A wireless energy supply method and system based on visual positioning

Abstract

The present invention discloses a wireless energy supply method and system based on visual positioning, belonging to the technical field of wireless energy supply; the present invention can locate products equipped with photovoltaic charging energy storage systems through machine vision methods, and adjust the illumination intensity, distance and illumination wavelength parameters of the illumination system for products equipped with photovoltaic charging energy storage systems according to the illumination intensity of the surrounding environment, so as to realize accurate and rapid charging of products equipped with photovoltaic charging energy storage systems.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless energy supply, and in particular relates to a wireless energy supply method and system based on visual positioning. Background Art

[0002] Solar energy is a renewable energy source. Using solar energy for charging can reduce dependence on non-renewable energy sources, help reduce consumption of resources such as fossil fuels, and use solar energy to charge can reduce greenhouse gas emissions, which is beneficial to protecting the environment and mitigating the impact of climate change. Compared with fuel generators or other traditional power generation equipment, solar charging systems usually have the advantages of no noise and low maintenance costs, making them more popular in outdoor, camping, ship and other scenarios. In addition, solar charging systems can operate independently and do not need to rely on traditional power grids, so they are very practical in remote areas, camping in the wild or in emergency situations. In addition, solar charging equipment is usually light and easy to carry, and has flexibility.

[0003] Studies have shown that by increasing the light intensity or the light intensity in a specific wavelength range, the charging power of solar cells can be increased, thereby effectively improving the efficiency of solar cells.

[0004] As proposed in Arshad, Rizwan, et al. "Improvement in solar panel efficiency using solar concentration by simple mirrors and by cooling." 2014 international conference on robotics and emerging allied technologies in engineering (iCREATE). IEEE, 2014, Cotal, Hector, et al. "III–V multijunction solar cells for concentrating photovoltaics." Energy & Environmental Science 2.2 (2009): 174-192, and Xie, WT, et al. "Concentrated solar energy applications using Fresnellenses: A review." Renewable and Sustainable Energy Reviews 15.6 (2011): 2588-2606, in a low-light environment, the charging efficiency of the solar cell can be further optimized by adjusting the illumination distance, illumination intensity, and wavelength parameters of the illumination device.

[0005] Under existing technical conditions, how to accurately locate and effectively control the photovoltaic charging system in a complex environment is an important research topic. Most of the current research focuses on using photovoltaic modules to obtain energy and store it in batteries, while ignoring the interactive optimization between the lighting system and photovoltaic modules.

[0006] In view of the shortcomings of the prior art, the present invention proposes a wireless energy supply method and system based on visual positioning. Through machine vision methods, products equipped with photovoltaic charging and energy storage systems can be accurately positioned, and the lighting parameters of the lighting system can be adjusted according to the ambient light intensity to achieve efficient and accurate wireless charging. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a wireless power supply method and system based on visual positioning to solve the above problems.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: A wireless energy supply method based on visual positioning, comprising the following steps:

[0009] S1. Use the visual positioning system to detect the distance of the product equipped with the photovoltaic charging energy storage system, obtain the distance information between the lighting system and the product under the current ambient light intensity, and obtain the light supply wavelength information of the lighting system under this light intensity;

[0010] S2, comparing the obtained distance information and light supply wavelength information with the preset distance threshold under the same light intensity and the light supply wavelength threshold of the lighting system under the same light intensity, and if either of them is not within the corresponding threshold, adjusting the distance information and the light supply wavelength information to make them within the corresponding threshold;

[0011] S3. Predict the light intensity in the current environment by linear regression, and obtain the distance prediction value and the light supply wavelength prediction value according to the light intensity prediction value. According to the distance prediction value and the light supply wavelength prediction value, determine whether the distance prediction value and the light supply wavelength prediction value are within the distance threshold under the corresponding predicted light intensity and the light supply wavelength threshold under the predicted light intensity. If not, adjust the distance information and the light supply wavelength information to make them within the corresponding thresholds. At the same time, associate the obtained distance prediction value and the light supply wavelength prediction value to form a light supply condition coefficient. Compare the obtained light supply condition coefficient with the preset light supply condition coefficient threshold. If it is not within the light supply condition coefficient threshold, adjust the distance information and the light supply wavelength information until the light supply condition coefficient is within the light supply condition coefficient threshold. The association expression of the light supply condition coefficient is:

[0012]

[0013] Among them, TX represents the light supply condition coefficient, GZ s,i Represents the distance information under the predicted light intensity, GZ f,i It indicates the distance information under the predicted light intensity and the light wavelength information, and N indicates the number of items;

[0014] S4. The photovoltaic charging energy storage system receives the light from the care system and converts light energy into electrical energy for charging the product, specifically: obtaining the charging temperature, charging voltage, and charging current information under the current environment, and comparing the three with the preset temperature threshold, voltage threshold, and current threshold. If any of the three exceeds the corresponding preset threshold, the temperature, voltage, or current is controlled, and the preset protection circuit is started to protect the circuit until the three reach the corresponding preset threshold. The obtained temperature information, voltage information, and current information are dimensionlessly processed and fitted to form a charging condition coefficient. The formed charging condition coefficient is compared with the preset charging condition coefficient threshold. If it exceeds the charging condition coefficient threshold, the temperature, voltage, and current are controlled until the charging condition coefficient is within the preset charging condition coefficient. The expression of the charging condition coefficient is:

[0015]

[0016] Wherein, CX represents the charging condition coefficient, T represents the temperature information, V represents the voltage information, I represents the current information, α represents the temperature influence factor, β represents the common influence factor of voltage and current, 0≤α≤1, 0≤β≤1, α+β=1;

[0017] S5. Evaluate the charging quality according to the power supply condition coefficient obtained in S3 and the charging condition coefficient obtained in S4, specifically: obtain the power supply condition coefficient in S3 and the charging condition coefficient in S4, perform fitting correlation on them, obtain the charging evaluation coefficient, compare the obtained charging evaluation coefficient with the preset charging evaluation coefficient threshold, and if it exceeds the charging evaluation coefficient threshold, adjust the charging condition coefficient and the power supply condition coefficient until the power supply condition coefficient is within the threshold, wherein the charging evaluation coefficient is expressed as:

[0018]

[0019] PG represents a charging evaluation coefficient, θ represents an influence weight of a power supply condition coefficient, μ represents an influence weight of a charging condition coefficient, TX represents a power supply condition coefficient, and CX represents a charging condition coefficient.

[0020] On the basis of the above technical solution, the present invention also provides the following optional technical solution:

[0021] Further technical solution: The photovoltaic charging energy storage system includes solar cells, a control circuit board and an energy storage battery.

[0022] Further technical solution: The visual positioning system determines the position and direction of objects within the field of view by identifying and tracking them, so as to accurately locate the position of solar cells so that the lighting system can effectively focus and enhance light energy onto these cells, including cameras and image acquisition devices, image processing units, deep learning and computer vision algorithms, positioning and tracking algorithms, control system interfaces, software and user interfaces, and data storage and communication modules.

[0023] Further technical solution: The lighting system is a light-emitting and optical path system capable of regulating light color, light intensity and light time parameters, including a light source, a reflector and a lens, a directional control device, a control system, a power management, a sensor system, a user interface and a remote control module.

[0024] Further technical solution: The solar cell includes any one of a polycrystalline silicon solar cell, a monocrystalline silicon solar cell, a perovskite solar cell, a III-V solar cell, a stacked solar cell, a perovskite / monocrystalline silicon stacked solar cell, an organic solar cell, a thin-film solar cell and a flexible solar cell.

[0025] A system using the wireless energy supply method based on visual positioning, comprising:

[0026] An information acquisition module, used to acquire distance information, light supply wavelength information, temperature information, voltage information, current information, charging condition coefficient, power supply condition coefficient and charging evaluation coefficient;

[0027] A storage module, used to store the information acquired by the information module;

[0028] A threshold module, used to compare the information obtained by the information acquisition module with a preset corresponding threshold;

[0029] An analysis module analyzes the information stored in the storage module to obtain a charging condition coefficient, a power supply condition coefficient, and a charging evaluation coefficient and stores the three in the storage module;

[0030] The control module performs information regulation on the lighting system and the photovoltaic charging energy storage system according to the comparison information of the threshold module.

[0031] A power supply device using the system comprises an illumination mechanism, a photovoltaic charging energy storage mechanism and a visual positioning mechanism.

[0032] The present invention provides a wireless energy supply method and system based on visual positioning, which has the following beneficial effects compared with the prior art:

[0033] 1. The present invention increases the illumination intensity by controlling the illumination distance and illumination wavelength, thereby improving the charging power of solar cells and effectively improving the utilization efficiency of solar cells. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the process of the present invention.

[0035] Figure 2 This is a scene diagram of the wireless charging function of an electric vehicle used in the present invention.

[0036] Figure 3 This is a scene diagram of the wireless power supply system for mobile phones according to the present invention.

[0037] Figure 4 This is a scene diagram of the wireless power supply system for a tablet computer according to the present invention.

[0038] Figure 5 This is a scene diagram of the wireless power supply system for a notebook computer according to the present invention.

[0039] Figure 6 This is a scene diagram of the wireless power supply system for wireless computer peripherals of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0041] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0042] See also Figure 1 , provided in one embodiment of the present invention, is a wireless energy supply method based on visual positioning, comprising the following steps:

[0043] S1. Use the visual positioning system to detect the distance of the product equipped with the photovoltaic charging energy storage system, obtain the distance information between the lighting system and the product under the current ambient light intensity, and obtain the light supply wavelength information of the lighting system under this light intensity;

[0044] S2, comparing the obtained distance information and light supply wavelength information with the preset distance threshold under the same light intensity and the light supply wavelength threshold of the lighting system under the same light intensity, and if either of them is not within the corresponding threshold, adjusting the distance information and the light supply wavelength information to make them within the corresponding threshold;

[0045] S3. Predict the light intensity in the current environment by linear regression, and obtain the distance prediction value and the light supply wavelength prediction value according to the light intensity prediction value. According to the distance prediction value and the light supply wavelength prediction value, determine whether the distance prediction value and the light supply wavelength prediction value are within the distance threshold under the corresponding predicted light intensity and the light supply wavelength threshold under the predicted light intensity. If not, adjust the distance information and the light supply wavelength information to make them within the corresponding thresholds. At the same time, associate the obtained distance prediction value and the light supply wavelength prediction value to form a light supply condition coefficient. Compare the obtained light supply condition coefficient with the preset light supply condition coefficient threshold. If it is not within the light supply condition coefficient threshold, adjust the distance information and the light supply wavelength information until the light supply condition coefficient is within the light supply condition coefficient threshold. The association expression of the light supply condition coefficient is:

[0046]

[0047] Among them, TX represents the light supply condition coefficient, GZ s,i Represents the distance information under the predicted light intensity, GZ f,i It indicates the distance information under the predicted light intensity and the light wavelength information, and N indicates the number of items;

[0048] S4. The photovoltaic charging energy storage system receives the light from the illumination system and converts the light energy into electrical energy for charging the product. Specifically:

[0049] S401, obtaining the charging temperature, charging voltage, and charging current information under the current environment, and comparing the three with the preset temperature threshold, voltage threshold, and current threshold. If any one of the three exceeds the corresponding preset threshold, the temperature, voltage, or current is controlled, and the preset protection circuit is started to protect the circuit until the three reach the corresponding preset threshold;

[0050] S402, performing dimensionless processing on the temperature information, voltage information, and current information obtained in S401 and performing fitting to form a charging condition coefficient, and comparing the formed charging condition coefficient with a preset charging condition coefficient threshold value. If the charging condition coefficient exceeds the charging condition coefficient threshold value, the temperature, voltage, and current are controlled until the charging condition coefficient is within the preset charging condition coefficient, wherein the expression of the charging condition coefficient is:

[0051]

[0052] Wherein, CX represents the charging condition coefficient, T represents temperature information, V represents voltage information, I represents current information, α represents the temperature influencing factor, β represents the common influencing factor of voltage and current, and the α and β are obtained by inputting the temperature, current and voltage into SPSS software for analysis, wherein 0≤α≤1, 0≤β≤1, α+β=1;

[0053] S5. Evaluate the charging quality according to the power supply condition coefficient obtained in S3 and the charging condition coefficient obtained in S4, specifically: obtain the power supply condition coefficient in S3 and the charging condition coefficient in S4, perform fitting correlation on them, obtain the charging evaluation coefficient, compare the obtained charging evaluation coefficient with the preset charging evaluation coefficient threshold, and if it exceeds the charging evaluation coefficient threshold, adjust the charging condition coefficient and the power supply condition coefficient until the power supply condition coefficient is within the threshold, wherein the charging evaluation coefficient is expressed as:

[0054]

[0055] PG represents the charging evaluation coefficient, θ represents the influence weight of the power supply condition coefficient, μ represents the influence weight of the charging condition coefficient, TX represents the power supply condition coefficient, and TX represents the charging condition coefficient.

[0056] A system using a wireless energy supply method based on visual positioning, comprising:

[0057] An information acquisition module, used to acquire distance information, light supply wavelength information, temperature information, voltage information, current information, charging condition coefficient, power supply condition coefficient and charging evaluation coefficient;

[0058] A storage module, used to store the information acquired by the information module;

[0059] A threshold module, used to compare the information obtained by the information acquisition module with a preset corresponding threshold;

[0060] An analysis module analyzes the information stored in the storage module to obtain a charging condition coefficient, a power supply condition coefficient, and a charging evaluation coefficient and stores the three in the storage module;

[0061] The control module performs information regulation on the lighting system and the photovoltaic charging energy storage system according to the comparison information of the threshold module.

[0062] A power supply device using the system comprises an illumination mechanism, a photovoltaic charging energy storage mechanism and a visual positioning mechanism, wherein the illumination mechanism comprises a steering mechanism capable of adjusting the illumination angle.

[0063] In an embodiment of the present invention, the photovoltaic charging energy storage system includes a solar cell, a control circuit board and an energy storage battery;

[0064] Among them, the solar cell includes any one of a polycrystalline silicon solar cell, a monocrystalline silicon solar cell, a perovskite solar cell, a III-V solar cell, a stacked solar cell, a perovskite / monocrystalline silicon stacked solar cell, an organic solar cell, a thin-film solar cell and a flexible solar cell.

[0065] Among them, the control circuit board and control chip include a microcontroller unit (MCU), a power management chip, a communication module, a driver and actuator interface, a sensor interface, a voltage and current sensor, and a protection circuit.

[0066] The microcontroller is the brain of the control board, responsible for processing all data input and output, such as sensor data, actuator commands, etc. It executes preset algorithms based on the input data (such as the voltage and current of the solar cell, ambient light conditions, etc.) to optimize charging efficiency and battery management. The power management chip is responsible for managing the power generated by the solar cell, including voltage regulation, current control, and battery charge and discharge management. They ensure safe battery charging, prevent overcharging and over-discharging, and extend battery life. The communication module (such as Wi-Fi, Bluetooth, or Zigbee module) enables the control board to communicate with other systems (such as central control systems or other smart devices), receive remote commands, and send status updates. The driver and actuator interfaces are used to connect and control external devices, such as the direction regulator of the lighting system. They receive instructions from the microcontroller to adjust the lighting angle to ensure that the solar panel receives the best light. The sensor interface is used to connect various sensors (such as light intensity sensors, temperature sensors, etc.), which provide real-time data about environmental conditions to help optimize system performance. The voltage and current sensors monitor the output of the solar cell, and the information is fed back to the microcontroller for adjusting the charging strategy and power management. The protection circuit is used for overvoltage, undervoltage, overcurrent, short circuit protection, etc. to ensure that the system will not be damaged under abnormal circumstances.

[0067] Among them, the energy storage battery includes any one of a lead-acid battery, a lithium-ion battery, a nickel-cadmium battery, a nickel-metal hydride battery, a sodium-sulfur battery, a flow battery, a supercapacitor and a hydrogen fuel cell.

[0068] In an embodiment of the present invention, the visual positioning system determines the position and direction of objects within the field of view by identifying and tracking them, so as to accurately locate the position of solar cells so that the lighting system can effectively focus and enhance light energy onto these cells, including cameras and image acquisition devices, image processing units, deep learning and computer vision algorithms, positioning and tracking algorithms, control system interfaces, software and user interfaces, and data storage and communication modules.

[0069] The camera is the most basic element in the visual positioning system, which is used to capture image data in the environment. These cameras may be monocular, binocular, or cameras with depth perception. The image processing unit is responsible for extracting useful information from the raw images received by the camera.

[0070] Deep learning models and computer vision algorithms are used to analyze images and identify and locate objects in them. Common algorithms include convolutional neural networks (CNNs) and other machine learning models that can identify the shape, size, and other features of objects.

[0071] Once the positioning and tracking algorithm identifies an object, the system will use various algorithms to track the position and movement of these objects in space, including the use of filters (such as Kalman filters) or optical flow technology.

[0072] Among them, the control system interface helps the visual positioning system to transmit the processed position information to the control system, and the control system adjusts the direction and intensity of the lighting system based on this information to optimize the charging efficiency of the solar cell.

[0073] Among other things, the software and user interface allow operators to monitor and adjust the vision positioning system's settings while displaying system status and diagnostic information.

[0074] Among them, the data storage and communication module is used to store image and location data, as well as to exchange data with other system components (such as photovoltaic charging energy storage system and lighting system).

[0075] Among them, cameras and image acquisition devices include but are not limited to monocular cameras, binocular cameras, infrared cameras, depth cameras, panoramic cameras, high-speed cameras, and industrial cameras. Among them, monocular cameras use a camera sensor to capture images, which is the most common type of camera. Among them, binocular cameras use two cameras at a certain distance to simulate human binocular vision, and estimate the depth of objects by analyzing the image differences between the two perspectives. Among them, infrared cameras can capture the thermal radiation of objects and are often used for monitoring in low-light environments or at night. In some cases, they can also be used to detect the thermal efficiency and heat dissipation of equipment. Among them, depth cameras (such as Microsoft's Kinect or Intel Real Sense) can provide depth information for each pixel, which is calculated by infrared projection and reception. Among them, panoramic cameras capture 360-degree environmental images through a wide-angle lens or a combination of multiple lenses, which are suitable for environments that require all-round monitoring. Among them, high-speed cameras can capture images at extremely high frame rates, which are suitable for recording fast-moving objects or analyzing high-speed events. Among them, industrial cameras are designed to operate in extreme industrial environments, usually have higher durability and adapt to a wider range of temperature and humidity, and can be used for visual positioning and monitoring tasks in harsh environments.

[0076] Among them, image processing units include embedded systems, computer vision-specific hardware, PC-based systems, cloud computing platforms, edge computing devices, and dedicated image processing software. Among them, embedded systems usually include microprocessors or digital signal processors (DSPs) with image processing functions. These devices can perform image preprocessing near the camera, such as filtering, edge detection, color conversion, etc. Among them, computer vision-specific hardware includes GPUs (graphics processing units), FPGAs (field programmable gate arrays) or ASICs (application-specific integrated circuits). These hardware can provide higher processing speed and efficiency and are suitable for complex image processing tasks. Among them, PC-based systems include personal computers or industrial computers, which use their powerful CPUs and GPUs to process image data. Such systems usually perform well in data processing capabilities and flexibility, but may not be as good as embedded systems in size and energy consumption. Among them, cloud computing platforms have extremely high requirements for data processing or applications that require large-scale storage. Some visual positioning systems may send image data to the cloud for processing. Cloud platforms can provide almost unlimited computing resources and storage space, while supporting advanced machine learning and deep learning algorithms. Edge computing devices combine the powerful functions of cloud computing with the instant response capabilities of embedded systems. Such devices perform most of the data processing locally and only send necessary information to the cloud, which helps reduce latency and bandwidth consumption. Dedicated image processing software includes specialized image processing software that runs on the above-mentioned hardware platform and is responsible for implementing specific image analysis and processing functions, such as object recognition, motion tracking, and 3D modeling.

[0077] Among them, deep learning and computer vision algorithms include convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), object detection algorithms, image segmentation algorithms, optical flow algorithms, feature matching and stereo vision algorithms, and depth estimation algorithms. Among them, CNNs are the most commonly used network structure for image recognition and processing in deep learning. It extracts hierarchical features in images through multiple layers of convolutional layers, which is very suitable for image classification, object detection, and image segmentation tasks. Among them, RNNs are mainly used for sequence data processing (such as speech or text). When processing video data, RNNs can be used to analyze images in time series, identify behavioral patterns in videos, or predict future actions. Among them, GANs are usually used to generate new image data, but can also be used for tasks such as enhancing image quality and performing image conversion, such as converting daytime images into nighttime scenes. Among them, object detection algorithms such as YOLO (You Only Look Once), SSD (Single Shot MultiDetector), Faster R-CNN, etc., can identify multiple objects and their locations in an image in a single forward propagation. Image segmentation algorithms such as U-Net, Mask R-CNN, etc., are used to classify each pixel in an image into different object categories, which are suitable for scene understanding and medical image processing. Among them, the optical flow algorithm is used to estimate the motion change of each image pixel, and is widely used in motion detection, video compression, and video effect generation.

[0078] Among them, feature matching and stereo vision algorithms such as SIFT (Scale-Invariant Feature Transform) and SURF (Speeded Up Robust Features) are used to find corresponding points between different images and are often used for image stitching and 3D scene reconstruction. Among them, the depth estimation algorithm uses a single image or image pair to restore depth information, which helps to perform 3D modeling in the absence of physical depth perception equipment.

[0079] Among them, the positioning and tracking algorithms include optical flow, Kalman filter, particle filter, Mean Shift and CamShift algorithms, multi-object tracking (MOT), deep learning tracking algorithms, and tracking using 3D information. The optical flow method is used to estimate the motion of objects or scenes in an image sequence. It calculates speed and direction based on the visual movement of the observation point between consecutive frames. The Kalman filter is a prediction-correction technique for estimating continuous time data. It is widely used in tracking and control systems, especially when dealing with noisy data. The particle filter, or sequential Monte Carlo method, represents the probability distribution through a set of random samples (particles) and is used for tracking problems of nonlinear and non-Gaussian processes. Mean Shift is a tracking algorithm based on the gradient ascent method that tracks the target by iteratively finding the maximum value of the probability density function. CamShift is a variant of Mean Shift that can adapt to changes in target size.

[0080] In an embodiment of the present invention, the lighting system is a light-emitting and optical path system capable of regulating parameters such as light color, light intensity and lighting time, including a light source, a reflector and a lens, a directional control device, a control system, a power management, a sensor system, a user interface and a remote control module.

[0081] Among them, the light source is the core part of the lighting system, including LED lights, halogen lamps, lasers or other types of high-efficiency lamps. Depending on the system requirements, a light source that can emit light of a specific wavelength may be used to maximize the photoelectric conversion efficiency of the solar cell. Among them, reflectors and lenses are used to control and guide the light to ensure that the light energy is effectively focused and irradiated on the target solar cell. Lenses can be used to focus or diffuse light, while reflectors help adjust the light path to optimize the lighting effect. Among them, the directional control device allows the angle and position of the light source to be adjusted to adapt to different lighting needs and environmental conditions. These devices may include motor-driven brackets that can automatically adjust the direction of the light source based on the input of the visual positioning system. Among them, the control system is responsible for coordinating the operation of the lighting system, including turning on, off, dimming and direction control of the light source. This system usually includes a microcontroller and related software, which can automatically adjust the lighting parameters based on feedback from environmental sensors or preset programs. Among them, the power management system ensures that the power supply of the lighting system is stable and reliable, including power adapters, voltage and current regulators, etc. This part is crucial to ensure the continuous and stable operation of the lighting system. The sensor system can include light intensity sensors and spectrum sensors to monitor lighting conditions in real time to ensure that the light intensity and spectral distribution meet the optimal working conditions of solar cells. The user interface allows the operator to configure and monitor the settings of the lighting system, while the remote control module supports remote operation via the network, including adjusting the light intensity, direction and working time.

[0082] As an application scenario of the present invention, Figure 2 As shown, for wireless charging of electric vehicles, first, an electric vehicle equipped with a photovoltaic charging system adapted to this system drives into a set area (such as a parking lot or a charging station, etc.), and then the visual positioning system finds and locates the specific position of the electric vehicle, and sends a light-emitting instruction to the lighting system. Then the lighting system receives the specific coordinates and lighting parameters, and accurately directs the light to the solar cell part of the electric vehicle to wirelessly charge the electric vehicle.

[0083] As an application scenario of the present invention, Figure 3 As shown, a wireless power supply system for mobile phones first brings a mobile phone equipped with a photovoltaic charging system adapted to the system into an indoor space (such as a study, office space or conference room, etc.), and places the mobile phone flat on the table. When the back of the mobile phone covered with solar cells faces upward, the visual positioning system finds and locates the specific position of the mobile phone, and sends a light-emitting instruction to the lighting system. Then the lighting system receives the specific coordinates and lighting parameters, and accurately emits light to the solar cell part of the mobile phone to wirelessly charge the mobile phone.

[0084] As an application scenario of the present invention, Figure 4As shown, a wireless power supply system for a tablet computer first brings a tablet computer equipped with a photovoltaic charging system adapted to the system into an indoor space (such as a study, office space or conference room, etc.), and places the tablet computer flat on the table. When the back of the tablet computer covered with solar cells faces upward, the visual positioning system finds and locates the specific position of the tablet computer, and sends a light-emitting instruction to the lighting system. Then the lighting system receives the specific coordinates and lighting parameters, and accurately directs the light to the solar cell part of the tablet computer to wirelessly charge the tablet computer.

[0085] As an application scenario of the present invention, Figure 5 As shown, a wireless power supply system for laptop computers first brings a laptop computer equipped with a photovoltaic charging system adapted to the system into an indoor space (such as a study, office space or conference room, etc.), places the laptop computer flat on the table, and when the outer surface of the laptop computer covered with solar cells faces upward, the visual positioning system finds and locates the specific position of the laptop computer, and sends a light-emitting instruction to the lighting system. Then the lighting system receives the specific coordinates and lighting parameters, and accurately emits light to the solar cell part of the laptop computer to wirelessly charge the laptop computer.

[0086] As an application scenario of the present invention, Figure 6 As shown, a wireless energy supply system for wireless computer peripherals first brings the wireless computer peripheral equipped with a photovoltaic charging system adapted to the system into an indoor space (such as a study, office space or conference room, etc.), and places the wireless computer peripheral flat on the table. When the outer surface of the wireless computer peripheral covered with solar cells faces upward, the visual positioning system finds and locates the specific position of the wireless computer peripheral, and sends a light-emitting instruction to the lighting system. Then the lighting system receives the specific coordinates and lighting parameters, and accurately emits light to the solar cell part of the wireless computer peripheral to wirelessly charge the wireless computer peripheral.

[0087] It should be noted that, in this article, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus.

[0088] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A wireless energy supply method based on visual positioning, characterized in that: The following steps are involved: S1. Use the visual positioning system to detect the distance of the product equipped with the photovoltaic charging energy storage system, obtain the distance information between the lighting system and the product under the current ambient light intensity, and obtain the light supply wavelength information of the lighting system under this light intensity; S2, comparing the obtained distance information and light supply wavelength information with the preset distance threshold under the same light intensity and the light supply wavelength threshold of the lighting system under the same light intensity, and if either of them is not within the corresponding threshold, adjusting the distance information and the light supply wavelength information to make them within the corresponding threshold; S3. Predict the light intensity in the current environment by linear regression, and obtain the distance prediction value and the light supply wavelength prediction value according to the light intensity prediction value. According to the distance prediction value and the light supply wavelength prediction value, determine whether the distance prediction value and the light supply wavelength prediction value are within the distance threshold under the corresponding predicted light intensity and the light supply wavelength threshold under the predicted light intensity. If not, adjust the distance information and the light supply wavelength information to make them within the corresponding thresholds. At the same time, associate the obtained distance prediction value and the light supply wavelength prediction value to form a light supply condition coefficient. Compare the obtained light supply condition coefficient with the preset light supply condition coefficient threshold. If it is not within the light supply condition coefficient threshold, adjust the distance information and the light supply wavelength information until the light supply condition coefficient is within the light supply condition coefficient threshold. The association expression of the light supply condition coefficient is: Among them, TX represents the light supply condition coefficient, GZ s,i Represents the distance information under the predicted light intensity, GZ f,i It indicates the light wavelength information under the predicted light intensity, and N indicates the number of items; S4. The photovoltaic charging energy storage system receives the illumination from the illumination system and converts the light energy into electrical energy for charging the product, specifically: obtaining the charging temperature, charging voltage and charging current information under the current environment, and comparing the three with the preset temperature threshold, voltage threshold and current threshold. If any one of the three exceeds the corresponding preset threshold, the temperature, voltage or current is controlled, and the preset protection circuit is started to protect the circuit until the three reach the corresponding preset threshold. The obtained temperature information, voltage information and current information are dimensionlessly processed and fitted to form a charging condition coefficient. The formed charging condition coefficient is compared with the preset charging condition coefficient threshold. If it exceeds the charging condition coefficient threshold, the temperature, voltage and current are controlled until the charging condition coefficient is within the preset charging condition coefficient. The expression of the charging condition coefficient is: Wherein, CX represents the charging condition coefficient, T represents the temperature information, V represents the voltage information, I represents the current information, α represents the temperature influence factor, β represents the common influence factor of voltage and current, 0≤α≤1, 0≤β≤1, α+β=1; S5. Evaluate the charging quality according to the power supply condition coefficient obtained in S3 and the charging condition coefficient obtained in S4, specifically: obtain the power supply condition coefficient in S3 and the charging condition coefficient in S4, perform fitting correlation on them, obtain the charging evaluation coefficient, compare the obtained charging evaluation coefficient with the preset charging evaluation coefficient threshold, and if it exceeds the charging evaluation coefficient threshold, adjust the charging condition coefficient and the power supply condition coefficient until the power supply condition coefficient is within the threshold, wherein the charging evaluation coefficient is expressed as: PG represents a charging evaluation coefficient, θ represents an influence weight of a power supply condition coefficient, μ represents an influence weight of a charging condition coefficient, TX represents a power supply condition coefficient, and CX represents a charging condition coefficient.

2. The wireless energy supply method based on visual positioning according to claim 1 is characterized in that: The photovoltaic charging energy storage system includes a solar cell, a control circuit board and an energy storage battery.

3. The wireless energy supply method and system based on visual positioning according to claim 2 is characterized in that: The visual positioning system identifies and tracks objects within the field of view to determine their position and orientation to accurately locate the position of solar cells so that the lighting system can effectively focus and enhance light energy onto these cells. The system includes cameras and image acquisition devices, image processing units, deep learning and computer vision algorithms, positioning and tracking algorithms, control system interfaces, software and user interfaces, and data storage and communication modules.

4. The wireless energy supply method and system based on visual positioning according to claim 3 is characterized in that: The lighting system is a light-emitting and optical path system capable of regulating light color, light intensity and light time parameters, including a light source, a reflector and a lens, a directional control device, a control system, a power management, a sensor system, a user interface and a remote control module.

5. The wireless energy supply method and system based on visual positioning according to claim 3 is characterized in that: The solar cell includes any one of a polycrystalline silicon solar cell, a monocrystalline silicon solar cell, a perovskite solar cell, a III-V solar cell, a stacked solar cell, a perovskite / monocrystalline silicon stacked solar cell, an organic solar cell, a thin film solar cell and a flexible solar cell.

6. A system using the wireless energy supply method based on visual positioning according to claim 1, characterized in that: include: An information acquisition module, used to acquire distance information, light supply wavelength information, temperature information, voltage information, current information, charging condition coefficient, power supply condition coefficient and charging evaluation coefficient; A storage module, used to store the information acquired by the information module; A threshold module, used to compare the information obtained by the information acquisition module with a preset corresponding threshold; An analysis module analyzes the information stored in the storage module to obtain a charging condition coefficient, a power supply condition coefficient, and a charging evaluation coefficient and stores the three in a value storage module; The control module performs information regulation on the lighting system and the photovoltaic charging energy storage system according to the comparison information of the threshold module.

7. A power supply device for the system according to claim 6, comprising an illumination mechanism, a photovoltaic charging energy storage mechanism and a visual positioning mechanism, wherein the illumination mechanism comprises a steering mechanism capable of adjusting the illumination angle.

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