Intelligent lithium battery system with multiple communication modes

Abstract

The application discloses a kind of intelligent lithium battery systems with multiple communication modes, belong to energy storage lithium battery intelligent management technical field.The system includes lithium battery energy storage module, BMS master module, multi-communication integrated module, DC / DC power regulation module and data acquisition module.Multi-communication integrated module on-board integration RS485, CAN2.0B, LAN Ethernet and 4G full network four-way communication channels and GPS theftproof monitoring unit, BMS master module executes adaptive discharge control algorithm, based on dynamic voltage offset Voffset Control DC / DC output reference voltage SetBus=Vbus+Voffset, when real-time discharge power Preal≤0.8×average power Pavg in peak price period, automatic boost compensation is carried out;Peak-valley flat electricity price adaptive charging algorithm is executed, according to the next peak discharge demand calculation required power Qneed=(Pdmax×Th) / Vbat With current power Qnow=LiCap×SoC, automatically determine flat rate period power supply Qsupply=Qneed‑Qnow.The application realizes multi-scene general adaptation, charge-discharge dynamic accurate control and remote intelligent management.

Description

Technical Field

[0001] This invention belongs to the field of intelligent management technology for energy storage lithium batteries, specifically relating to an intelligent lithium battery system that integrates multiple communication methods and has adaptive charge and discharge regulation functions. Background Technology

[0002] Currently, the intelligent lithium battery systems used in communication base stations and home energy storage scenarios generally adopt traditional fixed parameter control logic for charging and discharging management, and the communication methods are single and fixed, which cannot adapt to complex power grid conditions and diversified network operation and maintenance needs.

[0003] In terms of discharge control, traditional battery packs adopt a direct output mode, with fixed limits for maximum battery output power and output current. The conventional control logic is as follows: the battery can only discharge at full power when the bus voltage is lower than the battery pack output voltage and the load power is greater than or equal to the battery's rated output power. If other power supply equipment is connected to the bus, causing the bus voltage to be higher than or equal to the battery's preset output voltage, the battery pack will experience problems such as failure to discharge and a sudden drop in discharge power, severely limiting the battery's energy storage utilization rate and failing to meet the needs of continuous load power supply and energy dispatch.

[0004] In terms of charging management, traditional lithium batteries employ a fixed charging strategy of "constant current charging + end-point constant voltage floating charging," where the charging current and charging time are fixed parameters with no dynamic adjustment capability. However, existing energy storage scenarios generally have peak-valley-flat tiered electricity pricing mechanisms. The industry urgently needs battery systems that can dynamically adjust charging and discharging power and duration based on electricity price periods and load demand to achieve optimal energy dispatch and maximize economic benefits. Traditional fixed-mode charging solutions cannot adapt to the differentiated control requirements of peak-valley electricity prices, resulting in low energy utilization efficiency and poor economic benefits.

[0005] Meanwhile, the existing intelligent lithium battery communication architecture is simple, with most only configured with a single RS485 or CAN industrial communication interface, which only supports local short-distance debugging and cannot realize remote wireless operation and maintenance, cloud data interaction, and multi-platform networking adaptation. It is difficult to meet the intelligent, unmanned, and remote operation and maintenance management needs of modern energy storage equipment, and its scenario adaptability is extremely poor.

[0006] In summary, the existing technology has the following drawbacks:

[0007] (1) Poor discharge adaptability: The direct discharge logic is greatly affected by the bus voltage fluctuation. When the grid jitter or the intervention of external power supply causes the bus voltage to change, the battery cannot discharge stably, and the energy storage output stability is insufficient.

[0008] (2) Rigid charging strategy: The charging parameters are fixed and cannot be dynamically adjusted in combination with peak and valley flat electricity prices and subsequent discharge demand. The energy dispatch is unreasonable and the economic benefits are low.

[0009] (3) Limited communication capabilities: It only supports traditional industrial communication, lacks wired network and wireless IoT communication capabilities, cannot connect to cloud platforms and network management systems, and lacks intelligent operation and maintenance capabilities.

[0010] (4) Weak scenario versatility: A single device can only be adapted to a single scenario and cannot simultaneously meet the differentiated needs of multiple scenarios such as communication base stations and home energy storage. The device has poor versatility and high deployment costs.

[0011] To address the shortcomings of existing technologies, such as unstable discharge, rigid charging strategies, limited communication methods, and poor scenario adaptability, this invention provides an intelligent lithium battery system with multiple built-in communication methods. It aims to solve industry pain points such as the inability of traditional batteries to adapt to bus voltage fluctuations, match peak-valley electricity price optimal scheduling, and lack of intelligent operation and maintenance across multiple scenarios by integrating multi-modal communication modules and designing adaptive charging and discharging algorithms. This achieves dynamic and precise control of battery charging and discharging, universal adaptability across multiple scenarios, and remote intelligent management, significantly improving energy storage utilization and economic benefits. Summary of the Invention

[0012] The purpose of this invention is to address the shortcomings of existing technologies by providing an intelligent lithium battery system with multiple communication methods, thereby solving the problems of low efficiency in drawing retrieval, unstructured data, poor compatibility of multiple formats, and lack of integrated management in nuclear power instrumentation and control experiments.

[0013] A smart lithium battery system with multiple communication methods includes a lithium battery energy storage module, a BMS main control module, a multi-communication integrated module, a DC / DC power regulation module, and a data acquisition module.

[0014] The lithium battery energy storage module is electrically connected to the DC / DC power regulation module for storing and releasing electrical energy.

[0015] The data acquisition module is electrically connected to the lithium battery energy storage module and the external bus, respectively, and is used to collect cell voltage, cell temperature, bus voltage Vbus, discharge current and battery state of charge (SoC) in real time, and transmit the collected data to the BMS main control module.

[0016] The multi-communication integrated module is electrically connected to the BMS main control module. It integrates an RS485 industrial communication interface, a CAN2.0B industrial communication interface, a LAN Ethernet communication module, a 4G full-network wireless communication module, and an anti-theft monitoring module with a built-in GPS positioning unit. All units are integrated on the same main control circuit board.

[0017] The BMS main control module is electrically connected to the multi-communication integration module, the DC / DC power regulation module, and the data acquisition module. It receives control commands from the cloud platform through the multi-communication integration module, executes the adaptive discharge regulation algorithm and the peak-valley-flat electricity price adaptive charging algorithm, and outputs control signals to drive the DC / DC power regulation module to complete dynamic power regulation.

[0018] Furthermore, in the multi-communication integration module:

[0019] The RS485 industrial communication interface is compatible with the Modbus-RTU protocol and supports parallel networking of multiple battery clusters for local field debugging and battery cluster linkage control; the CAN2.0B industrial communication interface has a default baud rate of 500Kbps and is used for millisecond-level synchronization of cell voltage, individual cell temperature and fault alarm raw data; the two industrial communication buses are hardware isolated and independent of each other, allowing maintenance personnel to complete equipment maintenance, parameter configuration and firmware burning without external network access.

[0020] Furthermore, the LAN Ethernet communication module is equipped with a 10 / 100M adaptive RJ45 network port, and the underlying hardware has a built-in SNMPv3 protocol stack and MQTT3.1.1 protocol stack. The two protocol stacks can run online in parallel at the same time without the need for hardware switching.

[0021] The SNMPv3 protocol stack is used to interface with the network management system of the communication base station equipment room. The network management platform directly reads the battery equipment topology, bus voltage, SoC and fault alarm information, and supports scheduled online inspection, proactive fault reporting and asset ledger management.

[0022] The MQTT 3.1.1 protocol stack is used to interface with the cloud-based energy storage dispatching platform. The cloud platform issues adaptive voltage offset Voffset, time-division parameters for valley / peak / parity periods, and charging / discharging power threshold adjustment commands.

[0023] The LAN port supports both DHCP automatic IP allocation and static IP dual configuration modes, and has a built-in reconnection mechanism after disconnection.

[0024] Furthermore, the 4G full-network compatible wireless communication module integrates a tri-mode full-network compatible module (China Mobile, China Unicom, and China Telecom) as a redundant backup communication link for the LAN wired network port. The BMS main control module monitors the LAN port heartbeat data packets in real time, and automatically switches to the 4G channel for data transmission within 100ms when the wired network is disconnected, ensuring uninterrupted communication switching. The 4G module supports a low-power sleep strategy for IoT cards, reducing the data reporting frequency during steady-state device operation.

[0025] Furthermore, the anti-theft monitoring module integrates a GPS positioning unit to collect real-time latitude and longitude location data of the equipment. The positioning information and anti-theft alarm signals are simultaneously uploaded to the cloud platform via both LAN Ethernet and 4G wireless communication channels. The anti-theft monitoring module monitors the cabinet door magnetic signal and equipment displacement vibration signal in real time. Once an abnormality alarm is triggered, the alarm information is immediately pushed to the operation and maintenance backend and the administrator terminal simultaneously via LAN and 4G dual channels. At the same time, the BMS main control module locks the charging and discharging output circuit of the DC / DC power regulation module.

[0026] Furthermore, the adaptive discharge control algorithm includes basic constant differential discharge control logic:

[0027] The cloud platform sends the adaptive voltage offset Voffset to the BMS main control module via LAN or 4G communication; the data acquisition module collects the bus voltage Vbus in real time, and the BMS main control module calculates the DC / DC output reference voltage.

[0028] SetBus = Vbus + Voffset (1)

[0029] The BMS main control module sends the SetBus command to the DC / DC power regulation module. The DC / DC power regulation module controls the battery output voltage to be fixedly higher than the bus voltage by Voffset, ensuring that the battery has continuous discharge driving force. This design only slightly increases the output voltage difference and hardly charges the parallel lead-acid battery in the system, thus extending the lifespan of the lead-acid battery in the hybrid energy storage system.

[0030] The system reads the battery SoC in real time. If the SoC is lower than the preset discharge stop threshold, it controls the DC / DC to cut off the discharge circuit. If the SoC is higher than the threshold, it continues to perform constant differential voltage discharge and cyclically collects the bus voltage to dynamically correct the output reference voltage.

[0031] Furthermore, the adaptive discharge control algorithm also includes a peak-valence discharge dynamic boost power maintenance mechanism:

[0032] When the equipment is discharging during peak discharge periods (Th), the BMS main control module continuously calculates the current cycle's average discharge power (Pavg) and simultaneously collects the instantaneous discharge power (Preal) in real time. When Preal ≤ 0.8 × Pavg, it is determined that the real-time discharge power is less than 20% of the cycle's average power, resulting in insufficient output power and failure to achieve the preset peak-shaving effect. The BMS main control module automatically increases the voltage offset (Voffset), raises the DC / DC output reference voltage (SetBus), and widens the output voltage difference between the battery and the bus to increase the discharge current. After the voltage boost is completed, Preal is re-collected, and Voffset is iteratively adjusted until Preal recovers to above 0.8 × Pavg. The voltage offset (Voffset) has an adjustable upper limit, ensuring that the DC / DC output voltage does not exceed the cell's safe output range to avoid overvoltage damage to the battery and downstream load.

[0033] Furthermore, the peak-valley-flat electricity price adaptive charging algorithm includes:

[0034] The system supports independent configuration of specific hours and minutes for off-peak price period Tl, flat price period Tm, and peak price period Th. It executes the basic strategy of charging at maximum power during off-peak price and discharging at maximum power during peak price by default throughout the entire period, and also adds intelligent flat price power replenishment judgment logic.

[0035] During off-peak hours (Tl), the system controls the battery to charge at a constant power of maximum allowable charging power (Pcmax) until the battery is fully charged or the off-peak period ends, maximizing the storage of low-priced electricity.

[0036] During peak price periods (Th), the system controls the battery to discharge at a constant power of maximum allowable discharge power (Pdmax) to maximize energy storage consumption and reduce peak electricity costs.

[0037] During the off-peak period (Tm), charging is not performed by default; instead, intelligent prediction and replenishment are made based on the discharge demand of the next peak price.

[0038] Furthermore, the intelligent prediction and replenishment of electricity during the parity period includes the following steps:

[0039] The first step is to calculate the total amount of electricity required for full-power discharge during the next peak price period:

[0040] Qneed = (Pdmax × Th) / Vbat (2)

[0041] Where Vbat is the average operating voltage of the battery, and Th is the total discharge duration at peak valence in the next cycle.

[0042] The second step is to calculate the remaining battery capacity after the off-peak charging period ends:

[0043] Qnow = LiCap × SoC (3)

[0044] Wherein, LiCap is the rated total capacity of the battery, and SoC is the state of charge of the battery after full-power charging during off-peak hours.

[0045] The third step is to determine supply and demand and develop a grid parity subsidy strategy:

[0046] Scenario 1: When Qnow < Qneed, it is determined that the next peak price period can achieve full-power discharge with sufficient duration, but the existing power cannot support full discharge throughout. The system automatically initiates grid parity replenishment. Calculate the required replenishment power:

[0047] Qsupply = Qneed - Qnow (4)

[0048] Based on the usable charging time Tm, the charging power is adaptively calculated:

[0049] Pcharge = Qsupply × Vbat / Tm (5)

[0050] Under the premise of not exceeding the maximum charging power Pcmax and the maximum charging current limit of the battery, the power shortage is accurately replenished to ensure that the power is completely exhausted during peak price periods, with no waste of residual power and no power outage losses during peak periods.

[0051] Scenario 2: When Qnow ≥ Qneed, the stored power at the current valley price can fully cover the full-power discharge demand of the next peak price. During the flat price period, no charging is performed and the device remains in standby silence to avoid redundant power accumulation and ensure that the SoC returns to zero during the next valley price period, thus achieving optimal scheduling in a loop.

[0052] This invention's algorithm abandons the traditional fixed-duration, fixed-current charging mode. Instead, it uses the peak-price maximum discharge demand as the sole anchor point and reverses the process to calculate the off-peak-price charging volume and the parity-price replenishment volume: full energy storage during off-peak hours, full discharge during peak hours, and on-demand replenishment during parity hours. This precisely matches the electricity price rules for the three time periods throughout the day, completely realizing the optimal energy dispatch strategy of "peak-time electricity is just fully discharged, off-peak-time electricity is fully utilized, and parity-price electricity is zero-waste," thereby maximizing the arbitrage profits of the energy storage system.

[0053] Furthermore, all communication channels of the multi-communication integration module are hardware-independent and logically isolated in terms of data bus, supporting simultaneous parallel operation of multiple links and separate transmission of different service data without interference.

[0054] RS485 and CAN2.0B are used for local field debugging and multi-battery cluster linkage control.

[0055] LAN-SNMP interface with the local equipment room network management system of the communication base station;

[0056] LAN-MQTT interface connects to cloud-based energy storage and dispatching platforms;

[0057] 4G full network connectivity serves as a redundant backup for wired links, transmitting alarms, location data, and offline cached data.

[0058] The entire multi-communication architecture enables three-layer, multi-dimensional synchronous management and control of local field, data center intranet and remote cloud, solving the shortcomings of traditional lithium battery single communication which can only be adapted to a single operation and maintenance scenario.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] (1) Multi-communication integration: The board integrates five communication and security units, including RS485, CAN2.0B, LAN dual protocol, 4G full network access and GPS anti-theft. A single hardware can be adapted to three business scenarios, namely communication base station backup power, home energy storage and industrial and commercial peak shaving and valley filling, without modification. The hardware has a high degree of generalization, which greatly reduces the cost of R&D, production and material inventory for multiple versions.

[0061] (2) LAN Dual Protocol Parallel Innovation: The hardware has built-in SNMPv3 and MQTT3.1.1 dual protocol stacks running online simultaneously. SNMPv3 directly connects to the network management of the operator's base station equipment room without the need for a protocol conversion gateway; MQTT3.1.1 connects to the cloud energy storage scheduling platform to realize centralized remote energy scheduling of regional energy storage.

[0062] (3) Seamless 4G redundancy switching: The 4G module serves as a redundant backup for wired links. It automatically switches within 100ms after the wired network is disconnected, ensuring that data at unattended sites does not go offline. It is suitable for remote outdoor base stations without wired network coverage and distributed home energy storage scenarios.

[0063] (4) Adaptive discharge stable output: Based on constant voltage difference discharge control with dynamic voltage offset, the battery output voltage is always higher than the bus voltage Voffset, which solves the problem that traditional direct discharge cannot discharge due to bus voltage fluctuations; the dynamic boost power maintenance mechanism during peak price period ensures stable peak-shaving discharge power and improves arbitrage income.

[0064] (5) Peak-valley electricity price intelligent dispatch: The charging and discharging strategy is reversed by taking the maximum discharge demand at peak price as the anchor point, and the power replenishment is intelligently predicted during the flat price period, so as to realize that the power during the peak period is just discharged, the power during the valley period is fully utilized, and the power during the flat price period is zero wasted, thereby maximizing the arbitrage income of the energy storage system.

[0065] (6) Anti-theft communication linkage: GPS positioning and anti-theft alarm reuse the existing communication link. When an abnormal alarm is triggered, it is pushed synchronously and the charging and discharging output is locked. No additional independent communication hardware is required, and the hardware integration is higher. Attached Figure Description

[0066] Figure 1 This is a conventional lithium battery system framework;

[0067] Figure 2 This is the framework of the intelligent lithium battery charging and discharging management system of the present invention;

[0068] Figure 3 This is a flowchart of a traditional lithium battery discharge process.

[0069] Figure 4 A flowchart of a traditional lithium battery charging process;

[0070] Figure 5 This is an application diagram of the peak-valley price energy storage product of the present invention;

[0071] Figure 6 This is a flowchart of the intelligent lithium battery adaptive discharge software of the present invention;

[0072] Figure 7 This is a flowchart of the intelligent lithium battery adaptive charging software of the present invention. Detailed Implementation

[0073] 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. 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.

[0074] Please see Figure 1-7 The present invention provides a technical solution: an intelligent lithium battery system with multiple communication methods, including a lithium battery energy storage module, a BMS main control module, a multi-communication integrated module, a DC / DC power regulation module and a data acquisition module.

[0075] The lithium battery energy storage module is electrically connected to the DC / DC power regulation module for storing and releasing electrical energy.

[0076] The data acquisition module is electrically connected to the lithium battery energy storage module and the external bus, respectively, to collect cell voltage, single cell temperature, bus voltage Vbus, discharge current and battery state of charge (SoC) in real time, and transmit the collected data to the BMS main control module.

[0077] The multi-communication integrated module is electrically connected to the BMS main control module. It integrates an RS485 industrial communication interface, a CAN2.0B industrial communication interface, a LAN Ethernet communication module, a 4G full-network wireless communication module, and an anti-theft monitoring module with a built-in GPS positioning unit. All units are integrated on the same main control circuit board.

[0078] The BMS main control module is electrically connected to the multi-communication integration module, the DC / DC power regulation module, and the data acquisition module. It receives control commands from the cloud platform through the multi-communication integration module, executes the adaptive discharge regulation algorithm and the peak-valley-flat electricity price adaptive charging algorithm, and outputs control signals to drive the DC / DC power regulation module to complete dynamic power regulation.

[0079] In multi-communication integrated modules:

[0080] The RS485 industrial communication interface is compatible with the Modbus-RTU protocol and supports parallel networking of multiple battery clusters for local field debugging and battery cluster linkage control; the CAN2.0B industrial communication interface has a default baud rate of 500Kbps and is used for millisecond-level synchronization of cell voltage, individual cell temperature and fault alarm raw data; the two industrial communication buses are hardware isolated and independent of each other, allowing maintenance personnel to complete equipment maintenance, parameter configuration and firmware burning without external network access.

[0081] The LAN Ethernet communication module is equipped with a 10 / 100M adaptive RJ45 network port. The underlying hardware has a built-in SNMPv3 protocol stack and MQTT3.1.1 protocol stack, which can run online in parallel without the need for hardware switching.

[0082] The SNMPv3 protocol stack is used to interface with the network management system of the communication base station equipment room. The network management platform directly reads the battery equipment topology, bus voltage, SoC and fault alarm information, and supports scheduled online inspection, proactive fault reporting and asset ledger management.

[0083] The MQTT 3.1.1 protocol stack is used to interface with the cloud-based energy storage dispatching platform. The cloud platform issues adaptive voltage offset Voffset, time-division parameters for valley / peak / parity periods, and charging / discharging power threshold adjustment commands.

[0084] The LAN port supports both DHCP automatic IP allocation and static IP dual configuration modes, and has a built-in reconnection mechanism after disconnection.

[0085] The 4G full-network compatible wireless communication module integrates a tri-mode (China Mobile, China Unicom, and China Telecom) full-network compatible module, serving as a redundant backup communication link for the LAN wired network port. The BMS main control module monitors the LAN port heartbeat data packets in real time, automatically switching to the 4G channel within 100ms when the wired network is disconnected, ensuring uninterrupted communication switching. The 4G module supports low-power sleep strategies for IoT cards, reducing the data reporting frequency during steady-state device operation.

[0086] The anti-theft monitoring module integrates a GPS positioning unit to collect real-time latitude and longitude location data of the equipment. The positioning information and anti-theft alarm signals are simultaneously uploaded to the cloud platform via LAN Ethernet and 4G wireless communication channels. The anti-theft monitoring module monitors the cabinet door magnetic signal and equipment displacement vibration signal in real time. Once an abnormality alarm is triggered, the alarm information is immediately pushed to the operation and maintenance backend and the administrator terminal simultaneously through the LAN and 4G dual channels. At the same time, the BMS main control module locks the charging and discharging output circuit of the DC / DC power regulation module.

[0087] The adaptive discharge control algorithm includes basic constant differential discharge control logic:

[0088] The cloud platform sends the adaptive voltage offset Voffset to the BMS main control module via LAN or 4G communication; the data acquisition module collects the bus voltage Vbus in real time, and the BMS main control module calculates the DC / DC output reference voltage.

[0089] SetBus = Vbus + Voffset (1)

[0090] The BMS main control module sends the SetBus command to the DC / DC power regulation module. The DC / DC power regulation module controls the battery output voltage to be fixedly higher than the bus voltage by Voffset, ensuring that the battery has continuous discharge driving force. This design only slightly increases the output voltage difference and hardly charges the parallel lead-acid battery in the system, thus extending the lifespan of the lead-acid battery in the hybrid energy storage system.

[0091] The system reads the battery SoC in real time. If the SoC is lower than the preset discharge stop threshold, the DC / DC converter is controlled to cut off the discharge circuit. If the SoC is higher than the threshold, constant differential voltage discharge is continuously performed and the bus voltage is collected in a loop to dynamically correct the output reference voltage.

[0092] The adaptive discharge control algorithm also includes a peak-valence discharge dynamic boost power maintenance mechanism:

[0093] When the equipment is discharging during peak discharge periods (Th), the BMS main control module continuously calculates the current cycle's average discharge power (Pavg) and simultaneously collects the instantaneous discharge power (Preal) in real time. When Preal ≤ 0.8 × Pavg, it is determined that the real-time discharge power is less than 20% of the cycle's average power, resulting in insufficient output power and failure to achieve the preset peak-shaving effect. The BMS main control module automatically increases the voltage offset (Voffset), raises the DC / DC output reference voltage (SetBus), and widens the output voltage difference between the battery and the bus to increase the discharge current. After the voltage boost is completed, Preal is re-collected, and Voffset is iteratively adjusted until Preal recovers to above 0.8 × Pavg. The voltage offset (Voffset) has an adjustable upper limit, ensuring that the DC / DC output voltage does not exceed the cell's safe output range to avoid overvoltage damage to the battery and downstream load.

[0094] Peak-valley flat-rate adaptive charging algorithms include:

[0095] The system supports independent configuration of specific hours and minutes for off-peak price period Tl, flat price period Tm, and peak price period Th. It executes the basic strategy of charging at maximum power during off-peak price and discharging at maximum power during peak price by default throughout the entire period, and also adds intelligent flat price power replenishment judgment logic.

[0096] During off-peak hours (Tl), the system controls the battery to charge at a constant power of maximum allowable charging power (Pcmax) until the battery is fully charged or the off-peak period ends, maximizing the storage of low-priced electricity.

[0097] During peak price periods (Th), the system controls the battery to discharge at a constant power of maximum allowable discharge power (Pdmax) to maximize energy storage consumption and reduce peak electricity costs.

[0098] During the off-peak period (Tm), charging is not performed by default; instead, intelligent prediction and replenishment are made based on the discharge demand of the next peak price.

[0099] Intelligent prediction and replenishment of power during off-peak hours includes the following steps:

[0100] The first step is to calculate the total amount of electricity required for full-power discharge during the next peak price period:

[0101] Qneed = (Pdmax × Th) / Vbat (2)

[0102] Where Vbat is the average operating voltage of the battery, and Th is the total discharge duration at peak valence in the next cycle.

[0103] The second step is to calculate the remaining battery capacity after the off-peak charging period ends:

[0104] Qnow = LiCap × SoC (3)

[0105] Wherein, LiCap is the rated total capacity of the battery, and SoC is the state of charge of the battery after full-power charging during off-peak hours.

[0106] The third step is to determine supply and demand and develop a grid parity subsidy strategy:

[0107] Scenario 1: When Qnow < Qneed, it is determined that the next peak price period can achieve full-power discharge with sufficient duration, but the existing power cannot support full discharge throughout the entire period. The system automatically activates grid parity supplementary power. Calculate the amount of power that needs to be supplemented:

[0108] Qsupply = Qneed - Qnow (4)

[0109] Based on the usable charging time Tm, the charging power is adaptively calculated:

[0110] Pcharge = Qsupply × Vbat / Tm (5)

[0111] Under the premise of not exceeding the maximum charging power Pcmax and the maximum charging current limit of the battery, the power shortage is accurately replenished to ensure that the power is completely exhausted during peak price periods, with no waste of residual power and no power outage losses during peak periods.

[0112] Scenario 2: When Qnow ≥ Qneed, the stored power at the current valley price can fully cover the full-power discharge demand of the next peak price. During the flat price period, no charging is performed and the device remains in standby silence to avoid redundant power accumulation and ensure that the SoC returns to zero during the next valley price period, thus achieving optimal scheduling in a loop.

[0113] This invention's algorithm abandons the traditional fixed-duration, fixed-current charging mode. Instead, it uses the peak-price maximum discharge demand as the sole anchor point and reverses the process to calculate the off-peak-price charging volume and the parity-price replenishment volume: full energy storage during off-peak hours, full discharge during peak hours, and on-demand replenishment during parity hours. This precisely matches the electricity price rules for the three time periods throughout the day, completely realizing the optimal energy dispatch strategy of "peak-time electricity is just fully discharged, off-peak-time electricity is fully utilized, and parity-price electricity is zero-waste," thereby maximizing the arbitrage profits of the energy storage system.

[0114] All communication channels of the multi-communication integrated module are hardware-independent and logically isolated in terms of data bus, supporting simultaneous parallel operation of multiple links and separate transmission of different service data without interference.

[0115] RS485 and CAN2.0B are used for local field debugging and multi-battery cluster linkage control.

[0116] LAN-SNMP interface with the local equipment room network management system of the communication base station;

[0117] LAN-MQTT interface connects to cloud-based energy storage and dispatching platforms;

[0118] 4G full network connectivity serves as a redundant backup for wired links, transmitting alarms, location data, and offline cached data.

[0119] The entire multi-communication architecture enables three-layer, multi-dimensional synchronous management and control of local field, data center intranet and remote cloud, solving the shortcomings of traditional lithium battery single communication which can only be adapted to a single operation and maintenance scenario.

[0120] Example 1: Application of backup power for communication base stations

[0121] This embodiment uses a backup power scenario for a communication base station of a certain operator as an example to explain in detail the specific implementation process of the intelligent lithium battery system of the present invention. The base station is equipped with one set of 48V / 100Ah lithium battery energy storage module, which operates in parallel with the original lead-acid battery. The base station equipment room has deployed an SNMP network management system and is also connected to a cloud-based energy storage scheduling platform.

[0122] (1) System hardware deployment:

[0123] The lithium battery energy storage module has a rated capacity of 100Ah (LiCap), an average operating voltage of 51.2V (Vbat), a maximum charging power of 3000W (Pcmax), and a maximum discharging power of 3000W (Pdmax). The BMS main control module integrates multiple communication modules. An RS485 interface connects to the existing environmental monitoring terminal within the base station via the Modbus-RTU protocol. A CAN 2.0B interface is used for internal cell data acquisition and interaction within the BMS, with a baud rate of 500Kbps. A LAN port connects to the data center switch via a network cable, simultaneously running SNMPv3 and MQTT 3.1.1 protocols. A 4G module with an IoT SIM card is inserted for redundancy.

[0124] (2) Multi-communication channel operation:

[0125] The SNMPv3 protocol stack reports battery device topology, bus voltage (Vbus), SoC, and fault alarm information to the operator's data center network management system. The network management platform can perform periodic online inspections and receive proactive fault reports. The MQTT 3.1.1 protocol stack uploads battery operating data to the cloud-based energy storage scheduling platform. The cloud platform issues control parameters such as Voffset=0.5V, off-peak hours (00:00-08:00), peak hours (10:00-12:00 and 14:00-19:00), and flat-price hours (08:00-10:00 and 12:00-14:00) according to local peak-valley electricity pricing rules. The 4G module monitors the LAN heartbeat in real time. When the data center switch fails and the network is interrupted, it automatically switches to the 4G channel within 100ms to continue uploading data and receiving commands.

[0126] (3) Adaptive discharge regulation:

[0127] During peak hours (10:00-12:00), the cloud sends a Voffset of 0.5V. The data acquisition module collects the bus voltage Vbus = 53.0V in real time. The BMS calculates SetBus = 53.0 + 0.5 = 53.5V and controls the DC / DC output to 53.5V, allowing the battery to discharge at approximately 2000W. When the base station air conditioner starts, causing the bus voltage to rise to 53.8V, the battery will stop discharging in the traditional direct discharge mode. This invention's system collects Vbus = 53.8V in real time and dynamically corrects SetBus = 53.8 + 0.5 = 54.3V, allowing the battery to continue discharging stably.

[0128] When the base station load suddenly increases and the bus voltage rises further, causing Preal to drop below 0.8×Pavg, the BMS automatically increases Voffset from 0.5V to 0.8V, raises SetBus to 54.6V, and increases the discharge current until Preal recovers to above 0.8×Pavg. The upper limit of Voffset is set to 1.5V to ensure that the output voltage does not exceed the cell's safe range.

[0129] (4) Peak-valley electricity price adaptive charging:

[0130] During off-peak hours (00:00-08:00, Tl=8h), the system charges at a constant power of 3000W (Pcmax=3000W), reaching 100% SoC in approximately 1.7 hours. During the remaining off-peak hours, it continues to float charge. Qnow=100×100%=100Ah.

[0131] The system predicts the amount of electricity required for full-power discharge during the afternoon peak period from 14:00 to 19:00 (Th=5h):

[0132] Qneed = (3000 × 5) / 51.2 = 292.97Ah

[0133] Since Qneed = 292.97Ah > Qnow = 100Ah, the battery capacity cannot support full-power discharge during the long afternoon peak price period. However, during the morning peak price period from 10:00 to 12:00 (Th = 2h), the battery discharges first, requiring Qneed1 = (3000 × 2) / 51.2 = 117.19Ah > 100Ah. After the morning peak price ends, the SoC drops to approximately 0%. The system automatically replenishes power during the midday off-peak period from 12:00 to 14:00 (Tm = 2h).

[0134] Qsupply = 292.97 - 0 = 292.97Ah

[0135] Due to battery capacity limitations, the actual charge was only 100Ah. The average charging power Pcharge = 100 × 51.2 / 2 = 2560W < Pcmax = 3000W, which is within the limit. During the afternoon peak hours, the battery was discharged at Pdmax = 3000W for approximately 1.7 hours, effectively depleting the battery during peak hours.

[0136] Example 2: Application of Home Energy Storage

[0137] This embodiment takes a home energy storage scenario as an example, and is equipped with a 51.2V / 200Ah lithium battery energy storage module. There is no wired network coverage, and it relies on 4G communication.

[0138] The 4G module serves as the main communication link, connecting to a cloud-based home energy storage management platform via the MQTT 3.1.1 protocol. Users can remotely view the battery SoC, charging / discharging status, and historical power consumption data through a mobile app. An RS485 interface connects to the home inverter, and CAN 2.0B is used for internal BMS management. The anti-theft monitoring module's GPS positioning unit reports the device's location in real time, while door magnetic sensors and vibration sensors monitor the cabinet's status.

[0139] Users set peak and off-peak electricity pricing periods via the app, and the system automatically executes adaptive charging and discharging scheduling. When unauthorized mobile devices are detected, the vibration sensor triggers an alarm, and the alarm information is immediately pushed to the user's mobile phone and cloud platform via the 4G channel. At the same time, the BMS locks the DC / DC output circuit.

[0140] Example 3: Application of Peak Shaving and Valley Filling Scenarios in Industrial and Commercial Scenarios

[0141] This embodiment takes industrial and commercial energy storage in Dongguan as an example, configuring a 51.2V / 500Ah lithium battery energy storage module with Pcmax=15kW and Pdmax=15kW. Peak-valley electricity pricing periods in Dongguan are: 00:00-08:00 (valley price), 08:00-10:00 (flat price), 10:00-12:00 (peak price), 12:00-14:00 (flat price), and 14:00-19:00 (long-term peak price).

[0142] During off-peak hours at night, the battery is fully charged at 15kW to stockpile low-priced electricity. During peak hours in the morning, it is discharged at 15kW to profit from arbitrage. The system predicts that the peak period from 2:00 PM to 7:00 PM will last for 5 hours, requiring a power consumption of Qneed = (15000 × 5) / 51.2 = 1464.84 Ah, far exceeding the battery capacity of 500 Ah. Therefore, during the flat-price period from 12:00 PM to 2:00 PM, the battery is automatically replenished to full charge to fully match the afternoon peak discharge demand. This achieves precise matching of power supply and demand throughout the day, minimizing peak-period power depletion, and maximizing energy dispatch benefits.

[0143] The above three embodiments cover three typical application scenarios: communication base stations, home energy storage, and industrial and commercial peak shaving and valley filling, verifying the effectiveness and versatility of the multi-communication integrated and adaptive charge and discharge regulation of the present invention.

[0144] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart lithium battery system with multiple built-in communication methods, characterized in that, This includes a lithium battery energy storage module, a BMS main control module, a multi-communication integrated module, a DC / DC power regulation module, and a data acquisition module; The lithium battery energy storage module is electrically connected to the DC / DC power regulation module for storing and releasing electrical energy; The data acquisition module is electrically connected to the lithium battery energy storage module and the external bus respectively, and is used to collect cell voltage, single cell temperature, bus voltage Vbus, discharge current and battery state of charge SoC in real time, and transmit the collected data to the BMS main control module. The multi-communication integrated module is electrically connected to the BMS main control module. It integrates an RS485 industrial communication interface, a CAN2.0B industrial communication interface, a LAN Ethernet communication module, a 4G full-network wireless communication module, and an anti-theft monitoring module with a built-in GPS positioning unit. All units are integrated on the same main control circuit board. The BMS main control module is electrically connected to the multi-communication integration module, the DC / DC power regulation module, and the data acquisition module. It receives control commands from the cloud platform through the multi-communication integration module, executes the adaptive discharge regulation algorithm and the peak-valley-flat electricity price adaptive charging algorithm, and outputs control signals to drive the DC / DC power regulation module to complete dynamic power regulation.

2. The intelligent lithium battery system according to claim 1, characterized in that, In the multi-communication integration module: The RS485 industrial communication interface is compatible with the Modbus-RTU protocol and supports parallel networking of multiple battery clusters for local field commissioning and battery cluster linkage control. The CAN2.0B industrial communication interface has a default baud rate of 500Kbps, used for millisecond-level synchronization of raw data such as cell voltage, individual cell temperature, and fault alarms. The two industrial communication buses are hardware isolated and independent of each other, allowing maintenance personnel to complete equipment maintenance, parameter configuration, and firmware burning without needing an external network connection.

3. The intelligent lithium battery system according to claim 1, characterized in that, The LAN Ethernet communication module is equipped with a 10 / 100M adaptive RJ45 network port. The underlying hardware has a built-in SNMPv3 protocol stack and MQTT3.1.1 protocol stack, which can run online in parallel without the need for hardware switching. The SNMPv3 protocol stack is used to interface with the network management system of the communication base station equipment room. The network management platform directly reads the battery equipment topology, bus voltage, SoC and fault alarm information, and supports scheduled online inspection, active fault reporting and asset ledger management. The MQTT 3.1.1 protocol stack is used to interface with the cloud-based energy storage dispatching platform. The cloud platform issues adaptive voltage offset Voffset, time-division parameters for valley / peak / parity periods, and charging / discharging power threshold adjustment commands. The LAN port supports both DHCP automatic IP allocation and static IP dual configuration modes, and has a built-in reconnection mechanism after disconnection.

4. The intelligent lithium battery system according to claim 1, characterized in that, The 4G full-network wireless communication module has a built-in China Mobile, China Unicom and China Telecom tri-mode full-network module, which serves as a redundant backup communication link for the LAN wired network port. The BMS main control module monitors the LAN port heartbeat data packets in real time. When the wired network is disconnected, it automatically switches to the 4G channel to transmit data within 100ms, ensuring uninterrupted communication switching. The 4G module supports low-power sleep strategy for IoT cards, reducing the data reporting frequency during steady-state operation of the device.

5. The intelligent lithium battery system according to claim 1, characterized in that, The anti-theft monitoring module integrates a GPS positioning unit, which collects the latitude and longitude location data of the device in real time. The positioning information and anti-theft alarm signals are simultaneously uploaded to the cloud platform via LAN Ethernet and 4G wireless communication channels. The anti-theft monitoring module monitors the cabinet door magnetic signal and equipment displacement vibration signal in real time. Once an abnormality alarm is triggered, the alarm information is immediately pushed to the operation and maintenance backend and the administrator terminal through LAN and 4G dual channels. At the same time, the BMS main control module locks the charging and discharging output circuit of the DC / DC power regulation module.

6. The intelligent lithium battery system according to claim 1, characterized in that, The adaptive discharge control algorithm includes basic constant differential voltage discharge control logic: The cloud platform sends the adaptive voltage offset Voffset to the BMS main control module via LAN or 4G communication; The data acquisition module collects the bus voltage Vbus in real time, and the BMS main control module calculates the DC / DC output reference voltage. SetBus = Vbus + Voffset The BMS main control module sends the SetBus command to the DC / DC power regulation module, which controls the battery output voltage to be fixedly higher than the bus voltage by Voffset. The system reads the battery SoC in real time. If the SoC is lower than the preset discharge stop threshold, the DC / DC converter is controlled to cut off the discharge circuit. If the SoC is higher than the threshold, constant differential voltage discharge is continuously performed and the bus voltage is collected in a loop to dynamically correct the output reference voltage.

7. The intelligent lithium battery system according to claim 6, characterized in that, The adaptive discharge control algorithm also includes a peak discharge dynamic boost power maintenance mechanism: When the equipment is discharging during the peak discharge period (Th), the BMS main control module continuously calculates the average discharge power Pavg of the current cycle and synchronously collects the instantaneous discharge power Preal in real time. When Preal ≤ 0.8 × Pavg, the output power is determined to be insufficient. The BMS main control module automatically increases the voltage offset Voffset, raises the DC / DC output reference voltage SetBus, and expands the output voltage difference between the battery and the bus to increase the discharge current. After the voltage boost is complete, the Preal value is re-acquired, and the Voffset is iteratively adjusted until the Preal value recovers to above 0.8×Pavg; The voltage offset Voffset setting has an adjustable upper limit, ensuring that the DC / DC output voltage does not exceed the cell's safe output range.

8. The intelligent lithium battery system according to claim 1, characterized in that, The peak-valley flat-rate adaptive charging algorithm includes: The system supports independent configuration of specific hours and minutes for the off-peak period Tl, the flat-price period Tm, and the peak-price period Th; during the off-peak period Tl, the system controls the battery to charge at a constant power of the maximum allowable charging power Pcmax until the battery is fully charged or the off-peak period ends. During peak price periods (Th), the system controls the battery to discharge at a constant power of the maximum allowable discharge power (Pdmax). During the parity period Tm, the system intelligently predicts and replenishes power based on the discharge demand of the next peak price.

9. The intelligent lithium battery system according to claim 8, characterized in that, The intelligent prediction and replenishment of power during the off-peak period Includes the following steps: The first step is to calculate the total amount of electricity required for full-power discharge during the next peak price period: Qneed = (Pdmax × Th) / Vbat Where Vbat is the average operating voltage of the battery; The second step is to calculate the remaining battery capacity after the off-peak charging period ends: Qnow = LiCap × SoC Where LiCap is the rated total capacity of the battery; The third step is supply and demand determination: When Qnow < Qneed, the system automatically activates grid parity power supply and calculates the amount of electricity that needs to be supplied. Qsupply = Qneed – Qnow Based on the available time Tm at the parity level, the parity charging power Pcharge = Qsupply × Vbat / Tm is adaptively calculated to make up the missing power without exceeding the battery's maximum charging power Pcmax and maximum charging current limit. When Qnow ≥ Qneed, do not charge during the off-peak hours and remain in standby mode.

10. The intelligent lithium battery system according to claim 1, characterized in that, All communication channels of the multi-communication integrated module are hardware-independent and logically isolated in terms of data bus, supporting simultaneous parallel operation of multiple links and split transmission of different service data. RS485 and CAN2.0B are used for local field debugging and multi-battery cluster linkage control. LAN-SNMP interface with the local equipment room network management system of the communication base station; LAN-MQTT interface connects to cloud-based energy storage and dispatching platforms; 4G full network connectivity serves as a redundant backup for wired links, transmitting alarm, location, and offline cached data; The entire multi-communication architecture enables synchronized management and control across three layers: local site, data center intranet, and remote cloud.

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