Portable sterilization device having self-power generation function

Abstract

A portable sterilization device according to an embodiment comprises: a solar module which generates power through self-power generation using sunlight and charges an energy storage panel or a battery of the portable sterilization device with the generated power; an ambient light sensor which senses an intensity of ambient light; and a charging controller which controls self-power generation of the solar module and charging of the battery, wherein: the charging controller comprises a memory in which at least one instruction is stored and a processor; and the at least one instruction, when executed by the processor, causes the charging controller to collect battery state information including a state of charge (SOC) and a state of health (SoH) by monitoring the battery of the portable sterilization device, and control self-power generation of the solar module depending on at least one of the collected battery state information, driving information of the portable sterilization device, expected power usage, and a sensed intensity of ambient light.

Description

Portable sterilizer with self-powering function

[0001] The present disclosure relates to a portable sterilizing device, and more particularly, to a portable sterilizing device capable of generating power by solar power.

[0002] Unless otherwise indicated herein, the materials described in this section are not prior art to the claims of this application, and their inclusion in this section is not intended to be admitted as prior art.

[0003] A portable sterilizer is a device that uses light to kill or sterilize bacteria, viruses, and other pathogens, thereby cleaning hands or surfaces. Conventional portable sterilizers utilize ultraviolet (UV-C) sterilization or morning sterilization.

[0004] UV-C ultraviolet rays have a very short wavelength and are effective in sterilizing bacteria and viruses by destroying their DNA and RNA. Portable UV-C sterilizers are primarily used to sterilize hands, phones, keyboards, clothes, food, sleepwear, and portable electronic devices. The user performs the sterilization process by moving the device over the object to be sterilized or shining it directly on the object. Ozone, also used for sterilization, is effective in killing bacteria and viruses. Ozone destroys bacteria and viruses by breaking down oxygen molecules (O2) into O3 molecules, creating ozone. Some portable ozone generators are used to purify air and water, and these devices can also be used as air purifiers and water pipe cleaners.

[0005] Since the COVID-19 pandemic, people's awareness of hygiene has strengthened, leading to an increase in the use of portable sterilizers. Portable sterilizers require mobility and immediate use in emergencies. However, conventional portable sterilizers require charging, limiting their mobility. Furthermore, insufficient battery capacity can sometimes render them unusable in emergencies.

[0006] Furthermore, portable sterilizers that sterilize using steam have superior sterilizing capabilities compared to those that use light. However, they consume more power than light-based sterilizers, and the amount of power required varies significantly depending on the temperature, amount, and duration of the steam used for sterilization. Consequently, demand is growing for portable sterilizers that address power supply issues through self-generation and other means.

[0007] A portable sterilizing device equipped with a self-generation function according to an embodiment adjusts whether or not self-generation is performed and the amount of charge by self-generation according to the battery charge level, thereby enabling the portable sterilizing device that sprays steam to be used at any time.

[0008] In addition, the embodiment provides a self-power generation module using solar energy, and controls whether to generate self-power and the amount of power generated according to the ambient light and the remaining battery capacity of the portable sterilizing device, thereby improving charging efficiency.

[0009] Additionally, in the embodiment, ozone-containing sterilizing water is sprayed in a mist state to rapidly sterilize indoor objects and corresponding areas exposed to coronavirus (SARS-CoV-2).

[0010] In accordance with an embodiment, a portable sterilizing device comprises: a solar module that generates power through self-generation using solar energy and charges an energy storage panel or a battery of a portable sterilizing device with the generated power; an illuminance sensor that senses ambient illuminance; and a charge control device that controls self-generation of the solar module and charging of the battery; wherein the charge control device comprises a memory that stores at least one command; and a processor, wherein at least one command is executed by the processor to monitor the battery of the portable sterilizing device and collect battery status information including a charge amount and a state of health (SoH), and control self-generation of the solar module based on at least one of the collected battery status information, operating information of the portable sterilizing device, expected power usage, and sensed ambient illuminance.

[0011] The digital twin-based convergence village-level microgrid operation system and method as described above analyzes the power patterns of power sources and loads of villages or complexes of different types with different peak times, thereby improving energy utilization efficiency and stability. The portable sterilizing device equipped with a self-generation function according to the embodiment as described above performs self-generation through solar power according to the battery status such as the charge level and state of aging (SoH) of the battery equipped in the portable sterilizing device, the ambient illumination, and the power amount of the solar module, thereby increasing the time for which the battery of the portable sterilizing device is maintained at an appropriate capacity. This allows the portable sterilizing device to be used at any time regardless of the battery charge level, and improves the lifespan of the battery equipped in the portable sterilizing device.

[0012] In addition, the power generation efficiency of the solar module of the portable sterilizing device according to the embodiment is improved, and the remaining energy depending on whether the battery is fully charged is stored in the energy storage panel of the solar module, thereby enabling efficient use of energy.

[0013] In addition, in the embodiment, the charging time and charging amount are calculated based on the ambient light, battery status, charging amount, and expected power consumption according to the operating time of the sterilizing device, and self-generation is performed, thereby increasing the energy efficiency of the portable sterilizing device.

[0014] The effects of the present invention are not limited to the effects described above, and should be understood to include all effects that can be inferred from the detailed description of the present invention or the composition of the invention described in the claims.

[0015] Figures 1 to 3 are drawings showing a portable sterilizer equipped with a self-generation function according to an embodiment.

[0016] Figure 4 is a diagram showing a data processing configuration for self-generation and charging control of a portable sterilizer according to an embodiment.

[0017] Figure 5 is a drawing showing a block diagram of a charging control device (100) according to an embodiment.

[0018] FIG. 6 is a diagram showing the configuration of commands stored in the memory of a charging control device according to an embodiment.

[0019] Figure 7 is a diagram showing an example of a model that learns data stored in a learning unit according to an embodiment.

[0020] Hereinafter, the embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Regardless of the drawing numbers, identical or similar components will be given the same reference numbers, and redundant descriptions thereof will be omitted. The suffixes "module" and "part" used for components in the following description are assigned or used interchangeably only for the convenience of writing the specification, and do not in themselves have distinct meanings or roles. In addition, when describing the embodiments disclosed in this specification, if it is determined that a specific description of a related known technology may obscure the gist of the embodiments disclosed in this specification, a detailed description thereof will be omitted. In addition, the attached drawings are only intended to facilitate easy understanding of the embodiments disclosed in this specification, and the technical ideas disclosed in this specification are not limited by the attached drawings, and should be understood to include all modifications, equivalents, and substitutes included in the spirit and technical scope of the present invention.

[0021] Terms that include ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by these terms. These terms are used solely to distinguish one component from another.

[0022] When a component is referred to as being "connected" or "connected" to another component, it should be understood that it may be directly connected or connected to that other component, but that there may be other components intervening. Conversely, when a component is referred to as being "directly connected" or "connected" to another component, it should be understood that there are no other components intervening.

[0023] In this application, terms such as “include” or “have” are intended to specify the presence of a feature, number, step, operation, component, part or combination thereof described in the specification, but should be understood not to exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts or combinations thereof.

[0024] In this specification, the term "unit" includes a unit realized by hardware, a unit realized by software, and a unit realized using both. Furthermore, a single unit may be realized using two or more pieces of hardware, and two or more units may be realized by a single piece of hardware.

[0025] Some of the operations or functions described herein as being performed by a terminal, apparatus, or device may instead be performed by a server connected to the terminal, apparatus, or device. Similarly, some of the operations or functions described herein as being performed by a server may also be performed by a terminal, apparatus, or device connected to the server.

[0026] Hereinafter, the present invention will be described in detail with reference to the attached drawings.

[0027] Figures 1 to 3 are drawings showing a portable sterilizer equipped with a self-generation function according to an embodiment. Referring to Figures 1 to 3, the portable sterilizer according to the embodiment includes a solar module (15), a housing (10), an ozone gas supply unit (20), a compressed air supply unit (30), a water supply unit (40), and a power supply unit (50).

[0028] In the embodiment, a solar power generation module (15) is configured on the outside of the housing (10), which is the upper case, to convert light energy into power usable by the portable sterilizer.

[0029] In the embodiment, the solar power generation module (15) is a module that performs self-generation to store energy and charge the battery of a portable sterilizer, and may be configured to include a light sensor, a solar panel, a solar cell panel, and an inverter.

[0030] The housing (10) is provided to form the exterior of a portable sterilizer, and includes a water tank (12), a nozzle (14), and a Y mixing pipe (16). The water tank (12) is installed inside the housing (10) and is formed to store a certain amount of water inside. A water inlet (13) is formed at the upper portion of the water tank (12) and is exposed to the outside of the housing (10). Since the water inlet is exposed to the outside of the housing, water can be conveniently added to the water tank. A water outlet (not shown in the drawing) is formed at the lower portion of the water tank (12), and the water outlet is connected to a water supply hose (42) provided at a water supply unit (40).

[0031] The nozzle (14) is installed so as to be exposed to the outside on one side of the housing (10). This housing (10) plays a role in mixing ozone gas, compressed air, and water supplied from the ozone gas supply unit (20), the compressed air supply unit (30), and the water supply unit (40) and spraying them in a fog state. For this purpose, the nozzle (14) is formed as an atomizing nozzle. Here, the atomizing nozzle mixes gas and liquid internally and sprays the liquid in a fog state by the force of the compressed air. Since the structure of this atomizing nozzle is a well-known technology widely practiced by those skilled in the art in the field of chemical sterilizers or chemical sprayers prior to the application of the present invention, a description thereof will be omitted.

[0032] A Y-type mixing pipe (16) is connected to one side of the nozzle (14). An ozone gas supply unit (20) is connected to one branched side of the Y-type mixing pipe (16), and a compressed air supply unit (30) is connected to the other branched side of the Y-type mixing pipe (16). This Y-type mixing pipe (16) plays a role in mixing ozone gas supplied from the ozone gas supply unit (20) and compressed air supplied from the compressed air supply unit (30) and supplying the mixture to the nozzle (14). That is, the ozone gas of the ozone gas supply unit (20) and the compressed air of the compressed air supply unit (30) are mixed inside the Y-type mixing pipe (16) and then supplied to the nozzle.

[0033] The ozone gas supply unit (20) is provided to supply ozone gas to the nozzle (14), and includes an air pump (22), an ozone generator (24), and an ozone gas supply hose (26).

[0034] The air pump (22) sucks in air and supplies it to the ozone generator (24). The ozone generator (24) mixes the air sucked in by the air pump (22) with ozone to generate ozone gas. For this purpose, the ozone generator (24) is formed as a known ozone generating device. The ozone gas supply hose (26) is connected to one branched side of the Wiser mixing pipe (16) to supply the ozone gas generated by the ozone generator (24) to the nozzle (14).

[0035] The ozone gas supply unit (20) configured in this manner is structured to supply ozone gas generated by an air pump (22) and an ozone generator (24) to a branched side of a Wiser mixing pipe (16) through an ozone gas supply hose (26).

[0036] The compressed air supply unit (30) is provided to supply compressed air to the nozzle (14), and includes a compression pump (32) and a compressed air supply hose (34). The compression pump (32) generates compressed air and supplies it to the ozone generator (24). The compressed air supply hose (34) is connected to the other branched side of the Wiser mixing pipe (16) to supply the compressed air generated by the compression pump (32) to the nozzle (14).

[0037] The compressed air supply unit (30) configured in this manner is structured to supply compressed air generated by the compression pump (32) to the branched other side of the Wiser mixing pipe (16) through the compressed air supply hose (34). The water supply unit (40) is provided to supply water stored in the water tank (12) to the nozzle, and includes a water supply hose (42) and an electronic valve (44). The water supply hose (42) is connected to a water outlet formed at the bottom of the water tank (12). Accordingly, the water in the water tank (12) is supplied to the nozzle (14) by a drop. The electronic valve (44) is installed on the water supply hose (42). This electronic valve (44) plays a role in controlling the flow of water supplied from the water tank (12) to the nozzle (14) through the water supply hose (42). For this purpose, the electronic valve (44) is formed as a solenoid valve. That is, the electronic valve (44) opens and closes under the control of the control unit (52) to control the flow of water.

[0038] FIG. 4 is a diagram showing a data processing configuration for self-generation and charging control of a portable sterilizer according to an embodiment.

[0039] Referring to FIG. 4, the solar module (15) of the portable sterilizing device according to the embodiment can be configured to be connected to the battery (200) and the charging control device (100) of the portable sterilizing device.

[0040] In an embodiment, the charge control device (100) monitors the battery (200) of the portable sterilizer to collect battery status information. In an embodiment, the battery status information includes the state of charge (SoC) and the state of health (SoH) of the battery. In an embodiment, the state of health (SoH) of the battery is an indicator of the performance of the battery or storage device, and in an embodiment, it can be measured through the internal resistance of the battery. In an embodiment, the charge control device (100) controls the self-generation of the solar module (15) according to at least one of the collected battery status information, operating information including whether the portable sterilizer is in use, power usage prediction information, and sensed ambient illuminance. In an embodiment, the operating information is whether the portable sterilizer is in use and operation setting information. For example, the operating information may include the amount of steam emitted from the portable sterilizer, the spray speed, the temperature of the steam, etc.

[0041] Fig. 5 is a block diagram showing a charging control device (100) according to an embodiment.

[0042] The configuration of the charging control device (100) illustrated in Fig. 5 is merely a simplified example.

[0043] The communication unit (110) may be configured regardless of the communication mode, such as wired or wireless, and may be configured with various communication networks, such as a personal area network (PAN) and a wide area network (WAN). In addition, the communication unit (110) may operate based on the well-known World Wide Web (WWW), and may also utilize a wireless transmission technology used for short-distance communication, such as infrared (IrDA: Infrared Data Association) or Bluetooth. For example, the communication unit (110) may be responsible for transmitting and receiving data required to perform a technique according to an embodiment of the present disclosure.

[0044] The memory (120) may refer to any type of storage medium. For example, the memory (120) may include at least one type of storage medium among a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (e.g., SD or XD memory, etc.), a RAM (Random Access Memory), a SRAM (Static Random Access Memory), a ROM (Read-Only Memory), an EEPROM (Electrically Erasable Programmable Read-Only Memory), a PROM (Programmable Read-Only Memory), a magnetic memory, a magnetic disk, and an optical disk. Such a memory (120) may also constitute a database as illustrated in FIG. 1.

[0045] The memory (120) can store at least one instruction that can be executed by the processor (130). In addition, the memory (120) can store any type of information generated or determined by the processor (130) and any type of information received by the server (200). For example, the memory (120) stores RM data and RM protocols according to the user, as will be described later. In addition, the memory (120) stores various types of modules, instruction sets, and models.

[0046] The processor (130) may perform technical features according to embodiments of the present disclosure, which will be described later, by executing at least one instruction stored in the memory (120). In one embodiment, the processor (130) may be configured with at least one core and may include a processor for data analysis and / or processing, such as a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), or a tensor processing unit (TPU) of a computer device.

[0047] FIG. 6 is a diagram showing a configuration of commands stored in a memory of a charging control device according to an embodiment.

[0048] Referring to FIG. 6, a memory (120) according to an embodiment may be configured to include a collection unit (121), a preprocessing unit (122), a learning unit (123), and a control unit (124). The term 'unit' used in this specification should be interpreted to include software, hardware, or a combination thereof, depending on the context in which the term is used. For example, the software may be machine language, firmware, embedded code, and application software. As another example, the hardware may be a circuit, a processor, a computer, an integrated circuit, an integrated circuit core, a sensor, a MEMS (Micro-Electro-Mechanical System), a passive device, or a combination thereof.

[0049] The collection unit (121) collects a series of data required for controlling solar modules that perform self-generation and for controlling battery charging. For example, the collection unit (121) collects battery status information, which is a result of battery monitoring, operating information of a portable sterilizer, operating information of a solar module, etc. In an embodiment, the operating information of the solar module may include whether the solar module is in the process of self-generation, power production, and accumulated power. In addition, the collection unit (121) collects learning data of a model used in the charging control device (100). In an embodiment, the model may include a model for calculating the expected power usage of the portable sterilizer and the optimal capacity of the battery, and a model for calculating the power generation of the solar module. In an embodiment, the learning data of the model may include the actual power consumption according to the usage time of the portable sterilizer, and the optimal charge capacity and discharge capacity according to the state of health (SoH) of the battery. In addition, the learning data may include data on the power generation according to the operating time and illumination of the solar module.

[0050] The preprocessing unit (122) preprocesses the collected training data to remove data with bias or discrimination from the collected training data set. In an embodiment, the preprocessing unit (120) preprocesses the collected training data set and processes it into a form suitable for artificial intelligence model learning. For example, the preprocessing unit (122) may perform processes such as noise removal, outlier removal, and missing value processing. In addition, the preprocessing unit (122) may normalize data, remove outliers, or adjust the data scale through data preprocessing to prevent the model from learning unnecessary patterns.

[0051] The learning unit (123) trains a deep learning neural network with the collected training data set to implement a deep learning model. Fig. 7 is a diagram illustrating an example of a model stored in the learning unit and learning data according to an embodiment. Referring to Fig. 7, the learning unit (123) of the memory may store a power consumption prediction model (1), an optimal capacity calculation model (2), and a self-generation control model (3). Each module or model may be in the form of an application executable by the processor (130).

[0052] The power consumption prediction model (1) is an artificial neural network model that predicts the power consumption of a portable sterilizer based on its operating time, configured functions, and battery status. In an embodiment, the power consumption prediction model (1) learns the actual operating time, configured functions, and battery status of the portable sterilizer as input data, and learns the actual power consumption and battery discharge amount based on the input data as output data. Through this, the power consumption of the portable sterilizer based on its operating time, configured functions, and battery status can be predicted.

[0053] For example, the power consumption prediction model (1) learns from power consumption data by usage time of the portable sterilizing device, and by inputting usage time and usage time information of the portable sterilizing device into the power consumption prediction model, power usage prediction information can be obtained.

[0054] In addition, in the embodiment, the power consumption prediction model (1) predicts the power consumption according to the operating information of the portable sterilizing device. For example, the power consumption prediction model (1) predicts the power consumption according to the operating information including the intensity of the steam sprayed by the portable sterilizing device, the steam temperature, the speed, and the spraying duration.

[0055] The optimal capacity calculation model (2) calculates the optimal charge capacity and discharge capacity according to the battery temperature and the battery status of the portable sterilizer. Generally, the optimal charge capacity and discharge capacity of the battery are different depending on the battery aging state (Soh). The optimal capacity calculation model (2) according to the embodiment learns the optimal charge capacity and discharge capacity according to the battery aging state, receives the battery status of the portable sterilizer, and calculates the optimal charge capacity and discharge capacity. Through this, self-generation and battery charge / discharge control can be performed according to the optimal capacity based on the battery status installed in the portable sterilizer.

[0056] The self-generation control model (3) controls the self-generation of the solar module according to the ambient light and battery status, and adjusts the system to generate maximum power from sunlight. In the embodiment, the self-generation control model (3) maximizes the efficiency of the solar module and maximizes the use of its power generation capacity. In addition, it effectively manages the power stored in the energy storage panel of the solar module and the battery of the portable sterilizer, so that the power generated through self-generation can be stored and supplied when needed. Furthermore, the self-generation control model (3) generates and supplies power by considering the power usage patterns and requirements of the portable sterilizer.

[0057] The power generation prediction model (4) is a model that predicts the power generation of the solar modules installed in the portable sterilization device. In the embodiment, the power generation potential can be predicted based on environmental information including illuminance, weather information, and self-generation time.

[0058] A model in this specification may refer to any form of computer program that operates based on a network function, an artificial neural network, and / or a neural network. Throughout this specification, the terms model, neural network, network function, and neural network may be used interchangeably. A neural network is a network in which one or more nodes are interconnected through one or more links to form input node and output node relationships within the neural network. The characteristics of a neural network can be determined based on the number of nodes and links within the neural network, the correlation between the nodes and links, and the weight value assigned to each link. A neural network may be composed of a set of one or more nodes. A subset of the nodes constituting the neural network may constitute a layer.

[0059] A deep neural network (DNN) may refer to a neural network that includes multiple hidden layers in addition to an input layer and an output layer. A deep neural network may include a convolutional neural network (CNN), a recurrent neural network (RNN), an autoencoder, a generative adversarial network (GAN), a restricted boltzmann machine (RBM), a deep belief network (DBN), a Q network, a U network, a Siamese network, a generative adversarial network (GAN), a transformer, and the like. The description of the above-described deep neural network is merely an example, and the present disclosure is not limited thereto.

[0060] Neural networks can learn through at least one of the following methods: supervised learning, unsupervised learning, semi-supervised learning, self-supervised learning, or reinforcement learning. Neural network learning can be the process of applying knowledge to the neural network to perform a specific action.

[0061] Neural networks can be trained to minimize output errors. This process involves repeatedly inputting training data into the neural network, calculating the neural network output and target error for the training data, and backpropagating the neural network error from the output layer to the input layer to update the weights of each node in the neural network to reduce the error. In supervised learning, labeled data is used for each training data, while unsupervised learning uses unlabeled data. The amount of change in the connection weights of each updated node can be determined by the learning rate. The neural network's calculation of input data and backpropagation of errors can constitute a learning cycle (epoch). The learning rate can vary depending on the number of iterations in the neural network's training cycle. Additionally, to prevent overfitting, methods such as increasing the learning data, regularization, dropout that disables some nodes, and batch normalization layers can be applied.

[0062] In one embodiment, the model may borrow at least a portion of a transformer. The transformer may be composed of an encoder that encodes embedded data and a decoder that decodes the encoded data. The transformer may have a structure that receives a series of data and outputs a series of data of different types through encoding and decoding steps. In one embodiment, the series of data may be processed into a form operable by the transformer. The process of processing the series of data into a form operable by the transformer may include an embedding process. Expressions such as data tokens, embedding vectors, and embedding tokens may refer to data embedded in a form operable by the transformer.

[0063] To encode and decode a series of data, a transformer can utilize an attention algorithm to process the encoders and decoders within the transformer. An attention algorithm can refer to an algorithm that, for a given query, calculates the similarity for one or more keys, reflects this similarity in the values ​​corresponding to each key, and then weights and sums the values ​​to which the similarity is reflected to calculate an attention value.

[0064] Depending on how the query, key, and value are configured, various types of attention algorithms can be categorized. For example, if attention is obtained by setting the query, key, and value all to the same value, this could be a self-attention algorithm. If attention is obtained by reducing the dimensionality of the embedding vector to process a series of input data in parallel and then generating individual attention heads for each segmented embedding vector, this could be a multi-head attention algorithm.

[0065] In one embodiment, the transformer may be composed of modules that perform multiple multi-head self-attention algorithms or multi-head encoder-decoder algorithms. In one embodiment, the transformer may also include additional components other than attention algorithms, such as embedding, normalization, and softmax. Methods for constructing a transformer using attention algorithms may include methods disclosed in Vaswani et al., Attention Is All You Need, 2017 NIPS, which is incorporated herein by reference.

[0066] A transformer can be applied to various data domains, such as embedded natural language, segmented image data, and audio waveforms, to transform a series of input data into a series of output data. To transform data with various data domains into a series of data that can be input to a transformer, the transformer can embed the data. The transformer can process additional data that expresses the relative positional relationship or phase relationship between the series of input data. Alternatively, vectors expressing the relative positional relationship or phase relationship between the input data can be additionally reflected in the series of input data to embed the series of input data. In one example, the relative positional relationship between the series of input data may include, but is not limited to, word order within a natural language sentence, the relative positional relationship between each segmented image, and the time order of segmented audio waveforms. The process of adding information expressing the relative positional relationship or phase relationship between the series of input data may be referred to as positional encoding.

[0067] In one embodiment, the model may include, but is not limited to, at least one of a Recurrent Neural Network (RNN), a Long Short Term Memory (LSTM) network, a Deep Neural Network (DNN), a Convolutional Neural Network (CNN), and a Bidirectional Recurrent Deep Neural Network (BRDNN).

[0068] In one embodiment, the model may be a model trained using transfer learning. Transfer learning, in this context, refers to a learning method that pre-trains a large amount of unlabeled training data using semi-supervised or self-learning methods to obtain a pre-trained model for a first task, then fine-tunes the pre-trained model to suit a second task, and trains it on labeled training data using supervised learning to implement a target model.

[0069] Referring again to FIG. 6, the control unit (124) monitors the battery of the portable sterilizing device to collect battery status information including the amount of charge and the aging state (SoH, State of Health), and controls self-generation of the solar module based on at least one of the collected battery status information, operating information of the portable sterilizing device, power usage prediction information, and sensed ambient illuminance.

[0070] In an embodiment, the control unit (124) can collect expected power usage information through user input or analyze the usage pattern of the portable sterilizing device to calculate expected power usage information.

[0071] In an embodiment, the control unit (124) collects usage record data such as the operating time, operating cycle, and operating mode of the portable sterilizer to analyze the usage pattern. Thereafter, the usage record data is analyzed to identify the user's usage pattern. For example, the control unit (124) analyzes the usage record data to identify the time when the portable sterilizer is most frequently used and the time zone when power usage increases. Thereafter, the control unit (124) predicts power usage on an hourly or daily basis using a power consumption prediction model. In an embodiment, the control unit (124) calculates how much power the portable sterilizer is expected to use on a specific date and time. In an embodiment, the expected power usage information can be used by the control unit (124) to control self-generation. Specifically, the control unit (124) can communicate with the inverter of the solar module during a time zone when the expected power usage is high to adjust the output to the maximum point through MPPT (Maximum Power Point Tracking) control or increase the charge amount of the battery.

[0072] In the embodiment, the control unit (124) adjusts the output of the inverter of the solar module to the maximum point to generate the energy required to meet the current energy demand and simultaneously charge the battery. The control unit (124) protects the battery of the portable sterilizing device from overcharging or overdischarging depending on the state of the battery. To this end, the control unit (124) measures the internal resistance of the battery to calculate the state of aging (SoH) of the battery. Then, using the calculated state of aging (SoH) and the initial capacity of the battery, the charging capacity of the battery is calculated, and based on the calculated charging capacity and the charge amount of the battery, the charging requirement, which is the power to be used in the future, is calculated. Thereafter, the control unit (124) calculates the difference between the charging requirement and the battery charge amount as the power generation requirement through the solar module.

[0073] In the embodiment, the control unit (124) measures the power generated from the solar module through a power generation measuring device, and predicts the actual power generation of the solar module through a power generation prediction model by taking into account environmental conditions such as weather, amount of sunlight, and temperature. The power generation prediction model can collect environmental conditions through an illuminance sensor and a weather service server.

[0074] Additionally, in the embodiment, the control unit (124) calculates the required charging amount, which is the amount of power that needs to be charged, by considering the battery status, such as the battery's charge level and aging status. Thereafter, the self-generation time of the solar module can be calculated by considering the predicted power generation amount and the required charging amount.

[0075] For example, the control unit (124) can calculate the charging requirement, which is the amount of power required to maintain the battery in an optimal state or to use energy at a specific time period, based on the current state, capacity, and user needs of the battery.

[0076] Specifically, the control unit (124) can calculate the charging amount required according to mathematical expression 1.

[0077] Mathematical formula 1

[0078] Charge Required =

[0079] Target battery SOC (State of Charge)Current battery SOC + Self-Generation

[0080] In this embodiment, the target battery State of Charge (SOC) is the target charge level, which indicates how much the battery should be charged. For example, to charge the battery to 80%, the target SOC is 0.8. The current battery SOC is the SOC value indicating the current battery charge level. Self-generation refers to the amount of power generated by the solar module. The self-generation value represents the amount of power generated during a specific period and may vary by time zone.

[0081] Additionally, the control unit (124) compares the predicted power generation with the amount of power that needs to be charged to determine whether the power generation is sufficient for each time zone. If the power generation exceeds the required charging amount, the corresponding time zone is designated as a time zone where self-generation is possible. In the embodiment, after determining whether self-generation is possible for each time zone, the sum of these time zones is calculated to calculate the self-generation time of the solar module. The self-generation time refers to the time period during which the solar module can generate power on its own.

[0082] In addition, if the battery charge amount at the time of use is less than the expected power usage, the control unit (124) controls the self-generation of the solar module to charge an amount of power corresponding to the difference between the expected power usage and the battery charge amount.

[0083] To this end, the control unit (124) checks the current battery charge state through a battery management system (BMS) or battery monitoring equipment. The battery charge state indicates the current battery state of charge (SOC) and is used to calculate the required charging amount. The control unit (124) then calculates the expected power consumption at the time of use of the portable sterilization device. Furthermore, the control unit (124) compares the expected power consumption with the current battery state of charge (SOC) to calculate the required charging amount, which is the insufficient power. The required charging amount is the additional energy that must be charged to the battery.

[0084] Thereafter, in the embodiment, the control unit (124) monitors the power generation amount of the solar module. At this time, the control unit (124) collects the amount of power generated from the solar module, and if the amount of power generated from the solar module, which is the self-generation amount, does not meet the charging requirement, the control unit (124) transmits a maximum output signal to the inverter of the solar module, and the inverter adjusts the output of the solar module to the maximum point through MPPT (Maximum Power Point Tracking) control. In addition, in the embodiment, the battery can be charged with the power stored in the energy storage panel of the solar module.

[0085] In this embodiment, the inverter of a solar module tracks the maximum power point (MPPT) using an MPPT algorithm. The MPPT algorithm is a model that tracks the operating point of a solar panel to achieve maximum output under current environmental conditions. The MPPT algorithm monitors the output power by gradually adjusting the panel's voltage or current over a given time interval, and detects the maximum power point.

[0086] In addition, in the embodiment, the control unit (124) controls the self-generation of the solar module according to the surrounding environmental information. For example, the control unit (124) starts the self-generation of the solar module when the surrounding illuminance exceeds a certain value and the battery charge is less than the full capacity. In the embodiment, when the battery is fully charged but the surrounding illuminance exceeds a certain value and the power generation efficiency of the solar module exceeds a certain level, the self-generation starts, and the power generated by the self-generation is stored in the battery of the solar module.

[0087] In addition, in the embodiment, the control unit (124) calculates an optimal capacity including an optimal charge capacity and discharge capacity according to the temperature and aging state (SoH) of the battery, and controls self-generation of the solar module based on the calculated optimal capacity, charge amount, and expected power usage.

[0088] To this end, the control unit (124) models the characteristics of the battery in use to calculate the optimal capacity. In an embodiment, the control unit (124) models the battery characteristics through a mathematical model that takes into account the temperature, state of aging (SoH), capacity characteristics, etc. of the battery. Thereafter, the control unit (124) obtains the temperature and state of aging (SoH) of the battery through a sensor or algorithm that measures the internal temperature of the battery and estimates the state of aging (SoH). Thereafter, the control unit (124) calculates the optimal charge and discharge capacity through the optimal capacity calculation model based on the battery model and the current temperature and state of aging (SoH) information.

[0089] Thereafter, the control unit (124) collects the expected power usage according to the operational goals set by the system operator and monitors the amount of power generated from the solar panel. Thereafter, the control unit (124) determines whether the solar module is self-generating and whether energy is charged and stored. In an embodiment, the control unit (124) regulates charging and discharging to maintain a balance between the expected power usage and the self-generation amount. For example, if the charging amount exceeds the expected power usage, the control unit (124) stores the remaining energy in the energy storage panel of the solar module for later use.

[0090] In addition, the control unit (124) monitors the real-time power consumption and power consumption change amount of the portable sterilizing device and starts self-generation according to the power consumption and power consumption change amount. For example, the control unit (124) controls the solar module to start self-generation in the solar module when the power consumption or power consumption change amount exceeds a set threshold, such as when steam is continuously sprayed at a certain level or higher for a certain period of time in the portable sterilizing device or when high-temperature steam is generated, and the solar module is not operating. In an embodiment, the control unit (124) controls the solar module to start self-generation and generate power regardless of the battery charge amount (SoC) when the real-time power consumption or power consumption change amount exceeds a preset value.

[0091] To this end, the control unit (124) monitors the power usage of the portable sterilizing device in real time and calculates the change in power usage. Thereafter, the control unit (124) compares the current power usage and the change in power usage with a set threshold value (pre-set value). If the current power usage or the change in power exceeds the set threshold value, this indicates a situation in which excessive power supply is required. In other words, if the current power usage or the change in power exceeds the set threshold value, it indicates a situation in which the battery is rapidly discharging, and therefore, the control unit (124) enables self-generation to start regardless of the battery's state of charge (SoC).

[0092] In an embodiment, the control unit (124) senses the ambient illuminance in a situation where the battery discharge is rapidly progressing, and if the ambient illuminance exceeds a certain level and at least one of the power usage, the power usage change amount, and the battery discharge amount exceeds a certain level, the control unit (124) transmits a maximum output signal to the inverter of the solar module, and the inverter adjusts the output of the solar module to the maximum point through MPPT (Maximum Power Point Tracking) control. In an embodiment, if the ambient illuminance or temperature is below a certain level in a situation where the battery discharge is rapidly progressing, the control unit (124) predicts the amount of power to be used for self-generation through the solar module, and if the predicted amount of power is below a certain level, the control unit (124) transmits a maximum output signal to the inverter of the solar module, and the inverter adjusts the output of the solar module to the maximum point through MPPT (Maximum Power Point Tracking) control. In addition, in an embodiment, the control unit (124) starts charging the battery through the energy storage panel of the solar module when the ambient illuminance and the temperature are below a certain level and the amount of power to be used for self-generation exceeds a certain level.

[0093] In addition, the control unit (124) calculates the power generation efficiency of the solar module according to environmental information including the surrounding illuminance, and determines the driving amount and output amount of the solar module according to the calculated power generation efficiency. In an embodiment, the power generation efficiency may include the ratio of the power production amount of the solar module and the energy consumed to produce the corresponding power. Since the power generation efficiency is high when the illuminance and solar radiation are high, in the embodiment, the control unit (124) can calculate the driving time and output amount of the solar module according to the charging requirement and the power generation efficiency.

[0094] To this end, the control unit (124) calculates the power generation efficiency of the solar module according to the current illuminance and irradiance, and calculates an expected power generation amount through a power generation prediction model by considering that the efficiency of the module is high under conditions of high illuminance and irradiance. Thereafter, the operating time and output amount of the solar module are calculated based on the charging requirement and the power generation efficiency. Thereafter, the control unit (124) manages the operation of the solar module based on the calculated operating time and output amount information. In an embodiment, the control unit (124) activates the self-generation of the solar module at times of high illuminance and high irradiance, and operates the solar module only until the required output amount is produced, thereby enabling efficient operation of the solar module.

[0095] A portable sterilizing device equipped with a self-generation function according to an embodiment adjusts whether or not self-generation is performed and the amount of charge by self-generation according to the battery charge level, thereby enabling the portable sterilizing device that sprays steam to be used at any time.

[0096] Additionally, the embodiment provides a self-powering module utilizing solar energy, controlling whether and how much self-power is generated based on ambient lighting and the remaining battery capacity of the portable sterilizer, thereby improving charging efficiency. Furthermore, the embodiment sprays ozone-containing sterilizing water in a mist form, enabling rapid sterilization of indoor objects and areas exposed to the coronavirus (SARS-CoV-2).

[0097] The disclosed content is merely an example, and various modifications and implementations can be made by a person skilled in the art without departing from the gist of the claims claimed in the patent, so the scope of protection of the disclosed content is not limited to the specific embodiments described above.

Claims

1. In a portable sterilization device, A solar module that generates electricity through self-generation using solar energy and charges an energy storage panel or a battery of the portable sterilizing device with the generated electricity; A light sensor that senses ambient light; and A charging control device that controls self-generation of the solar module and charging of the battery; The above charging control device; a memory storing at least one instruction; and Includes a processor, By executing at least one instruction by the processor, A portable sterilizing device that monitors the battery of the portable sterilizing device to collect battery status information including the amount of charge and the aging state (SoH, State of Health), and controls self-generation of the solar module based on at least one of the collected battery status information, operating information of the portable sterilizing device, expected power usage, and sensed ambient illuminance.

2. In the first paragraph, the portable sterilizing device; A portable sterilizing device characterized in that the state of aging (SoH) of the battery is calculated by measuring the internal resistance of the battery, the charging capacity of the battery is calculated using the calculated state of aging (SoH) and the initial capacity of the battery, the charging amount required, which is power to be used in the future, is calculated based on the calculated charging amount and the charging amount of the battery, and the difference between the charging amount required and the battery charging amount is calculated as the power generation amount required through a solar module.

3. In the first paragraph, the portable sterilizing device; A portable sterilizing device characterized in that a power consumption prediction model is trained using power consumption data by usage time, and operation information including the usage time of the portable sterilizing device is input into the power consumption prediction model to obtain the expected power usage of the portable sterilizing device.

4. In the third paragraph, the portable sterilizing device; A portable sterilizing device characterized in that, when the battery charge at the time of use is less than the expected power usage, the self-generation of the solar module is controlled to charge an amount of power corresponding to the difference between the expected power usage and the battery charge.

5. In the first paragraph, the portable sterilizing device; A portable sterilizing device characterized in that it starts self-generation of a solar module when the ambient illuminance exceeds a certain value and the battery charge is less than the full capacity.

6. In the first paragraph, the portable sterilizing device; A portable sterilization device characterized in that it calculates an optimal capacity including an optimal charge capacity and discharge capacity according to the temperature and aging state (SoH) of the battery, and controls self-generation of a solar module based on the calculated optimal capacity, charge amount, and expected power usage.

7. In the first paragraph, the portable sterilizing device; A portable sterilizing device characterized in that, when the battery of the portable sterilizing device is fully charged and the ambient illuminance exceeds a certain level, power is stored through self-generation in the energy storage panel of the solar module.

Images