Intelligent battery charging and discharging management system and method based on 5G cloud computing platform

Abstract

A battery intelligent charge and discharge management system and method based on a 5G cloud computing platform, comprising: a battery management system-on-chip based on a dual CPU architecture, a 5G communication unit, a database server, a cloud computing platform, a web server and a visualization terminal; the battery management system-on-chip with a dual CPU architecture is used to realize the collection of operating status data of each battery pack, and realize the SOC estimation, SOH estimation, fault diagnosis, and charge and discharge control of the battery based on the battery data information; the 5G communication unit is connected to the battery management system-on-chip with the dual CPU architecture, and is used to transmit the operating status information and location information of the battery pack to the cloud computing platform in real time, and receive control parameters and signals transmitted from the cloud computing platform; the cloud computing platform is used to realize multi-dimensional battery parameter extraction and BMS control strategy, and realize collaborative control of cloud-assisted battery management system; the present invention uses 5G as a carrier, and realizes active safety management and intelligent charge and discharge control of battery packs through edge computing, cloud state estimation and correction.

Description

Technical Field

[0001] The present invention relates to the technical field of power battery management systems, and in particular to a battery active safety charge and discharge management system that uses 5G communication as a carrier and combines on-chip systems, edge computing, and cloud-based state estimation and charge and discharge decision-making. Background Art

[0002] With the rapid development of new energy vehicles, the demand for power batteries is booming. The power battery system poses great challenges to safety issues due to the large-scale and grouped use of single cells. In order to achieve safe and efficient management of power lithium batteries, the development of advanced lithium battery management systems (Battery Management System, BMS) is currently a hot and difficult issue that has attracted widespread attention.

[0003] (1) Current status of foreign BMS research. Foreign countries started early in the field of electric vehicles, and BMS research is mainly concentrated in automobile companies. In recent years, some large automobile manufacturers have conducted in-depth exploration and research on various types of batteries, achieved a series of research results, and successfully commercialized a series of BMS, such as: Germany's BADICHEQ system and BATTMAN system; the BMS used in the Prius hybrid car produced by Toyota Motor of Japan; and the BMS used in the pure electric vehicles produced by Tesla of the United States.

[0004] (2) Current status of domestic BMS research. The domestic electric vehicle industry started late, but the industry has developed rapidly. There are many universities and research institutes in China that are committed to BMS research, such as the Olympic pure electric bus BMS developed by Beijing Jiaotong University and Huizhou Yineng; and the BMS developed by Harbin Guantuo Company, which was jointly established by Harbin Institute of Technology and Beijing Institute of Technology.

[0005] Since many key technologies and bottlenecks have not been broken through, the BMS currently installed and running is not well matched with the vehicle and the battery used. In addition, the traditional BMS matches and calibrates the battery based on experimental data, which is difficult to meet the high accuracy and high safety requirements of electric vehicles. With the advent of the 5G high-speed information age, the development of large-scale multi-input multi-output communication, micro base stations, and beamforming technologies have provided a foundation for real-time cloud-based battery parameter and status estimation and cloud-assisted battery charging and discharging management. Summary of the invention

[0006] The purpose of the present invention is to provide a battery intelligent charge and discharge management system based on 5G communication technology, which can combine the system on chip with the cloud computing platform technology, and realize active and efficient charge and discharge management of the battery through edge computing, cloud parameter estimation and correction, and cloud-assisted charge and discharge decision-making, thereby laying a theoretical and technical foundation for the healthy management and safe operation of power batteries.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is: a battery intelligent charging and discharging management system based on a 5G cloud computing platform, comprising:

[0008] Battery management system-on-chip, 5G communication unit, database server, cloud computing platform, web server and visualization terminal based on dual CPU architecture;

[0009] The dual-CPU architecture battery management system-on-chip is used to collect operating status data of each battery pack, and to estimate the SOC, SOH, fault diagnosis, and charge and discharge control of the battery based on the battery data information, wherein the battery pack includes a plurality of batteries;

[0010] The 5G communication unit is connected to the battery management system of the dual CPU architecture, and is used to transmit the operating status information and location information of the battery pack to the cloud computing platform in real time, and receive the control parameters and signals transmitted from the cloud computing platform;

[0011] The cloud computing platform is used to store, analyze and transmit battery operation data and positioning information, realize multi-dimensional battery parameter extraction, BMS control strategy and multi-state comprehensive estimation of battery packs, and use battery status information to formulate intelligent charging and discharging control strategies to achieve cloud-assisted battery management system collaborative control;

[0012] The visualization terminal realizes web browser access and relies on search engines and data engines to realize data retrieval, analysis, visualization display and user preference settings.

[0013] Furthermore, the battery management system-on-chip with dual CPU architecture adopts a master-slave architecture mode, including a host unit and a slave unit. The slave unit is responsible for collecting the single cell voltage, current, and temperature data information of each battery pack, and the host unit realizes the battery SOC estimation, SOH estimation, fault diagnosis, and charge and discharge control based on the transmitted battery data information.

[0014] Furthermore, the host unit includes a power supply voltage stabilization and filtering circuit, a host CAN communication interface, a voltage and current detection circuit, a relay control circuit, and a host unit CPU chip;

[0015] The power supply voltage stabilization and filtering circuit includes 3.3V, 5V and 12V voltage stabilization circuits, which are responsible for power supply and connected to the host unit CPU chip, the host CAN communication interface, the high voltage and current detection circuit, and the 5G communication unit and the slave unit;

[0016] The host CAN communication interface includes a host internal CAN interface and a host external CAN interface;

[0017] The slave unit includes a CPU chip, a voltage detection circuit ADC, a temperature detection circuit, a CAN interface in the slave, and a balancing circuit.

[0018] Furthermore, the 5G communication unit includes a single-chip minimum system, a communication module and a positioning module; the single-chip minimum system includes an ARM core processor and peripheral circuits to perform data calculation and data transmission functions; the communication module uses 5G communication technology to realize battery pack operating status data transmission, remote parameter calibration, and charging and discharging control signal reception; the positioning module relies on the GPS / Beidou dual satellite navigation system to realize real-time positioning function.

[0019] Furthermore, the 5G communication unit includes a core processor STM32 chip, a power supply voltage stabilization filter circuit, a 5G chip communication circuit, a GPS / BD positioning circuit, and an external CAN interface. The power supply voltage stabilization circuit is responsible for providing a stable power supply for the core processor chip, the 5G chip communication circuit, and the GPS / BD positioning circuit. The external CAN interface of the 5G communication unit is connected to the external CAN interface of the host unit to perform real-time transmission of battery operation data and external control signals.

[0020] Furthermore, the cloud computing platform performs edge computing based on the battery pack operating status data collected by the battery management system-on-chip, executes the BMS algorithm and control strategy, and returns the cloud control instructions to the system-on-chip for auxiliary collaborative control;

[0021] Unified storage of battery operation data, and unification and standardization of data;

[0022] The cloud computing platform deploys big data algorithms and battery charge and discharge control algorithms. The big data algorithms extract multi-dimensional battery parameters, estimate comprehensive status, and diagnose faults based on real-time / historical charge and discharge data. The battery charge and discharge control algorithm makes intelligent charge and discharge control decisions based on the estimated battery status information and the user charging preference information input by the application layer.

[0023] Through access via a web browser, data retrieval, analysis, visualization and user preference settings can be achieved.

[0024] Furthermore, the visualization terminal sends a request based on a web browser, receives battery data and vehicle information from a cloud server, and performs visualization processing, including a login interface, a main interface, a battery data information visualization interface, and a vehicle location information interface; at the same time, in order to solve the problem that different users and the same user have different charging requirements in different environments, in the battery data information visualization interface, users can set their own charging preferences based on their actual needs and the battery status information provided by the cloud, determine the priority of charging speed and battery life, and return the preference parameters to the cloud to assist in intelligent battery charging and discharging decisions.

[0025] According to another aspect of the present invention, a battery intelligent charging and discharging management method based on a 5G cloud computing platform is proposed, comprising the following steps:

[0026] Step 1, the battery management system-on-chip of the dual CPU architecture (1) is powered on and initialized, the slave uses the AD sampling chip to collect battery voltage and temperature information, and uses CAN communication to realize information exchange with the host; the host realizes SOC estimation, SOH estimation, fault diagnosis and charge and discharge control of the battery based on the battery operation data collected by the slave, and sends the execution command to the slave through CAN, and sends the battery data to the communication unit through CAN;

[0027] Step 2: The communication unit receives the battery operation data from the host, and uses the positioning module to perform Beidou / GPS dual satellite navigation system positioning, packages the battery operation data and location information, and uploads them to the cloud computing platform using 5G wireless communication. At the same time, it receives the battery charging and discharging and coordinated control instructions from the cloud computing platform and transmits them to the on-chip system;

[0028] Step 3: The cloud computing platform receives the battery operation data uploaded by the communication unit, uses the edge computing server to execute the BMS estimation algorithm and control strategy, and returns the cloud collaborative control instructions to the on-chip system to provide real-time BMS algorithm auxiliary calculation; at the same time, the edge data is collected, processed, aggregated, and uploaded to the cloud server;

[0029] Step 4: All battery operation data are stored in a unified manner, and the raw data is converted into converted data that can be used for reporting, visualization, analysis, and machine learning tasks, and stored in a MYSQL database or SQL server to form a unified and standardized battery management system spatiotemporal database;

[0030] Step 5: Use the 5G intelligent cloud computing platform big data algorithm deployed on the cloud computing platform to extract multi-dimensional battery parameters and estimate comprehensive status based on real-time / historical charging and discharging data;

[0031] Step 6: The battery intelligent charging and discharging algorithm deployed on the cloud computing platform formulates a battery charging and discharging strategy based on the accurately estimated battery state of charge information SOC and health information SOH and the user preference setting information input by the visualization terminal;

[0032] Step 7: Return the comprehensive estimation results of battery parameters and status of the cloud computing platform and the formulated charging and discharging strategy to the on-chip system to achieve remote parameter and status correction and cloud computing platform-assisted battery charging and discharging management;

[0033] Step 8: The visualization terminal sends a request to the cloud computing platform server based on the web browser and receives the battery data and vehicle information from the server, performs visualization, and displays it on the web page. At the same time, it displays the user access port to assist the user in setting the charging and discharging preferences according to their own needs.

[0034] Furthermore, the step 8 specifically includes: using the SOC estimation given by the cloud computing platform to determine the balance state of the battery pack by comparing the SOC difference between the highest SOC and the lowest SOC battery cells in the battery pack; if the difference between the high and low SOC battery cells of the battery pack exceeds a set threshold, that is, the SOC max -SOC min >10%, active balancing management is performed to improve the inconsistency of battery cells by actively discharging the highest SOC battery cell to the battery pack and actively charging the lowest SOC battery cell.

[0035] Furthermore, step 6 further includes deploying a charge and discharge control algorithm on the cloud computing platform, performing charge control based on the charging preference fed back by the user, and performing discharge control based on the battery SOC and SOH states evaluated in real time:

[0036] During the operation and management of the battery, the charging and discharging status of the battery is first determined. If the battery is in the charging process, the charging current of the battery pack is controlled by collecting the user's pre-set charging preferences, including the charging speed requirements and the battery life requirements, using the NSGA2 multi-objective optimization algorithm. Under the condition of meeting the battery safety constraints, the optimal Pareto frontier is found. At this time, the corresponding charging strategy is formulated considering customer needs. If the battery is in the discharge process, the SOC and SOH states of the battery cells are calculated based on facts. Under the condition of meeting the user's power demand, high SOC and high SOH battery cells are given priority for discharge, and the battery inconsistency is adjusted during the discharge process.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. The present invention adopts a battery management system-on-chip with a dual CPU architecture. The host and the slave work independently and interact using CAN communication. It supports functional safety level C and has good flexibility.

[0039] 2. The present invention can realize collaborative control of cloud-assisted battery management systems based on big data, and use cloud-based real-time / historical data to jointly estimate battery model parameters and states.

[0040] 3. The present invention can realize cloud-assisted balancing management of battery packs, accurately calculate the remaining capacity of each battery cell based on cloud big data, and then accurately predict the balancing time required for each cell, formulate a balancing control strategy, and effectively improve the inconsistency of the battery pack.

[0041] 4. The present invention realizes active safety management of battery packs based on a cloud computing platform. By analyzing the ambient temperature, road conditions and other conditions, the thermal management strategy for the battery is started in advance. In addition, a safe and efficient charging and discharging strategy is formulated according to the charging and discharging preferences set by the user to improve the battery utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a block diagram of the intelligent battery charge and discharge management system of the present invention;

[0043] Figure 2 This is a hardware structure diagram of the master and slave machines and the communication unit of the present invention;

[0044] Figure 3 This is a block diagram of the cloud computing platform architecture used in the present invention;

[0045] Figure 4 It is a work flow chart of the present invention;

[0046] Figure 5 This is a flow chart of the intelligent charging and discharging strategy of the present invention. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all 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 protection scope of the present invention.

[0048] The present invention discloses a battery intelligent charge and discharge management system based on a 5G cloud computing platform, including an on-chip battery management system based on a dual CPU architecture, a 5G communication unit, a cloud computing platform and a visualization terminal. The battery management system based on the dual CPU architecture adopts a master-slave architecture mode. The slave is responsible for collecting the single cell voltage, current, temperature and other information of each battery pack. The host realizes the battery state of charge (SOC) estimation, health state (SOH) estimation, fault diagnosis, thermal management control and charge and discharge control based on the battery data information. The host and slave interact through the controller area network (CAN) communication; the communication unit uses the 5G communication module and the positioning module to realize the real-time transmission of battery data and the real-time positioning of the GPS / Beidou dual satellite navigation system and receive remote parameters and control information from the cloud computing platform; the cloud computing platform stores, analyzes and transmits the battery operation data and positioning information, realizes multi-dimensional battery parameter extraction, BMS control strategy and multi-state comprehensive estimation of the battery pack, and uses the battery status information to formulate intelligent charge and discharge control strategy to realize the collaborative control of the cloud-assisted battery management system; the visualization terminal realizes web browser access, and relies on the search engine and data engine to realize data retrieval, analysis, visualization display and user preference settings.

[0049] According to one embodiment of the present invention, an intelligent battery charge and discharge management system based on a 5G cloud computing platform has a structural block diagram as shown below: Figure 1 As shown, it includes: a battery management system-on-chip based on a dual CPU architecture, a 5G communication unit, a database server, a cloud computing platform, a web server, and a visualization terminal.

[0050] The battery management system-on-chip adopting a dual CPU architecture adopts a master-slave architecture mode, and can realize battery operation data collection, battery comprehensive state estimation, charge and discharge control, and fault diagnosis.

[0051] Specifically, the master CPU is mainly responsible for CAN communication, BMS strategy algorithm, charge and discharge control, and interaction with the communication unit, while the slave CPU is mainly responsible for voltage signal and temperature signal acquisition. The master-slave architecture mode can effectively avoid conflicts between sampling signals and control signals and improve the operating efficiency of the on-chip system.

[0052] Further, if Figure 2 As shown, the host unit includes a power supply voltage stabilizing and filtering circuit, a host CAN communication interface, a high voltage and current detection circuit, a relay control circuit, and a host CPU chip S32K;

[0053] The power supply voltage stabilization and filtering circuit includes 3.3V, 5V and 12V voltage stabilization circuits, which are responsible for power supply and connected to the host CPU chip, the host CAN communication interface, the high voltage and current detection circuit, and the 5G communication unit and the slave unit;

[0054] The host CAN communication interface includes a host internal CAN interface and a host external CAN interface;

[0055] The high voltage and current detection circuit can detect: such as high voltage detection (voltage range: 3.8V-4V), low voltage detection (voltage range: 2V-2.5V), overcurrent detection (current range: 1.05C-1.2C), etc.

[0056] The slave unit includes a CPU chip MC9S08DZ60, a voltage detection circuit (ADC), a temperature detection circuit (including a temperature sensor), a CAN interface in the slave, and a balancing circuit.

[0057] The BMS strategy algorithm is deployed in the CPU of the host unit, and battery status prediction, fault diagnosis, and charge and discharge control can be achieved based on the collected signals of the CPU of the slave unit.

[0058] Specifically, the CPU of the slave unit transmits the collected voltage, current and temperature signals to the CPU of the master unit using the CAN communication in the slave unit. The CPU of the master unit uses the collected signals for fault diagnosis, such as high voltage detection (voltage range: 3.8V-4V), low voltage detection (voltage range: 2V-2.5V), overcurrent detection (current range: 1.05C-1.2C), etc. The CPU of the master unit can also further use the collected signals to predict the battery status, such as battery SOC prediction: using the traditional ampere-hour integration method, by recording the battery charge and discharge current and time, the battery SOC is calculated.

[0059] The 5G communication unit is used to realize two-way data transmission and real-time positioning between the system on chip and the cloud computing platform.

[0060] Specifically, the 5G communication unit's single-chip minimum system includes a high-performance ARM core processor and peripheral circuits, which ensures efficient computing and data transmission functions; the communication module uses 5G communication technology to achieve large-scale, high-speed battery pack operating status data transmission, remote parameter calibration, and charging and discharging control signal reception; the positioning module relies on the GPS / Beidou dual satellite navigation system to achieve real-time positioning functions.

[0061] Further, if Figure 2As shown, the 5G communication unit includes a core processor STM32 chip, a power supply voltage stabilization filter circuit, a 5G chip communication circuit, a GPS / BD positioning circuit, and an external CAN interface. The power supply voltage stabilization circuit is responsible for providing a stable power supply for the core processor chip, the 5G chip communication circuit, and the GPS / BD positioning circuit. The external CAN interface of the 5G communication unit is connected to the external CAN interface of the host unit to perform real-time transmission of battery operation data and external control signals.

[0062] The cloud computing platform realizes data storage, provides real-time BMS algorithm-assisted calculation and battery charging and discharging auxiliary management.

[0063] Specifically, if Figure 3 As shown, the cloud computing platform includes a facility layer, a data layer, a platform layer, and an application layer. The facility layer performs edge computing based on the battery pack operating status data collected by the on-chip system, and executes the BMS algorithm and control strategy; the data layer realizes the unified storage of battery operating data, and unifies and standardizes the data; the platform layer deploys big data algorithms and battery charge and discharge control algorithms. The big data algorithm realizes the joint estimation of battery model parameters and status based on real-time / historical data in the cloud. The battery charge and discharge control algorithm makes intelligent charge and discharge control decisions through the estimated battery status information and the user charging preference information input by the application layer; the application layer realizes data retrieval, analysis, visualization, and user preference settings through access to a web browser.

[0064] The balancing control algorithm deployed on the cloud computing platform realizes active balancing management of the battery pack based on the SOC estimation realized by the cloud computing platform.

[0065] Specifically, if Figure 4 As shown in the figure, the accurate SOC estimation provided by the cloud computing platform is used to determine the balance state of the battery pack by comparing the SOC difference between the highest SOC and the lowest SOC battery cells in the battery pack. If the difference between the high and low SOC battery cells of the battery pack exceeds the set threshold (SOC max -SOC min >10%), active balancing management is performed, by actively discharging the highest SOC battery cell to the battery pack and actively charging the lowest SOC battery cell, effectively improving the inconsistency of the battery cells. Compared with the traditional BMS that uses the battery terminal voltage signal for active balancing control, the present invention performs active balancing management based on high-precision cloud SOC estimation data, effectively avoiding the defect that the terminal voltage cannot truly and objectively reflect the internal state of the battery.

[0066] The charge and discharge control algorithm deployed on the cloud computing platform performs charging control based on the charging preference fed back by the user, and performs discharge control based on the battery SOC and SOH states evaluated in real time.

[0067] Specifically, if Figure 5 As shown in the figure, in the process of battery operation and management, the battery's charge and discharge status is first determined. If the battery is in the charging process, by collecting the user's pre-set charging preferences (such as charging speed requirements, battery life requirements, etc.), the advanced NSGA2 multi-objective optimization algorithm is used to control the charging current of the battery pack, and the optimal Pareto frontier is found under the condition of meeting the battery safety constraints (such as charging current <1.05C). At this time, the corresponding charging strategy is formulated under the consideration of customer needs; if the battery is in the discharge process, in order to avoid the inconsistency of the battery pack as much as possible, the SOC and SOH of the battery cell are calculated by facts, and the high SOC and high SOH battery cells are preferentially arranged for discharge under the condition of meeting the user's power demand, and the battery inconsistency is further adjusted during the discharge process.

[0068] The visualization terminal is used for retrieving, analyzing, visualizing and setting user preferences of battery data and vehicle information.

[0069] Specifically, the visualization terminal includes a login interface, a main interface, a battery data information visualization interface, and a vehicle location information interface. In order to solve the problem that different users and the same user have different charging requirements in different environments, in the battery data information visualization interface, users can set their own charging preferences according to their actual needs and the battery status information provided by the cloud, determine the priority of charging speed and battery life, and return the preference parameters to the cloud to assist in intelligent battery charging and discharging decisions.

[0070] Based on the system of the present invention, the intelligent charging and discharging management method includes the following steps:

[0071] ① The dual-CPU battery management system-on-chip is powered on and initialized. The slave unit uses the AD sampling chip to collect battery voltage and temperature information, and uses CAN communication to achieve information interaction with the host. The host unit realizes battery SOC estimation, SOH estimation, fault diagnosis, and charge and discharge control based on the battery operation data collected by the slave unit, and sends the execution command to the slave unit through CAN, and sends the battery data to the communication unit through CAN.

[0072] ② The communication unit receives the battery operation data from the host, and uses the positioning module (S1216F8-BD) to perform Beidou / GPS dual satellite navigation system positioning, packages the battery operation data and location information, and uploads them to the cloud computing platform using 5G wireless communication. At the same time, it receives battery charging and discharging and coordinated control instructions from the cloud computing platform and transmits them to the on-chip system;

[0073] ③ The cloud computing platform receives the battery operation data uploaded by the communication unit, uses the edge computing server to execute the BMS estimation algorithm and control strategy, and returns the cloud collaborative control instructions to the on-chip system to provide real-time BMS algorithm auxiliary calculation; at the same time, the edge data is collected, processed, aggregated, and uploaded to the cloud server;

[0074] ④ All battery operation data are stored in a unified manner, and the raw data is converted into converted data that can be used for reporting, visualization, analysis, and machine learning tasks, and stored in a MYSQL database or SQL server to form a unified and standardized battery management system spatiotemporal database;

[0075] ⑤ Through the 5G intelligent cloud computing platform big data algorithm deployed on the cloud computing platform, multi-dimensional battery parameter extraction and comprehensive state estimation are performed based on real-time / historical charging and discharging data;

[0076] ⑥ The battery intelligent charging and discharging algorithm deployed on the cloud computing platform formulates the best battery charging and discharging strategy based on the accurately estimated battery SOC and SOH information and the user preference setting information input by the application layer;

[0077] ⑦ Return the comprehensive estimation results of battery parameters and status of the cloud computing platform and the formulated charging and discharging strategy to the on-chip system to achieve remote parameter and status correction and cloud computing platform-assisted battery charging and discharging management;

[0078] ⑧ The visualization terminal sends a request to the cloud computing platform server based on the web browser and receives the battery data and vehicle information from the server, performs visualization processing, and displays it on the web page. At the same time, it displays the user access port to assist users in setting charging and discharging preferences according to their own needs.

[0079] Although the above describes the illustrative specific embodiments of the present invention to facilitate those skilled in the art to understand the present invention, and it should be clear that the present invention is not limited to the scope of the specific embodiments, for those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations using the concept of the present invention are protected.

Claims

1. A battery intelligent charging and discharging management system based on a 5G cloud computing platform, characterized in that: include: Battery management system-on-chip, 5G communication unit, database server, cloud computing platform, web server and visualization terminal based on dual CPU architecture; The dual-CPU architecture battery management system-on-chip is used to collect operating status data of each battery pack, and to estimate the SOC, SOH, fault diagnosis, and charge and discharge control of the battery based on the battery data information, wherein the battery pack includes a plurality of batteries; The 5G communication unit is connected to the battery management system of the dual CPU architecture, and is used to transmit the operating status information and location information of the battery pack to the cloud computing platform in real time, and receive the control parameters and signals transmitted from the cloud computing platform; The cloud computing platform is used to store, analyze and transmit battery operation data and positioning information, realize multi-dimensional battery parameter extraction, BMS control strategy and multi-state comprehensive estimation of battery packs, and use battery status information to formulate intelligent charging and discharging control strategies to achieve cloud-assisted battery management system collaborative control; The visualization terminal realizes web browser access, and relies on search engines and data engines to realize data retrieval, analysis, visualization display and user preference settings; The cloud computing platform performs edge computing based on the battery pack operating status data collected by the battery management system-on-chip, executes the BMS algorithm and control strategy, and returns the cloud control instructions to the system-on-chip for auxiliary collaborative control; Unified storage of battery operation data, and unification and standardization of data; The cloud computing platform deploys big data algorithms and battery charge and discharge control algorithms. The big data algorithms extract multi-dimensional battery parameters, estimate comprehensive status, and diagnose faults based on real-time / historical charge and discharge data. The battery charge and discharge control algorithm makes intelligent charge and discharge control decisions based on the estimated battery status information and the user charging preference information input by the application layer. Access through a web browser to achieve data retrieval, analysis, visualization and user preference settings; The visualization terminal sends a request based on a web browser, receives battery data and vehicle information from a cloud server, and performs visualization processing, including a login interface, a main interface, a battery data information visualization interface, and a vehicle location information interface; at the same time, in order to solve the problem that different users and the same user have different charging requirements in different environments, in the battery data information visualization interface, users can set their own charging preferences according to their actual needs and the battery status information provided by the cloud, determine the priority of charging speed and battery life, and return the preference parameters to the cloud to assist in battery intelligent charging and discharging decision-making.

2. According to claim 1, a battery intelligent charge and discharge management system based on a 5G cloud computing platform is characterized in that: The dual-CPU architecture battery management system-on-chip adopts a master-slave architecture mode, including a host unit and a slave unit. The slave unit is responsible for collecting the single cell voltage, current, and temperature data information of each battery pack, and the host unit realizes the battery SOC estimation, SOH estimation, fault diagnosis, and charge and discharge control based on the transmitted battery data information.

3. According to claim 2, a battery intelligent charge and discharge management system based on a 5G cloud computing platform is characterized in that: The host unit includes a power supply voltage stabilization and filtering circuit, a host CAN communication interface, a voltage and current detection circuit, a relay control circuit, and a host unit CPU chip; The power supply voltage stabilization and filtering circuit includes 3.3V, 5V and 12V voltage stabilization circuits, which are responsible for power supply and connected to the host unit CPU chip, the host CAN communication interface, the high voltage and current detection circuit, and the 5G communication unit and the slave unit; The host CAN communication interface includes a host internal CAN interface and a host external CAN interface; The slave unit includes a CPU chip, a voltage detection circuit ADC, a temperature detection circuit, a CAN interface in the slave, and a balancing circuit.

4. According to claim 1, a battery intelligent charge and discharge management system based on a 5G cloud computing platform is characterized in that: The 5G communication unit includes a single-chip minimum system, a communication module and a positioning module; the single-chip minimum system includes an ARM core processor and peripheral circuits for data calculation and data transmission; the communication module uses 5G communication technology to realize battery pack operating status data transmission, remote parameter calibration, and charging and discharging control signal reception; the positioning module relies on the GPS / Beidou dual satellite navigation system to realize real-time positioning function.

5. A battery intelligent charging and discharging management method based on a 5G cloud computing platform, applied to the system described in claim 1, characterized in that: The steps include: Step 1: The battery management system-on-chip of the dual CPU architecture is powered on and initialized. The slave unit uses the AD sampling chip to collect battery voltage and temperature information, and uses CAN communication to achieve information exchange with the host unit; The host unit realizes the battery SOC estimation, SOH estimation, fault diagnosis and charge and discharge control based on the battery operation data collected by the slave unit, and sends the execution command to the slave unit through CAN, and sends the battery data to the communication unit through CAN; Step 2: The communication unit receives the battery operation data from the host, and uses the positioning module to perform Beidou / GPS dual satellite navigation system positioning, packages the battery operation data and location information, and uploads them to the cloud computing platform using 5G wireless communication. At the same time, it receives the battery charging and discharging and coordinated control instructions from the cloud computing platform and transmits them to the on-chip system; Step 3: The cloud computing platform receives the battery operation data uploaded by the communication unit, uses the edge computing server to execute the BMS estimation algorithm and control strategy, and returns the cloud collaborative control instructions to the on-chip system to provide real-time BMS algorithm auxiliary calculation; at the same time, the edge data is collected, processed, aggregated, and uploaded to the cloud server; Step 4: All battery operation data are stored in a unified manner, and the raw data is converted into converted data that can be used for reporting, visualization, analysis, and machine learning tasks, and stored in a MYSQL database or SQL server to form a unified and standardized battery management system spatiotemporal database; Step 5: Use the 5G intelligent cloud computing platform big data algorithm deployed on the cloud computing platform to extract multi-dimensional battery parameters and estimate comprehensive status based on real-time / historical charging and discharging data; Step 6: The battery intelligent charging and discharging algorithm deployed on the cloud computing platform formulates a battery charging and discharging strategy based on the accurately estimated battery state of charge information SOC and health information SOH and the user preference setting information input by the visualization terminal; Step 7: Return the comprehensive estimation results of battery parameters and status of the cloud computing platform and the formulated charging and discharging strategy to the on-chip system to achieve remote parameter and status correction and cloud computing platform-assisted battery charging and discharging management; Step 8: The visualization terminal sends a request to the cloud computing platform server based on the web browser and receives the battery data and vehicle information from the server, performs visualization, and displays it on the web page. At the same time, it displays the user access port to assist the user in setting the charging and discharging preferences according to their own needs.

6. According to claim 5, a battery intelligent charging and discharging management method based on a 5G cloud computing platform is characterized in that: The step 8 specifically includes: Using the SOC estimation given by the cloud computing platform, the balance state of the battery pack is determined by comparing the SOC difference between the highest SOC and the lowest SOC battery cells in the battery pack; if the difference between the high and low SOC battery cells of the battery pack exceeds the set threshold, the SOC max -SOC min >10%, active balancing management is performed to improve the inconsistency of battery cells by actively discharging the battery cell with the highest SOC to the battery pack and actively charging the battery cell with the lowest SOC.

7. According to claim 5, a battery intelligent charging and discharging management method based on a 5G cloud computing platform is characterized in that: The step 6 specifically includes deploying a charge and discharge control algorithm on a cloud computing platform, performing charge control based on the charging preference feedback from the user, and performing discharge control based on the battery SOC and SOH status evaluated in real time: In the process of battery operation and management, the battery's charge and discharge status is first determined. If the battery is in the charging process, the charging current of the battery pack is controlled by collecting the user's pre-set charging preferences, including the charging speed requirements and battery life requirements, using the NSGA2 multi-objective optimization algorithm. Under the condition of meeting the battery safety constraints, the optimal Pareto frontier is found. At this time, the corresponding charging strategy is formulated taking into account customer needs. If the battery is in the discharge process, the SOC and SOH states of the battery cells are calculated based on facts. Under the condition of meeting the user's power demand, high SOC and high SOH battery cells are preferentially arranged for discharge, and the battery inconsistency is adjusted during the discharge process.

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