Wireless networking communication method and system for battery monitoring

Abstract

The invention relates to a wireless networking communication method and system for battery monitoring, and belongs to the technical field of battery monitoring and wireless communication. The method comprises the following steps: initializing a battery monitoring wireless communication node, selecting a wireless signal access point mode, configuring a network identifier and an encryption parameter in combination with a wireless networking state, and distributing a dynamic connection signal; selecting the node with the highest signal intensity as a father node to establish a wireless mesh network, and updating local network topology information after successful connection; monitoring a signal difference before and after connection according to a communication feedback loop, maintaining a connection state when the signal difference is within a safety range, and terminating weak signal connection through a signal priority selection method when the signal difference exceeds safety communication strength; and packaging a monitoring data packet in combination with an onion routing mechanism, de-packaging and forwarding the data layer by layer on each intermediate node, and transmitting the battery monitoring data of the child nodes to a battery monitoring management cloud.

Description

Technical Field

[0001] This invention belongs to the field of battery monitoring and wireless communication technology, specifically relating to a wireless networking communication method and system for battery monitoring. Background Technology

[0002] With the large-scale deployment of energy storage systems, electric vehicle power batteries, backup power systems, and distributed energy devices, battery monitoring systems are playing an increasingly important role in ensuring battery safety, improving operational efficiency, and extending battery life. Traditional battery monitoring relies heavily on wired networks or single-point wireless communication to collect and upload monitoring data. However, in scenarios involving multiple nodes, multiple regions, or even cross-device clusters, wired methods are complex to install, have high installation and maintenance costs, and lack flexibility, making them unsuitable for dynamically expanding battery monitoring needs. Meanwhile, single-point wireless communication methods are limited by coverage, link stability, and device capacity, making it difficult to meet the requirements of multi-module collaborative monitoring.

[0003] Currently, commonly used wireless communication methods in battery monitoring systems include Wi-Fi, ZigBee, and Bluetooth Mesh. While these technologies can achieve local node interconnection, they generally suffer from the following technical bottlenecks: First, the network topology relies on fixed or pre-configured node roles, resulting in insufficient network scalability and an inability to achieve adaptive reconfiguration. Second, signal quality is easily affected by barriers, interference, or electromagnetic environments; traditional single-link or fixed parent node methods lack dynamic switching capabilities, easily leading to communication interruptions. Third, in scenarios with densely distributed multi-nodes, issues such as inter-node interference, channel congestion, and load imbalance are significant; without an effective network status assessment mechanism, it is difficult to achieve stable and high-throughput communication performance. Fourth, monitoring devices lack distributed autonomy; routing selection often relies on single-point decisions, easily causing bottlenecks or even single-point failures.

[0004] Existing monitoring systems mostly employ centralized data transmission paths, where all child nodes directly upload data to the master node or gateway. As the number of monitoring nodes increases and data frequency rises, the load on the central node rapidly increases, leading to problems such as packet loss and increased latency, severely impacting the real-time performance and reliability of the monitoring system. In complex battery arrays or cross-regional monitoring scenarios, centralized architectures struggle to provide sufficient network redundancy and cannot promptly adjust transmission paths when nodes move, join, leave the network, or experience signal changes.

[0005] On the other hand, as battery monitoring evolves towards intelligence and real-time capabilities, monitoring systems not only need to sense battery data but also require the ability to self-monitor and self-adjust network status. How nodes can automatically select the optimal connection path based on real-time signal conditions, network load, and topology changes has become one of the key technologies for highly reliable wireless monitoring systems. Simultaneously, data transmission security and resistance to attacks have become important considerations, with multi-hop networks increasingly demanding higher requirements for data encryption and routing security in complex scenarios.

[0006] In summary, traditional battery monitoring communication methods have significant shortcomings in terms of network stability, scalability, node autonomy, and data transmission efficiency. There is an urgent need for a wireless networking communication method that can self-organize, self-optimize, dynamically perceive the wireless environment, and support highly reliable multi-hop data transmission, in order to solve the problem that existing multi-node battery monitoring systems cannot cope with complex environments and dynamic changes. Summary of the Invention

[0007] To address the aforementioned problems in the existing technology, this invention provides a wireless networking communication method for battery monitoring. The objective of this invention can be achieved through the following technical solutions: S1: Initialize the battery monitoring wireless communication node, select the wireless signal access point mode, configure the wireless network identifier based on the acquired wireless signal strength and network load data, and allocate dynamic connection signals. S2: Detect the wireless signal strength of the battery monitoring wireless communication node based on the signal strength scanning algorithm, select the node with the highest signal strength as the parent node to establish a wireless mesh network, issue a connection command to access the wireless mesh network according to the dynamic connection signal, and update the local network topology information after successful connection. S3: Based on the communication feedback loop, monitor the signal difference before and after the connection. When the signal difference is within the safe range, maintain the connection. When the signal difference exceeds the safe communication strength, terminate the weak signal connection through the signal priority selection method. S4: Combine the onion routing mechanism to encapsulate monitoring data packets, and maintain an internal routing table according to the network topology information and data transmission requirements. Decapsulate and forward data layer by layer at each intermediate node, and transmit the battery monitoring data of the child nodes to the battery monitoring management cloud.

[0008] Specifically, the battery monitoring wireless communication node initialization process is as follows: obtain network load parameters according to the local battery monitoring default configuration, the network load parameters include data packet loss rate and channel occupancy rate, calculate the corresponding signal quality score through a sound signal quality assessment method, automatically configure the node's channel number and network identifier, and initialize the battery monitoring wireless communication node.

[0009] Specifically, the network load data includes packet loss rate and channel occupancy rate. Based on the statistical network load indicators, the signal strength indication value and signal-to-noise ratio of the surrounding nodes are obtained, and the network load indicators are converted into a unified signal quality score through a weighted signal quality assessment algorithm to quantify the wireless network status.

[0010] Specifically, the dynamic connection signal is based on the node status of the wireless network state. It adaptively allocates signals, connection durations and network resources to high-priority nodes and accesses the wireless mesh network after receiving the allocated dynamic connection signal. When the signal quality of the connected node decreases or the signal difference with other nodes exceeds the secure communication strength, the priority of the node is re-evaluated and the signal connection allocation strategy is adjusted.

[0011] Specifically, the method for establishing the wireless mesh network is as follows: a hybrid topology of hierarchical tree structure and local mesh is adopted. In the hierarchical tree structure, the backbone is a spanning tree rooted at the node with the strongest signal, and temporary mesh links are allowed to be established between nodes in the same layer in local weak signal areas.

[0012] Specifically, the execution process of the signal strength scanning algorithm includes: periodically broadcasting scan request frames, calculating the average signal strength and fluctuation variance of the received response frames, filtering low-quality nodes according to a preset signal strength threshold, weighting and sorting candidate parent nodes in combination with historical connection records, selecting the node with the highest score as the parent node, and updating the local cached list of fast reconnection nodes.

[0013] Specifically, the maintenance method of the hierarchical tree structure and local grid hybrid topology is as follows: the root node broadcasts topology update messages periodically, the lower-level nodes adjust the parent-child node relationship according to the received messages, and when signal attenuation is detected in a local weak signal area, the nodes actively initiate grid link negotiation, establish point-to-point redundant paths to monitor link status, and automatically dismantle the current path when the utilization rate of the redundant path is lower than the preset idle link threshold.

[0014] Specifically, the method for monitoring the signal difference before and after connection in the communication feedback loop is as follows: before the node accesses the wireless mesh network, it records the initial signal strength value and signal-to-noise ratio as the signal quality benchmark before connection. When the calculated signal difference is less than the threshold, it indicates that the connection status is good and the network connection can be maintained. The signal quality benchmark is set with an allowable fluctuation value based on the network environment. If the signal difference exceeds the threshold, it indicates that the connection is unstable, and a new connection path is selected or the current connection is terminated.

[0015] Specifically, the process of terminating a weak signal connection using the signal priority selection method is as follows: after terminating the weak signal connection, immediately start sorting the backup parent node list and select the second-best node from the backup list to re-associate.

[0016] Specifically, the execution process of the onion routing mechanism is as follows: the battery monitoring data is encrypted and encapsulated in multiple layers according to the communication source node, and forwarding header information is added to each layer. At the intermediate node, only the outer layer is decapsulated, and the inner layer packet is forwarded according to the routing table until the data packet reaches the battery monitoring management cloud to complete the full decapsulation.

[0017] Specifically, the method for client mode to access the network of other nodes is as follows: dynamically adjust the signal transmission interval according to the network load, and prioritize the processing of child node access requests when acting as an access point.

[0018] Specifically, a wireless networking communication system for battery monitoring includes: Dynamic connection signal allocation module: Initializes the battery monitoring wireless communication node, selects the wireless signal access point mode, configures the network identifier of the wireless network according to the acquired wireless signal strength and network load data, and allocates dynamic connection signals; Signal strength detection module: Detects the wireless signal strength of the battery monitoring wireless communication node based on the signal strength scanning algorithm, selects the node with the highest signal strength as the parent node to establish a wireless mesh network, issues a connection command to access the wireless mesh network according to the dynamic connection signal, and updates the local network topology information after successful connection; Communication feedback monitoring module: Based on the communication feedback loop, monitor the signal difference before and after the connection. When the signal difference is within a safe range, maintain the connection. When the signal difference exceeds the safe communication strength, terminate the weak signal connection using the signal priority selection method. Data encapsulation and forwarding module: Combines the onion routing mechanism to encapsulate monitoring data packets, and maintains its own internal routing table according to the network topology information and data transmission requirements. It decapsulates and forwards data layer by layer at each intermediate node, and transmits the battery monitoring data of the child nodes to the battery monitoring management cloud.

[0019] The beneficial effects of this invention are as follows: The wireless networking communication method for battery monitoring provided by this invention can effectively solve the technical problems of fixed network topology, unstable connection, insufficient scalability, and poor reliability of multi-node data transmission in existing battery monitoring systems, and has the following beneficial effects: By simultaneously enabling both wireless signal access point mode and client mode in the battery monitoring wireless communication node, the node acquires dual-role capabilities, allowing it to autonomously choose to access or be accessed when the network environment changes, thus achieving a truly distributed self-organizing network structure. This mechanism significantly improves the interconnection flexibility between multiple nodes and the network's self-healing capabilities.

[0020] The parent node selection strategy based on the signal strength scanning algorithm, combined with the dynamic connection signal allocation method, enables nodes to automatically select the best access path according to the real-time signal strength and network load status. This avoids the link congestion or weak communication link problems caused by fixed parent nodes in traditional methods, and significantly improves connection stability and data throughput.

[0021] By introducing a communication feedback loop to monitor the signal difference before and after connection, the system can dynamically assess link quality and adjust node connection status in real time. When connection quality deteriorates, the system can automatically terminate weak signal links and switch to a better node, improving the reliability and stability of wireless communication, and is especially suitable for complex application environments with multiple obstacles and interference.

[0022] By combining the onion routing mechanism to achieve distributed multi-hop encrypted transmission and dynamically maintaining routing tables at each node, battery monitoring data can be efficiently and securely transmitted to the monitoring and management cloud across a multi-node network. This transmission mechanism not only enhances network security but also improves the flexibility and redundancy of data paths, significantly improving the overall communication performance of large-scale, multi-region battery monitoring systems.

[0023] In summary, this invention provides a highly reliable, highly scalable, and highly adaptive wireless networking communication scheme for battery monitoring systems. Attached Figure Description

[0024] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0025] Figure 1 This is a schematic diagram of the structure of a wireless networking communication method and system for battery monitoring according to the present invention.

[0026] Figure 2 This is a schematic diagram of the onion routing mechanism described in the wireless networking communication method and system for battery monitoring according to the present invention. Detailed Implementation

[0027] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0028] Example 1, Please see Figure 1 A wireless networking communication method for battery monitoring: S1: Initialize the battery monitoring wireless communication node, select the wireless signal access point mode, configure the wireless network identifier based on the acquired wireless signal strength and network load data, and allocate dynamic connection signals. S2: Detect the wireless signal strength of the battery monitoring wireless communication node based on the signal strength scanning algorithm, select the node with the highest signal strength as the parent node to establish a wireless mesh network, issue a connection command to access the wireless mesh network according to the dynamic connection signal, and update the local network topology information after successful connection. S3: Based on the communication feedback loop, monitor the signal difference before and after the connection. When the signal difference is within the safe range, maintain the connection. When the signal difference exceeds the safe communication strength, terminate the weak signal connection through the signal priority selection method. S4: Combine the onion routing mechanism to encapsulate monitoring data packets, and maintain an internal routing table according to the network topology information and data transmission requirements. Decapsulate and forward data layer by layer at each intermediate node, and transmit the battery monitoring data of the child nodes to the battery monitoring management cloud.

[0029] In this embodiment, the battery monitoring wireless communication node initialization process is as follows: obtain network load parameters according to the local battery monitoring default configuration, the network load parameters include data packet loss rate and channel occupancy rate, calculate the corresponding signal quality score through a sound signal quality assessment method, automatically configure the node's channel number and network identifier, and initialize the battery monitoring wireless communication node.

[0030] In this embodiment, the network load data includes packet loss rate and channel occupancy rate. The signal strength indication value and signal-to-noise ratio of surrounding nodes are obtained based on the statistical network load indicators, and the network load indicators are converted into a unified signal quality score through a weighted signal quality assessment algorithm to quantify the wireless network status.

[0031] In this embodiment, the dynamic connection signal is based on the node status of the wireless network state. The signal, connection duration and network resources are adaptively allocated to high-priority nodes. After receiving the allocated dynamic connection signal, the node is connected to the wireless mesh network. When the signal quality of the connected node decreases or the signal difference with other nodes exceeds the secure communication strength, the priority of the node is re-evaluated and the signal connection allocation strategy is adjusted.

[0032] In this embodiment, taking a 12-node monitoring cluster as an example, each node has dual capabilities in wireless signal access point mode and client mode, and supports 2.4 GHz Wi-Fi communication protocol, AES-128 encryption method and data forwarding mechanism based on onion routing.

[0033] I. Wireless Mesh Network Construction Process After the system starts, each node enters the initialization phase, automatically turns on the wireless signal access point mode, and uses "MonitorMesh" as the network identifier (SSID). It adopts the AES-128-CBC encryption mode. The key example is: Key= 3A 91 F2 67 88 4B C3 24 9D 00 FF A2 71 6D 3B C1; IV = 00 11 22 33 44 5566 77 88 99 AA BB CC DD EE FF.

[0034] The node simultaneously enables client mode to scan surrounding grid nodes. Each node broadcasts a signal strength data packet every 50ms. The wireless signal access point mode includes a client mode, which uses the current battery monitoring wireless communication node as a client, selects the access point with the strongest signal as the parent node to access the network of other nodes, and automatically synchronizes the parent node, including: Network identifier: MonitorMesh; Node number: e.g., Node_05; Signal strength RSSI: -54 dBm; Signal-to-noise ratio (SNR): 27 dB; Current channel occupancy: 18%.

[0035] Each node uses a signal strength scanning algorithm to select the node with the best signal from its surroundings as its parent node, thus forming a wireless mesh network. For example, Node_05 selects Node_02, with RSSI = -49 dBm, as its parent node from the scan list.

[0036] II. Dynamic Connection Signal Evaluation and Allocation Methods The node calculates the signal quality index Q based on the signal strength RSSI, signal-to-noise ratio SNR, and network load (including packet loss rate PLR ​​and channel occupancy rate CO). This index is used for the generation of dynamic connection signals. The signal quality calculation formula is as follows: , The weights are set as follows: w1=0.35, w2=0.30, w3=0.20, w4=0.15.

[0037] The RSSI and SNR standardization methods are as follows: , , The node uses Q=0.89 as a dynamic connection signal and initiates a connection request.

[0038] III. Communication Feedback Loop and Signal Difference Monitoring Before connection, Node_05 records the signal baseline before connection: RSSI_pre = -51 dBm, SNR_pre = 25 dB; after connection, real-time signal is recorded every 200 ms: RSSI_post = -53 dBm, SNR_post = 24 dB.

[0039] The signal difference is calculated as follows: , The system has a preset safety signal difference threshold of 8. If D ≥ 8 in the future, the node will automatically disconnect and the parent node will be reselected.

[0040] IV. Data transmission process based on the onion routing mechanism like Figure 2 All monitoring nodes use the onion routing mechanism when uploading data to the cloud master node (Node_01): Node_08 → Node_05 → Node_02 → Node_01, and the data packets are uploaded with three layers of encryption.

[0041] The encryption layers are shown below (AES-128-CBC): Layer 3 (Destination: Node_05), Layer 2 (Destination: Node_02), Layer 1 (Destination: Node_01); intermediate nodes decrypt layer by layer: Node_05 can only decrypt the third layer to obtain the next hop Node_02, Node_02 can only decrypt the second layer to obtain the next hop Node_01, and Node_01 decrypts the innermost layer to obtain the actual monitoring data.

[0042] In this embodiment, the method for establishing the wireless mesh network is as follows: a hybrid topology of hierarchical tree structure and local mesh is adopted. In the hierarchical tree structure, the backbone is a spanning tree with the node with the strongest signal as the root. Temporary mesh links are allowed to be established between nodes in the same layer in local weak signal areas.

[0043] In this embodiment, the execution process of the signal strength scanning algorithm includes: periodically broadcasting scan request frames, calculating the average signal strength and fluctuation variance of the received response frames, filtering low-quality nodes according to a preset signal strength threshold, weighting and sorting candidate parent nodes in combination with historical connection records, selecting the node with the highest score as the parent node, and updating the local cached list of fast reconnection nodes.

[0044] In this embodiment, the maintenance method of the hierarchical tree structure and local grid hybrid topology is as follows: the root node broadcasts topology update messages periodically, the lower-level nodes adjust the parent-child node relationship according to the received messages, and when signal attenuation is detected in a local weak signal area, the node actively initiates grid link negotiation, establishes point-to-point redundant paths to monitor link status, and automatically removes the current path when the utilization rate of the redundant path is lower than the preset idle link threshold.

[0045] In this embodiment, the nodes are first initialized: each node simultaneously enables wireless access point mode broadcasting of the SSID and encryption parameters, and client mode scanning of surrounding signals. The node controller collects RSSI values ​​and network load, and calculates the normalized signal quality score. If the score > 0.8, a dynamic connection signal is generated and broadcast "Access Allowed".

[0046] Parent node selection: Using a signal strength scanning algorithm, nodes periodically broadcast scan requests. Upon receiving responses, they calculate the average RSSI and variance, selecting the node with the highest RSSI as the parent node to establish a connection and updating the local topology table. After a successful connection, signal difference is monitored via heartbeat packets. If the difference is >10dB, a signal priority selection method is triggered to terminate the weak connection, and the suboptimal node is quickly re-associated from the backup list.

[0047] Data transmission: The collected battery data is encapsulated into multi-layered data packets via Onion routing, with a forwarding header added to each layer. Intermediate nodes decapsulate the data layer by layer and forward it to the root node, finally uploading it to the cloud. The entire process ensures end-to-end latency of <200ms and supports redundant paths to improve reliability.

[0048] Multiple battery monitoring wireless communication nodes are deployed on each battery module of the vehicle's battery pack to collect data such as battery voltage, temperature, current, and remaining capacity in real time, and transmit this data to the cloud management platform via a wireless mesh network. These nodes employ a dual-role mode to achieve self-organizing networking and dynamic connectivity.

[0049] In this embodiment, the method for monitoring the signal difference before and after connection in the communication feedback loop is as follows: before the node accesses the wireless mesh network, it records the initial signal strength value and signal-to-noise ratio as the signal quality benchmark before connection. When the calculated signal difference is less than the threshold, it indicates that the connection status is good and the network connection can be maintained. The signal quality benchmark is set with an allowable fluctuation value based on the network environment. If the signal difference exceeds the threshold, it indicates that the connection is unstable, and a new connection path is selected or the current connection is terminated.

[0050] In this embodiment, the process of terminating a weak signal connection using the signal priority selection method is as follows: after terminating the weak signal connection, immediately start sorting the backup parent node list and select the second-best node from the backup list to re-associate.

[0051] In this embodiment, the execution process of the onion routing mechanism is as follows: the battery monitoring data is encrypted and encapsulated in multiple layers according to the communication source node, and forwarding header information is added to each layer. At the intermediate node, only the outer layer is decapsulated, and the inner layer packet is forwarded according to the routing table until the data packet reaches the battery monitoring management cloud to complete the full decapsulation.

[0052] In this embodiment, the method for client mode to access the network of other nodes is as follows: dynamically adjust the signal transmission interval according to the network load, and prioritize the processing of child node access requests when acting as an access point.

[0053] Example 2 This invention also provides a wireless networking communication system for battery monitoring, specifically including: Dynamic connection signal allocation module: Initializes the battery monitoring wireless communication node, selects the wireless signal access point mode, configures the network identifier of the wireless network according to the acquired wireless signal strength and network load data, and allocates dynamic connection signals; Signal strength detection module: Detects the wireless signal strength of the battery monitoring wireless communication node based on the signal strength scanning algorithm, selects the node with the highest signal strength as the parent node to establish a wireless mesh network, issues a connection command to access the wireless mesh network according to the dynamic connection signal, and updates the local network topology information after successful connection; Communication feedback monitoring module: Based on the communication feedback loop, monitor the signal difference before and after the connection. When the signal difference is within a safe range, maintain the connection. When the signal difference exceeds the safe communication strength, terminate the weak signal connection using the signal priority selection method. Data encapsulation and forwarding module: Combines the onion routing mechanism to encapsulate monitoring data packets, and maintains its own internal routing table according to the network topology information and data transmission requirements. It decapsulates and forwards data layer by layer at each intermediate node, and transmits the battery monitoring data of the child nodes to the battery monitoring management cloud.

[0054] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A wireless networking communication method for battery monitoring, characterized in that, include: S1: Initialize the battery monitoring wireless communication node, select the wireless signal access point mode, configure the wireless network identifier based on the acquired wireless signal strength and network load data, and allocate dynamic connection signals. S2: Detect the wireless signal strength of the battery monitoring wireless communication node based on the signal strength scanning algorithm, select the node with the highest signal strength as the parent node to establish a wireless mesh network, issue a connection command to access the wireless mesh network according to the dynamic connection signal, and update the local network topology information after successful connection. S3: Based on the communication feedback loop, monitor the signal difference before and after the connection. When the signal difference is within the safe range, maintain the connection. When the signal difference exceeds the safe communication strength, terminate the weak signal connection through the signal priority selection method. S4: Combine the onion routing mechanism to encapsulate monitoring data packets, and maintain an internal routing table according to the network topology information and data transmission requirements. Decapsulate and forward data layer by layer at each intermediate node, and transmit the battery monitoring data of the child nodes to the battery monitoring management cloud.

2. The method according to claim 1, characterized in that, The initialization process of the battery monitoring wireless communication node is as follows: obtain network load parameters according to the local battery monitoring default configuration, including data packet loss rate and channel occupancy rate, calculate the corresponding signal quality score through a sound signal quality assessment method, automatically configure the node's channel number and network identifier, and initialize the battery monitoring wireless communication node.

3. The method according to claim 1, characterized in that, The network load data includes packet loss rate and channel occupancy rate. Based on the statistical network load indicators, the signal strength indicators and signal-to-noise ratio of surrounding nodes are obtained, and the network load indicators are converted into a unified signal quality score through a weighted signal quality assessment algorithm to quantify the wireless network status.

4. The method according to claim 1, characterized in that, The method for allocating dynamic connection signals is as follows: based on the node status of the wireless network, signals, connection durations, and network resources are adaptively allocated to nodes with high priority. After receiving the allocated dynamic connection signal, the node is connected to the wireless mesh network. When the signal quality of the connected node decreases or the signal difference with other nodes exceeds the secure communication strength, the priority of the node is re-evaluated and the signal connection allocation strategy is adjusted.

5. The method according to claim 2, characterized in that, The method for establishing the wireless mesh network is as follows: a hybrid topology of hierarchical tree structure and local mesh is adopted. In the hierarchical tree structure, the backbone is a spanning tree rooted at the node with the strongest signal. Temporary mesh links are allowed to be established between nodes in the same layer in local weak signal areas.

6. The method according to claim 5, characterized in that, The execution process of the signal strength scanning algorithm includes: periodically broadcasting scan request frames, calculating the average signal strength and fluctuation variance of the received response frames, filtering low-quality nodes according to a preset signal strength threshold, weighting and sorting candidate parent nodes in combination with historical connection records, selecting the node with the highest score as the parent node, and updating the local cached list of fast reconnection nodes.

7. The method according to claim 4, characterized in that, The maintenance method for the hierarchical tree structure and local grid hybrid topology is as follows: the root node periodically broadcasts topology update messages, the lower-level nodes adjust the parent-child node relationship according to the received messages, and when signal attenuation is detected in a local weak signal area, the node actively initiates grid link negotiation, establishes point-to-point redundant paths to monitor link status, and automatically removes the current path when the utilization rate of the redundant path is lower than the preset idle link threshold.

8. The method according to claim 2, characterized in that, The method for monitoring the signal difference before and after connection in the communication feedback loop is as follows: before the node accesses the wireless mesh network, the initial signal strength value and signal-to-noise ratio are recorded as the signal quality benchmark before connection. When the calculated signal difference is less than the threshold, it indicates that the connection status is good and the network connection can be maintained. The signal quality benchmark is set with an allowable fluctuation value based on the network environment. If the signal difference exceeds the threshold, it indicates that the connection is unstable, and a new connection path is selected or the current connection is terminated.

9. The method according to claim 4, characterized in that, The process of terminating a weak signal connection using the signal priority selection method is as follows: after terminating the weak signal connection, immediately start sorting the backup parent node list and select the second-best node from the backup list to re-associate.

10. The method according to claim 1, characterized in that, The execution process of the onion routing mechanism is as follows: the battery monitoring data is encrypted and encapsulated in multiple layers according to the communication source node, and forwarding header information is added to each layer. At the intermediate node, only the outer layer is decapsulated, and the inner layer packet is forwarded according to the routing table until the data packet reaches the battery monitoring management cloud to complete the full decapsulation.

11. The method according to claim 2, characterized in that, The maintenance process of the internal routing table is as follows: each candidate link is evaluated for cost score based on the real-time signal strength indication value between adjacent nodes, the link with the lowest score is selected as the next hop node, and expired routing table entries are cleared when a neighboring node is detected to have disappeared.

12. A wireless networking communication system for battery monitoring, used to perform the method as described in any one of claims 1-12, characterized in that, include: Dynamic connection signal allocation module: Initializes the battery monitoring wireless communication node, selects the wireless signal access point mode, configures the network identifier of the wireless network according to the acquired wireless signal strength and network load data, and allocates dynamic connection signals; Signal strength detection module: Detects the wireless signal strength of the battery monitoring wireless communication node based on the signal strength scanning algorithm, selects the node with the highest signal strength as the parent node to establish a wireless mesh network, issues a connection command to access the wireless mesh network according to the dynamic connection signal, and updates the local network topology information after successful connection; Communication feedback monitoring module: Based on the communication feedback loop, monitor the signal difference before and after the connection. When the signal difference is within a safe range, maintain the connection. When the signal difference exceeds the safe communication strength, terminate the weak signal connection using the signal priority selection method. Data encapsulation and forwarding module: Combines the onion routing mechanism to encapsulate monitoring data packets, and maintains its own internal routing table according to the network topology information and data transmission requirements. It decapsulates and forwards data layer by layer at each intermediate node, and transmits the battery monitoring data of the child nodes to the battery monitoring management cloud.

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