a Simscape Power System module of Matlab, so that the reliability and the accuracy of the selected flexible solar panel are ensured, and the reliability and the accuracy of the photovoltaic endurance system of the intelligent battery of the unmanned aerial vehicle are improved. The optimal energy utilization can be realized under different illumination conditions; in the aspect of an intelligent battery management system, the charging process is optimized by monitoring the battery state of the unmanned aerial vehicle in real time based on an STM32 single-chip microcomputer module, and accurate electric quantity management and energy distribution are achieved. And efficient utilization of the battery is ensured. On the premise that low-altitude economic development is advocated at present, the performance of the small unmanned aerial vehicle can be reasonably optimized, energy waste is reduced, and the actual flight time of the unmanned aerial vehicle is further prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) endurance, and in particular to an intelligent battery photovoltaic endurance system for an unmanned aerial vehicle (UAV). Background Art

[0002] Under the current technological background, the endurance of small unmanned aerial vehicles (UAVs) has become a core factor limiting their widespread application. In China, research on the endurance of small drones has shown a booming trend in recent years. Many scientific research institutions and enterprises have invested heavily in technology research and development in order to break through the endurance problem. For example, some research teams have effectively improved the endurance of small drones by improving battery technology, optimizing motor efficiency, and introducing renewable energy such as solar energy. Internationally, the endurance of small drones has also received widespread attention. Many developed countries have deep technical accumulation in battery technology, material science, etc., which provides strong support for solving the endurance problem. For example, researchers in the United States, Europe and other regions have significantly improved the endurance of small drones by adopting advanced lithium-ion batteries, graphene materials and other technical means.

[0003] Battery technology is the bottleneck of small UAV power systems. Improving its energy density and charging and discharging efficiency is the key to achieving long-term flight. Lithium-ion batteries are widely used due to their high energy density, but their thermal runaway risk and limited cycle life are still urgent problems to be solved. As a potential alternative, solid-state batteries have attracted much attention due to their high energy density, long cycle life and excellent safety performance, although they are still in the research and development stage.

[0004] It is worth noting that although some research results have been achieved in the endurance of small drones at home and abroad, there are still many challenges. For example, how to further improve battery energy density and optimize flight control algorithms are all urgent issues to be solved.

[0005] In general, the research on small UAV endurance technology is in a period of vitality and challenges. Through interdisciplinary cooperation, continuous technological innovation, and adaptation and improvement of existing laws and regulations, the present invention has made a lot of investigations on the current research status at home and abroad, combined with the current popular technology and its own capabilities to propose solutions, and strive to get out of the dilemma of some of the problems caused by endurance issues in the actual use of UAVs. For this reason, this application now proposes an intelligent battery photovoltaic endurance system for UAVs. Summary of the invention

[0006] Technical Solution The main purpose of the present invention is to solve the situation that the UAV's battery life is insufficient and it cannot continue to fly in the face of sudden emergencies. A device for automatically charging the battery is provided by connecting a device for real-time monitoring of the battery power to the lithium battery. When the power drops to a predetermined value, a device for triggering the battery to supplement the power is provided, aiming to overcome the problem that most current charging devices are not best applicable to small low-altitude UAVs.

[0007] To achieve the above object, the present invention provides the following technical solution: An intelligent battery photovoltaic endurance system for a UAV, including a photovoltaic panel, an intelligent battery management system, an energy storage device, and a flight controller; the specific implementation technology is as follows: Preferably, the photovoltaic panel is installed on the top or a specific position of the UAV, responsible for capturing solar energy and converting it into electrical energy. The photovoltaic panel uses a flexible perovskite solar cell, which can be curled, is not easy to break, has a light weight, and good toughness, to ensure stable power supply under light conditions.

[0008] Among them, the UAV photovoltaic power generation system requires a converter with a high voltage gain to meet the power consumption needs of the system. At the input end of the solar UAV, two Boost cascade topologies are adopted for the solar UAV. To improve the utilization rate of solar energy, the MPPT control method is adopted to achieve the tracking of the maximum power. After being boosted by the Boost converter, generally part of the energy is stored in an energy storage system mainly composed of lithium batteries, and further through a bidirectional DC-DC converter, power is supplied to equipment such as on-board navigation, cameras, and communication systems. The bidirectional DC-DC converter realizes bidirectional energy transmission. In the case of realizing the same function, the bidirectional converter is easier to be modularized and lightweight than the single-phase converter. When the sunlight is sufficient, the solar panel supplies power to the load and the battery through the DC grid. When the solar battery cannot supply power at night, the energy is provided by the battery, flows through the conversion to the DC bus, and then the DC bus supplies power to the load.

[0009] Preferably, the intelligent battery management system is integrated inside the UAV, responsible for monitoring the battery state, managing the charging process, and optimizing the battery usage efficiency. This system can accurately measure the voltage, temperature, and current of the battery unit, and predict the remaining battery life and performance through algorithms.

[0010] This design is a real-time online monitoring system for the performance of UAV batteries based on the STM32 single-chip microcomputer. The AD acquisition module is used to monitor the UAV battery, and the connection is simple and the disassembly is convenient. Without damaging the original structure of the UAV battery, the flight safety of the UAV is improved. This design adopts an online measurement method to monitor the UAV battery status in real time during the UAV flight, can timely and accurately master the performance of the UAV battery, and quickly and effectively control the flight state of the UAV according to the UAV battery status. At the same time, the working condition of the UAV battery can be reported to the cloud in real time, which is equivalent to real-time backup of the "black box" data of the aircraft to the cloud, so as to conduct online monitoring of the UAV battery, observe the battery power of the UAV, and timely report the voltage status of each core, ensuring the normal flight of the UAV; this device can also monitor the voltage status of each core of other multi-core lithium batteries, and timely report the status of the UAV battery pack to ensure the normal operation of the equipment.

[0011] Preferably, the energy storage device is generally a lithium-ion battery pack with high energy density, which is used to store the electric energy generated by the photovoltaic panel and provide power for the UAV. The energy storage device is connected to the intelligent battery management system to achieve precise power management and energy distribution.

[0012] Preferably, the flight controller works in coordination with the intelligent battery management system to adjust the orientation and angle of the photovoltaic panel according to the flight state and mission requirements of the UAV, so as to maximize the capture of solar energy.

[0013] Compared with the prior art, the present invention provides an intelligent battery photovoltaic endurance system for UAVs, which has the following beneficial effects: 1. For the intelligent battery photovoltaic endurance system of this UAV, the photovoltaic panel can continuously convert solar energy into electric energy to provide continuous power support for the UAV, which significantly extends the flight time of the UAV, enabling it to perform tasks for a longer time. Especially in the case of long-term hovering or remote flight, the intelligent battery management system ensures the efficient use of the battery by real-time monitoring of the battery status and optimizing the charging process, which reduces energy waste and further extends the actual flight time of the UAV.

[0014] 2. For the intelligent battery photovoltaic endurance system of this UAV, when traditional UAVs execute tasks, they often need to return to the ground charging station frequently due to insufficient battery power, resulting in low task execution efficiency. The intelligent battery photovoltaic endurance system reduces this charging interruption, enabling the UAV to continuously execute tasks, improving the integrity and efficiency of task execution. In case of emergency, the UAV needs to quickly reach the scene and execute tasks. The intelligent battery photovoltaic endurance system ensures that the UAV has a long endurance time, enabling it to quickly respond and continuously execute tasks, providing strong support for rescue and monitoring work.

[0015] 3. The intelligent battery photovoltaic endurance system of the drone uses an intelligent battery management system to monitor the power status of the battery pack in real time during use. When the power is lower than the preset threshold, the charging process is started. The electric energy generated by the photovoltaic panels is preferentially used for the flight requirements of the drone through the power management algorithm of the intelligent battery management system, and the remaining electric energy is stored in the battery pack. During the charging process, the intelligent battery management system adjusts the charging rate and current magnitude according to the real-time status of the battery pack to ensure battery safety and extend its service life. Description of the Drawings

[0016] Figure 1 Schematic diagram of the working process of the drone endurance system of the present invention Figure 2 Schematic diagram of the technical principle of energy conversion and status monitoring of the drone endurance system of the present invention; Figure 3 Schematic diagram of the overall technical process of the drone endurance system of the present invention. Detailed Implementation Modes

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0018] An intelligent battery photovoltaic endurance system for a drone includes photovoltaic panels, an intelligent battery management system, an energy storage device, and a flight controller; the specific steps are as follows: S1. Conversion process and adjustment of the photovoltaic panels; S2. Power management and adjustment of the charging process; S3. Task execution and status monitoring.

[0019] Furthermore, the photovoltaic panels are installed on the top or a specific position of the drone and are responsible for capturing solar energy and converting it into electric energy. The photovoltaic panels use high-efficiency materials to ensure stable power supply under light conditions; when converting electric energy, when converting light to electricity, the solar panels face the sun directly to effectively capture and collect the energy of solar radiation. Monocrystalline silicon photovoltaic materials with high conversion efficiency are used, and the design of the panels is optimized to maximize the sunlight receiving area. In the solar panels, photons strike the semiconductor material, exciting electrons to generate current, realizing the direct conversion of light energy to electric energy. The direct current is converted into alternating current through an inverter, and the voltage and frequency are adjusted to meet the specific load requirements. Through the energy storage system and intelligent control system, the stability and reliability of the power supply are ensured. Through devices such as intelligent electricity meters and energy management systems, the monitoring of power generation, energy storage management, power consumption scheduling, etc. are realized to improve energy utilization efficiency; Among them, the intelligent control during the conversion of electrical energy: Based on the processed data, the system monitors the operating status of the photovoltaic panels in real time. Through preset thresholds or complex algorithm models, it determines whether the photovoltaic panels are in a normal, abnormal, or emergency state. According to the results of the status monitoring, the system intelligently formulates control strategies to optimize the operation of the photovoltaic panels or respond to abnormal situations. After the control actions are executed, the system collects data from the photovoltaic panels again to evaluate the control effect. If the expected goal is not achieved, it adjusts according to the feedback information, reformulates the control strategy and executes it until the power collection status of the photovoltaic panels reaches the optimal or stable state. During the monitoring process, if serious faults or safety hazards are found in the photovoltaic panels, the system immediately triggers an alarm mechanism to notify relevant personnel for handling. At the same time, it automatically executes protection actions, such as cutting off the faulty circuit, starting the emergency backup power supply, etc., to prevent the expansion of the accident.

[0020] Among them, use EDA tools for the design of the circuit schematic diagram, considering the electromagnetic compatibility (EMC) and signal integrity (SI) of the circuit. Use advanced EDA tools for circuit simulation to predict and solve possible electromagnetic interference problems. Design the heat dissipation solution of the circuit using the obtained data to ensure the stable operation of the circuit under high-load conditions.

[0021] Use Simulink for circuit simulation experiments to verify the correctness and feasibility of the circuit design. Static simulation will verify the performance of the circuit at different operating points, while dynamic simulation will simulate the behavior of the circuit under transient conditions.

[0022] Use the Simscape Power Systems module of Matlab to establish a model containing a flexible perovskite solar cell and a main battery. Consider the flexible perovskite solar cell as a power source and the main battery as a load. Use parameter scanning and Monte Carlo simulation to evaluate the performance and reliability of the system under different conditions.

[0023] Furthermore, the intelligent battery management system is integrated inside the drone, responsible for monitoring the battery status, managing the charging process, and optimizing the battery usage efficiency. This system can accurately measure the voltage, temperature, and current of the battery cells, and predict the remaining battery life and performance through algorithms.

[0024] Furthermore, the energy storage device is generally a high-energy-density lithium-ion battery pack, used to store the electrical energy generated by the photovoltaic panels and provide power for the drone. The energy storage device is connected to the intelligent battery management system to achieve precise power management and energy distribution.

[0025] Furthermore, the flight controller works in coordination with the intelligent battery management system to adjust the orientation and angle of the photovoltaic panels according to the flight status and mission requirements of the drone to maximize the capture of solar energy.

[0026] Working principle When the intelligent battery photovoltaic endurance system of the UAV works, it first starts and initializes the system. After the system starts, it turns on the power supply of the UAV, starts the flight controller and the intelligent battery management system. The intelligent battery management system conducts an initial detection of the battery pack, including reading parameters such as voltage, temperature, and current, to ensure that the battery is in a safe state. The flight controller checks the mechanical components and sensor status of the UAV to ensure that the UAV has the conditions for flight; after the UAV takes off, the flight controller adjusts the orientation and angle of the photovoltaic panels according to the preset flight path and mission requirements. During the flight, the flight controller continuously monitors the light intensity and the output power of the photovoltaic panels, and automatically adjusts the panel angle to maximize the capture efficiency of solar energy; the photovoltaic panels can continuously convert solar energy into electrical energy, providing continuous power support for the UAV, which significantly extends the flight time of the UAV and enables it to perform tasks for a longer time. Especially in the case of long-term hovering or long-distance flight requirements, the intelligent battery management system ensures the efficient use of the battery by monitoring the battery status in real time and optimizing the charging process. This reduces energy waste and further extends the actual flight time of the UAV.

[0027] During the use process, the intelligent battery management system monitors the power status of the battery pack in real time. When the power is lower than the preset threshold, it starts the charging process. The electrical energy generated by the photovoltaic panels is preferentially used for the flight requirements of the UAV through the power management algorithm of the intelligent battery management system, and the remaining electrical energy is stored in the battery pack. During the charging process, the intelligent battery management system adjusts the charging rate and current magnitude according to the real-time status of the battery pack to ensure battery safety and extend its service life; the UAV conducts flight and data collection according to the preset mission. The intelligent battery management system continuously monitors the power and performance status of the battery pack and transmits relevant data to the ground control station through the flight controller. The ground control station conducts remote monitoring and scheduling of the UAV based on the received data to ensure the smooth execution of the mission, thus solving the problem that traditional UAVs often need to frequently return to the ground charging station for charging due to insufficient battery power during mission execution, resulting in low mission execution efficiency. The intelligent battery photovoltaic endurance system reduces this charging interruption, enabling the UAV to continuously execute the mission and improving the integrity and efficiency of mission execution. In case of an emergency, the UAV needs to quickly reach the scene and execute the mission. The intelligent battery photovoltaic endurance system ensures that the UAV has a long endurance time, enabling it to quickly respond and continuously execute the mission, providing strong support for rescue and monitoring work.

[0028] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent battery photovoltaic endurance system for an unmanned aerial vehicle, characterized in that: It includes photovoltaic panels that can adjust their angles according to the ambient light to ensure sufficient energy supply, energy storage devices that store the electricity converted by the panels, and the power supply of the energy storage device to the drone is regulated by the intelligent battery management system and the flight controller; The photovoltaic panel conversion process and regulation include: The data input end uses two Boost cascade topologies and MPPT control methods to achieve power tracking, and the energy is stored in the lithium battery energy storage system after the Boost converter boosts the voltage. The power management and charging process regulation include: Based on the STM32 microcontroller, the AD acquisition module is used to monitor the battery of the drone. At the same time, the working status is reported to the cloud in real time, and the power and voltage status are monitored online. The energy storage device for storing the electric energy converted by the battery panel comprises: The energy storage device is generally a high-energy-density lithium-ion battery pack, which is used to store the electricity generated by photovoltaic panels and provide power for drones. The energy storage device is connected to the intelligent battery management system to achieve precise power management and energy distribution; The task execution and status monitoring include: The data is collected through the designed analog circuit and sampling circuit to obtain the battery voltage. The analog quantity is input into the ADC circuit and converted into digital information. The measured data is compared with the set value. If the voltage is lower than the set value, an alarm is sounded to remind the user that the battery is in a low-power state and to land the drone in time. If the battery cell voltage is normal, it enters the circulation state and continues monitoring.

2. A battery model based on MPPT algorithm and using Matlab's Simscape Power Systems module to ensure that the selected flexible solar panels can achieve optimal energy utilization, characterized by: The photovoltaic panel is installed on the top of the drone or at a specific location, responsible for capturing solar energy and converting it into electrical energy. The photovoltaic panel uses flexible perovskite high-efficiency materials to ensure stable power supply under lighting conditions. Follow the steps below: Step 1: After the drone takes off, the angle adjuster adjusts the direction and angle of the photovoltaic panel according to the changes in light intensity in the environment; Step 2: Based on the maximum power point tracking (MPPT) algorithm, to ensure the best charging efficiency under different lighting and temperature conditions, design low-power, high-performance charging management circuits, including precise control of current and voltage, taking into account the real-time and computational complexity of the algorithm to ensure that they can run efficiently on actual hardware.

3. A method for optimizing the charging process by real-time monitoring of the battery status of the drone itself based on the STM32 single-chip microcomputer module, characterized in that: The intelligent battery management system is integrated into the drone and is responsible for monitoring the battery status, managing the charging process and optimizing the battery efficiency. The system can accurately measure the voltage, temperature and current of the battery unit and predict the remaining battery life and performance through algorithms. The system is carried out in the following steps: Step 1: After the drone is running, collect and analyze the power information; Step 2: Determine and upload monitoring data in real time and perform program design; Step 3: When the UAV battery is low, control the photovoltaic battery to replenish energy for the UAV, thereby achieving connection with the above-mentioned charging technology.

4. The intelligent battery photovoltaic endurance system for a drone according to claim 1, characterized in that: The energy storage device is generally a high-energy-density lithium-ion battery pack, which is used to store the electricity generated by photovoltaic panels and provide power for the drone. The energy storage device is connected to an intelligent battery management system to achieve precise power management and energy distribution.

5. The intelligent battery photovoltaic endurance system for a drone according to claim 2, characterized in that: The flight controller works in conjunction with the intelligent battery management system, and an angle adjuster is designed according to the flight status and mission requirements of the drone to adjust the orientation of the photovoltaic panels to maximize the capture of solar energy. The specific steps of the photovoltaic panel conversion process and adjustment in step 1 are as follows: Step 1.1: After the drone takes off, the angle adjuster adjusts the direction and angle of the photovoltaic panel according to the changes in light intensity in the environment; Step 1.2: During the flight, the environmental detection device continuously monitors the light intensity and the output power of the photovoltaic panels, and automatically adjusts the charging efficiency and frequency.

6. The intelligent battery photovoltaic endurance system for a drone according to claim 2, characterized in that: The specific steps of task execution and status monitoring in step 2 are as follows: Step 2.1, the drone flies and collects data according to the preset mission; Step 2.2 Use EDA tools to design the circuit schematic. Considering the electromagnetic compatibility (EMC) and signal integrity (SI) of the circuit, use advanced EDA tools to simulate the circuit to predict and solve possible electromagnetic interference problems. Use the data obtained to design the circuit's heat dissipation solution to ensure stable operation of the circuit under high load conditions. Step 2.3: Use Simulink to conduct circuit simulation experiments to verify the correctness and feasibility of the circuit design. Static simulation will verify the performance of the circuit at different operating points, while dynamic simulation will simulate the behavior of the circuit under transient conditions. Step 2.4: Use Matlab's Simscape Power Systems module to build a model that includes a flexible perovskite solar cell and a main battery. Consider the flexible perovskite solar cell as a power source and the main battery as a load. Use parameter sweeps and Monte Carlo simulations to evaluate the performance and reliability of the system under different conditions. Step 2.4, the intelligent battery management system continuously monitors the power and performance status of the battery pack and transmits relevant data to the controller through the data module; Step 2.5: The ground control remotely monitors and dispatches the UAV based on the received data to ensure the smooth execution of the mission.

7. The intelligent battery photovoltaic endurance system for a drone according to claim 3, characterized in that: The intelligent monitoring system is responsible for monitoring the battery status, managing the charging process and optimizing the battery efficiency. The specific steps of step 1, power information collection and analysis, are as follows: Step 1.1: In the power monitoring and control device, the voltage signal in the power grid must be collected first for subsequent calculation and processing. Both signals are analog signals, so an analog signal input circuit design is required. Voltage signal input commonly uses voltage transformers and resistor dividers. Step 1.2: This voltage sampling uses a resistor divider network and a pseudo-differential input method. According to the calculation, the sampling data can meet the design value.

8. The intelligent battery photovoltaic endurance system for a drone according to claim 3, characterized in that Selection of single chip microcomputer, selection of voltage stabilizer, design of digital tube display circuit: Step 2 uploads monitoring data in real time, and the specific steps of program design are as follows: Step 2.1, STM32 main control module uses STM32F407VET6 single-chip microcomputer chip. STM32F407VET6 is a high-performance ARM Cortex-M4 core microcontroller chip produced by STMicroelectronics. It belongs to the F4 series in the STM32 series. The advantages of using STM32F407VET6 as the STM32 main control module include: high-performance Cortex-M4 processor, rich peripheral interfaces, advanced analog functions, and low power consumption; Step 2.2, among the linear integrated voltage regulators, the three-terminal voltage regulator has only three lead terminals, has the advantages of few external components, stable performance, and easy use, so it is widely used. Since this circuit design requires an output voltage of 5V, the three-terminal voltage regulator 7805 is selected; Step 2.

3. This design uses a static display circuit for LED digital tubes. Each display occupies a separate I / O interface with a latching function. The microcontroller only needs to send the glyph code to be displayed to the interface circuit until there is new data to be displayed, and then send a new glyph code. This reduces the CPU load to a minimum.

9. The intelligent battery photovoltaic endurance system for a drone according to claim 3, characterized in that Selection of single chip microcomputer, selection of voltage stabilizer, design of digital tube display circuit: the specific steps of step three power management and charging process are as follows: Step 3.1: During the charging process, the intelligent battery management system adjusts the charging rate and current according to the real-time status of the battery pack to ensure battery safety and extend its service life; Step 3.2, this project uses the STM32F407VET6 microcontroller chip to replace the switching elements on the dc-dc converter to power the device. The STM32F407VET6 is a high-performance microcontroller based on ARM Cortex-M4, with rich peripheral interfaces and high processing power. It uses PWM (pulse width modulation) signals to control external power switches. The STM32F407VET6 first generates PWM signals through its built-in timer, and then drives the external switching devices through appropriate drive circuits (such as transistors, gate drive chips, etc.). In this way, the working principle of the dc-dc converter can be simulated to realize the power supply of the device. Step 3.3: The electricity generated by the photovoltaic panels is used for UAV flight needs first through the power management algorithm of the intelligent battery management system, and the remaining electricity is stored in the battery pack; first, constant current charging is performed, and when the charging voltage reaches 4.2V, it enters the second stage, that is, constant voltage charging. At this time, the charging current gradually decreases to zero, indicating that the battery is fully charged.

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