Fully-immersed power supply charging method and system

Abstract

The invention relates to the technical field of power supply charging, and discloses a fully-immersed power supply charging method and system, and the method comprises the steps: analyzing the charging feature information of power supply equipment; matching the charging feature information with historical charging data in a preset charging strategy library to obtain charging matching data, and calculating a charging integrating degree of an adaptive charging strategy and the charging state parameters; analyzing the charging type of the power supply equipment, performing strategy retrieval on the adaptive charging strategy to obtain a retrieved charging strategy, formulating a charging supply plan of the power supply equipment, analyzing a professional supply path in the charging supply plan, and generating a charging control instruction of the power supply equipment; positioning an optimal energy charging path of the power supply equipment, detecting real-time physical state parameters of a charging medium of the power supply equipment, and calculating an energy efficiency conversion rate of the charging medium in the optimal energy charging path; and formulating a fully-immersed charging scheme adaptive to the power supply equipment. According to the invention, the charging efficiency of the fully-immersed power supply can be improved.

Description

Technical Field

[0001] The present invention relates to a fully immersed power charging method and system, belonging to the technical field of power charging. Background Art

[0002] Charging the power supply is a key support for the stable operation of the device. At present, the charging field mainly adopts technologies such as conventional contact charging, wireless inductive charging, and liquid cooling assisted charging. Conventional contact charging realizes power transmission through simple physical connection, but its charging interface is prone to wear, and there are safety hazards in humid or special environments. The charging efficiency is also difficult to meet the fast charging requirements of high-power devices. Wireless inductive charging gets rid of the cable bondage and is convenient to use. However, the transmission distance is short, the efficiency is low, and it is greatly affected by foreign object interference, making it difficult to achieve stable and efficient charging. Although liquid cooling assisted charging can solve the heat dissipation problem during charging and improve the charging power to a certain extent, the cooling system is complex and the cost is high, and it cannot comprehensively improve the charging performance. In addition, in occasions with strict requirements for charging safety and space layout, the existing charging technologies cannot meet the high-efficiency charging requirements of devices in a fully immersed environment. Therefore, an efficient fully immersed power charging method is needed. Summary of the Invention

[0003] The present invention provides a fully immersed power charging method and system, and its main purpose is to improve the efficiency of fully immersed power charging.

[0004] To achieve the above purpose, a fully immersed power charging method provided by the present invention includes: Obtaining the device parameter information of the power supply device to be charged, and analyzing the charging characteristic information of the power supply device based on the device parameter information; Matching the charging characteristic information with the historical charging data in the preset charging strategy library to obtain charging matching data, querying the adapted charging strategy in the charging matching data, and real-time monitoring the charging state parameters of the power supply device during the charging process, and calculating the charging fit degree between the adapted charging strategy and the charging state parameters; Analyzing the charging type of the power supply device based on the charging fit degree, retrieving the adapted charging strategy based on the charging type to obtain a retrieved charging strategy, and extracting the core charging operation key points in the retrieved charging strategy; Formulating a charging supply plan for the power supply device based on the core charging operation key points, analyzing the professional supply path in the charging supply plan, and querying the charging supply criterion corresponding to the professional supply path, and generating a charging control instruction for the power supply device based on the charging supply criterion; Based on the charging control instruction, locate the optimal charging path of the power supply device, detect the real-time physical state parameters of the charging medium of the power supply device, and calculate the energy efficiency conversion rate of the charging medium in the optimal charging path based on the real-time physical state parameters; Record the charging waveform of the power supply device during the charging process, and formulate a full-immersion charging scheme adapted to the power supply device in combination with the energy efficiency conversion rate and the charging waveform.

[0005] Optionally, analyzing the charging characteristic information of the power supply device based on the device parameter information includes: Identify the parameter tags corresponding to the device parameter information, and query the charging standard protocol and device identifier corresponding to the power supply device; Analyze the tag coupling between the parameter tags and the charging standard protocol; Based on the device identifier, analyze the device characteristics corresponding to the power supply device, and based on the device characteristics, analyze the tag logical relationship between the parameter tags; Combine the tag coupling and the tag logical relationship to analyze the charging characteristic information of the power supply device from the device parameter information.

[0006] Optionally, the analyzing the tag coupling between the parameter tags and the charging standard protocol includes: Perform characterization extraction on the parameter tags to obtain parameter tag characterizations, and construct a tag characterization vector corresponding to the parameter tag characterizations; Perform text parsing processing on the charging standard protocol to obtain key protocol terms; Perform vectorization processing on the key protocol terms to obtain key protocol term vectors; Combine the tag characterization vector and the key protocol term vector, and calculate the coupling coefficient between the parameter tags and the charging standard protocol through the following formula: ; Where A represents the coupling coefficient between the parameter tags and the charging standard protocol, represents the tag characterization vector corresponding to the a-th tag in the parameter tags, represents the key protocol term vector corresponding to the b-th protocol in the charging standard protocol, a and b respectively represent the serial numbers corresponding to the parameter tags and the charging standard protocol, and m and n respectively represent the quantities corresponding to the parameter tags and the charging standard protocol; Based on the coupling coefficient, analyze the tag coupling between the parameter tags and the charging standard protocol.

[0007] Optionally, the calculating the charging fitness between the adapted charging strategy and the charging state parameters includes: Query the charging timing link corresponding to the power supply device, and determine the charging transmission attribute corresponding to the power supply device based on the charging timing link; Allocate the state weight corresponding to each charging state in the charging state parameter based on the charging transmission attribute; Determine the state setting value corresponding to each charging state in the charging state parameter based on the adapted charging strategy; Calculate the charging fit degree between the adapted charging strategy and the charging state parameter by combining the charging state parameter, the state setting value, and the state weight.

[0008] Optionally, the calculating the charging fit degree between the adapted charging strategy and the charging state parameter by combining the charging state parameter, the state setting value, and the state weight includes: ; where E represents the charging fit degree between the adapted charging strategy and the charging state parameter, represents the state weight of the d-th charging state in the charging state parameter, represents the state setting value of the d-th charging state in the charging state parameter, represents the actual measured value of the d-th charging state in the charging state parameter, d represents the charging state serial number of the charging state parameter, q represents the number of charging states of the charging state parameter, represents the maximum value of the d-th charging state in the actual measured value, represents the minimum value of the d-th charging state in the actual measured value.

[0009] Optionally, the analyzing the charging type of the power supply device based on the charging fit degree includes: Determine the charging priority of the power supply device based on the charging fit degree; Analyze the battery characteristics of the battery used by the power supply device and the current device usage scenario; Extract the key scene features of the current device usage scenario, and analyze the core charging requirements corresponding to the key scene features; Determine the charging type of the power supply device based on the core charging requirements, the battery characteristics, and the charging priority.

[0010] Optionally, the extracting the core charging operation key points in the retrieved charging strategy includes: Analyze the strategy structure corresponding to the retrieved charging strategy, and determine the key operation steps in the strategy based on the strategy structure; Extract the charging parameters in the key operation steps, and identify the device charging stage and device status corresponding to the key operation steps; Combine the device charging stage and the device status, and perform an adaptability adjustment on the charging parameters to obtain adapted charging parameters; Based on the adapted charging parameters, extract the core charging operation key points in the retrieved charging strategy.

[0011] Optionally, the generating the charging control instruction for the power supply device based on the charging supply criterion includes: Analyze the criterion execution specification corresponding to the charging supply criterion; Based on the criterion execution specification, determine the charging execution level corresponding to the power supply device; According to the charging execution level, refine the charging execution process corresponding to the power supply device; Based on the charging execution process, build the charging control framework corresponding to the power supply device; Based on the charging control framework, generate the charging control instruction for the power supply device.

[0012] Optionally, the calculating the energy efficiency conversion rate of the charging medium in the optimal energy charging path based on the real-time physical state parameters includes: Perform noise reduction processing on the real-time physical state parameters to obtain noise-reduced physical state parameters; Based on the noise-reduced physical state parameters, construct the medium energy efficiency state tensor of the charging medium; Perform an energy charging thermodynamic simulation on the medium energy efficiency state tensor to obtain the path energy distribution cloud map of the charging medium in the optimal energy charging path; Perform gradient field domain segmentation on the path energy distribution cloud map to obtain an energy gradient partition map; Identify the energy strong gradient intervals in the energy gradient partition map, and quantify the effective energy transmission flux and polarization loss flux in the energy strong gradient intervals; Based on the effective energy transmission flux and the polarization loss flux, calculate the energy efficiency conversion rate of the charging medium in the optimal energy charging path.

[0013] To solve the above problems, the present invention also provides a fully submerged power supply charging system, and the system includes: A charging characteristic information analysis module, configured to obtain the device parameter information of the power supply device to be charged, and analyze the charging characteristic information of the power supply device based on the device parameter information; The charging compatibility calculation module is used to match the charging feature information with the historical charging data in the preset charging policy library to obtain charging matching data, query the adapted charging policy in the charging matching data, and real-time monitor the charging status parameters of the power device during the charging process, and calculate the charging compatibility between the adapted charging policy and the charging status parameters; The core charging operation key point extraction module is used to analyze the charging type of the power device based on the charging compatibility, perform policy retrieval on the adapted charging policy based on the charging type to obtain the retrieved charging policy, and extract the core charging operation key points in the retrieved charging policy; The charging control instruction generation module is used to formulate the charging replenishment plan of the power device based on the core charging operation key points, analyze the professional replenishment path in the charging replenishment plan, query the charging replenishment criterion corresponding to the professional replenishment path, and generate the charging control instruction of the power device based on the charging replenishment criterion; The energy efficiency conversion rate calculation module is used to locate the optimal energy charging path of the power device based on the charging control instruction, detect the real-time physical state parameters of the charging medium of the power device, and calculate the energy efficiency conversion rate of the charging medium in the optimal energy charging path based on the real-time physical state parameters; The fully immersed charging scheme formulation module is used to record the charging waveform of the power device during the charging process, and formulate a fully immersed charging scheme adapted to the power device in combination with the energy efficiency conversion rate and the charging waveform.

[0014] Compared with the problems described in the background art, the present invention analyzes the charging characteristic information of the power supply device based on the device parameter information, and can convert complex and numerous parameters into clear and highly targeted charging guidance information, laying an important basis for subsequent processing. Further, the present invention matches the charging characteristic information with the historical charging data in the preset charging strategy library to obtain charging matching data, which can deeply analyze the charging requirements of the power supply device, query the adapted charging strategy in the charging matching data, greatly improve the accuracy and efficiency of charging management, and provide a better and more practical charging service experience for the power supply device. Based on the charging compatibility, the present invention analyzes the charging type of the power supply device, can accurately grasp the actual state and requirements during the charging process of the power supply device, helps the charging management system provide a highly adapted charging strategy for the power supply device, improves the charging efficiency, ensures the device safety, extends the battery service life, and optimizes the overall charging service experience. Further, the present invention formulates the charging supply plan for the power supply device based on the core charging operation points, can significantly optimize the charging process, fully meet the charging requirements of the power supply device under different usage scenarios and performance requirements, and effectively improve the charging efficiency. Further, the present invention locates the optimal charging path of the power supply device based on the charging control instruction, can improve the charging efficiency, greatly shorten the charging duration, reduce the energy loss during charging, effectively protect the battery health, and reduce the risk of device failures caused by charging. The present invention formulates a full-immersion charging scheme adapted to the power supply device by combining the energy efficiency conversion rate and the charging waveform, can significantly improve the charging efficiency, reduce the energy loss during charging, reduce the charging time, and thus improve the high efficiency of full-immersion power charging. Therefore, the full-immersion power charging method and system provided by the embodiments of the present invention can improve the high efficiency of full-immersion power charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic flowchart of a full-immersion power charging method provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of modules for implementing the full-immersion power charging method provided by an embodiment of the present invention.

[0016] The implementation, functional features, and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] An embodiment of the present application provides a fully immersed power charging method. The execution subject of the fully immersed power charging method includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the fully immersed power charging method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc.

[0019] Embodiment 1: Refer to Figure 1 As shown, it is a schematic flowchart of the fully immersed power charging method provided by an embodiment of the present invention. In this embodiment, the fully immersed power charging method includes: S1. Obtain the device parameter information of the power device to be charged, and based on the device parameter information, analyze the charging characteristic information of the power device.

[0020] By analyzing the charging characteristic information of the power device based on the device parameter information, the present invention can convert complex and numerous parameters into clear and highly targeted charging guidance information, laying an important basis for subsequent processing. Among them, the power device includes various devices that need external charging, with a wide range of sources, including both portable electronic devices such as mobile phones and tablet computers, and large power-consuming devices such as electric vehicles and power tools; the device parameter information involves multiple aspects, such as the rated voltage, indicating the voltage value required for the device to work normally; the rated current, determining the maximum current allowed to pass through the device during charging; the battery capacity, reflecting how much electrical energy the device can store; the charging interface type, determining the types of charging cables and charging devices that are compatible with it. The charging characteristic information refers to the clear, systematic, and practical interpretation results of the charging requirements and characteristics of the power device obtained through the analysis and integration of the device parameter information, which can clarify the key requirements for device charging, such as the charging power range, the estimated charging duration, the charging temperature limit, etc.

[0021] As an embodiment of the present invention, the analyzing the charging characteristic information of the power device based on the device parameter information includes: Identify the parameter tags corresponding to the device parameter information, and query the charging standard protocol and device identifier corresponding to the power device; Analyze the tag coupling between the parameter tags and the charging standard protocol; Based on the device identifier, analyze the device characteristics corresponding to the power device, and based on the device characteristics, analyze the tag logic relationship between the parameter tags; Combine the tag coupling and the tag logic relationship to analyze the charging characteristic information of the power device from the device parameter information.

[0022] Among them, the parameter tag is the name identifier corresponding to the device parameter information, which is used to classify and refer to the parameters; the charging standard protocol and the device identifier are respectively the charging specification criteria and identity identification corresponding to the power supply device; the tag coupling is the degree of mutual dependence and mutual influence between the parameter tag and the charging standard protocol; the device characteristics are the inherent attributes and functional characteristics corresponding to the power supply device; the tag logical relationship is the inherent connection between parameter tags that conforms to certain rules.

[0023] Further, the parameter tag corresponding to the device parameter information can be identified by a tag identification tool, the tag identification tool being compiled by a programming language; the charging standard protocol and device identification corresponding to the power supply device can be queried through the device manual; Identify the functional description content in the device identification, and analyze the device characteristics corresponding to the power supply device according to the functional description content; based on the device characteristics, analyze the label logical relationship between the parameter labels, such as using a semantic analysis model to sort out the implication, cause and effect, parallel and other associations between the labels, and explore the intrinsic connection between parameter labels in describing dimensions such as device charging requirements, status and performance, so as to lay a solid foundation for the subsequent accurate analysis of charging feature information; combine the label coupling and the label logical relationship, and analyze the charging feature information of the power supply device from the device parameter information, for example, by constructing a label relationship map, quantitatively analyzing the association strength of different labels, and deriving charging feature information such as the charging voltage and current adaptation range, the optimal charging time, and the temperature control requirements during the charging process based on the label logic.

[0024] Further, as an optional embodiment of the present invention, the analyzing the tag coupling between the parameter tag and the charging standard protocol includes: Extracting the parameter label representation to obtain the parameter label representation, and constructing a label representation vector corresponding to the parameter label representation; Performing text parsing on the charging standard agreement to obtain key terms of the agreement; Performing vector processing on the key terms of the agreement to obtain a key terms vector of the agreement; Combining the label characterization vector and the protocol key clause vector, the coupling coefficient between the parameter label and the charging standard protocol is calculated by the following formula: ; Where A represents the coupling coefficient between the parameter label and the charging standard protocol, Represents the label representation vector corresponding to the ath label in the parameter label, It represents the protocol key clause vector corresponding to the b-th protocol in the charging standard protocol. a and b respectively represent the parameter label and the serial number corresponding to the charging standard protocol, and m and n respectively represent the parameter label and the quantity corresponding to the charging standard protocol. Based on the coupling coefficient, analyze the label coupling between the parameter label and the charging standard protocol.

[0025] Among them, the parameter label represents the numerical feature description of the parameter label; the label representation vector is the multi-dimensional feature vector corresponding to the parameter label representation; the protocol key clause is the technical index and operation specification defined in the charging standard protocol; the protocol key clause vector is the quantization coding vector of the protocol key clause.

[0026] Furthermore, the parameter label representation can be extracted through feature engineering methods to obtain the parameter label representation; the label representation vector corresponding to the parameter label representation can be constructed through a vector space model; the charging standard protocol can be parsed through natural language processing technology to obtain the protocol key clause; the protocol key clause can be vectorized through a word embedding algorithm to obtain the protocol key clause vector; based on the coupling coefficient, the label coupling between the parameter label and the charging standard protocol is analyzed through a correlation analysis algorithm. The higher the coupling coefficient, the stronger the correlation between the two in the label dimension and the higher the label coupling; conversely, the lower the coupling coefficient, the lower the label coupling.

[0027] S2. Match the charging feature information with the historical charging data in the preset charging strategy library to obtain charging matching data, query the adapted charging strategy in the charging matching data, and monitor the charging status parameters of the power device during the charging process in real time, and calculate the charging fit degree between the adapted charging strategy and the charging status parameters.

[0028] By matching the charging feature information with the historical charging data in the preset charging strategy library, the present invention can obtain charging matching data, deeply analyze the charging requirements of the power device, query the adapted charging strategy in the charging matching data, greatly improve the accuracy and efficiency of charging management, and provide a better and more practical charging service experience for the power device.

[0029] Among them, the preset charging strategy library refers to a systematically organized and constructed database storing a large amount of knowledge and data related to the charging field, including the standard charging curves of different types of power supply devices, the optimal charging strategies under various charging scenarios, such as the applicable conditions and operation specifications of fast charging, slow charging, constant voltage charging, constant current charging and other strategies; the charging matching data refers to the part of historical charging data extracted from the matching relationship set and closely related to the current charging characteristic information. These data contain key information in past similar charging cases. The adapted charging strategy is the charging method in the charging matching data. Further, the charging characteristic information can be matched with the historical charging data in the preset charging strategy library through a matching algorithm to obtain the charging matching data, such as the fuzzy matching algorithm; the adapted charging strategy can be obtained by querying the strategy information recorded in the charging matching data.

[0030] The present invention calculates the charging fitness degree between the adapted charging strategy and the charging state parameters, can judge whether the charging strategy is reasonable, promptly detect charging anomalies, and then flexibly adjust the charging strategy according to the charging fitness degree, providing a more demand-oriented and personalized charging service for the power supply device, greatly improving the effectiveness of the charging service and the safety of the device. Among them, the charging state parameters refer to a series of quantitative indicators that can reflect the current charging state characteristics and performance of the power supply device during the charging process. These parameters can be measured from multiple dimensions, including but not limited to charging current, charging voltage, battery temperature, remaining charging time, charging progress, etc. The charging fitness degree is a quantitative indicator used to measure the degree of fit between the adapted charging strategy and the charging state parameters. The larger the value, the better the fit between the adapted charging strategy and the charging state parameters, that is, the current charging strategy can better meet the actual state and requirements of the power supply device during the charging process; the smaller the value, the worse the fit. Further, the charging state parameters of the power supply device are obtained in real time through sensors and data acquisition systems.

[0031] As an embodiment of the present invention, calculating the charging fitness degree between the adapted charging strategy and the charging state parameters includes: Query the charging time sequence link corresponding to the power supply device, and determine the charging transmission attribute corresponding to the power supply device based on the charging time sequence link; Based on the charging transmission attribute, assign a state weight to each charging state in the charging state parameters; Based on the adapted charging strategy, determine the state setting value corresponding to each charging state in the charging state parameters; Combine the charging state parameters, the state setting value and the state weight to calculate the charging fitness degree between the adapted charging strategy and the charging state parameters.

[0032] Among them, the charging timing link is the charging stage division corresponding to the power supply device; the charging transmission attribute is the unique electrical transmission property corresponding to the power supply device; the state weight is the evaluation weight coefficient corresponding to each charging state in the charging state parameters; the state set value is the parameter target value corresponding to the charging state parameters determined based on the adapted charging strategy.

[0033] Furthermore, the charging timing link corresponding to the power supply device can be queried through the built-in charging information recording module or the charging management system of the device; based on the charging timing link, the charging transmission attribute corresponding to the power supply device is determined. For example, in the fast charging stage, the charging transmission attribute usually shows high current input and relatively large charging power, enabling electric energy to be quickly transmitted to the power supply device in a short time, significantly shortening the charging duration; based on the charging transmission attribute, the state weight corresponding to each charging state in the charging state parameters is allocated. If the charging transmission attribute indicates that it is in the fast charging stage, in order to balance quickly replenishing the battery and the long-term health of the battery, a higher weight is given to the charging state that can ensure the battery does not overheat and maintain reasonable voltage and current. For example, the weight of the charging state that can adjust the current in real time to prevent the battery from being damaged by high current heating is set to 0.8; for the charging state that may exacerbate battery loss, such as the state of continuous high current and unstable voltage, the weight is set to 0.2. In the slow charging stage, a high weight is given to the state that helps the battery to charge evenly and extend its life, such as the state of small amplitude fluctuation and stable low current charging; the recorded state values in the adapted charging strategy are retrieved, and each state value is used as the state set value corresponding to the charging state parameters.

[0034] Furthermore, as an optional embodiment of the present invention, calculating the charging fit degree between the adapted charging strategy and the charging state parameters by combining the charging state parameters, the state set values, and the state weights includes: ; where E represents the charging fit degree between the adapted charging strategy and the charging state parameters, represents the state weight of the d-th charging state in the charging state parameters, represents the state set value of the d-th charging state in the charging state parameters, represents the actual measured value of the d-th charging state in the charging state parameters, d represents the charging state serial number of the charging state parameters, q represents the number of charging states of the charging state parameters, represents the maximum value of the d-th charging state in the actual measured value of the charging state parameters, represents the minimum value of the d-th charging state in the actual measured value of the charging state parameters.

[0035] S3. Analyze the charging type of the power supply device based on the charging compatibility. Based on the charging type, perform a strategy retrieval on the adaptive charging strategy to obtain a retrieved charging strategy, and extract the core charging operation key points in the retrieved charging strategy.

[0036] Based on the charging compatibility, the present invention analyzes the charging type of the power supply device, which can accurately grasp the actual state and requirements during the charging process of the power supply device, assist the charging management system to provide a highly adaptable charging strategy for the power supply device, improve the charging efficiency, ensure the device safety, extend the battery service life, optimize the overall charging service experience. Among them, the charging type refers to the category definition of the current charging demand of the power supply device after comprehensively considering various information such as charging compatibility, power supply device type, battery characteristics, and charging scenario, such as emergency fast charging type, balanced maintenance type, conventional slow charging type, etc.

[0037] As an embodiment of the present invention, the analysis of the charging type of the power supply device based on the charging compatibility includes: Determine the charging priority of the power supply device based on the charging compatibility; Analyze the battery characteristics of the battery used by the power supply device and the current device usage scenario; Extract the key features of the current device usage scenario, and analyze the core charging requirements corresponding to the key features of the scenario; Determine the charging type of the power supply device based on the core charging requirements, the battery characteristics, and the charging priority.

[0038] Among them, the charging priority is determined based on the interval of the charging compatibility, which reflects the urgency of the current charging demand of the power supply device. If the charging compatibility is in the highly compatible interval, it means that the current charging strategy is relatively adaptable and the charging urgency is relatively low; on the contrary, if the charging compatibility is in the low compatibility interval, it indicates that the charging strategy needs to be adjusted and the charging urgency is relatively high; the current device usage scenario is the usage environment of the power supply device; the key features of the charging scenario are the information set reflecting the characteristics of the charging environment, device usage status, etc. in the current device usage scenario, including whether the charging location is portable, whether the power supply device is in use, whether the remaining power can meet the short-term demand, etc.; the core charging requirement refers to the charging requirement that plays a decisive role in determining the charging type extracted from the key features of the charging scenario. For example, when the power supply device is outdoors and the power is extremely low and urgently needs to recover a certain amount of power in a short time, the core charging requirement is emergency fast charging.

[0039] Furthermore, divide the charging compatibility into corresponding intervals by the equal-distance division method or the clustering algorithm based on machine learning, and determine the charging priority of the power supply device according to the compatibility interval. By integrating machine learning algorithms and big data analysis techniques, it is possible to collect the performance data of the battery during different charge-discharge cycles, as well as the environmental parameters and operating load data in the device usage scenario. By using clustering algorithms and association rule mining techniques, the battery characteristics can be accurately characterized, the device usage scenario patterns can be identified, and the battery characteristics of the battery used by the power device and the current device usage scenario can be analyzed. The key scene features of the current device usage scenario can be realized through a feature extraction model, such as extracting key features from the charging device feedback data and user operation information based on a convolutional neural network or a recurrent neural network. Analyzing the core charging requirements reflected by the key features can be achieved through a semantic understanding algorithm, such as using natural language processing technology to analyze the charging scenario description text and mine the core charging requirements. Based on the core charging requirements, the battery characteristics, and the charging priority, a multi-dimensional decision-making algorithm, such as comprehensively applying the analytic hierarchy process and fuzzy logic reasoning, is used to determine the charging type of the power device. For example, when the core charging requirement is to quickly replenish the battery power, the battery can tolerate high-power charging, and the charging priority is high, the weights of various factors are determined by means of the analytic hierarchy process, and then the charging scenario is comprehensively evaluated through fuzzy logic reasoning to determine that the device is suitable for the high-power fast charging type.

[0040] Based on the charging type, the present invention performs a strategy retrieval on the adapted charging strategy, which helps the charging management system quickly obtain the strategy that meets the charging requirements of the power device, avoids blindly screening among a large number of charging strategies, improves the accuracy and timeliness of the charging decision-making, and at the same time provides scientific guidance for subsequent charging operations, enhancing the user's satisfaction with the charging service.

[0041] Among them, the adapted charging strategy library refers to a pre-constructed and stored collection of charging strategies for different power devices and charging scenarios, which covers voltage and current regulation schemes for different charging stages, protection strategies for abnormal situations such as battery overheating and overcharging, and optimization strategies for improving charging efficiency and extending battery life. The retrieved charging strategy refers to the charging strategy selected from the adapted charging strategy library that highly matches the current charging type of the power device, and it includes a series of specific charging operation steps and parameter settings.

[0042] Optionally, the strategy retrieval of the adapted charging strategy can be achieved through a strategy indexing technique, such as using an index structure based on a hash table or an inverted index to quickly retrieve the adapted charging strategy library, so as to locate the relevant charging strategy.

[0043] The present invention extracts the core charging operation points from the retrieved charging strategy to assist the charging device in accurately executing the charging task, avoiding ineffective or incorrect operations, improving the stability and safety of the charging process, and at the same time providing clear and concise charging guidance for users. Among them, the core charging operation points refer to the key instructions and parameters that are further refined based on the retrieved charging strategy and can directly guide the charging device to perform effective charging. For example, in a certain fast charging strategy, the core charging operation points can be "constant current charging with a current of 2A in the initial stage, and when the battery voltage reaches 4.2V, switch to the constant voltage charging mode and maintain the voltage at 4.2V".

[0044] As an embodiment of the present invention, the extraction of the core charging operation points from the retrieved charging strategy includes: Analyze the strategy structure corresponding to the retrieved charging strategy, and based on the strategy structure, determine the key operation steps in the strategy; Extract the charging parameters in the key operation steps, and identify the device charging stage and device state corresponding to the key operation steps; Combine the device charging stage and the device state to perform an adaptability adjustment on the charging parameters to obtain adapted charging parameters; Based on the adapted charging parameters, extract the core charging operation points from the retrieved charging strategy.

[0045] Among them, the strategy structure refers to the organizational form and logical architecture of the retrieved charging strategy, including the process sequence of the strategy, conditional judgment branches, etc. For example, some charging strategies will select different charging paths according to the battery temperature; the key operation steps refer to the operation links that play a decisive role in achieving the charging goal in the retrieved charging strategy, such as the switching of the charging mode, the handling of abnormal situations, etc.; the charging parameters refer to the quantitative indicators such as voltage, current, and time involved in the key operation steps, which directly affect the charging effect; the adaptability adjustment refers to optimizing the charging parameters according to the real-time state and charging stage of the power supply device to ensure the safety and efficiency of the charging process. For example, when the battery temperature is too high, the charging current is appropriately reduced.

[0046] Furthermore, the policy structure corresponding to the analyzed retrieval charging policy can be implemented through a process mining tool. For example, use ProM or Disco to perform process analysis on the charging policy to determine the policy structure; the determination of the key operation steps in the policy can be implemented through a rule engine. For example, based on the preset key operation recognition rules, screen out the key operation steps from the policy process; the extraction of the charging parameters involved in the key operation steps can be implemented through a data parsing algorithm. For example, use regular expressions or JSON parsing technology to extract charging parameters from the policy text; the adaptation adjustment of the charging parameters can be implemented through a feedback control algorithm. For example, based on the real-time monitoring data of the power supply device, dynamically adjust the charging parameters; the extraction of the core charging operation key points in the retrieval charging policy can be implemented through a text summarization algorithm. For example, use LexRank or SumBasic to generate a summary of the charging policy text to determine the core charging operation key points.

[0047] S4. Based on the core charging operation key points, formulate a charging replenishment plan for the power supply device, analyze the professional replenishment path in the charging replenishment plan, query the charging replenishment criteria corresponding to the professional replenishment path, and generate a charging control instruction for the power supply device based on the charging replenishment criteria.

[0048] Through formulating a charging replenishment plan for the power supply device based on the core charging operation key points, the present invention can significantly optimize the charging process, comprehensively meet the charging requirements of the power supply device under different usage scenarios and performance requirements, and effectively improve the charging efficiency. Among them, the charging replenishment plan is a charging policy that is systematic and targeted, designed based on the real-time state, charging requirements of the power supply device, and the impact of various charging operations on the battery performance and charging process. Further, based on the core charging operation key points, formulating the charging replenishment plan for the power supply device, the specific planning steps are as follows: With the help of professional data analysis tools, deeply analyze the key parameters of the core charging operation key points from multiple dimensions, including the timing relationship between different key points, power demand characteristics, etc.; use machine learning algorithms to learn the past charging data and usage scenario data of the power supply device to construct a device charging characteristic model; based on the analysis results of the operation key points and the device charging characteristic model, generate multiple sets of charging plan pre-schemes adapted to the current state of the power supply device; subsequently, use a multi-objective optimization algorithm to comprehensively consider multiple dimensions of goals such as charging efficiency, battery health loss, and device usage requirements, and screen and optimize the charging plan pre-schemes to form a scientific, reasonable, and practical charging replenishment plan for the power supply device.

[0049] By analyzing the professional supply path in the charging supply plan and querying the charging supply criteria corresponding to the professional supply path, on the one hand, the present invention can help the charging management system promptly detect potential problems in the charging path and optimize and adjust them; on the other hand, with the charging supply criteria as a reference, the safety and standardization of the charging process can be ensured, the reliability of the charging service can be improved, and the power supply equipment can be assisted to successfully achieve the charging goal.

[0050] Among them, the professional supply path refers to a series of ordered charging operation steps and strategies planned by the charging management system for the power supply equipment to achieve the charging supply plan. For example, for mobile phone charging, the professional supply path may be to first perform constant current charging, and when the battery voltage reaches a certain value, switch to constant voltage charging until it is full; the charging supply criteria are a series of standards and specifications formulated in the charging field to ensure charging safety, efficiency, and standardize charging behaviors, covering battery safety standards, such as regulations to prevent overcharging and over-discharging; charging efficiency optimization requirements, such as methods to improve the utilization rate of charging power; and equipment compatibility specifications to ensure that the charging equipment is compatible with the power supply equipment. Optionally, the analysis of the professional supply path in the charging supply plan can be achieved through a path analysis tool, such as using Petri nets or fault tree analysis to evaluate the path of the charging supply plan, so as to obtain the professional supply path; the query of the charging supply criteria corresponding to the professional supply path can be achieved through a knowledge database, such as using an SQL database or a NoSQL database to perform an associated query on the professional supply path and its criteria, so as to determine the charging supply criteria.

[0051] Based on the charging supply criteria, the present invention generates a charging control instruction for the power supply equipment, which can make the charging operation more standardized and precise, and the precise control instruction can effectively guide the charging equipment to execute the operation, quickly respond to the charging demand of the power supply equipment, and improve the charging stability. Among them, the charging control instruction is generated according to the charging control framework and is an instruction used to guide the charging equipment to perform specific operations during the charging process. For example, when it is detected that the battery temperature is too high during the charging process, the charging control instruction will require the charging equipment to reduce the charging power to ensure battery safety.

[0052] As an embodiment of the present invention, the generation of the charging control instruction for the power supply equipment based on the charging supply criteria includes: Analyze the criterion execution specification corresponding to the charging supply criteria; Based on the criterion execution specification, determine the charging execution level corresponding to the power supply equipment; According to the charging execution level, refine the charging execution process corresponding to the power supply equipment; Based on the charging execution process, build the charging control framework corresponding to the power supply equipment; Generate a charging control instruction for the power supply device based on the charging control framework.

[0053] Among them, the criterion execution specification refers to the specific operation requirements and guiding principles of the charging replenishment criterion in practical applications. For example, in the criterion for preventing battery overcharging, the criterion execution specification will clearly stipulate that when the battery power reaches 95%, the charging current needs to be reduced, and when it reaches 98%, charging stops; the charging execution level is a division of the depth and complexity of charging operations according to the criterion execution specification and the specific situation of the power supply device. For example, for ordinary lithium battery devices, the charging execution level is relatively low, mainly focusing on conventional charging processes and safety protection; for high-capacity and high-value energy storage devices, the charging execution level will be higher, and more strict charging monitoring and refined charging control are required; the charging execution process is a series of ordered charging operation steps formulated for a specific charging execution level, covering all links from the start to the end of charging, and clarifying the tasks and order that the charging device needs to complete at each stage. For example, in the charging execution process of an electric vehicle, the battery needs to be detected first, and then an appropriate charging mode is selected according to the battery status and grid conditions; the charging control framework is constructed based on the charging execution process and is used to guide the overall architecture and mode of interaction between the charging device and the power supply device. For example, in the charging control framework, it will be clear that during the charging process, the charging device needs to continuously monitor parameters such as the power, voltage, and temperature of the power supply device and adjust the charging strategy according to the monitoring results. Furthermore, the parsing of the criterion execution specification corresponding to the charging replenishment criterion can be achieved through a text parsing tool. For example, regular expressions or semantic analysis tools are used to parse the charging replenishment criterion to obtain the criterion execution specification; the determination of the charging execution level corresponding to the power supply device can be achieved through a hierarchical evaluation model. For example, clustering analysis or decision tree models are used to evaluate and classify the charging requirements and characteristics of the power supply device to determine the charging execution level; the extraction of the charging execution process corresponding to the power supply device can be achieved through a process mining tool. For example, ProM or Disco is used to mine and extract the charging execution process; the construction of the charging control framework corresponding to the power supply device can be achieved through a framework design tool. For example, Visio or OmniGraffle is used to visually design the charging control framework to construct the charging control framework; the generation of the charging control instruction for the power supply device can be achieved through an instruction generation algorithm. For example, a state machine algorithm or a rule engine is used to generate corresponding charging control instructions according to the status of the charging device.

[0054] S5. Based on the charging control instruction, locate the optimal charging path of the power supply device, detect the real-time physical state parameters of the charging medium of the power supply device, and calculate the energy efficiency conversion rate of the charging medium in the optimal charging path based on the real-time physical state parameters.

[0055] Based on the charging control instruction, the present invention locates the optimal charging path of the power supply device, which can improve the charging efficiency, significantly shorten the charging duration, reduce the energy loss during charging, effectively protect the battery health, and reduce the risk of device failures caused by charging. Among them, the optimal charging path is the charging path and operation process that can maximize the power transmission efficiency, optimize the transmission stability, and conform to the device safety standard and the actual load of the power grid on the premise of meeting the charging requirements of the power supply device; the charging medium is xx of the power supply device, and the real-time physical state parameters are the physical and chemical state indicators that can affect the power transmission and charging effect shown by the charging medium of the power supply device during the charging process, such as parameters like temperature, humidity, and conductivity. Further, based on the charging control instruction, the steps to locate the optimal charging path of the power supply device are as follows: First, analyze the charging control instruction and extract key power transmission parameters such as charging current, voltage, and power in the instruction; then, according to the self-attributes of the power supply device type, battery capacity, remaining power, etc., as well as the number and characteristics of charging interfaces, construct multiple feasible charging path models; then, through a multi-objective evaluation system, consider the power transmission efficiency, stability, charging duration, and device heating conditions, and use multi-objective optimization algorithms such as genetic algorithms and particle swarm algorithms to screen and sort each charging path model; then, combine external factors such as the real-time load of the power grid and peak-valley electricity prices to dynamically adjust the sorting results; finally, determine the optimal charging path that conforms to the current state of the power supply device and can achieve efficient and stable charging; the real-time physical state parameters of the charging medium of the power supply device can be detected by deploying sensors such as temperature sensors, humidity sensors, and electrochemical sensors at key parts of the charging medium.

[0056] Based on the real-time physical state parameters, the present invention calculates the energy efficiency conversion rate of the charging medium in the optimal charging path, which can understand the energy utilization efficiency of the charging process, promptly detect abnormal energy consumption in the charging link, and thus lay an important basis for formulating a full-immersion charging scheme adapted to the power supply device in the future. Among them, the energy efficiency conversion rate represents a quantitative index of the energy utilization efficiency of the real-time physical state parameters in the optimal charging path, that is, during the charging process, the proportion of the effective electric energy actually stored in the power supply device in the total electric energy input to the power supply device, which is used to intuitively reflect the effective utilization degree of electric energy by the charging system under specific real-time physical state parameters and the optimal charging path.

[0057] As an embodiment of the present invention, calculating the energy efficiency conversion rate of the charging medium in the optimal charging path based on the real-time physical state parameters includes: Perform noise reduction processing on the real-time physical state parameters to obtain noise-reduced physical state parameters; Based on the noise-reduced physical state parameters, construct a medium energy efficiency state tensor of the charging medium; Conduct a charging thermodynamics simulation on the medium energy efficiency state tensor to obtain the path energy distribution nephogram of the charging medium in the optimal charging path; Perform gradient field domain segmentation on the path energy distribution nephogram to obtain an energy gradient partition diagram; Identify the strong energy gradient intervals in the energy gradient partition diagram, and quantify the effective energy transmission flux and polarization loss flux in the strong energy gradient intervals; Based on the effective energy transmission flux and the polarization loss flux, calculate the energy efficiency conversion rate of the charging medium in the optimal charging path.

[0058] Among them, the noise-reduced physical state parameters are the results obtained by performing noise reduction processing on the real-time physical state parameters. The medium energy efficiency state tensor is a quantity used to describe the energy efficiency state of the charging medium constructed based on the noise-reduced physical state parameters. The path energy distribution nephogram is a graph reflecting the energy distribution of the charging medium in the optimal charging path obtained by conducting a charging thermodynamics simulation on the medium energy efficiency state tensor. The energy gradient partition diagram is a partition graph obtained by performing gradient field domain segmentation on the path energy distribution nephogram. The strong energy gradient intervals are the regions with stronger energy gradients in the energy gradient partition diagram. The effective energy transmission flux and the polarization loss flux are physical quantities reflecting the energy transmission and loss in the strong energy gradient intervals.

[0059] Furthermore, the real-time physical state parameters can be subjected to noise reduction processing through a moving average filtering algorithm to obtain noise-reduced physical state parameters. Based on the noise-reduced physical state parameters, the medium energy efficiency state tensor of the charging medium can be constructed by using tensor analysis theory and multi-physical field coupling modeling methods. The charging thermodynamics simulation of the medium energy efficiency state tensor can be carried out by setting boundary conditions and parameters matching the charging thermodynamics process through professional finite element analysis software to obtain the path energy distribution nephogram of the charging medium in the optimal charging path. The energy gradient partition diagram can be obtained by performing gradient field domain segmentation on the path energy distribution nephogram through digital image processing techniques such as edge detection and threshold segmentation. The strong energy gradient intervals in the energy gradient partition diagram can be identified by using a pattern recognition algorithm based on the energy gradient threshold range. The effective energy transmission flux and the polarization loss flux in the strong energy gradient intervals can be quantified by setting virtual sensors in the strong energy gradient intervals and combining transmission line theory and electromagnetic loss models. Based on the effective energy transmission flux and the polarization loss flux, the energy efficiency conversion rate of the charging medium in the optimal charging path is calculated. The calculation steps are as follows: By virtue of the energy efficiency conversion rate being equal to the ratio of the effective energy transmission flux to the sum of the effective energy transmission flux and the polarization loss flux, calculate the preliminary energy efficiency conversion value, and then compare this value with the historical data under different working conditions of the charging system in multiple dimensions, and use a linear regression algorithm to correct the data deviation, so as to obtain an accurate energy efficiency conversion rate that conforms to the actual working conditions.

[0060] S6. Record the charging waveform of the power supply device during the charging process, and formulate a full-immersion charging scheme adapted to the power supply device in combination with the energy efficiency conversion rate and the charging waveform.

[0061] In the present invention, by formulating a full-immersion charging scheme adapted to the power supply device in combination with the energy efficiency conversion rate and the charging waveform, the charging efficiency can be significantly improved, the energy loss during the charging process can be reduced, the charging time can be shortened, and thus the high efficiency of the full-immersion power charging is improved. Among them, the charging waveform is a curve form that characterizes the change of the charging current or voltage with time during the charging process, thereby reflecting the dynamic characteristics of the charging process; the full-immersion charging scheme is adapted to the power supply device, completely immerses the power supply device in a coolant with good electrical insulation and heat dissipation performance, and realizes a systematic strategy for efficient and safe charging by regulating the charging waveform and charging parameters. Further, high-precision current sensors and voltage sensors can be used to collect data in real time at a certain sampling frequency, and the analog signals are converted into digital signals by a data acquisition card and stored in a database to record the charging waveform of the power supply device during the charging process; in combination with the energy efficiency conversion rate and the charging waveform, a full-immersion charging scheme adapted to the power supply device is formulated. The formulation steps are as follows: classify and sort out the collected energy efficiency conversion rate and charging waveform, use the clustering analysis algorithm to divide different energy efficiency and waveform combination types, clarify the charging performance of the power supply device under various combinations, based on the division results, establish a charging effect evaluation model, use the charging duration, heating degree, battery life loss, etc. as evaluation indicators, quantitatively analyze the influence of different combinations on the power supply device, obtain the comprehensive evaluation value of each combination, based on the evaluation value, use the multi-objective optimization algorithm, and consider factors such as charging efficiency, safety, and device life at the same time, screen out the best matching scheme of the energy efficiency conversion rate and the charging waveform, and determine the supporting parameters of the full-immersion charging such as the coolant flow rate and temperature to form a full-immersion charging scheme adapted to the power supply device.

[0062] Compared with the problems described in the background art, the present invention analyzes the charging characteristic information of the power supply device based on the device parameter information, and can convert complex and numerous parameters into clear and highly targeted charging guidance information, laying an important basis for subsequent processing. Further, the present invention matches the charging characteristic information with the historical charging data in the preset charging strategy library to obtain charging matching data, which can deeply analyze the charging requirements of the power supply device, query the adapted charging strategy in the charging matching data, greatly improve the accuracy and efficiency of charging management, and provide a better and more practical charging service experience for the power supply device. Based on the charging fit degree, the present invention analyzes the charging type of the power supply device, can accurately grasp the actual state and requirements during the charging process of the power supply device, helps the charging management system to provide a highly adapted charging strategy for the power supply device, improves the charging efficiency, ensures the safety of the device, extends the battery life, and optimizes the overall charging service experience. Further, the present invention formulates a charging replenishment plan for the power supply device based on the core charging operation points, which can significantly optimize the charging process, fully meet the charging requirements of the power supply device under different usage scenarios and performance requirements, and effectively improve the charging efficiency. Further, the present invention locates the optimal charging path of the power supply device based on the charging control instruction, which can improve the charging efficiency, greatly shorten the charging duration, reduce the energy loss during charging, effectively protect the battery health, and reduce the risk of device failures caused by charging. By combining the energy efficiency conversion rate and the charging waveform, the present invention formulates a full-immersion charging plan adapted to the power supply device, which can significantly improve the charging efficiency, reduce the energy loss during charging, shorten the charging time, and thus improve the high efficiency of full-immersion power charging. Therefore, the full-immersion power charging method and system provided by the embodiments of the present invention can improve the high efficiency of full-immersion power charging.

[0063] Embodiment 2: As Figure 2 shown, it is a functional module diagram of a full-immersion power charging system of the present invention.

[0064] The full-immersion power charging system 200 of the present invention can be installed in an electronic device. According to the functions achieved, the full-immersion power charging system may include a charging characteristic information analysis module 201, a charging fit degree calculation module 202, a core charging operation point extraction module 203, a charging control instruction generation module 204, an energy efficiency conversion rate calculation module 205, and a full-immersion charging plan formulation module 206. The modules of the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by the processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0065] In the embodiments of the present invention, the functions of each module / unit are as follows: The charging feature information analysis module 201 is configured to obtain the device parameter information of the power supply device to be charged, and analyze the charging feature information of the power supply device based on the device parameter information; The charging compatibility calculation module 202 is configured to match the charging feature information with the historical charging data in the preset charging policy library to obtain charging matching data, query the applicable charging policy in the charging matching data, and real-time monitor the charging state parameters of the power supply device during the charging process, and calculate the charging compatibility between the applicable charging policy and the charging state parameters; The core charging operation key point extraction module 203 is configured to analyze the charging type of the power supply device based on the charging compatibility, perform policy retrieval on the applicable charging policy based on the charging type to obtain a retrieved charging policy, and extract the core charging operation key points in the retrieved charging policy; The charging control instruction generation module 204 is configured to formulate a charging supply plan for the power supply device based on the core charging operation key points, analyze the professional supply path in the charging supply plan, query the charging supply criterion corresponding to the professional supply path, and generate a charging control instruction for the power supply device based on the charging supply criterion; The energy efficiency conversion rate calculation module 205 is configured to locate the optimal energy charging path of the power supply device based on the charging control instruction, detect the real-time physical state parameters of the charging medium of the power supply device, and calculate the energy efficiency conversion rate of the charging medium in the optimal energy charging path based on the real-time physical state parameters; The full-immersion charging scheme formulation module 206 is configured to record the charging waveform of the power supply device during the charging process, and formulate a full-immersion charging scheme suitable for the power supply device in combination with the energy efficiency conversion rate and the charging waveform.

[0066] Specifically, each module in the full-immersion power charging system 200 in the embodiments of the present invention uses the same technical means as those in the above-mentioned Figure 1 full-immersion power charging method, and can produce the same technical effects, which will not be elaborated here.

[0067] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-mentioned exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A fully submerged power charging method, characterized in that, The method includes: Obtaining device parameter information of a power supply device to be charged, and analyzing charging characteristic information of the power supply device based on the device parameter information; Matching the charging characteristic information with historical charging data in a preset charging strategy library to obtain charging matching data, querying an adapted charging strategy in the charging matching data, and real-time monitoring charging status parameters of the power supply device during the charging process, and calculating a charging fit degree between the adapted charging strategy and the charging status parameters; Analyzing the charging type of the power supply device based on the charging fit degree, performing strategy retrieval on the adapted charging strategy based on the charging type to obtain a retrieved charging strategy, and extracting core charging operation key points in the retrieved charging strategy; Formulating a charging replenishment plan for the power supply device based on the core charging operation key points, analyzing a professional replenishment path in the charging replenishment plan, and querying a charging replenishment criterion corresponding to the professional replenishment path, and generating a charging control instruction for the power supply device based on the charging replenishment criterion; Locating an optimal energy charging path of the power supply device based on the charging control instruction, detecting real-time physical state parameters of a charging medium of the power supply device, and calculating an energy efficiency conversion rate of the charging medium in the optimal energy charging path based on the real-time physical state parameters; Recording a charging waveform of the power supply device during the charging process, and formulating a full-immersion charging scheme adapted to the power supply device in combination with the energy efficiency conversion rate and the charging waveform.

2. The fully immersed power charging method according to claim 1, characterized in that The analyzing the charging characteristic information of the power supply device based on the device parameter information includes: Identifying a parameter label corresponding to the device parameter information, and querying a charging standard protocol and a device identifier corresponding to the power supply device; Analyzing a label coupling between the parameter label and the charging standard protocol; Analyzing device characteristics corresponding to the power supply device based on the device identifier, and analyzing a label logical relationship between the parameter labels based on the device characteristics; Analyzing the charging characteristic information of the power supply device from the device parameter information in combination with the label coupling and the label logical relationship.

3. The fully submerged power charging method according to claim 2, wherein The analyzing the label coupling between the parameter label and the charging standard protocol includes: Performing feature extraction on the parameter label to obtain a parameter label feature, and constructing a label feature vector corresponding to the parameter label feature; Performing text parsing processing on the charging standard protocol to obtain key protocol terms; Performing vectorization processing on the key protocol terms to obtain key protocol term vectors; Combining the label feature vector and the key protocol term vectors, and calculating a coupling coefficient between the parameter label and the charging standard protocol through the following formula: ； Among them, A represents the coupling coefficient between the parameter label and the charging standard protocol, represents the label characterization vector corresponding to the a-th label in the parameter label, represents the protocol key clause vector corresponding to the b-th protocol in the charging standard protocol, where a and b respectively represent the serial numbers corresponding to the parameter label and the charging standard protocol, and m and n respectively represent the quantities corresponding to the parameter label and the charging standard protocol; Analyzing the label coupling between the parameter label and the charging standard protocol based on the coupling coefficient.

4. The fully immersed power charging method according to claim 1, wherein, The calculating the charging fit degree between the adapted charging strategy and the charging status parameters includes: Querying a charging timing link corresponding to the power supply device, and determining a charging transmission attribute corresponding to the power supply device based on the charging timing link; Based on the charging transmission attribute, assign a state weight corresponding to each charging state in the charging state parameter; Based on the adaptive charging strategy, determine a state setting value corresponding to each charging state in the charging state parameter; Combine the charging state parameter, the state setting value, and the state weight to calculate the charging fitness degree between the adaptive charging strategy and the charging state parameter.

5. The fully submerged power charging method according to claim 4, wherein The combining the charging state parameter, the state setting value, and the state weight to calculate the charging fitness degree between the adaptive charging strategy and the charging state parameter includes: ； where E represents the charging compatibility degree for adapting the charging strategy and the charging state parameters, represents the state weight of the d-th charging state in the charging state parameters, represents the state setting value of the d-th charging state in the charging state parameters, represents the actual measured value of the d-th charging state in the charging state parameters, d represents the charging state serial number of the charging state parameters, q represents the number of charging states of the charging state parameters, represents the maximum value of the d-th charging state in the actual measured value, represents the minimum value of the d-th charging state in the actual measured value.

6. The fully submerged power charging method according to claim 1, characterized in that The analyzing the charging type of the power supply device based on the charging fitness degree includes: Based on the charging fitness degree, determine the charging priority of the power supply device; Analyze the battery characteristics of the battery used by the power supply device and the current device usage scenario; Extract the key scenario features of the current device usage scenario and analyze the core charging requirements corresponding to the scenario key features; Based on the core charging requirements, the battery characteristics, and the charging priority, determine the charging type of the power supply device.

7. The fully submerged power charging method according to claim 1, wherein, The extracting the core charging operation key points in the retrieved charging strategy includes: Analyze the strategy structure corresponding to the retrieved charging strategy, and based on the strategy structure, determine the key operation steps in the strategy; Extract the charging parameters in the key operation steps and identify the device charging stage and device state corresponding to the key operation steps; Combine the device charging stage and the device state to perform an adaptability adjustment on the charging parameters to obtain adapted charging parameters; Based on the adapted charging parameters, extract the core charging operation key points in the retrieved charging strategy.

8. The fully immersed power charging method according to claim 1, wherein, The generating the charging control instruction for the power supply device based on the charging replenishment criterion includes: Analyze the criterion execution specification corresponding to the charging replenishment criterion; Based on the criterion execution specification, determine the charging execution level corresponding to the power supply device; According to the charging execution level, refine the charging execution process corresponding to the power supply device; Based on the charging execution process, build the charging control framework corresponding to the power supply device; Based on the charging control framework, generate the charging control instruction for the power supply device.

9. The fully submerged power charging method according to claim 1, characterized in that The calculating the energy efficiency conversion rate of the charging medium in the optimal energy charging path based on the real-time physical state parameter includes: Perform noise reduction processing on the real-time physical state parameter to obtain a noise-reduced physical state parameter; Based on the noise-reduced physical state parameter, construct the medium energy efficiency state tensor of the charging medium; Perform an energy charging thermodynamic simulation on the medium energy efficiency state tensor to obtain the path energy distribution cloud map of the charging medium in the optimal energy charging path; Perform gradient field domain segmentation on the path energy distribution cloud map to obtain an energy gradient partition map; Identify the energy strong gradient intervals in the energy gradient partition map and quantify the effective energy transmission flux and polarization loss flux in the energy strong gradient intervals; Based on the effective energy transmission flux and the polarization loss flux, calculate the energy efficiency conversion rate of the charging medium in the optimal energy charging path.

10. A fully submerged power charging system, characterized in that, The system includes: A charging characteristic information analysis module, which is used to obtain the device parameter information of the power supply device to be charged, and based on the device parameter information, analyze the charging characteristic information of the power supply device; A charging compatibility calculation module, which is used to match the charging characteristic information with the historical charging data in the preset charging strategy library to obtain charging matching data, query the applicable charging strategy in the charging matching data, and real-time monitor the charging status parameters of the power supply device during the charging process, and calculate the charging compatibility between the applicable charging strategy and the charging status parameters; A core charging operation key point extraction module, which is used to analyze the charging type of the power supply device based on the charging compatibility, perform strategy retrieval on the applicable charging strategy based on the charging type to obtain a retrieved charging strategy, and extract the core charging operation key points in the retrieved charging strategy; A charging control instruction generation module, which is used to formulate a charging supply plan for the power supply device based on the core charging operation key points, analyze the professional supply path in the charging supply plan, query the charging supply criterion corresponding to the professional supply path, and generate a charging control instruction for the power supply device based on the charging supply criterion; An energy efficiency conversion rate calculation module, which is used to locate the optimal energy charging path of the power supply device based on the charging control instruction, detect the real-time physical state parameters of the charging medium of the power supply device, and calculate the energy efficiency conversion rate of the charging medium in the optimal energy charging path based on the real-time physical state parameters; A full-immersion charging scheme formulation module, which is used to record the charging waveform of the power supply device during the charging process, and formulate a full-immersion charging scheme suitable for the power supply device in combination with the energy efficiency conversion rate and the charging waveform.

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