Intelligent power conversion cabinet control system and power conversion cabinet

Abstract

The invention discloses an intelligent power conversion cabinet control system and a power conversion cabinet, and relates to the technical field of power conversion cabinet control, and the system comprises a user interaction module, a touch screen and voice recognition convenient operation, and multilingual interaction; the battery management module is used for accurately monitoring parameters, quickly early warning abnormity and intelligently regulating and controlling charging and discharging; the battery replacement control module is high in identity verification speed and stable, accurate and fast in battery replacement operation; the data storage and analysis module is used for mass data storage and deep mining; the communication module is used for realizing dual-mode stable transmission and encrypted cache; the cabinet body comprises a plurality of battery cabins, the protection is comprehensive, the heat dissipation is intelligent, the modular design is beneficial to expansion, and the high-speed bus is strongly connected. The system is convenient in interaction and efficient in battery replacement. The battery management is accurate, the service life is prolonged, the data-driven operation is optimized, the communication is safe and stable, the remote monitoring is convenient, the cabinet body design is reasonable, the protection and heat dissipation are good, the modularization is flexible, the battery replacement service experience and operation benefits are powerfully improved, and the development of the intelligent battery replacement field is promoted.

Description

Technical Field

[0001] The present invention relates to the field of power exchange cabinet control technology, and in particular to an intelligent power exchange cabinet control system and a power exchange cabinet. Background Art

[0002] As the world pays more and more attention to environmental protection and sustainable development, electric vehicles, such as electric bicycles and electric motorcycles, are widely used due to their environmental protection and convenience. This trend has led to a sharp increase in demand for battery charging and replacement services. Traditional charging methods face many challenges, and smart battery swap cabinets have emerged.

[0003] The traditional charging mode mainly relies on fixed charging piles, which have many inconveniences and limitations. First, the charging time is long, and users often need to wait for several hours to complete charging. This greatly affects the work efficiency of time-constrained users, such as food delivery riders and couriers. Secondly, the distribution of charging piles is limited by the site. In some old residential areas, commercial centers and other densely populated areas, parking spaces are tight, and it is difficult to lay charging piles on a large scale, which makes it difficult for users to find charging positions. Moreover, long-term use of charging piles will accelerate battery aging, affect battery life, and increase the cost of battery replacement for users.

[0004] In addition, the traditional way of managing batteries is relatively extensive. The lack of real-time and accurate monitoring of battery power, temperature, voltage and other parameters makes it impossible to promptly detect potential safety hazards of batteries, such as overheating and overcharging, which can easily cause safety accidents such as fires. In terms of battery maintenance and operation, due to the lack of effective data analysis and management methods, it is difficult to reasonably allocate, maintain and recycle batteries according to their usage, resulting in waste of resources and increased operating costs.

[0005] At the same time, the interaction experience between users and charging facilities is not good. When users operate charging piles, they often face problems such as complex interfaces and inconvenient payment. There is a lack of convenient information query and feedback channels. For example, they cannot timely understand the battery charging progress, whether the remaining power can meet the travel needs, etc. It is also difficult to provide timely feedback and handle problems encountered during the charging process.

[0006] Furthermore, with the popularization of electric vehicles, batteries of different brands and models have different specifications, and traditional charging facilities have poor compatibility and are unable to meet diverse battery charging needs.

[0007] In summary, the existing charging mode and related management methods can no longer meet the needs of the rapid development of electric vehicles. Therefore, the development of an intelligent battery swap cabinet control system and a battery swap cabinet has extremely important practical significance, which can effectively solve many drawbacks of traditional charging methods, realize rapid replacement, accurate management and safety monitoring of batteries, improve user experience, and optimize the utilization of battery resources and operational efficiency. Summary of the invention

[0008] The present invention proposes an intelligent power exchange cabinet control system and a power exchange cabinet to solve the problems mentioned in the above-mentioned prior art.

[0009] In order to achieve the above object, the present invention adopts the following technical solution: an intelligent power exchange cabinet control system, comprising: User interaction module: equipped with a touch screen and voice recognition device, users can log in, register, select battery replacement packages, check battery power and location information, and report problems through touch operations or voice commands; the touch screen uses capacitive multi-touch technology, and the voice recognition device builds an acoustic model based on a deep learning algorithm; In the construction of the acoustic model, speech data with different accents and environments are first collected, pre-emphasized, framed, windowed, and MFCC features are extracted; the input layer receives features, and the DNN part sets 3-5 layers of fully connected hidden layers and ReLU activation function to extract features, followed by 2-3 layers of bidirectional LSTM units to capture timing information, and the output layer uses softmax classification; during training, the data set is divided, cross entropy loss and optimization algorithm are selected, small batch training is performed and adjusted according to the validation set, regularization and early stopping methods are used to prevent overfitting, and finally the format is converted and deployed in the user interaction device of the smart battery swap cabinet; Battery management module: real-time monitoring of the battery power, temperature, voltage, and charging current parameters in the battery swap cabinet. When the battery parameters are abnormal, including the power is lower than the set threshold, the temperature is too high or too low, the early warning mechanism is automatically activated. The early warning information can be pushed to the administrator terminal and the user's mobile phone within 5 seconds. The fuzzy logic control algorithm is used to control the battery charging and discharging process, and the charging current is dynamically adjusted according to the real-time status of the battery. Specifically: determine the input variables of the fuzzy logic control, including the real-time power, temperature and charging current of the battery, and the output variable is the adjustment amount of the charging power or discharge current; define the fuzzy sets of input and output variables based on experimental data and battery characteristic knowledge, including the power can be divided into low, medium and high fuzzy sets, and the temperature is divided into cold, suitable and hot fuzzy sets; build a fuzzy rule base; during operation, the system collects input variable data, and after fuzzification processing, obtains fuzzy output according to fuzzy rule reasoning, and then clears it into precise control adjustment amount to achieve precise control of battery charging and discharging; Battery swap control module: After receiving the user's request for battery swap, it verifies the user's identity and package permissions. If the verification is successful, it controls the robotic arm or transmission device to accurately remove the fully charged battery and insert the empty battery returned by the user. During the battery swap process, the battery connection status is detected in real time, and the electromagnetic induction sensor is used to detect the connection reliability. If an abnormality occurs, the battery swap is automatically interrupted and a fault prompt and record are given; Data storage and analysis module: Stores user information, battery replacement records, and battery information data, and uses data mining algorithms to analyze the data, including analyzing user battery replacement habits, the relationship between battery usage frequency and lifespan; uses density-based clustering algorithms to mine user battery replacement behavior patterns to provide decision-making basis for operation management; Communication module: 4G / 5G and Wi-Fi dual communication modes are adopted to ensure stable communication between the control system and the server, user terminal, and administrator terminal, with a data transmission rate of no less than 100Mbps. When the network signal is interrupted, the communication mode is automatically switched and data is cached, with the cached data volume being no less than 100MB. After the network is restored, the cached data is automatically uploaded to ensure data integrity and normal operation of the system. The communication module uses time division multiplexing technology to optimize the data transmission channel and improve the transmission efficiency by more than 30%.

[0010] Remote monitoring module: The administrator can view the operating status of the battery swap cabinet in real time through the remote monitoring platform, including the number of batteries, power distribution, number of battery swaps, and fault information. The monitoring data update interval does not exceed 10 seconds. Some functions of the battery swap cabinet can be remotely controlled, including restarting the system and emergency stop of battery swap operations. The remote monitoring platform uses virtual reality VR technology to display the internal structure and battery status of the battery swap cabinet to enhance the intuitiveness of monitoring.

[0011] Furthermore, when charging the battery, the battery management module adopts an intelligent charging algorithm to dynamically adjust the charging power according to the remaining power, temperature, and aging factors of the battery. The intelligent charging algorithm adopts a neural network prediction model to predict the battery charging curve and optimizes the charging power according to the prediction results.

[0012] Furthermore, during the battery replacement process, the battery replacement control module uses image recognition technology to inspect the appearance of the battery to identify whether the battery is damaged, bulging, or leaking. If any abnormality is found, the battery replacement is refused and the user and administrator are notified. Image recognition uses a convolutional neural network CNN model, and the training set contains 100,000 battery appearance images, and image enhancement technology is used to expand the data set.

[0013] Furthermore, the data storage and analysis module incorporates external factors such as time, location, and weather when analyzing the user's battery replacement habits, and adopts a hybrid model that combines multivariate linear regression with a neural network. The neural network in the hybrid model uses a long short-term memory network (LSTM) to process time series data.

[0014] Furthermore, the communication module adopts an encrypted communication protocol to encrypt the transmitted data, the encryption algorithm adopts AES or RSA algorithm, the encryption strength is not less than 128 bits, and the encrypted communication protocol adopts a key exchange algorithm to dynamically generate a session key.

[0015] Furthermore, when a user provides feedback on a problem, the user interaction module uses natural language processing technology to semantically understand and classify the problem input by the user, automatically matches solutions and displays them to the user. The natural language processing technology is based on a pre-trained language model and combines the domain knowledge graph to perform semantic analysis.

[0016] Furthermore, a smart battery exchange cabinet includes the smart battery exchange cabinet control system and a cabinet body, wherein the cabinet body is provided with multiple battery compartments, the battery compartments are equipped with charging interfaces, temperature sensors, and smoke sensors, the charging interface adopts a fool-proof design, the fire protection level of the battery compartment reaches V-0 level, the cabinet surface adopts anti-rust and anti-ultraviolet coating, the cabinet body is also provided with a cooling fan and ventilation holes, the cooling fan adopts an intelligent speed control algorithm, and automatically adjusts the speed according to the difference between the battery compartment temperature and the ambient temperature, the adjustment range is 500-2000 rpm, and the intelligent speed control algorithm adopts a proportional integral differential PID controller.

[0017] Furthermore, the cabinet adopts a modular design. According to the flexible combination of the number and layout of battery compartments, each module has an independent control system and communication module. The modules are connected by a high-speed bus with a data transmission rate of 1Gbps. The high-speed bus adopts fiber optic communication technology.

[0018] Compared with the prior art, the present invention has the following beneficial effects: In terms of user experience, the user interaction module is convenient and efficient, the touch and voice operations respond quickly and accurately, the multi-language support meets diverse needs, and the accuracy rate of problem feedback processing exceeds 90%. The battery swap control module swaps batteries quickly, which can be completed within 30 seconds, with fast identity authentication and accurate connection detection, which effectively saves user time and ensures a smooth battery swap process.

[0019] For battery management, high-precision monitoring and intelligent control significantly improve safety and life. Accurate parameter detection can timely warn of abnormalities, fuzzy logic controls charging and discharging, and has high adjustment accuracy. The intelligent charging algorithm can also shorten the charging time by 20% - 30%, reduce battery loss, and reduce user costs.

[0020] The data storage and analysis module uses deep data mining to achieve a prediction accuracy of over 90%, providing a scientific basis for operational decisions and facilitating the rational allocation of resources and service optimization. The dual-mode communication module ensures stable communication, the encryption protocol ensures data security, low bit error rate, and time-division multiplexing technology improves transmission efficiency by more than 30%, enhancing system reliability and privacy.

[0021] The remote monitoring module has strong real-time performance, fast data update, quick remote control response, and intuitive display of VR technology, which facilitates administrators to efficiently manage operations and handle faults in a timely manner, ensuring the continuous and stable operation of the power exchange cabinet.

[0022] The cabinet design is unique, the modular structure is flexible and changeable, easy to install, maintain and expand, the high-speed bus data transmission rate reaches 1Gbps, and the optical fiber communication has strong anti-interference. The battery compartment is fully protected, fireproof and foolproof, and the heat dissipation is intelligent, providing a safe and stable environment for the battery, extending the service life of the cabinet and battery, and effectively promoting the development and progress of the field of intelligent battery replacement. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic block diagram of a smart battery swap cabinet control system proposed by the present invention; Figure 2 This is a schematic diagram of the structure proposed by the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0026] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0027] Reference Figure 1-Figure 2 :A smart power exchange cabinet control system, comprising: User interaction module: equipped with a touch screen and voice recognition device, users can log in, register, select battery replacement packages, check battery power and location information, and report problems through touch operations or voice commands. The touch screen uses capacitive multi-touch technology, with a touch response time of less than 0.2 seconds, and supports gesture recognition operations, such as pinch-to-zoom to view battery details. The voice recognition device builds an acoustic model based on a deep learning algorithm, with a voice recognition accuracy rate of more than 95%, and supports multi-language interaction, making it convenient for different user groups to use; In constructing the acoustic model, speech data with different accents and environments are first collected, pre-emphasized, framed, windowed, and MFCC features are extracted; the input layer receives the features, and the DNN part sets 3-5 fully connected hidden layers and ReLU activation functions to extract features, followed by 2-3 layers of bidirectional LSTM units to capture timing information, and the output layer uses softmax classification; during training, the data set is divided, the cross entropy loss and optimization algorithm are selected, small batch training is performed and adjusted according to the validation set, regularization and early stopping methods are used to prevent overfitting, and finally the format is converted and deployed in the user interaction device of the smart battery swap cabinet.

[0028] Battery management module: Real-time monitoring of battery power, temperature, voltage, charging current and other parameters in the battery swap cabinet. High-precision sensors are used, with power detection accuracy of ±2% and temperature detection accuracy of ±0.5℃. When battery parameters are abnormal, such as power below the set threshold, temperature too high or too low, the early warning mechanism is automatically activated, and the early warning information can be pushed to the administrator terminal and the user's mobile phone within 5 seconds. At the same time, the fuzzy logic control algorithm is used to control the charging and discharging process of the battery, and the charging current is dynamically adjusted according to the real-time status of the battery, with an adjustment accuracy of ±0.1A to ensure the safety and life of the battery. Specifically: determine the input variables of the fuzzy logic control, including the real-time power, temperature and charging current of the battery, and the output variable is the adjustment amount of the charging power or discharge current; based on experimental data and battery characteristic knowledge, define the fuzzy set of input and output variables, including power can be divided into low, medium and high fuzzy sets, and temperature is divided into cold, suitable and hot fuzzy sets; build a fuzzy rule base; during operation, the system collects input variable data, after fuzzification processing, obtains fuzzy output according to fuzzy rule reasoning, and then clears it into precise control adjustment amount to achieve precise control of battery charging and discharging.

[0029] Battery swap control module: After receiving the user's request for battery swap, verify the user's identity and package permissions, and the identity verification time is less than 1 second. If the verification is successful, control the robotic arm or transmission device to accurately remove the fully charged battery and put in the empty battery returned by the user. The battery swap operation time does not exceed 30 seconds. During the battery swap process, the battery connection status is detected in real time. The electromagnetic induction sensor is used to detect the connection reliability. The connection detection accuracy rate reaches more than 99%. If an abnormality occurs, the battery swap is automatically interrupted and a fault prompt and record is given.

[0030] Data storage and analysis module: Stores a large amount of data such as user information, battery replacement records, and battery information, with a storage capacity of no less than 1TB. Use data mining algorithms to analyze data, such as analyzing user battery replacement habits, the relationship between battery usage frequency and life, etc. Use density-based clustering algorithms to mine user battery replacement behavior patterns to provide decision-making basis for operation management. The accuracy of data mining analysis results reaches more than 90%, and the analysis model can be automatically updated according to new data.

[0031] Communication module: 4G / 5G and Wi-Fi dual communication modes are adopted to ensure stable communication between the control system and the server, user terminal, and administrator terminal, with a data transmission rate of no less than 100Mbps. When the network signal is interrupted, the communication mode is automatically switched and data is cached, with the cached data volume being no less than 100MB. After the network is restored, the cached data is automatically uploaded to ensure data integrity and normal operation of the system. The communication module uses time division multiplexing technology to optimize the data transmission channel and improve the transmission efficiency by more than 30%.

[0032] Remote monitoring module: Administrators can view the operating status of the battery swap cabinet in real time through the remote monitoring platform, including the number of batteries, power distribution, number of battery swaps, fault information, etc. The monitoring data update interval does not exceed 10 seconds. Some functions of the battery swap cabinet can be remotely controlled, such as restarting the system, emergency stop of battery swap operations, etc. The remote control command response time is less than 5 seconds, realizing remote operation and management of the battery swap cabinet. The remote monitoring platform uses virtual reality (VR) technology to display the internal structure and battery status of the battery swap cabinet to enhance the intuitiveness of monitoring.

[0033] In the present invention, the battery management module adopts an intelligent charging algorithm when charging the battery, and dynamically adjusts the charging power according to factors such as the remaining power, temperature, and aging degree of the battery. The charging power adjustment range is 100W-1000W to improve charging efficiency and reduce battery loss. The intelligent charging algorithm uses a neural network prediction model to predict the battery charging curve, and optimizes the charging power according to the prediction results, which can shorten the charging time by 20%-30%.

[0034] The battery replacement control module of the present invention makes full use of advanced image recognition technology to conduct a comprehensive and detailed inspection of the battery appearance during the battery replacement operation. The image recognition technology is built on the basis of a convolutional neural network (CNN) model. The CNN model can automatically extract key features in the battery appearance image, such as shape, texture, color change and other information, through a combination of multi-layer convolutional layers, pooling layers and fully connected layers, so as to accurately determine whether the battery has abnormal conditions such as damage, bulging, leakage, etc. In the model training stage, battery appearance images of various brands, models, usage levels and different lighting and shooting angles are collected as training sets. At the same time, in order to further improve the generalization ability of the model and effectively deal with various complex image scenes that may be encountered in practical applications, image enhancement technology is used, including random rotation, flipping, cropping, brightness and contrast adjustment, etc., to expand the original training set and generate more diverse training samples, so that the model can learn richer and more representative image features. After training and optimization of a large number of samples, the image recognition model finally achieved a high accuracy rate of more than 98%. During the battery replacement process, once an abnormality in the battery appearance is detected, the battery replacement rejection mechanism is immediately triggered, and a detailed abnormality notification is sent to the user and administrator at the same time, including the abnormality type, battery number and other information, so that corresponding measures can be taken in time to ensure the safety and reliability of the battery replacement process.

[0035] When analyzing the user's battery replacement habits, the data storage and analysis module of the present invention introduces multiple external factors to achieve more accurate predictions, covering time dimensions (such as weekdays, weekends, holidays, different time periods of the day, etc.), location information (such as residential areas, workplaces, frequently visited commercial areas, etc.) and weather conditions (sunny, rainy, snowy, high and low temperatures, etc.). In terms of model construction, a hybrid model architecture that integrates multiple linear regression and neural networks is adopted. The multiple linear regression part preliminarily models the linear relationship between each factor and the battery replacement behavior to explore the basic influencing rules. The neural network part uses a long short-term memory network (LSTM) to process time series data. The unique memory unit structure of LSTM can effectively store and transmit information in long time series, and selectively forget or retain past information through a gating mechanism, thereby keenly capturing the dynamic changes of users' battery replacement habits over time, such as fluctuations in the frequency of battery replacement in different seasons and time periods. During the training process, the results of multivariate linear regression and the output of the LSTM network are comprehensively weighted. After repeated training and optimization of a large amount of historical battery swapping data, the model parameters are continuously adjusted, so that the model's prediction accuracy of user battery swapping behavior is significantly improved. Compared with a single model or traditional analysis methods that do not consider these factors, the prediction accuracy is increased by more than 15%, providing strong data support and decision-making basis for the precise operation and personalized services of smart battery swapping cabinets.

[0036] The communication module of the present invention focuses on ensuring the security and privacy of data during data transmission, and adopts a rigorous encryption communication protocol for this purpose. Among them, the encryption algorithm uses the industry standard AES (Advanced Encryption Standard) or RSA (Rivest–Shamir–Adleman) algorithm, and the encryption strength is set to not less than 128 bits. When the AES algorithm is applied, it uses a fixed-length data block (such as 128 bits) as a unit, and encrypts the data through multiple rounds of complex replacement and permutation operations. Each round is transformed according to a specific key arrangement table. The key is dynamically generated by the key exchange algorithm to ensure the uniqueness of the key for each session, which greatly enhances the security of encryption. For the RSA algorithm, the mathematical problem of large integer decomposition is used to realize encryption and decryption through the cooperation of public key and private key. The public key is publicly used for data encryption, and the private key is kept confidential for decryption, which effectively prevents data from being stolen or tampered with. During the data transmission process, the bit error rate is strictly controlled through technical means such as cyclic redundancy check (CRC) to keep it at an extremely low level of less than 0.01%, thereby building a solid security line for user data and system data, ensuring the integrity and confidentiality of data during transmission. Whether it is the user's personal identity information, battery replacement usage records, or system operation status data, battery management data, etc., they can all be reliably encrypted and protected to prevent any potential malicious attacks and information leakage risks.

[0037] The user interaction module involved in the present invention relies on advanced natural language processing technology to carry out semantic understanding and classification when processing user feedback issues. Specifically, a pre-trained language model obtained through large-scale corpus training is used, such as the BERT (Bidirectional Encoder Representations from Transformers) model, which deeply encodes the text through a multi-layer transformer architecture to effectively capture the semantic relationship and contextual information between words. Combined with a specially constructed knowledge graph for the field of smart battery swap cabinets, the graph integrates professional knowledge such as battery swap processes, battery characteristics, common faults and solutions, and stores information in the form of a graph structure. When a user enters a question, the pre-trained language model first converts the question text into a semantic vector representation, and then performs semantic analysis and reasoning based on the domain knowledge graph, accurately matches the corresponding solution, and displays it to the user in real time, thereby ensuring that the problem solving accuracy rate reaches more than 90%.

[0038] The present invention also discloses an intelligent battery exchange cabinet, in which a plurality of battery compartments are provided in the cabinet, and a charging interface, a temperature sensor, and a smoke sensor are provided in the battery compartment. The charging interface adopts a foolproof design to ensure that the battery is correctly inserted, and the fire protection level of the battery compartment reaches V-0 level, which can effectively prevent fire caused by battery failure. The cabinet surface adopts anti-rust and anti-ultraviolet coating to extend the service life of the cabinet. The cabinet is also provided with a cooling fan and ventilation holes. The cooling fan adopts an intelligent speed regulation algorithm to automatically adjust the speed according to the difference between the battery compartment temperature and the ambient temperature. The adjustment range is 500-2000 rpm to ensure that the temperature inside the cabinet is appropriate, and the ventilation area of ​​the ventilation holes is not less than 10% of the cabinet surface area. The intelligent speed regulation algorithm adopts a proportional integral differential (PID) controller to achieve precise speed regulation.

[0039] In the present invention, the cabinet adopts modular design, and the number and layout of battery compartments can be flexibly combined. Each module has an independent control system and communication module. The modules are connected by a high-speed bus, and the data transmission rate reaches 1Gbps, which is convenient for installation, maintenance and expansion. The high-speed bus adopts optical fiber communication technology, which has strong anti-interference ability and stable transmission.

[0040] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent power exchange cabinet control system, characterized in that: include: User interaction module: equipped with a touch screen and voice recognition device, users can log in, register, select battery replacement packages, check battery power and location information, and report problems through touch operations or voice commands; the touch screen uses capacitive multi-touch technology, and the voice recognition device builds an acoustic model based on a deep learning algorithm; In the construction of the acoustic model, speech data in different accents and environments are first collected, pre-emphasized, framed, windowed, and MFCC features are extracted; The input layer receives features. The DNN part has 3-5 fully connected hidden layers and ReLU activation function to extract features, followed by 2-3 bidirectional LSTM units to capture timing information, and the output layer uses softmax classification. During training, the data set is divided, cross entropy loss and optimization algorithm are selected, small batch training is performed and adjusted according to the validation set, regularization and early stopping methods are used to prevent overfitting, and the final format is converted and deployed in the user interaction device of the smart battery swap cabinet. Battery management module: real-time monitoring of the battery power, temperature, voltage, and charging current parameters in the battery swap cabinet. When the battery parameters are abnormal, including the power being lower than the set threshold, the temperature being too high or too low, the early warning mechanism is automatically activated, and the fuzzy logic control algorithm is used to control the battery charging and discharging process. The charging current is dynamically adjusted according to the real-time status of the battery. Specifically, the input variables of the fuzzy logic control are determined, including the real-time power, temperature, and charging current of the battery, and the output variable is the adjustment amount of the charging power or discharge current; Based on experimental data and knowledge of battery characteristics, fuzzy sets of input and output variables are defined, including low, medium and high fuzzy sets for power and cold, suitable and hot fuzzy sets for temperature. Build fuzzy rule base; During operation, the system collects input variable data, and after fuzzification processing, it obtains fuzzy output according to fuzzy rule reasoning, and then further clarifies it into precise control adjustment quantity to realize the control of battery charging and discharging; Battery swap control module: After receiving the user's request for battery swap, verify the user's identity and package permissions. If the verification is successful, control the robotic arm or transmission device to remove the fully charged battery and insert the empty battery returned by the user. During the battery swap process, the battery connection status is detected in real time, and the electromagnetic induction sensor is used to detect the connection reliability. If an abnormality occurs, the battery swap is automatically interrupted and a fault prompt and record are given; Data storage and analysis module: Stores user information, battery replacement records, and battery information data, and uses data mining algorithms to analyze the data, including analyzing user battery replacement habits, the relationship between battery usage frequency and lifespan; uses density-based clustering algorithms to mine user battery replacement behavior patterns to provide decision-making basis for operation management; Communication module: It adopts 4G / 5G and Wi-Fi dual communication modes to ensure the communication between the control system and the server, user terminal, and administrator terminal. The data transmission rate is not less than 100Mbps. When the network signal is interrupted, the communication mode is automatically switched and the data is cached. The amount of cached data is not less than 100MB. After the network is restored, the cached data is automatically uploaded. The communication module uses time division multiplexing technology to optimize the data transmission channel; Remote monitoring module: The administrator can view the operating status of the battery swap cabinet in real time through the remote monitoring platform, including the number of batteries, power distribution, number of battery swaps, and fault information. The monitoring data update interval does not exceed 10 seconds. Some functions of the battery swap cabinet can be remotely controlled, including restarting the system and emergency stopping of battery swap operations. The remote monitoring platform uses virtual reality VR technology to display the internal structure and battery status of the battery swap cabinet.

2. The intelligent power exchange cabinet control system according to claim 1 is characterized in that: When charging the battery, the battery management module adopts an intelligent charging algorithm to dynamically adjust the charging power according to the remaining power, temperature and aging degree of the battery. The intelligent charging algorithm adopts a neural network prediction model to predict the battery charging curve and optimizes the charging power according to the prediction results.

3. The intelligent power exchange cabinet control system according to claim 1 is characterized in that: During the battery replacement process, the battery replacement control module uses image recognition technology to inspect the battery appearance to identify whether the battery is damaged, bulging, or leaking. If any abnormality is found, the battery replacement will be rejected and the user and administrator will be notified. Image recognition uses a convolutional neural network (CNN) model. The training set contains 100,000 battery appearance images, and image enhancement technology is used to expand the data set.

4. The intelligent power exchange cabinet control system according to claim 1 is characterized in that: The data storage and analysis module incorporates external factors such as time, location, and weather when analyzing the user's battery replacement habits, and adopts a hybrid model that combines multivariate linear regression with a neural network. The neural network in the hybrid model uses a long short-term memory network (LSTM) to process time series data.

5. The intelligent power exchange cabinet control system according to claim 1 is characterized in that: The communication module adopts an encrypted communication protocol to encrypt the transmitted data. The encryption algorithm adopts AES or RSA algorithm, the encryption strength is not less than 128 bits, and the encrypted communication protocol adopts a key exchange algorithm to dynamically generate a session key.

6. The intelligent power exchange cabinet control system according to claim 1 is characterized in that: When a user gives feedback on a problem, the user interaction module uses natural language processing technology to semantically understand and classify the problem input by the user, automatically matches solutions and displays them to the user. The natural language processing technology is based on a pre-trained language model and combines the domain knowledge graph to perform semantic analysis.

7. An intelligent power exchange cabinet, characterized in that: It includes the intelligent battery exchange cabinet control system described in any one of claims 1-6, and a cabinet body, the cabinet body is provided with multiple battery compartments, the battery compartments are equipped with charging interfaces, temperature sensors, and smoke sensors, the charging interface adopts a fool-proof design, the fire protection level of the battery compartment reaches V-0 level, the cabinet surface is coated with anti-rust and anti-ultraviolet coating, the cabinet body is also provided with a cooling fan and ventilation holes, the cooling fan adopts an intelligent speed control algorithm, and automatically adjusts the speed according to the difference between the battery compartment temperature and the ambient temperature, the adjustment range is 500-2000 rpm, and the intelligent speed control algorithm adopts a proportional integral differential PID controller.

8. The intelligent power exchange cabinet according to claim 7, characterized in that: The cabinet adopts a modular design. According to the number and layout of the combined battery compartments, each module has an independent control system and communication module. The modules are connected by a high-speed bus with a data transmission rate of 1Gbps. The high-speed bus adopts optical fiber communication technology.

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