Multi-link collaborative wireless communication battery management system

Abstract

The invention discloses a multi-link collaborative wireless communication battery management system, and relates to the field of wireless communication networks. The system comprises a battery data acquisition module, a multi-link communication module, an intelligent control module, an energy management module and a cloud management platform. And the battery data acquisition module is electrically connected to the battery module. A scene recognition rule base is pre-stored in the heterogeneous link scheduling unit, a scene type is matched according to real-time environment sensor data, then a corresponding link combination is started, Bluetooth 5.0 and ZigBee 3.0 links are started in an indoor close-range scene, and the data acquisition requirements of low power consumption, short distance and high frequency are met; in a remote monitoring scene, the main 4G / 5G cellular link is used for transmitting state data, the standby Wi-Fi link is used for transmitting large-capacity data, the advantages of all the links are brought into full play, and the utilization efficiency of spectrum resources is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication networks, and in particular to a multi-link coordinated wireless communication battery management system. Background Art

[0002] Traditional battery management systems have many limitations in wireless communication. Most use single-link communication. In complex electromagnetic environments, such as industrial plants and densely populated urban areas with tall buildings, signals are susceptible to interference, leading to data transmission interruptions or errors. This makes it impossible to accurately obtain key parameters such as battery voltage, current, state of charge (SOC), and state of health (SOH) in real time. When devices are mobile or transmitting over long distances, the coverage and transmission rate of single-link communication are insufficient, resulting in delays in the battery management system's monitoring and control of the battery, affecting the safe and stable operation of the battery.

[0003] Although the existing multi-link communication battery management system adopts multiple links, it lacks an intelligent coordination mechanism between the links and cannot dynamically adjust link resources according to environmental changes and data transmission needs, resulting in inefficient spectrum resource utilization and increased energy consumption. In terms of heterogeneous link coordination, there is no effective scenario adaptation strategy, and the advantages of each link cannot be fully utilized in different scenarios, making it difficult to achieve efficient and reliable data transmission and battery management.

[0004] Therefore, we have made improvements to this and proposed a multi-link collaborative wireless communication battery management system. Summary of the Invention

[0005] The present invention provides the following technical solutions:

[0006] The specific application is as follows:

[0007] A multi-link collaborative wireless communication battery management system, comprising: a battery data acquisition module, a multi-link communication module, an intelligent control module, an energy management module and a cloud management platform;

[0008] A battery data acquisition module, electrically connected to the battery module, for collecting voltage, current, temperature, state of charge (SOC), and state of health (SOH) parameters of the battery module, generating a data packet with a timestamp and sending it to the multi-link communication module;

[0009] A multi-link communication module, communicatively connected to the battery data acquisition module and the intelligent control module, integrating Bluetooth, Wi-Fi, ZigBee, and cellular network communication units. Each communication unit is independently configured with a transceiver antenna and a modem module, and is used to establish a wireless transmission link according to the scheduling instructions of the intelligent control module;

[0010] Among them, a time division duplex coordinator is set between each communication unit of the multi-link communication module, and the channel occupation time slot of each link is divided according to the scheduling instruction of the intelligent control module to avoid co-frequency interference.

[0011] An intelligent control module is electrically connected to the multi-link communication module and the energy management module, and includes a link status monitoring unit, an intelligent dynamic link fusion unit, a heterogeneous link scheduling unit, and an anti-interference game decision unit. The link status monitoring unit collects the channel signal-to-noise ratio (SNR), transmission delay (RTT), packet loss rate (PER), and spectrum occupancy parameters of each communication unit in real time, generates a link state vector, and inputs it to the intelligent dynamic link fusion unit. The intelligent dynamic link fusion unit has a built-in deep learning neural network model, which takes the link state vector and the data packet type of the battery data acquisition module as input and outputs multi-link data. A fusion strategy, which includes the bandwidth allocation ratio and data packet reassembly rules for each link; a heterogeneous link scheduling unit, which pre-stores a scene recognition rule base, which includes characteristic parameter thresholds for indoor / outdoor, close / long distance, and high-dynamic / static scenes, matches the scene type according to real-time environmental sensor data, and outputs a link combination activation instruction for the corresponding scene to the multi-link communication module; an anti-interference game decision unit, which constructs a strategy space including link frequency band, modulation mode, and transmission power, establishes a benefit function for each link based on game theory, reaches a Nash equilibrium state through distributed iterative calculation, and outputs an anti-interference parameter adjustment instruction to the multi-link communication module;

[0012] The deep learning neural network model of the intelligent dynamic link fusion unit achieves data fusion through the following steps:

[0013] SA1, start;

[0014] SA2: Perform timestamp alignment and Kalman filter noise reduction on the same type of battery data transmitted on different links;

[0015] SA3: Allocate link transmission weights based on data packet priority. The priority of data packets is control instructions > real-time status data > historical data.

[0016] SA4: Extract the data features of each link through the convolutional neural network and output the optimal data fusion sequence through the fully connected layer;

[0017] SA5, end.

[0018] The scenario recognition rule base of the heterogeneous link scheduling unit includes:

[0019] Indoor close-range scenario, distance <10m, GPS signal strength <-130dBm: Enable Bluetooth 5.0 and ZigBee 3.0 links for battery data collection, with a transmission period of ≤50ms;

[0020] Remote monitoring scenarios, with a distance greater than 1km and a cellular network signal strength greater than -100dBm, use the primary 4G / 5G cellular link to transmit status data, and the backup Wi-Fi link to transmit large-capacity battery image data.

[0021] In high-dynamic scenarios, when vehicle acceleration is greater than 0.5g, both the cellular link and the Bluetooth link are enabled simultaneously. The cellular link transmits the original data, and the Bluetooth link transmits the checksum to achieve redundant data transmission.

[0022] An energy management module is electrically connected to the battery pack and the intelligent control module, collects the total voltage of the battery pack, the remaining power SoE, and the charge and discharge current, generates an energy status signal and sends it to the intelligent control module, and simultaneously receives the link power consumption control instruction from the intelligent control module and adjusts the operating parameters of the power amplifier module of each communication unit;

[0023] The link power consumption control strategy of the energy management module includes:

[0024] When the remaining battery power SoE is less than 20%, each communication unit is forced to enter low power mode, the Bluetooth link transmission power is ≤4dBm, and the ZigBee link transmission rate is reduced to 250kbps;

[0025] When the battery is in charging state and the charging current is greater than 0.1C, 5% to 10% of the charging power is allocated to the cellular link, and its modulation method is upgraded to high-order modulation to increase the transmission rate.

[0026] The cloud management platform is communicatively connected to the multi-link communication module, receives battery data through the multi-link communication module, generates a battery status assessment report and a link optimization strategy based on big data analysis, and transmits the report back to the intelligent control module.

[0027] The working steps of the battery data acquisition module are as follows:

[0028] SB1, start;

[0029] SB2. Use an analog-to-digital converter to sample the voltage, current, and temperature signals of the battery module in real time at a set frequency, and record the sampling time to generate a timestamp;

[0030] SB3. Calculate the battery's state of charge (SOC) based on the ampere-hour integration method combined with the open-circuit voltage correction algorithm, and estimate the battery's state of health (SOH) using a capacity decay model.

[0031] SB4. Pack the collected and calculated voltage, current, temperature, SOC, and SOH data, add a timestamp and checksum, and generate a data packet with a timestamp;

[0032] SB5, sending the data packet to the multi-link communication module;

[0033] SB6, end.

[0034] The working steps of the multi-link communication module are as follows:

[0035] SC1, start;

[0036] SC2, receiving the dispatch instruction from the intelligent control module and determining the wireless communication link to be enabled, where the wireless communication link includes Bluetooth, Wi-Fi, ZigBee, and cellular network;

[0037] SC3: Configure the transceiver antennas and modem module parameters for the enabled communication units to establish wireless transmission links.

[0038] SC4 receives data packets sent by the battery data acquisition module and transmits them through the established wireless link according to the scheduling instructions of the intelligent control module, or receives data returned by the cloud management platform through the wireless link and forwards it to the intelligent control module;

[0039] SC5, end.

[0040] The working steps of the intelligent control module include: the working steps of the link status monitoring unit, the working steps of the intelligent dynamic link fusion unit, the working steps of the heterogeneous link scheduling unit and the working steps of the anti-interference game decision unit;

[0041] The link status monitoring unit works as follows:

[0042] SD1, start;

[0043] SD2, real-time collection of channel signal-to-noise ratio, transmission delay, packet loss rate and spectrum occupancy parameters of each communication unit;

[0044] SD3, organize the collected parameters and generate a link state vector;

[0045] SD4, inputs the link state vector to the intelligent dynamic link fusion unit;

[0046] SD5, end.

[0047] The working steps of the intelligent dynamic link fusion unit are as follows:

[0048] SE1, start;

[0049] SE2, receiving the link state vector input by the link state monitoring unit and the data packet type of the battery data acquisition module;

[0050] SE3: Perform timestamp alignment and Kalman filter noise reduction on the same type of battery data transmitted on different links;

[0051] SE4. Allocate link transmission weights based on data packet priority, where the priority is: control instructions > real-time status data > historical data;

[0052] SE5: Extract the data features of each link through a convolutional neural network and output the optimal data fusion sequence through a fully connected layer, namely the multi-link data fusion strategy, including the bandwidth allocation ratio of each link and the data packet reassembly rules;

[0053] SE6, sends the multi-link data fusion strategy to the multi-link communication module to guide data transmission;

[0054] SE7, end.

[0055] The working steps of the heterogeneous link scheduling unit are as follows:

[0056] SF1, start;

[0057] SF2, obtain real-time environmental sensor data;

[0058] SF3, matching real-time environmental sensor data with a pre-stored scene recognition rule library to determine the current scene type, where the scene recognition rule library includes characteristic parameter thresholds for indoor / outdoor, close / long distance, and high-dynamic / stationary scenes;

[0059] SF4, based on the scenario type, retrieves the link combination activation instruction corresponding to the scenario from the rule library and sends it to the multi-link communication module;

[0060] SF5, the end.

[0061] The working steps of the anti-interference game decision unit are as follows:

[0062] SG1, start;

[0063] SG2: Construct a strategy space that includes link frequency band, modulation mode, and transmit power;

[0064] SG3. Based on game theory, establish the payoff function for each link: Ui = α·(1-PERi)+β·(1-γ·fcollision)-δ·Ptx, where Ui is the payoff of the i-th link, α, β, and δ are weight coefficients, PERi is the link packet loss rate, fcollision is the frequency band conflict probability, and Ptx is the transmit power. The optimal strategy combination for each link is iteratively solved using the gradient descent method.

[0065] SG4, iteratively calculate the profit function through the gradient descent method to solve the optimal strategy combination for each link;

[0066] SG5. When the convergence condition is reached, the anti-interference parameter adjustment instruction of each link is sent to the multi-link communication module, wherein the anti-interference parameter adjustment instruction includes: frequency band, modulation mode, and transmit power adjustment value;

[0067] SG6, end.

[0068] The working steps of the energy management module are as follows:

[0069] SH1, start;

[0070] SH2, real-time collection of battery pack total voltage, remaining capacity SoE and charge and discharge current to generate energy status signal;

[0071] SH3, sending the energy status signal to the intelligent control module;

[0072] SH4, receiving the link power consumption control instruction sent by the intelligent control module;

[0073] SH5. Adjust the operating parameters of the power amplifier modules of each communication unit according to the link power consumption control instruction;

[0074] SH6, end.

[0075] The working steps of the cloud management platform are as follows:

[0076] SI1, start;

[0077] SI2, receiving the battery data uploaded by the battery data acquisition module through the multi-link communication module;

[0078] SI3: Process battery data based on big data analysis algorithms to generate battery status assessment reports and link optimization strategies;

[0079] SI4. Send the battery status assessment report and link optimization strategy back to the intelligent control module through the multi-link communication module;

[0080] SI5, end.

[0081] Compared with the prior art, the present invention has the following beneficial effects:

[0082] 1. The heterogeneous link scheduling unit of the present invention pre-stores a scene recognition rule library, matches the scene type according to the real-time environmental sensor data, and then enables the corresponding link combination. In indoor close-range scenarios, Bluetooth 5.0 and ZigBee 3.0 links are enabled to meet the low-power, short-distance, and high-frequency data acquisition requirements; in remote monitoring scenarios, the main 4G / 5G cellular link is used to transmit status data, and the backup Wi-Fi link is used to transmit large-capacity data, giving full play to the advantages of each link and improving the efficiency of spectrum resource utilization.

[0083] 2. The anti-interference game decision-making unit constructs a strategy space that includes link frequency bands, modulation methods, and transmission power. It establishes a profit function based on game theory and reaches a Nash equilibrium state through distributed iterative calculations. This enables the system to automatically adjust link parameters according to the interference situation, effectively avoiding interference frequency bands. In environments with severe interference, it reduces the packet loss rate of data transmission and ensures the stability of data transmission.

[0084] 3. The energy management module collects relevant parameters of the battery pack and adjusts the operating parameters of the power amplifier module of each communication unit according to the remaining battery power and charging status. When the remaining battery power is low, each communication unit is forced to enter low-power mode to reduce battery energy consumption. When the battery is charging, the charging power is reasonably allocated to the cellular link and the modulation method is upgraded to increase the transmission rate.

[0085] 4. The cloud management platform receives battery data through a multi-link communication module, uses big data analysis to generate battery status assessment reports and link optimization strategies, and transmits them back to the intelligent control module. This closed-loop management model enables accurate assessment of battery status and optimized configuration of links, supports remote monitoring and fault diagnosis, and improves the intelligence level and operation and maintenance efficiency of the battery management system.

[0086] 5. By integrating multiple communication units and building a multi-link collaborative architecture, the intelligent dynamic link fusion unit uses a deep learning neural network model to perform timestamp alignment and Kalman filtering noise reduction on data transmitted on different links, and allocates link transmission weights based on data packet priority, making data transmission more stable and reliable, reducing the risk of data loss due to interference, and improving the accuracy of data transmission in complex electromagnetic environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 This is a system diagram of this application;

[0088] Figure 2 This is a schematic diagram of the workflow of the battery data acquisition module of this application;

[0089] Figure 3 This is a schematic diagram of the workflow of the multi-link communication module of this application;

[0090] Figure 4 This is a schematic diagram of the workflow of the intelligent control module of this application;

[0091] Figure 5 A schematic diagram of the workflow of the energy management module of this application;

[0092] Figure 6 This is a flowchart of the cloud management platform for this application. DETAILED DESCRIPTION

[0093] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in 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 part of the embodiments of the present invention, not all of them.

[0094] Therefore, the following detailed description of the embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely represents some embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0095] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features and technical solutions therein may be combined with each other.

[0096] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0097] In the description of the present invention, it should be noted that the terms "upper" and "lower" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or the orientations or positional relationships in which the inventive product is typically placed when in use, or the orientations or positional relationships commonly understood by those skilled in the art. Such terms are intended solely to facilitate the description of the present invention and simplify the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first" and "second" and the like are used solely for distinction and should not be construed as indicating or implying relative importance.

[0098] The present invention provides the following technical solutions:

[0099] Please refer to Figure 1-6 , a multi-link collaborative wireless communication battery management system, including: battery data acquisition module, multi-link communication module, intelligent control module, energy management module and cloud management platform;

[0100] A battery data acquisition module, electrically connected to the battery module, for collecting voltage, current, temperature, state of charge (SOC), and state of health (SOH) parameters of the battery module, generating a data packet with a timestamp and sending it to the multi-link communication module;

[0101] A multi-link communication module, communicatively connected to the battery data acquisition module and the intelligent control module, integrating Bluetooth, Wi-Fi, ZigBee, and cellular network communication units. Each communication unit is independently configured with a transceiver antenna and a modem module, and is used to establish a wireless transmission link according to the scheduling instructions of the intelligent control module;

[0102] Among them, a time division duplex coordinator is set between each communication unit of the multi-link communication module, and the channel occupation time slot of each link is divided according to the scheduling instruction of the intelligent control module to avoid co-frequency interference.

[0103] An intelligent control module is electrically connected to the multi-link communication module and the energy management module, and includes a link status monitoring unit, an intelligent dynamic link fusion unit, a heterogeneous link scheduling unit, and an anti-interference game decision unit. The link status monitoring unit collects the channel signal-to-noise ratio (SNR), transmission delay (RTT), packet loss rate (PER), and spectrum occupancy parameters of each communication unit in real time, generates a link state vector, and inputs it to the intelligent dynamic link fusion unit. The intelligent dynamic link fusion unit has a built-in deep learning neural network model, which takes the link state vector and the data packet type of the battery data acquisition module as input and outputs multi-link data. A fusion strategy, which includes the bandwidth allocation ratio and data packet reassembly rules for each link; a heterogeneous link scheduling unit, which pre-stores a scene recognition rule base, which includes characteristic parameter thresholds for indoor / outdoor, close / long distance, and high-dynamic / static scenes, matches the scene type according to real-time environmental sensor data, and outputs a link combination activation instruction for the corresponding scene to the multi-link communication module; an anti-interference game decision unit, which constructs a strategy space including link frequency band, modulation mode, and transmission power, establishes a benefit function for each link based on game theory, reaches a Nash equilibrium state through distributed iterative calculation, and outputs an anti-interference parameter adjustment instruction to the multi-link communication module;

[0104] The deep learning neural network model of the intelligent dynamic link fusion unit achieves data fusion through the following steps:

[0105] SA1, start;

[0106] SA2: Perform timestamp alignment and Kalman filter noise reduction on the same type of battery data transmitted on different links;

[0107] SA3: Allocate link transmission weights based on data packet priority. The priority of data packets is control instructions > real-time status data > historical data.

[0108] SA4: Extract the data features of each link through the convolutional neural network and output the optimal data fusion sequence through the fully connected layer;

[0109] SA5, end.

[0110] The scenario recognition rule base of the heterogeneous link scheduling unit includes:

[0111] Indoor close-range scenario, distance <10m, GPS signal strength <-130dBm: Enable Bluetooth 5.0 and ZigBee 3.0 links for battery data collection, with a transmission period of ≤50ms;

[0112] Remote monitoring scenarios, with a distance greater than 1km and a cellular network signal strength greater than -100dBm, use the primary 4G / 5G cellular link to transmit status data, and the backup Wi-Fi link to transmit large-capacity battery image data.

[0113] In high-dynamic scenarios, when vehicle acceleration is greater than 0.5g, both the cellular link and the Bluetooth link are enabled simultaneously. The cellular link transmits the original data, and the Bluetooth link transmits the checksum to achieve redundant data transmission.

[0114] An energy management module is electrically connected to the battery pack and the intelligent control module, collects the total voltage of the battery pack, the remaining power SoE, and the charge and discharge current, generates an energy status signal and sends it to the intelligent control module, and simultaneously receives the link power consumption control instruction from the intelligent control module and adjusts the operating parameters of the power amplifier module of each communication unit;

[0115] The link power consumption control strategy of the energy management module includes:

[0116] When the remaining battery power SoE is less than 20%, each communication unit is forced to enter low power mode, the Bluetooth link transmission power is ≤4dBm, and the ZigBee link transmission rate is reduced to 250kbps;

[0117] When the battery is in charging state and the charging current is greater than 0.1C, 5% to 10% of the charging power is allocated to the cellular link, and its modulation method is upgraded to high-order modulation to increase the transmission rate.

[0118] The cloud management platform is communicatively connected to the multi-link communication module, receives battery data through the multi-link communication module, generates a battery status assessment report and a link optimization strategy based on big data analysis, and transmits the report back to the intelligent control module.

[0119] The working steps of the battery data acquisition module are as follows:

[0120] SB1, start;

[0121] SB2. Use an analog-to-digital converter to sample the voltage, current, and temperature signals of the battery module in real time at a set frequency, and record the sampling time to generate a timestamp;

[0122] SB3. Calculate the battery's state of charge (SOC) based on the ampere-hour integration method combined with the open-circuit voltage correction algorithm, and estimate the battery's state of health (SOH) using a capacity decay model.

[0123] SB4. Pack the collected and calculated voltage, current, temperature, SOC, and SOH data, add a timestamp and checksum, and generate a data packet with a timestamp;

[0124] SB5, sending the data packet to the multi-link communication module;

[0125] SB6, end.

[0126] The working steps of the multi-link communication module are as follows:

[0127] SC1, start;

[0128] SC2, receiving the dispatch instruction from the intelligent control module and determining the wireless communication link to be enabled, where the wireless communication link includes Bluetooth, Wi-Fi, ZigBee, and cellular network;

[0129] SC3: Configure the transceiver antennas and modem module parameters for the enabled communication units to establish wireless transmission links.

[0130] SC4 receives data packets sent by the battery data acquisition module and transmits them through the established wireless link according to the scheduling instructions of the intelligent control module, or receives data returned by the cloud management platform through the wireless link and forwards it to the intelligent control module;

[0131] SC5, end.

[0132] The working steps of the intelligent control module include: the working steps of the link status monitoring unit, the working steps of the intelligent dynamic link fusion unit, the working steps of the heterogeneous link scheduling unit and the working steps of the anti-interference game decision unit;

[0133] The link status monitoring unit works as follows:

[0134] SD1, start;

[0135] SD2, real-time collection of channel signal-to-noise ratio, transmission delay, packet loss rate and spectrum occupancy parameters of each communication unit;

[0136] SD3, organize the collected parameters and generate a link state vector;

[0137] SD4, inputs the link state vector to the intelligent dynamic link fusion unit;

[0138] SD5, end.

[0139] The working steps of the intelligent dynamic link fusion unit are as follows:

[0140] SE1, start;

[0141] SE2, receiving the link state vector input by the link state monitoring unit and the data packet type of the battery data acquisition module;

[0142] SE3: Perform timestamp alignment and Kalman filter noise reduction on the same type of battery data transmitted on different links;

[0143] SE4. Allocate link transmission weights based on data packet priority, where the priority is: control instructions > real-time status data > historical data;

[0144] SE5: Extract the data features of each link through a convolutional neural network and output the optimal data fusion sequence through a fully connected layer, namely the multi-link data fusion strategy, including the bandwidth allocation ratio of each link and the data packet reassembly rules;

[0145] SE6, sends the multi-link data fusion strategy to the multi-link communication module to guide data transmission;

[0146] SE7, end.

[0147] The working steps of the heterogeneous link scheduling unit are as follows:

[0148] SF1, start;

[0149] SF2, obtain real-time environmental sensor data;

[0150] SF3, matching real-time environmental sensor data with a pre-stored scene recognition rule library to determine the current scene type, where the scene recognition rule library includes characteristic parameter thresholds for indoor / outdoor, close / long distance, and high-dynamic / stationary scenes;

[0151] SF4, based on the scenario type, retrieves the link combination activation instruction corresponding to the scenario from the rule base and sends it to the multi-link communication module;

[0152] SF5, the end.

[0153] The working steps of the anti-interference game decision unit are as follows:

[0154] SG1, start;

[0155] SG2: Construct a strategy space that includes link frequency band, modulation mode, and transmit power;

[0156] SG3. Based on game theory, establish the payoff function for each link: Ui = α·(1-PERi)+β·(1-γ·fcollision)-δ·Ptx, where Ui is the payoff of the i-th link, α, β, and δ are weight coefficients, PERi is the link packet loss rate, fcollision is the frequency band conflict probability, and Ptx is the transmit power. The optimal strategy combination for each link is iteratively solved using the gradient descent method.

[0157] SG4, iteratively calculate the profit function through the gradient descent method to solve the optimal strategy combination for each link;

[0158] SG5. When the convergence condition is reached, the anti-interference parameter adjustment instruction of each link is sent to the multi-link communication module, wherein the anti-interference parameter adjustment instruction includes: frequency band, modulation mode, and transmit power adjustment value;

[0159] SG6, end.

[0160] The working steps of the energy management module are as follows:

[0161] SH1, start;

[0162] SH2, real-time collection of battery pack total voltage, remaining capacity SoE and charge and discharge current to generate energy status signal;

[0163] SH3, sending the energy status signal to the intelligent control module;

[0164] SH4, receiving the link power consumption control instruction sent by the intelligent control module;

[0165] SH5. Adjust the operating parameters of the power amplifier modules of each communication unit according to the link power consumption control instruction;

[0166] SH6, end.

[0167] The working steps of the cloud management platform are as follows:

[0168] SI1, start;

[0169] SI2, receiving the battery data uploaded by the battery data acquisition module through the multi-link communication module;

[0170] SI3: Process battery data based on big data analysis algorithms to generate battery status assessment reports and link optimization strategies;

[0171] SI4. Send the battery status assessment report and link optimization strategy back to the intelligent control module through the multi-link communication module;

[0172] SI5, end.

[0173] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0174] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features and technical solutions therein may be combined with each other.

[0175] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0176] The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described in the present invention. Although this specification has described the present invention in detail with reference to the above embodiments, the present invention is not limited to the above specific implementation methods. Therefore, any modification or equivalent replacement of the present invention; and all technical solutions and improvements thereof that do not depart from the spirit and scope of the invention are included in the scope of the claims of the present invention.

Claims

1. A multi-link collaborative wireless communication battery management system, characterized in that: include: Battery data acquisition module, multi-link communication module, intelligent control module, energy management module and cloud management platform; A battery data acquisition module, electrically connected to the battery module, for collecting voltage, current, temperature, state of charge (SOC), and state of health (SOH) parameters of the battery module, generating a data packet with a timestamp and sending it to the multi-link communication module; A multi-link communication module, communicatively connected to the battery data acquisition module and the intelligent control module, integrating Bluetooth, Wi-Fi, ZigBee, and cellular network communication units. Each communication unit is independently configured with a transceiver antenna and a modem module, and is used to establish a wireless transmission link according to the scheduling instructions of the intelligent control module; An intelligent control module is electrically connected to the multi-link communication module and the energy management module, and includes a link status monitoring unit, an intelligent dynamic link fusion unit, a heterogeneous link scheduling unit, and an anti-interference game decision unit. The link status monitoring unit collects the channel signal-to-noise ratio (SNR), transmission delay (RTT), packet loss rate (PER), and spectrum occupancy parameters of each communication unit in real time, generates a link state vector, and inputs it to the intelligent dynamic link fusion unit. The intelligent dynamic link fusion unit has a built-in deep learning neural network model, which takes the link state vector and the data packet type of the battery data acquisition module as input and outputs multi-link data. A fusion strategy, which includes the bandwidth allocation ratio and data packet reassembly rules for each link; a heterogeneous link scheduling unit, which pre-stores a scene recognition rule base, which includes characteristic parameter thresholds for indoor / outdoor, close / long distance, and high-dynamic / static scenes, matches the scene type according to real-time environmental sensor data, and outputs a link combination activation instruction for the corresponding scene to the multi-link communication module; an anti-interference game decision unit, which constructs a strategy space including link frequency band, modulation mode, and transmission power, establishes a benefit function for each link based on game theory, reaches a Nash equilibrium state through distributed iterative calculation, and outputs an anti-interference parameter adjustment instruction to the multi-link communication module; An energy management module is electrically connected to the battery pack and the intelligent control module, collects the total voltage of the battery pack, the remaining power SoE, and the charge and discharge current, generates an energy status signal and sends it to the intelligent control module, and simultaneously receives the link power consumption control instruction from the intelligent control module and adjusts the operating parameters of the power amplifier module of each communication unit; The cloud management platform is communicatively connected to the multi-link communication module, receives battery data through the multi-link communication module, generates a battery status assessment report and a link optimization strategy based on big data analysis, and transmits the report back to the intelligent control module.

2. A multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The deep learning neural network model of the intelligent dynamic link fusion unit implements data fusion through the following steps: SA1, start; SA2: Perform timestamp alignment and Kalman filter noise reduction on the same type of battery data transmitted on different links; SA3: Allocate link transmission weights based on data packet priority. The priority of data packets is control instructions > real-time status data > historical data. SA4: Extract the data features of each link through the convolutional neural network and output the optimal data fusion sequence through the fully connected layer; SA5, end.

3. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The scenario recognition rule base of the heterogeneous link scheduling unit includes: Indoor close-range scenario, distance <10m, GPS signal strength <-130dBm: Enable Bluetooth 5.0 and ZigBee 3.0 links for battery data collection, with a transmission period of ≤50ms; Remote monitoring scenarios, with a distance greater than 1km and a cellular network signal strength greater than -100dBm, use the primary 4G / 5G cellular link to transmit status data, and the backup Wi-Fi link to transmit large-capacity battery image data. In high-dynamic scenarios, when vehicle acceleration is greater than 0.5g, both the cellular link and the Bluetooth link are enabled simultaneously. The cellular link transmits the original data, and the Bluetooth link transmits the checksum to achieve redundant data transmission.

4. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The link power consumption control strategy of the energy management module includes: When the remaining battery power SoE is less than 20%, each communication unit is forced to enter low power mode, the Bluetooth link transmission power is ≤4dBm, and the ZigBee link transmission rate is reduced to 250kbps; When the battery is in charging state and the charging current is greater than 0.1C, 5% to 10% of the charging power is allocated to the cellular link, and its modulation method is upgraded to high-order modulation to increase the transmission rate.

5. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: A time division duplex coordinator is set between each communication unit of the multi-link communication module to divide the channel occupation time slot of each link according to the scheduling instruction of the intelligent control module to avoid co-frequency interference.

6. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The working steps of the battery data acquisition module are as follows: SB1, start; SB2. Use an analog-to-digital converter to sample the voltage, current, and temperature signals of the battery module in real time at a set frequency, and record the sampling time to generate a timestamp; SB3. Calculate the battery's state of charge (SOC) based on the ampere-hour integration method combined with the open-circuit voltage correction algorithm, and estimate the battery's state of health (SOH) using a capacity decay model. SB4. Pack the collected and calculated voltage, current, temperature, SOC, and SOH data, add a timestamp and checksum, and generate a data packet with a timestamp; SB5, sending the data packet to the multi-link communication module; SB6, end.

7. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The working steps of the multi-link communication module are as follows: SC1, start; SC2, receiving the dispatch instruction from the intelligent control module and determining the wireless communication link to be enabled, where the wireless communication link includes Bluetooth, Wi-Fi, ZigBee, and cellular network; SC3: Configure the transceiver antennas and modem module parameters for the enabled communication units to establish wireless transmission links. SC4 receives data packets sent by the battery data acquisition module and transmits them through the established wireless link according to the scheduling instructions of the intelligent control module, or receives data returned by the cloud management platform through the wireless link and forwards it to the intelligent control module; SC5, end.

8. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The working steps of the intelligent control module include: the working steps of the link status monitoring unit, the working steps of the intelligent dynamic link fusion unit, the working steps of the heterogeneous link scheduling unit and the working steps of the anti-interference game decision unit; The link status monitoring unit works as follows: SD1, start; SD2, real-time collection of channel signal-to-noise ratio, transmission delay, packet loss rate and spectrum occupancy parameters of each communication unit; SD3, organize the collected parameters and generate a link state vector; SD4, inputs the link state vector to the intelligent dynamic link fusion unit; SD5, end. The working steps of the intelligent dynamic link fusion unit are as follows: SE1, start; SE2, receiving the link state vector input by the link state monitoring unit and the data packet type of the battery data acquisition module; SE3: Perform timestamp alignment and Kalman filter noise reduction on the same type of battery data transmitted on different links; SE4. Allocate link transmission weights based on data packet priority, where the priority is: control instructions > real-time status data > historical data; SE5: Extract the data features of each link through a convolutional neural network and output the optimal data fusion sequence through a fully connected layer, namely the multi-link data fusion strategy, including the bandwidth allocation ratio of each link and the data packet reassembly rules; SE6, sends the multi-link data fusion strategy to the multi-link communication module to guide data transmission; SE7, end. The working steps of the heterogeneous link scheduling unit are as follows: SF1, start; SF2, obtain real-time environmental sensor data; SF3, matching real-time environmental sensor data with a pre-stored scene recognition rule library to determine the current scene type, where the scene recognition rule library includes characteristic parameter thresholds for indoor / outdoor, close / long distance, and high-dynamic / stationary scenes; SF4, based on the scenario type, retrieves the link combination activation instruction corresponding to the scenario from the rule base and sends it to the multi-link communication module; SF5, the end. The working steps of the anti-interference game decision unit are as follows: SG1, start; SG2: Construct a strategy space that includes link frequency band, modulation mode, and transmit power; SG3. Based on game theory, establish the payoff function for each link: Ui = α·(1-PERi)+β·(1-γ·fcollision)-δ·Ptx, where Ui is the payoff of the i-th link, α, β, and δ are weight coefficients, PERi is the link packet loss rate, fcollision is the frequency band conflict probability, and Ptx is the transmit power. The optimal strategy combination for each link is iteratively solved using the gradient descent method. SG4, iteratively calculate the profit function through the gradient descent method to solve the optimal strategy combination for each link; SG5. When the convergence condition is reached, the anti-interference parameter adjustment instruction of each link is sent to the multi-link communication module, wherein the anti-interference parameter adjustment instruction includes: frequency band, modulation mode, and transmit power adjustment value; SG6, end.

9. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The working steps of the energy management module are as follows: SH1, start; SH2, real-time collection of battery pack total voltage, remaining capacity SoE and charge and discharge current to generate energy status signal; SH3, sending the energy status signal to the intelligent control module; SH4, receiving the link power consumption control instruction sent by the intelligent control module; SH5. Adjust the operating parameters of the power amplifier modules of each communication unit according to the link power consumption control instruction; SH6, end.

10. The multi-link coordinated wireless communication battery management system according to claim 1, characterized in that: The working steps of the cloud management platform are as follows: SI1, start; SI2, receiving the battery data uploaded by the battery data acquisition module through the multi-link communication module; SI3: Process battery data based on big data analysis algorithms to generate battery status assessment reports and link optimization strategies; SI4. Send the battery status assessment report and link optimization strategy back to the intelligent control module through the multi-link communication module; SI5, end.

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