A method for realizing parallel connection based on BMS system

Abstract

The application discloses a kind of based on BMS system and machine implementation method, by designing the battery pack module with same structure and parameter, and integrated independent BMS system and communication module, so that it can communicate with central controller.Communication controller as the nerve center of system, connect all battery pack module, realize data centralized management and control, and according to battery state data, formulate energy management strategy.At the same time, a complete safety protection mechanism is set, the safety parameters of battery pack are monitored, and protection measures are taken immediately in abnormal conditions.In addition, remote monitoring and intelligent management are realized through the Internet, ensuring the stability and efficiency of system operation.The application uses modular design, reasonable communication protocol and efficient central control system, simplifies the management and maintenance of battery system, enhances the flexibility and response speed of the system, thereby providing strong technical support for renewable energy application.

Description

Technical Field

[0001] This invention belongs to the field of battery technology, specifically relating to a parallel implementation method based on a BMS system. Background Technology

[0002] With the development of battery energy storage technology, battery management systems (BMS) have become an indispensable component to improve the performance and reliability of battery systems. Especially in applications requiring large energy output or redundancy, connecting multiple battery packs or modules in parallel (parallel operation) to increase the system's total capacity, power, or redundancy has become a common solution. This parallel operation not only improves system availability and efficiency but also further enhances system safety and economy through intelligent management methods.

[0003] Existing parallel operation methods based on BMS systems mainly include modular design, communication connections, central controllers, energy management strategies, safety protection mechanisms, and remote monitoring. Among these, modular design allows battery packs to be designed as modular units with identical structures and parameters. Each module contains several individual battery cells and integrates an independent BMS system. This design not only improves system scalability but also facilitates maintenance.

[0004] In existing technologies, modular battery pack designs need to ensure that battery modules from different manufacturers and of different specifications can be interchanged and connected in parallel. This requires the design of standard communication interfaces and connection methods to facilitate connection and communication between modules. Furthermore, it is necessary to ensure that each battery pack module has independent battery management circuits and protection mechanisms to prevent a single module failure from affecting the overall system. Summary of the Invention

[0005] The purpose of this invention is to provide a parallel operation method based on a BMS system, which not only simplifies the management and maintenance of the battery system, but also improves the system's flexibility and response speed through real-time data acquisition, dynamic strategy adjustment and optimized scheduling, thereby solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for parallel implementation based on a BMS system, the method comprising the following steps:

[0007] a. Design battery pack modules with identical structure and parameters. Each battery pack module contains several individual battery cells and integrates an independent BMS system. Install a communication module in each battery pack module to enable it to communicate with the central controller and select a communication protocol.

[0008] b. Install a central controller as the hub of the parallel system, connecting all battery modules to achieve centralized data management and control. Based on the SOC, voltage (V), and temperature (T) data reported by each battery module, the central controller calculates the optimal energy allocation scheme using an energy management algorithm. The energy management algorithm formula is: E opt =f(SOC) i V i ,T i ), where E opt SOC represents the optimal energy allocation scheme. i V i T i These represent the charge, voltage, and temperature of the i-th battery module, respectively. Based on the calculation results, the central controller determines the charging / discharging control and equalization adjustment methods.

[0009] c. Establish a comprehensive safety protection mechanism, including but not limited to setting safety protection parameters and thresholds, and using algorithms to detect short circuits, overcharges, and over-discharges. Once an abnormality is detected, protective measures are immediately taken. The safety protection algorithm formula is as follows:

[0010] Safety = g(Safety) parameters Safety thresholds ), where Safety represents the safety status, Safety parameters Represents safety parameters, Safety thresholds This represents a preset safety threshold. If Safety is true, the system is safe; otherwise, a protection action is triggered.

[0011] d. Enable remote monitoring and intelligent management, conduct real-time monitoring, control and data analysis of the system through Internet connection, and allow users to conduct real-time monitoring, remote control and data analysis of the system through terminal devices;

[0012] e. After the system is built, perform system debugging and optimization to ensure stable system operation.

[0013] Preferably, the module in step (a) also includes ensuring that each battery pack module has independent battery management circuitry and protection mechanisms.

[0014] Preferably, the communication protocol selected in step (a) includes, but is not limited to, CAN bus and Modbus.

[0015] Preferably, the central controller in step (b) includes a control algorithm, employing a distributed control strategy to ensure effective communication and data synchronization between modules. The algorithm formula is as follows:

[0016] Where C(t) represents the control output at time t, f is a nonlinear function used to process the input data; W i D is the data weight assigned to the i-th module; i (t) represents the data input of the ii-th module at time t.

[0017] Preferably, the energy management strategy in step (b) includes formulating a charging and discharging strategy based on real-time data and forecast results, and remotely updating the strategy via TCP protocol to quickly respond to grid changes. The charging and discharging strategy formula is as follows:

[0018] P charge / discharge (t)=g(E t E pred ,S t ,P grid (t) where P charge / discharge (t) represents the charging and discharging power at time t; E t This is the current energy storage state; E pred It is the predicted future state of energy storage; S t This refers to the battery state information at time t; P grid (t) represents the grid power demand at time t; g is a function that determines the charging and discharging power based on variables.

[0019] Preferably, the safety protection mechanism in step (c) includes setting safety protection parameters and thresholds to achieve multiple protections against short circuits, overcharge, and over-discharge, and to cut off the power supply in a timely manner.

[0020] Preferably, the remote monitoring and intelligent management in step (d) includes establishing a connection via the TCP protocol and transmitting data in JSON format.

[0021] Preferably, the system debugging and optimization in step (e) includes a comprehensive check of whether the connections of each part are normal and whether the parameters are accurate, and adjusting and optimizing the system according to the actual operating conditions.

[0022] Preferably, the method further includes backup, employing dual backup communication modules or different types of communication protocols.

[0023] Preferably, the method further includes fault diagnosis and isolation functions, that is, each BMS has an independent fault diagnosis function, and the main control system can isolate the faulty BMS.

[0024] Technical effects and advantages of the present invention: The parallel implementation method based on BMS system proposed in this invention has the following advantages compared with the prior art:

[0025] This invention, through modular design, a rational communication protocol, and a highly efficient central control system, effectively enables parallel operation of battery packs, improving system operating efficiency and safety. Specifically, this approach not only simplifies battery system management and maintenance but also enhances system flexibility and response speed through real-time data acquisition, dynamic strategy adjustment, and optimized scheduling, providing technical support for the widespread application of renewable energy. Attached Figure Description

[0026] Figure 1 This is a flowchart of the parallel implementation method of the BMS system based on the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] This invention provides a parallel implementation method based on a BMS system, such as... Figure 1 As shown, the method includes the following steps:

[0029] a. Design battery pack modules with identical structure and parameters. Each battery pack module contains several individual battery cells and integrates an independent BMS system. This design improves system scalability and maintainability, ensuring that each battery pack module has similar performance and characteristics. Install a communication module in each battery pack module to enable it to communicate with the central controller, and select a communication protocol.

[0030] Achieve standardized design for battery pack modules, ensuring interchangeability and parallel connection of modules from different manufacturers and specifications. Design standard communication interfaces and connection methods to facilitate connection and communication between modules. Ensure each battery pack module has independent battery management circuits and protection mechanisms to prevent single-module failures from affecting the overall system. Select appropriate communication protocols, such as CAN bus or Modbus, to achieve data transmission and communication between battery pack modules. Consider the stability of communication lines and the reliability of signal transmission to ensure unimpeded communication between modules in the system.

[0031] Furthermore, the aforementioned battery pack module also includes battery management circuits and protection mechanisms to ensure that each battery pack module has independent operation. Each battery pack module's BMS system establishes a communication connection with the central controller via a communication module to achieve data transmission. The communication module can use communication protocols such as CAN bus or Modbus to transmit the battery pack's status data to the central controller.

[0032] b. Install a central controller as the hub of the parallel system, connecting all battery modules to achieve centralized data management and control. Based on the SOC, voltage (V), and temperature (T) data reported by each battery module, the central controller calculates the optimal energy allocation scheme using an energy management algorithm. The energy management algorithm formula is: E opt =f(SOC) i V i ,T i ), where E opt SOC represents the optimal energy allocation scheme. i V i T i These represent the charge, voltage, and temperature of the i-th battery module, respectively. Based on the calculation results, the central controller determines the charging / discharging control and equalization adjustment methods. The central controller calculates the optimal energy allocation scheme through an energy management algorithm based on the charge SOC, voltage V, and temperature T data reported by each battery module. The energy management strategy can be adjusted according to user needs to achieve efficient energy utilization and stable system operation.

[0033] The central controller also features real-time monitoring, control, and fault diagnosis functions, enabling dynamic adjustments based on the battery pack's status. It employs a distributed control strategy to ensure effective communication and data synchronization between modules. Furthermore, energy management strategies can be adjusted according to user needs to achieve efficient energy utilization and stable system operation.

[0034] The central controller collects data such as SOC, voltage, and temperature from the battery module in real time via the TCP protocol, and uses data analysis algorithms to predict future electricity demand and price changes, providing a basis for formulating charging and discharging strategies.

[0035] Dynamic strategy adjustment: Based on the prediction results, the central controller can dynamically adjust the charging and discharging strategy. For example, it can charge when the electricity price is low and discharge when the electricity price is high to maximize economic benefits.

[0036] Furthermore, the central controller possesses real-time monitoring, control, and fault diagnosis functions, enabling dynamic adjustments based on the battery pack's state. The central controller includes a control algorithm and employs a distributed control strategy to ensure effective communication and data synchronization between modules. It continuously collects battery status data from each BMS module and performs real-time analysis based on this data. The central controller uses a nonlinear function f to process the input data and dynamically adjusts the control strategy according to the battery pack's state. The algorithm formula is as follows:

[0037] Where C(t) represents the control output at time t, f is a nonlinear function used to process the input data; W i D is the data weight assigned to the i-th module; i (t) represents the data input of the ii-th module at time t. This formula aims to quantify the impact of different module data on the overall control system and make corresponding control decisions accordingly.

[0038] Distributed Control Strategy: To ensure effective communication and data synchronization between modules, the central controller employs a distributed control strategy. This strategy allows each battery module to operate independently while simultaneously enabling collaborative work through shared information. A key aspect of the distributed control strategy is data synchronization and consistency assurance. For example, a timestamp mechanism is used to ensure data up-to-dateness, and two-phase commit techniques are employed to manage read and write operations between modules to prevent data conflicts.

[0039] Energy management strategies include developing charging and discharging strategies based on real-time data and forecasts, and updating these strategies remotely via TCP protocol to quickly respond to grid changes. The charging and discharging strategy formula is as follows:

[0040] P charge / discharge (t)=g(E t E pred ,S t ,P grid (t) where P charge / discharge (t) represents the charging and discharging power at time t; E t This is the current energy storage state; E pred It is the predicted future state of energy storage; S t This refers to the battery state information at time t; P grid (t) represents the grid power demand at time t; g is a function that determines the charging and discharging power based on variables.

[0041] By remotely updating strategies via the TCP protocol, the system can adapt to grid changes more quickly, reducing mismatches caused by strategy update delays. Charging and discharging strategies based on real-time data and forecasts can better balance energy supply and demand, avoid waste, and extend battery life. Remote strategy updates increase system flexibility, allowing for rapid strategy adjustments to meet demands in different scenarios. Real-time monitoring and forecasting enable proactive preventative measures, reducing the probability of system instability or failures due to unforeseen circumstances.

[0042] The central controller should possess data acquisition, analysis, and control functions. The central controller is an Energy Management System (EMS) cloud platform. In the energy storage system, the EMS cloud platform uses the TCP protocol to adjust peak-shaving and valley-shaving strategies to maximize the benefits of electricity. The following is an explanation of the analysis and strategy logic from the perspective of energy storage:

[0043] Peak shaving refers to the practice of releasing stored electrical energy through energy storage systems during peak electricity demand periods to reduce grid load, while during off-peak periods, the energy storage systems are recharged to store excess electrical energy. This strategy can effectively balance grid load, reduce electricity costs, and improve the utilization rate of renewable energy.

[0044] The EMS cloud platform acts as a central control system, responsible for monitoring and managing the operational status of energy storage devices. Through real-time data analysis, EMS can predict electricity demand and price fluctuations, thereby formulating corresponding charging and discharging strategies.

[0045] The TCP protocol provides a reliable communication mechanism, ensuring stable data transmission between the EMS and energy storage devices. Through the TCP protocol, the EMS can receive real-time grid load, price information, and energy storage device status, enabling it to respond quickly.

[0046] Data Acquisition and Analysis: EMS collects real-time data on grid load, prices, and weather via the TCP protocol, and uses data analysis algorithms to predict future electricity demand and price changes.

[0047] Charge / discharge decisions: Based on the prediction results, EMS formulates charge / discharge strategies. For example, charging when electricity prices are low and discharging when electricity prices are high, in order to maximize economic benefits.

[0048] Optimized scheduling: Based on the real-time status of the power grid and the charging and discharging capacity of energy storage devices, the EMS optimizes the scheduling strategy to ensure the efficient use of electrical energy.

[0049] Feedback mechanism: By monitoring the operating status of energy storage devices, EMS can adjust strategies in a timely manner to ensure system flexibility and response speed.

[0050] By employing peak-shaving and valley-shaving strategies, energy storage systems can reduce electricity procurement costs and improve electricity utilization efficiency, thereby maximizing economic benefits. Furthermore, participating in electricity market regulation services can also bring additional revenue to energy storage systems.

[0051] Through intelligent scheduling on the EMS cloud platform and reliable communication via the TCP protocol, energy storage systems can effectively implement peak-shaving strategies to maximize the benefits of electricity. This not only helps reduce electricity costs but also promotes the use of renewable energy and drives sustainable development. Based on data such as battery module charge, voltage, and temperature, energy management strategies are formulated to determine how to control and balance the charging and discharging of the battery pack to achieve efficient system operation.

[0052] In energy storage systems, energy management strategies are crucial for ensuring efficient system operation and maximizing economic benefits. The following is a logical explanation of energy management strategies:

[0053] Maximizing economic benefits: By optimizing the timing of charging and discharging, the cost of electricity procurement is reduced and revenue is increased.

[0054] Power grid stability: Balance power grid load, reduce peak-hour power demand, and improve power grid reliability.

[0055] Renewable energy utilization: Improve the absorption capacity of renewable energy sources such as wind and solar power, and reduce dependence on fossil fuels.

[0056] Real-time monitoring: Through sensors and smart devices, data such as grid load, energy storage device status, and weather conditions are monitored in real time.

[0057] Data analytics: Using data analytics tools to identify electricity demand patterns and price fluctuations, and to predict future electricity demand.

[0058] Peak-hour discharge: During peak electricity demand periods, energy storage systems release stored electrical energy to reduce grid load and avoid high electricity prices.

[0059] Off-peak charging: During periods of low electricity demand, the energy storage system is charged to store electrical energy during periods of low electricity prices.

[0060] Dynamic adjustment: The charging and discharging strategy is dynamically adjusted according to real-time electricity prices and grid load changes to cope with emergencies.

[0061] Prioritization: Prioritize based on electricity demand, price, and the charging and discharging capacity of energy storage devices to ensure efficient use of resources.

[0062] Multi-objective optimization: When formulating scheduling strategies, multiple objectives such as economic benefits, environmental impact, and system stability are considered for comprehensive optimization.

[0063] Feedback and Adjustment

[0064] Real-time feedback: By monitoring the system's operational status, feedback information can be obtained in real time to evaluate the effectiveness of the strategy.

[0065] Strategy Adjustment: Adjust energy management strategies promptly based on feedback to ensure system flexibility and adaptability.

[0066] Reduce electricity costs: By employing efficient charging and discharging strategies, reduce electricity procurement costs and improve economic efficiency.

[0067] Reduce carbon emissions: Increase the utilization rate of renewable energy, reduce dependence on fossil fuels, lower carbon emissions, and promote sustainable development.

[0068] Energy management strategies are central to the efficient operation of energy storage systems. Through real-time data acquisition, dynamic charging and discharging strategies, optimized scheduling, and feedback adjustments, energy storage engineers can ensure the maximization of the system's economic and environmental benefits. This not only helps improve grid stability but also promotes the widespread adoption of renewable energy.

[0069] c. Establish a comprehensive safety protection mechanism, including but not limited to setting safety protection parameters and thresholds, and using algorithms to detect short circuits, overcharges, and over-discharges. Once an abnormality is detected, protective measures are immediately taken. The safety protection algorithm formula is as follows:

[0070] Safety = g(Safety) parameters Safety thresholds ), where Safety represents the safety status, Safety parameters Represents safety parameters, Safety thresholds This represents a preset safety threshold. If Safety is true, the system is safe; otherwise, a protection action is triggered.

[0071] Furthermore, the safety protection mechanism includes setting safety protection parameters and thresholds to achieve multiple protections against short circuits, overcharge, and over-discharge, and to cut off the power supply in a timely manner, thereby ensuring the safe operation of the system and equipment.

[0072] In energy storage systems, implementing safety protection measures is crucial to ensuring the safe and reliable operation of the system. The following is a strategic explanation of the implementation logic for these safety protection measures:

[0073] Preventing accidents: Reduce the risk of equipment failure and accidents through effective safety measures.

[0074] Protect personnel safety: Ensure the safety of operators and the surrounding environment, and prevent personal injury.

[0075] Ensure equipment integrity: Protect energy storage equipment and related facilities, and extend equipment lifespan.

[0076] Identify potential risks: Conduct a comprehensive risk assessment of the energy storage system to identify potential safety hazards, such as battery overheating, short circuits, and leaks.

[0077] Assess risk levels: Classify identified risks based on their likelihood and impact, and determine the risks to be addressed first.

[0078] Redundancy design: Redundancy design is adopted in critical systems, such as dual power supplies and backup equipment, to ensure normal operation in the event of a failure of the main system.

[0079] Protective measures: Design physical protective measures, such as firewalls, explosion-proof walls, and isolation facilities, to reduce the possibility of accidents.

[0080] Real-time monitoring: Install sensors for temperature, pressure, current, etc., to monitor the operating status of energy storage equipment in real time.

[0081] Alarm system: An alarm system is set up so that when abnormal conditions (such as overheating, overpressure, etc.) are detected, an alarm is issued in a timely manner and protective measures are taken automatically.

[0082] Establish operating procedures: Develop detailed operating procedures and emergency plans to ensure that operators can respond correctly in all situations.

[0083] Regular training: Provide regular training to operators to improve their safety awareness and emergency response capabilities, and ensure that they are familiar with operating procedures.

[0084] Regular inspections: Conduct regular safety inspections of energy storage equipment to ensure that the equipment is in good condition and to promptly identify and address any potential problems.

[0085] Maintenance and upkeep: Develop an equipment maintenance and upkeep plan, and carry out regular maintenance to ensure the safety and reliability of the equipment.

[0086] Emergency Response Plan: Develop a detailed emergency response plan, including accident handling procedures, personnel evacuation plans, and emergency resource allocation.

[0087] Drills and assessments: Conduct emergency drills regularly to assess the effectiveness of emergency plans and ensure a rapid response in the event of an actual accident.

[0088] Implementing safety protection measures is fundamental to the safe operation of energy storage systems. Through risk assessment, safety design, monitoring and alarm systems, operating procedures and training, and regular inspections and maintenance, energy storage engineers can effectively reduce accident risks and protect the safety of personnel and equipment. This not only helps improve system reliability but also enhances public trust in energy storage technology, promoting its widespread application.

[0089] d. Enables remote monitoring and intelligent management. The system is monitored, controlled, and analyzed in real-time via internet connection. Users can perform real-time monitoring, remote control, and data analysis through terminal devices. Furthermore, remote monitoring and intelligent management includes establishing connections via TCP protocol and transmitting data in JSON format. Users can monitor, control, and analyze the system in real-time through PCs, mobile apps, and other terminal devices, improving system efficiency and convenience.

[0090] In the Energy Management System (EMS) cloud platform, a remote monitoring system is configured via TCP protocol to update energy management strategies in real time, thereby maximizing the benefits of electricity. The following is a detailed description of the implementation strategy and communication protocol:

[0091] Sensor deployment: Sensors are deployed at the interface between the energy storage device and the grid to collect data such as current, voltage, power, and temperature in real time.

[0092] Data transmission: The collected data is transmitted to the EMS cloud platform via the TCP protocol to ensure the real-time performance and accuracy of the data.

[0093] Load forecasting: Using historical data and machine learning algorithms to predict future electricity demand and price fluctuations.

[0094] Status monitoring: Real-time monitoring of the status of energy storage devices, analyzing their charging and discharging efficiency and health status.

[0095] Strategy Formulation: Based on real-time data and forecasts, formulate charging and discharging strategies. For example, charge when electricity prices are low and discharge when electricity prices are high.

[0096] Remote update: The EMS policy is updated remotely via TCP protocol to ensure that the system can respond quickly to changes in the power grid.

[0097] Priority management: Optimize charging and discharging scheduling based on electricity demand, price, and energy storage device status to ensure efficient resource utilization.

[0098] Multi-objective optimization: When formulating scheduling strategies, multiple objectives such as economic benefits, environmental impact, and system stability are considered for comprehensive optimization.

[0099] Real-time feedback mechanism: By monitoring the system's operating status, feedback information is obtained in real time to evaluate the effectiveness of the strategy.

[0100] Strategy iteration: Based on feedback, adjust and optimize energy management strategies in a timely manner to ensure the flexibility and adaptability of the system.

[0101] Applications of the TCP protocol

[0102] Connection establishment: The EMS cloud platform and the remote monitoring system establish a persistent connection through the TCP protocol to ensure the reliability of data transmission.

[0103] Data format: JSON format is used for data transmission, which is convenient for parsing and processing.

[0104] Heartbeat mechanism: Sends heartbeat packets periodically to ensure connection stability and real-time performance, and promptly detects and handles connection anomalies.

[0105] Error handling: Design an error handling mechanism to automatically retry or log errors when data transmission fails or is abnormal, ensuring system stability.

[0106] By leveraging real-time data acquisition, dynamic strategy adjustment, and optimized scheduling, combined with reliable communication via the TCP protocol, the EMS cloud platform effectively maximizes the benefits of electricity. This strategy not only improves the efficiency of power resource utilization but also enhances the system's flexibility and responsiveness, supporting the widespread application of renewable energy.

[0107] e. After system setup, perform system debugging and optimization to ensure stable operation. System debugging and optimization include a comprehensive check of all connections for proper functioning and parameter accuracy, and adjustments based on actual operating conditions. Through these steps, the battery parallel operation method based on the BMS system can effectively achieve parallel operation of battery packs, improve system performance and stability, and simultaneously realize intelligent management and remote monitoring of the battery parallel operation system.

[0108] In summary, the battery parallel operation method based on the BMS system achieves effective management and operation of battery packs through modular design, communication connection, central controller, energy management strategy, safety protection mechanism and remote monitoring, providing an effective solution for the intelligent and sustainable development of energy storage systems.

[0109] In another embodiment, the above-described BMS-based parallel operation method further includes backup, employing dual backup communication modules or different types of communication protocols. The dual backup communication modules implement data backup and fault recovery mechanisms to prevent data loss and leakage.

[0110] In another embodiment, the above-described parallel implementation method based on a BMS system further includes fault diagnosis and isolation functions. Each BMS has an independent fault diagnosis function, and the main control system can isolate faulty BMSs. By utilizing intelligent battery pack modules to monitor battery status in real time, and in conjunction with real-time data acquisition and analysis, fault diagnosis and prevention are achieved, allowing for the early detection and handling of battery pack faults and ensuring stable system operation.

[0111] The following are detailed definitions of key terms and abbreviations used in parallel implementation:

[0112] BMS: Battery Management System, a system responsible for monitoring, protecting, and managing batteries.

[0113] Parallel Connection: Connecting multiple battery packs, modules, or batteries in series to increase capacity, power, or redundancy.

[0114] SOC: State of Charge, indicating the current electrical energy stored in the battery.

[0115] SOH: State of Health, indicating the degree of performance and capacity degradation of the battery.

[0116] Cell: The basic unit that makes up a battery pack / module, with specific capacity and voltage.

[0117] Battery pack / module: A functional unit consisting of multiple individual battery cells, typically with a management system.

[0118] Balancing: Ensures that the voltage or capacity of each individual cell in the battery pack / module remains consistent to improve the performance and lifespan of the battery pack.

[0119] Master-Slave Control: In a parallel system, a master controller is responsible for coordinating and managing multiple slave controllers to ensure the normal operation of the system.

[0120] Thermal Management: Monitors and controls the temperature of the battery pack / module to prevent damage caused by overheating or overcooling.

[0121] Fault Diagnosis: Real-time monitoring of faults in the battery system and ensuring safe system operation through alarms or automatic switching of protection measures.

[0122] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for parallel implementation based on a BMS system, characterized in that, The method includes the following steps: a. Design battery pack modules with identical structure and parameters. Each battery pack module contains several individual battery cells and integrates an independent BMS system. Install a communication module in each battery pack module to enable it to communicate with the central controller and select a communication protocol. b. Install a central controller as the hub of the parallel system, connecting all battery modules to achieve centralized data management and control. Based on the SOC, voltage (V), and temperature (T) data reported by each battery module, the central controller calculates the optimal energy allocation scheme using an energy management algorithm. The energy management algorithm formula is: E opt =f(SOC) i V i ,T i ), where E opt SOC represents the optimal energy allocation scheme. i V i T i These represent the charge, voltage, and temperature of the i-th battery module, respectively. Based on the calculation results, the central controller determines the charging / discharging control and equalization adjustment methods. Step b includes: predicting electricity demand and electricity price fluctuations through real-time data analysis, and formulating charging and discharging strategies; c. Establish a comprehensive safety protection mechanism, including setting safety protection parameters and thresholds, and using algorithms to detect short circuits, overcharges, and over-discharges. Once an abnormality is detected, protective measures are immediately taken. The safety protection algorithm formula is as follows: Safety = g(Safety) parameters Safety thresholds ), where Safety represents the safety status, Safety parameters Represents safety parameters, Safety thresholds This represents a preset safety threshold. If Safety is true, the system is safe; otherwise, a protection action is triggered. d. Enable remote monitoring and intelligent management, conduct real-time monitoring, control and data analysis of the system through Internet connection, and allow users to conduct real-time monitoring, remote control and data analysis of the system through terminal devices; e. After the system is built, perform system debugging and optimization to ensure stable system operation; The central controller in step (b) includes a control algorithm, employing a distributed control strategy to ensure effective communication and data synchronization between modules. The control algorithm formula is as follows: Where C(t) represents the control output at time t, f is a nonlinear function used to process the input data; W i D is the data weight assigned to the i-th module; i (t) represents the data input of the i-th module at time t.

2. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, Ensure that each battery module has independent battery management circuits and protection mechanisms.

3. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, The communication protocol selected in step (a) includes CAN bus and / or Modbus.

4. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, Step (b) includes remotely updating the strategy via TCP protocol to quickly respond to grid changes; the charging / discharging strategy formula is as follows: P charge / discharge (t)=g(E t E pred ,S t ,P grid (t) where P charge / discharge (t) represents the charging and discharging power at time t; E t This is the current energy storage state; E pred It is the predicted future state of energy storage; S t This refers to the battery state information at time t; P grid (t) represents the grid power demand at time t; g is a function that determines the charging and discharging power based on variables.

5. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, The safety protection mechanism in step (c) includes setting safety protection parameters and thresholds to achieve multiple protections against short circuits, overcharge, and over-discharge, and to cut off the power supply in a timely manner.

6. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, The remote monitoring and intelligent management in step (d) includes establishing a connection via the TCP protocol and transmitting data in JSON format.

7. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, The system debugging and optimization in step (e) includes checking whether the connections of each part are normal and whether the parameters are accurate, and adjusting and optimizing the system according to the actual operation.

8. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, The method also includes backup, employing dual backup communication modules or different types of communication protocols.

9. The method for parallel implementation based on a BMS system according to claim 1, characterized in that, The method also includes fault diagnosis and isolation functions. Each BMS has an independent fault diagnosis function, and the main control system can isolate faulty BMSs.

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