Integrated esim electric energy meter 4g communication module cooperative control method and system

Abstract

This application discloses a collaborative control method and system for a 4G communication module of an energy meter integrating eSIM. It overcomes the inherent limitations of traditional 4G module hardware architecture, achieving deep integration and adaptation between the eSIM chip and the 4G module. The design without exposed physical interfaces significantly improves the module's environmental adaptability and anti-interference capabilities. The board-level high-speed direct connection architecture eliminates external bus transmission losses, breaking through the performance bottleneck of traditional solutions from the hardware perspective. It achieves a fundamental shift from single-dimensional static decision-making to multi-dimensional, fully coordinated collaborative control. It breaks the limitations of traditional independent and statically fixed eSIM chip and 4G module master control state management, endowing the module with microsecond-level state coordination and dynamic power consumption optimization capabilities. It abandons the simplistic approach of traditional static device identification and single-point security protection, constructing a hardware-level, end-to-end collaborative and trusted access system throughout the entire lifecycle.

Description

Technical Field

[0001] This invention relates to the field of electricity meter application technology, and in particular to a collaborative control method and system for an electricity meter 4G communication module integrated with eSIM. Background Technology

[0002] With the deepening of smart grid construction, electricity meters, as the core terminal for power data collection and management, face stringent requirements regarding the stability, ease of operation and maintenance, and security of remote communication. Currently, mainstream electricity meter 4G communication modules adopt a traditional pluggable SIM card architecture. While this meets basic transmission needs, it suffers from inherent pain points such as difficult operation and maintenance and poor environmental adaptability when adapted to the outdoor, remote deployment and 15-20 year long lifespan characteristics of electricity meters. eSIM technology, with its advantages of remote configuration, physical tamper-proofing, and multi-carrier compatibility, has become the optimal solution to address these shortcomings. However, existing solutions do not achieve integrated eSIM and 4G module functionality, still employing a separate architecture of "independent eSIM + independent 4G module," and lack targeted software optimization strategies. This results in poor adaptability, low collaborative efficiency, and high costs, making it difficult to meet the needs of smart grid development.

[0003] Existing technologies have significant limitations:

[0004] 1. Lack of multi-dimensional collaborative adaptation mechanism: Existing technologies make communication strategy decisions based on only a single-dimensional parameter, without establishing a quantitative coupling and collaborative adaptation mechanism among business scenarios, network environment, and device status. This results in high-priority services failing to meet real-time performance standards, network resource scheduling imbalance, low utilization, and excessively high device power consumption and significantly reduced battery life.

[0005] 2. Lack of software-layer collaborative control between eSIM and 4G module: In existing eSIM solutions, the eSIM chip and 4G module only implement basic hardware communication, without software-layer collaborative control and real-time status synchronization mechanism. This results in serious lag in dual-chip status synchronization and power consumption scheduling, excessively high eSIM profile switching latency, and no scenario-based proactive switching strategy, making it unable to adapt to dynamic service scenarios.

[0006] 3. Inadequate Operation and Security Protection System: Traditional SIM cards have poor environmental adaptability, high maintenance costs throughout their lifecycle, and are susceptible to unauthorized replacement; existing eSIM solutions lack a strong binding mechanism between the eSIM identifier and the device identifier, resulting in insufficient security in the identity authentication mechanism, making them vulnerable to imitation, cracking, and cyberattacks, and failing to meet the high security and low maintenance requirements for long-term outdoor deployments.

[0007] Therefore, there is an urgent need to innovate the design of the eSIM-4G integrated module architecture and develop targeted software optimization solutions to improve the module's adaptability to power scenarios. Summary of the Invention

[0008] The purpose of this application is to provide a collaborative control method and system for an energy meter 4G communication module integrated with eSIM, so as to solve the technical problems of the lack of multi-dimensional collaborative adaptation, insufficient collaboration between eSIM chip and 4G module software layer, and imperfect operation and maintenance and security protection system in the existing energy meter 4G module.

[0009] To address the aforementioned technical issues, this application provides a collaborative control method for a 4G communication module of an energy meter integrating an eSIM. By replacing the physical SIM card with an eSIM chip, it constructs three core systems: multi-dimensional collaborative scheduling, inter-chip collaborative control, and highly reliable identity authentication. This enables second-level fault alarms, efficient network resource utilization, low-power operation, and highly reliable device identity management throughout the energy meter's lifecycle. The eSIM chip is embedded within the 4G module to form an eSIM-4G module, which communicates with the main control chip of the eSIM-4G module through a standard interface. The control method includes:

[0010] S1: The eSIM-4G module's operating status parameters, 4G network operating parameters, and electricity meter service data are collected in real time through a unified interface abstraction layer. The operating status parameters include battery power and service scenario status. The service scenario status is defined based on a finite state machine and includes idle state, data acquisition state, configuration state, and alarm state.

[0011] S2: Based on the aforementioned operating status parameters, 4G network operating parameters, and electricity meter service data, a three-dimensional collaborative model of service scenario, network environment, and device status is constructed. This three-dimensional collaborative model uses a weighted comprehensive scoring algorithm to calculate a comprehensive network quality score. The scoring formula for the weighted comprehensive scoring algorithm is as follows: S_RSRP, S_loss, and S_delay are the standardized scores of signal strength, packet loss rate, and latency, respectively, and the weight coefficients ω1, ω2, and ω3 are dynamically adjusted according to the business scenario status.

[0012] S3: Based on the output of the three-dimensional collaborative model, the operating mode of the 4G module and the working state of the eSIM chip are adjusted using a dynamic power scheduling algorithm. The 4G module operating modes include PSM power-saving mode, eDRX extended discontinuous reception mode, normal operating mode, and high-power mode. The dynamic power scheduling algorithm uses a power prediction formula. Where P0 is the module's basic power consumption, α is the service scenario coefficient, and β is the device state coefficient. The coordinated switching between the 4G module's operating mode and the eSIM chip's operating state is achieved through an event-driven mechanism, which is triggered by a hardware interrupt. The real-time mapping table between the eSIM chip's operating state and the 4G module's operating mode is stored in shared memory, and the state synchronization latency is ≤5ms.

[0013] S4: Establish a one-to-one correspondence between the eSIM chip's EID identifier and the 4G module's IMEI identifier for device identity. Use the IMEI identifier + EID identifier as a unique device fingerprint, and perform hash operation using the national cryptographic SM3 hash algorithm to generate a 256-bit fixed-length, tamper-proof, unique device identity credential.

[0014] S5: Based on the device identity credentials, a challenge-response mechanism is used to perform two-way identity authentication with the power master station. The authentication key is K_auth=HMAC−SHA256EID. After successful authentication, a secure session is established, where SHA256EID represents the master station's private key.

[0015] S6: Under the secure session, the TLS1.3 protocol and SM4-CBC algorithm are used to implement the end-to-end encrypted transmission and update of the eSIM configuration file. Each configuration packet carries a 64-bit serial number. The main station maintains a sliding window to detect replay attacks.

[0016] S7: When the overall network quality score is lower than a preset threshold, trigger eSIM redundancy profile switching and dynamic optimization of 4G module network parameters, with eSIM redundancy profile switching latency ≤2 seconds;

[0017] S8: The electricity meter business data is cached and managed hierarchically through a multi-level ring buffer. The multi-level ring buffer includes a high-speed buffer with a capacity of 1MB, a business buffer with a capacity of 4MB, and a persistent buffer with a capacity of 128MB. The configuration execution, data transmission and operation status are verified through a multi-dimensional closed-loop verification mechanism, and an alarm is triggered when an anomaly occurs.

[0018] As a preferred embodiment, in a collaborative control method for a 4G communication module of an energy meter integrating eSIM, the parameter standardization logic of the weighted comprehensive scoring algorithm in step S2 is as follows:

[0019] S_RSRP is calculated with -115dBm as 0 points and -90dBm as 100 points. The formula is S_RSRP={RSRP−(−115)} / {−90−(−115)}×100.

[0020] The standardized score of network packet loss rate, S_loss, is calculated with 10% as 0 points and 0% as 100 points. The formula is S_loss = (10% - loss_rate) / 10% × 100.

[0021] Where loss_rate is the actual measured network packet loss rate (percentage).

[0022] The standardized score for network transmission delay, S_delay, is calculated with 500ms as 0 points and 100ms as 100 points. The formula is S_delay=(500-delay) / (500-100)×100.

[0023] Here, delay is the actual measured network transmission delay (unit: ms).

[0024] As a preferred embodiment, in a collaborative control method for a 4G communication module of an energy meter integrating eSIM, the weight coefficients of the weighted comprehensive scoring algorithm in step S2 are dynamically adjusted according to the service scenario status as follows:

[0025] When the business scenario is in an idle state, ω3 increases to 0.4, ω1=0.3, and ω2=0.3;

[0026] When the business scenario is data acquisition, ω1=0.4, ω2=0.3, ω3=0.3;

[0027] When the business scenario is in configuration mode, ω1 is increased to 0.5, ω2=0.2, and ω3=0.3;

[0028] When the business scenario is in alarm state, ω2 increases to 0.5, ω1=0.3, and ω3=0.2.

[0029] As a preferred embodiment, a collaborative control method for a 4G communication module of an integrated eSIM electricity meter, wherein the service scenario coefficient α in step S3 is determined according to the service scenario state, with α=0.2 for idle state, α=0.6 for data acquisition state, α=1.0 for configuration state, and α=0.8 for alarm state;

[0030] The device state coefficient β is determined based on the battery charge. When the battery charge is ≥70%, β=1.0; when the battery charge is 30% < 70%, β=0.8; and when the battery charge is ≤30%, β=0.5.

[0031] As a preferred embodiment, a collaborative control method for a 4G communication module of an integrated eSIM electricity meter is provided. In step S3, the 4G module operating modes are as follows: PSM power saving mode average power consumption ≤1mA, eDRX extended discontinuous reception mode average power consumption ≤10mA, normal operation mode average power consumption 150mA, and high power mode average power consumption 500mA.

[0032] The reception period of the eDRX extended discontinuous reception mode is dynamically adjusted, and the adjustment formula is T_eDRX=max{20s,min(600s,T_base×Score / 60)};

[0033] Where T_eDRX is the actual reception period (in seconds) of the eDRX extended discontinuous reception mode; T_base is the baseline reception period of the eDRX mode (preset initial value); and Score is the overall network quality score (0-100 points).

[0034] The eSIM chip's operating states include active and sleep modes. The sleep mode corresponds to the PSM power-saving mode and the eDRX extended discontinuous reception mode, while the active mode corresponds to the normal operating mode and the high-power mode.

[0035] As a preferred embodiment, a collaborative control method for a 4G communication module of an integrated eSIM electricity meter, wherein the association relationship of the device identity mentioned in step S4 is written into the secure storage area by the system and fixed when the module leaves the factory, and cannot be modified through an external interface;

[0036] The device fingerprint is generated by concatenating "electricity meter number + eSIM_EID" and then using the SM3 hash algorithm to generate a 256-bit identity credential. The identity credential is compared and verified with the pre-stored credential on the main station during each authentication.

[0037] Among them, eSIMEID is a globally unique, tamper-proof, and indelible hardware-level electronic serial number that is burned into the chip's secure storage area by the manufacturer once when the eSIM chip leaves the factory.

[0038] As a preferred embodiment, a collaborative control method for a 4G communication module of an energy meter integrating eSIM, wherein the challenge-response mechanism in step S5 includes:

[0039] The 4G module sends an authentication request to the main station containing the device fingerprint, timestamp, and random number Nonce_A;

[0040] Nonce_A is randomly generated by the eSIM-4G module (client) when initiating an authentication request. It is used by the module to verify the legitimacy of the master station: the master station must be able to correctly encrypt Nonce_A with its own private key. Only when the module decrypts and compares the results can it be confirmed that the master station is not a fake base station.

[0041] After verifying the device fingerprint, the master station generates an authentication key K_auth using the HMAC-SHA256 algorithm, with the master station's private key and eSIM_EID as parameters. The authentication key, timestamp, and random number Nonce_B are then encrypted using the SM4 algorithm and returned.

[0042] Nonce_B is randomly generated by the power master station (server) after verifying the module's identity. It is used by the master station to verify the module's legitimacy: the module must be able to correctly encrypt Nonce_B with its own private key. Only when the master station decrypts and compares the results can it be confirmed that the module is not an illegal counterfeit device.

[0043] The 4G module decrypts and verifies K_auth, and uses the HMAC-SHA256 algorithm to calculate and generate a response key using the device private key and the random number Nonce_B as parameters to generate the response K_resp.

[0044] After the main site verifies K_resp, a secure session is established.

[0045] As a preferred embodiment, a collaborative control method for a 4G communication module of an integrated eSIM electricity meter, wherein the key of the SM4-CBC algorithm in step S6 is derived from the secure session key, the IV uses a random number + timestamp, each configuration packet carries a 16-byte message authentication code, which is generated by the secure session key and the configuration packet content using the HMAC-SHA256 algorithm, and is used to verify the integrity and source legitimacy of the configuration packet; after the configuration file is received, the overall integrity of the file is verified by the CRC32 check algorithm, wherein the IV represents the initialization vector.

[0046] As a preferred embodiment, a collaborative control method for a 4G communication module of an integrated eSIM electricity meter is provided. In step S7, the preset threshold is a network quality comprehensive score ≤60 or signal strength ≤-105dBm or packet loss rate ≥5% or latency ≥300ms. The 4G module network parameters include transmit power, channel selection and receive time window.

[0047] The transmit power adjustment range is 10dBm~23dBm, and the adjustment formula is P_tx=max{10dBm,min(23dBm,P_base+(60-Score) / 10)};

[0048] The receiving time window is adjusted from 10ms to 50ms, and the adjustment formula is T_rx=max{10ms,min(50ms,T_base×(100-Score) / 40)}; if the overall network quality score is still ≤60 after 3 consecutive adjustments, an alarm is triggered and reported to the main station.

[0049] Among them, Score is the comprehensive network quality score (0-100 points) calculated by the three-dimensional collaborative model, P_base is the factory preset reference transmit power (dBm) of the 4G module, and T_base is the preset reception time window reference period (ms) of the 4G module.

[0050] To address the aforementioned technical problems, this application also provides a 4G communication module system for an energy meter integrating eSIM, which is integrated into the main control chip of the eSIM-4G module, comprising:

[0051] Data acquisition unit: used to collect the operating status parameters of the eSIM-4G module, the operating parameters of the 4G network, and the service data of the electricity meter in real time, and transmit the collected data to each functional module;

[0052] Power consumption coordination scheduling module: It has a built-in dynamic power consumption scheduling algorithm that dynamically adjusts the 4G module operation mode and eSIM chip working status based on the operation status parameters transmitted by the data acquisition unit.

[0053] The remote security configuration module includes a configuration file encryption submodule, a device identity authentication submodule, a configuration integrity verification submodule, and an encryption / decryption processing submodule. It enables two-way authentication between the 4G module and the master station, decryption of information sent from the master station, and encryption of electricity meter information. It also integrates a secure transmission module to ensure secure transmission of eSIM configuration files and secure uploading of electricity meter data. Leveraging the ESAM interface class, it provides hardware security support for device identity binding, two-way authentication, and encrypted configuration file transmission, achieving collaborative reinforcement of software and hardware security, ensuring secure data transmission across all interfaces, and guaranteeing reliable execution of configuration updates and data protection.

[0054] The ESAM interface is a communication interface between the eSIM-4G module and the ESAM hardware security chip built into the energy meter, used to call hardware-level encryption operations, identity authentication and key secure storage capabilities.

[0055] Dynamic network adaptation module: Built-in scene awareness algorithm, based on the 4G network operation parameters transmitted by the data acquisition unit, triggers eSIM redundancy profile switching and 4G module network parameters optimization;

[0056] Business data processing module: As the core data interaction carrier between the eSIM-4G module and the main control chip, it integrates a data classification submodule, a batch upload scheduling submodule, and a communication function adaptation submodule. Through layered design, it realizes differentiated and efficient transmission of power business data, and also has the ability to integrate preset communication functions and adapt to multiple types of interfaces.

[0057] The preset communication functions cover the entire process of communication interaction capabilities, including connection, read and write operation, operation reporting and secure transmission protection functions, covering all business scenarios of remote communication for electricity meters;

[0058] The interface adaptation capability is fully compatible with the core business interfaces of the electricity meter, including basic business interfaces and event objects, frozen data, file transfer, device management, ESAM, and wireless public / private network communication interfaces. It can realize multi-dimensional power data compatible acquisition, standardized encapsulation and stable transmission, and ensure seamless connection between the eSIM-4G module and different models of electricity meters.

[0059] Storage unit: Used to cache collected electricity meter service data, preset parameters, operation logs and eSIM configuration files.

[0060] Compared with the prior art, the collaborative control method and system for an integrated eSIM 4G communication module of an energy meter provided by the present invention has at least the following beneficial effects:

[0061] 1. This invention breaks through the inherent limitations of the traditional 4G module hardware architecture of electricity meters, achieving deep integration and adaptation between the eSIM chip and the 4G module, replacing the two traditional mainstream solutions (plug-in physical SIM card or separate external eSIM chip architecture), realizing remote over-the-air operation of the entire process of operator switching, plan change, and parameter configuration, and completely solving the on-site operation and maintenance problems; the design without exposed physical interfaces greatly improves the module's environmental adaptability and anti-interference ability, and the board-level high-speed direct connection architecture eliminates external bus transmission loss, breaking through the performance bottleneck of traditional solutions from the hardware root.

[0062] 2. This invention achieves a fundamental shift from single-dimensional static decision-making to multi-dimensional, fully coordinated control. Existing technologies rely solely on battery power or network quality for operational strategy decisions, failing to establish a quantitative coupling relationship between power service scenarios, network environment, and equipment status. This results in locally optimal but globally suboptimal decision outcomes, leading to problems such as high-priority service blocking, low network resource utilization, and significant power waste. This invention constructs an integrated control system encompassing six dimensions: hardware architecture coordination, operational status coordination, three-dimensional service coordination, end-to-end security coordination, network adaptation dynamic coordination, and closed-loop operation management coordination. Its core is a three-dimensional coordinated control model of power service scenarios, network environment, and equipment status. This model can adaptively adjust operational strategies according to different service scenarios of the electricity meter, achieving globally optimal matching of service priorities, network resources, and equipment status. This completely solves the core problems of poor service adaptability and low resource utilization efficiency in traditional solutions.

[0063] 3. This invention breaks through the limitations of traditional eSIM chip and 4G module main control state management being independent and statically fixed, endowing the module with microsecond-level state coordination and dynamic power consumption optimization capabilities; the event-driven state synchronization mechanism based on hardware interrupts replaces the traditional periodic polling method, realizing lag-free state synchronization between the eSIM chip and the 4G module; the accompanying dynamic power consumption scheduling algorithm can accurately match the operating mode according to the service scenario and device status, significantly reducing invalid power consumption loss, significantly improving the battery life after the power meter is powered off, and ensuring the stable operation of the module in various dynamic scenarios.

[0064] 4. This invention abandons the simplistic approach of traditional static device identification and single-point security protection, and constructs a hardware-level, end-to-end collaborative and trusted access system that spans the entire lifecycle. Existing technologies often use static IMEIs that can be modified by software or SIM cards that can be easily replaced as device identifiers. These are easily forged and difficult to trace. Identity authentication, configuration transmission, and data protection are independent of each other, posing a single-point vulnerability and failing to meet the high security and compliance requirements of the power industry. This invention uses a one-time programmable OTP memory to achieve irreversible hardware-level identity binding between the eSIM chip and the 4G module's main control, establishing an immutable physical root of trust. It constructs a full-link collaborative security mechanism for identity authentication, configuration encryption, data protection, and integrity verification. Combined with national cryptographic algorithms and dynamic access control, it achieves closed-loop security management throughout the entire lifecycle of module access, use, and exit, effectively resisting various network attacks and unauthorized access risks, and fully meeting the compliance requirements of high-security scenarios in the power Internet of Things.

[0065] 5. Through the synergistic effect of the above-mentioned innovative mechanisms, this invention achieves comprehensive improvement in multiple dimensions such as hardware adaptability, resource utilization efficiency, business response capability, operational reliability, security protection level, and ease of operation and maintenance. In terms of hardware adaptability, the architecture has been upgraded from traditional pluggable and discrete to an integrated architecture, expanding the adaptability scenarios from conventional indoor environments to various complex power scenarios such as outdoor wide-temperature environments, strong interference, and remote weak signals. In terms of resource utilization efficiency, the architecture has evolved from single-dimensional extensive scheduling to multi-dimensional global collaborative optimization, significantly improving network resource utilization and power consumption control accuracy. In terms of service response capability, the latency of fault alarms has been reduced from minutes to seconds, fully meeting the real-time requirements of core power industry businesses. In terms of operational reliability, the architecture has been upgraded from periodic polling-based lagging state management to event-driven real-time synchronization, significantly reducing communication interruption and failure rates. In terms of security protection level, the architecture has evolved from a static and easily forged identification system to a hardware-level immutable end-to-end trusted system, meeting the Level 3 security requirements of the power industry. In terms of operation and maintenance convenience, the architecture has been upgraded from on-site meter removal and debugging and manual card replacement to full-process remote configuration and plug-and-play functionality, significantly reducing operation and maintenance manpower and time costs. This invention systematically solves the long-standing industry pain points of 4G modules for electricity meters, such as difficult operation and maintenance, low reliability, poor coordination, and weak security protection. It provides core technical support for the large-scale, long-lifecycle, and highly secure and stable operation of power Internet of Things (IoT) terminal devices, and has significant technological advancements and extremely high industrial application value. Attached Figure Description

[0066] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0067] Figure 1 A system architecture diagram of a 4G communication module for an energy meter with integrated eSIM provided in this application embodiment;

[0068] Figure 2 A flowchart of a three-dimensional collaborative control method provided in an embodiment of this application;

[0069] Figure 3 This is a flowchart of a dynamic power consumption scheduling algorithm provided in an embodiment of this application;

[0070] Figure 4 This is a schematic diagram of a secure remote configuration process provided in an embodiment of this application;

[0071] Figure 5 A flowchart of a dynamic network adaptation algorithm provided in an embodiment of this application;

[0072] In the diagram: 1. Data acquisition unit; 2. Power consumption collaborative scheduling module; 3. Remote security configuration module; 30. Configuration file encryption submodule; 31. Device identity authentication submodule; 32. Configuration integrity verification submodule; 33. Encryption and decryption processing submodule; 34. Secure transmission module; 4. Dynamic network adaptation module; 5. Business data processing module; 50. Data classification submodule; 51. Batch upload scheduling submodule; 52. Communication function adaptation submodule; 6. Storage unit. Detailed Implementation

[0073] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0074] The core of this application is to provide a collaborative control method and system for an energy meter 4G communication module integrated with eSIM, which solves the problems of lack of multi-dimensional collaborative adaptation, insufficient collaboration between eSIM chip and 4G module software layer, and imperfect operation and maintenance and security protection system in existing energy meter 4G modules.

[0075] Figure 1 This application provides a system architecture diagram of a 4G communication module for an integrated eSIM energy meter. Figure 2 This is a flowchart of a three-dimensional collaborative control method provided in an embodiment of this application. Figure 3 This is a flowchart of a dynamic power scheduling algorithm provided in an embodiment of this application. Figure 4 This is a schematic diagram of a secure remote configuration process provided in an embodiment of this application. Figure 5 A flowchart of a dynamic network adaptation algorithm provided in an embodiment of this application is shown below. Figures 1 to 5 As shown. Figure 2The demonstration showcases the complete process of data acquisition, dynamic power consumption adjustment, security configuration updates, network adaptation optimization, service data transmission, closed-loop verification, and anomaly handling, as well as the logical connections between each step, clearly defining the nodes of eSIM-related operations (configuration updates, profile switching) within the process. Figure 3 The demonstration shows the power consumption mode judgment logic and triggering conditions based on service type and battery level, as well as the collaborative switching process between 4G module operating mode and eSIM working state (active / dormant), including the application logic of power consumption prediction formula. Figure 4 The document demonstrates the entire process of eSIM configuration files from the power master station to module execution, including detailed steps of encryption processing, dual authentication, integrity verification, and the processing logic corresponding to different verification results. Figure 5 The core demonstration includes network quality parameter collection, weighted score calculation (including the application of the comprehensive network quality score formula), threshold comparison, and the linkage process between eSIM redundancy profile switching and 4G module network parameter optimization.

[0076] S1 Multi-Source Data Precision Acquisition

[0077] S1.1 eSIM-4G Module Operating Status Parameter Acquisition: Core operating parameters are acquired in real time through the built-in sensors and main control chip interface of the eSIM-4G module. Specifically, the remaining battery power of the energy meter is collected every 60 seconds by an integrated power sensor. The sensor quantizes the voltage signal into a digital signal via an analog-to-digital converter (ADC). The MCU reads the raw data and performs piecewise linear calibration using the following calibration formula:

[0078] Q cal =Q raw ⋅k i +b i

[0079] Among them, Q cal Q represents the calibrated battery capacity (in %). raw To collect raw electricity data (unit: %), k i b is the interval calibration coefficient. i This is the interval offset;

[0080] The power consumption detection ranges from 0% to 30% (k1=1.05, b1=−0.5), 30% to 70% (k2=1.02, b2=0), and 70% to 100% (k3=0.98, b3=2.0), ensuring a power detection error of ≤2%. Service types are identified through the main control chip's task scheduling status, categorized into four types: idle, data acquisition, eSIM configuration update, and fault alarm. Network signal strength is collected in real-time by the 4G module's built-in detection unit, measured in dBm. All operating status parameters and timestamps are packaged into standard data frames and sent to the data acquisition module via the internal bus.

[0081] S1.2 4G Network Operation Parameter Acquisition: Data acquisition is completed by the network monitoring unit built into the 4G module, including three core parameters: signal strength, packet loss rate, and latency. Signal strength is acquired in real time; packet loss rate is calculated by counting the number of lost frames transmitted per unit time; and latency is obtained by sending test packets and recording the round-trip time difference. The acquired latency data is calibrated using multiple sampling and averaging to eliminate the impact of instantaneous network fluctuations. The calibration formula is:

[0082]

[0083] in, The time delay after calibration (unit: ms). The number of samples (value 10). The delay for the i-th sampling (in milliseconds) is ≤5ms after calibration. The collected network parameters, after standardization, are packaged with a timestamp and sent to the data acquisition module.

[0084] S1.3 Electricity Meter Business Data Acquisition: By adapting to the RS485 / UART standard interface of the electricity meter and considering the adaptation requirements of interface types (energy, maximum demand, phase variable, power, harmonic variable, data variable, event object, parameter variable, frozen data, file transfer, device management, application connection, ESAM interface, and wireless public / private network communication interface), the core business data of the corresponding interface is accurately collected. Fault alarm data (such as voltage anomalies and current anomalies, corresponding to event object and parameter variable types) is collected in real time. Real-time electricity consumption data (corresponding to energy, power, phase variable, etc.) is sampled at a frequency of 15 minutes / time. Monthly electricity consumption report data (corresponding to frozen data and maximum demand, etc.) is collected at fixed times daily. During the acquisition process, plaintext + MAC methods are used to complete data integrity verification to ensure no data loss or erroneous collection. After successful verification, the data is packaged with a timestamp and transmitted to the data acquisition module.

[0085] S2 Multi-Dimensional Triggering Mechanism

[0086] S2.1 Power Consumption Adjustment Trigger Mechanism: The system maintains battery level and service type status registers to monitor module operating status in real time. When the battery level is detected to be ≤30% and the service type is idle, a low-power mode is triggered; when the service type is eSIM configuration update or fault alarm, a high-power mode is triggered; when the battery level is between 30% and 70% and the service type is data acquisition, a normal power mode is triggered; when the battery level is ≥70%, the current power mode remains unchanged. The trigger signal is immediately sent to the power consumption coordination scheduling module after generation.

[0087] S2.2 Configuration Update Trigger Mechanism: The system continuously monitors the command port issued by the power master station. Configuration update commands are transmitted in an encrypted format, containing information such as command identifier, configuration file digest, and master station signature. When a configuration update command is received, the system first verifies the validity of the master station signature. If the signature verification is successful, the command content is parsed, triggering the secure remote configuration process. If the signature verification fails, the configuration update is rejected, and an exception log is generated and reported to the power master station.

[0088] S2.3 Network Adaptation Trigger Mechanism: A comprehensive network quality score is calculated based on a scene-aware algorithm. The scoring formula is as follows:

[0089]

[0090] in, For the comprehensive network quality score, ω1, ω2, and ω3 are the weighting coefficients for each parameter (0.4, 0.3, and 0.3 respectively, summing to 1); S_RSRP, S_loss, and S_delay are the standardized scores (0-100 points) for signal strength, packet loss rate, and latency, respectively. The parameter standardization logic is as follows: ① Signal strength (S_RSRP): -115dBm is set to 0 points, -90dBm to 100 points, calculated using a linear mapping; ② Packet loss rate: 10% is set to 0 points, 0% to 100 points, calculated using an inverse linear mapping; ③ Latency: 500ms is set to 0 points, 100ms to 100 points, calculated using an inverse linear mapping. When the comprehensive score... When the signal strength is ≤60, or any parameter reaches a preset threshold (signal strength ≤-105dBm, packet loss rate ≥5%, latency ≥300ms), the network adaptation optimization process is triggered, a trigger signal is generated and sent to the dynamic network adaptation module.

[0091] S2.4 Data Transmission Trigger Mechanism: Trigger rules are set based on business data types. Fault alarm data is transmitted in real time; real-time electricity consumption data is transmitted in batches according to a preset collection cycle; monthly electricity consumption report data is transmitted in batches at fixed time periods each day. When transmission is triggered, a data type identifier is generated synchronously and sent to the business data processing module.

[0092] S3 Data Encapsulation and Cache Management

[0093] S3.1 Data Encapsulation Mechanism: The data encapsulation module performs structured processing on the collected multi-source heterogeneous data, generating standardized data packets. First, it reads various types of data from the data acquisition module, performs secondary integrity checks, marks and isolates abnormal data. Then, it generates a globally unique sequence number for valid data, consisting of a module identifier, a timestamp, and data type encoding. Finally, it constructs a four-element data packet structure containing "data type identifier - data length - data value - checksum," with the following specific format:

[0094]

[0095] Among them, TypeID is a 1-byte data type encoding, Len is a 2-byte data length, Value is a variable-length data value, and CheckSum is a 2-byte CRC checksum. The encapsulated data packet is sent to the cache management module via the internal bus.

[0096] S3.2 Chained Buffer Management Mechanism: A three-level circular buffer (BUF_A, BUF_B, BUF_C) is used to achieve redundant data storage and sequential management. During buffer initialization, the initial positions of the write and read pointers are set. The write pointer is updated cyclically in the order "BUF_A→BUF_B→BUF_C→BUF_A", writing the encapsulated data packets sequentially into the buffer to ensure sequential data storage. The read pointer always points to the currently readable data position, reading data according to the first-in, first-out (FIFO) principle. After reading, the data is marked as "overwriteable". When an ACK signal indicating data transmission completion is received, the write pointer is allowed to overwrite the old data in the corresponding buffer; if no ACK signal is received, a copy of the data is retained until retransmission is complete or a timeout occurs, preventing data loss.

[0097] S4 data transmission optimization mechanism

[0098] S4 data transmission optimization mechanism: Based on the preset communication function system, a complete data transmission link is built to achieve full-process communication adaptation;

[0099] S4.1 Adaptive Retransmission Mechanism: Real-time monitoring of network packet loss rate and dynamic adjustment of data retransmission frequency. When packet loss rate ≤ 3%, retransmit once; when 3% < packet loss rate ≤ 5%, retransmit twice; when packet loss rate > 5%, if retransmission fails after three attempts, trigger the network adaptation optimization process (Profile switching). A timeout retransmission mechanism is used during retransmission, with the timeout period dynamically set based on current network latency to ensure retransmission efficiency.

[0100] S5 Software Collaborative Optimization Core Algorithm

[0101] S5.1 Dynamic Power Consumption Scheduling Algorithm: Employing a scenario-threshold mapping model, it establishes a mapping relationship between business scenarios, battery level, and power consumption modes. A fuzzy control algorithm is used to achieve smooth mode switching, avoiding sudden power consumption fluctuations. The power consumption prediction formula is defined as follows:

[0102]

[0103] in, P0 represents the predicted power consumption (in W), P0 represents the module's base power consumption (in W), α represents the service scenario coefficient (α=0.2 for idle scenario, α=0.6 for data acquisition scenario, α=1.0 for eSIM configuration scenario, and α=0.8 for fault alarm scenario), and β represents the battery power coefficient (β=1.0 when battery power ≥70%, β=0.8 when battery power < 70%, and β=0.5 when battery power ≤ 30%). Based on the predicted power consumption results, the system outputs a 4G module operating mode (PSM / eDRX / normal / high power) and eSIM working state (active / sleep) switching command.

[0104] S5.2 Scene-Aware Network Adaptation Algorithm: Based on the collected network parameters and comprehensive scoring results, when the network adaptation optimization process is triggered, the algorithm first filters redundant operator profiles stored in the eSIM, prioritizing the profile with the best signal strength. Simultaneously, it adjusts the 4G module's network parameters, including transmit power (adjustment range 10dBm~23dBm), channel selection, and receive time window (adjustment range 10ms~50ms). After parameter adjustment, the comprehensive network quality score is recalculated until the score (S>60), completing the network adaptation optimization.

[0105] S6 Closed-Loop Verification and State Control

[0106] S6.1 Multi-dimensional Closed-Loop Verification Mechanism: ① Configuration Execution Verification: After completing the eSIM configuration update, the configuration parameters are extracted and compared with the configuration summary in the command issued by the power master station. If they match, the verification passes and a configuration completion log is recorded; if they do not match, the verification fails and the configuration retransmission process is triggered. ② Data Transmission Verification: The integrity of the uploaded service data is verified. If the verification passes, the data transmission is marked as complete; if the verification fails, a data retransmission mechanism is triggered. If the retransmission fails after 3 attempts, an anomaly is reported. ③ Operational Status Verification: The power consumption of the 4G module, the working status of the eSIM chip, and the network quality score are monitored in real time and compared with preset normal thresholds to ensure that the module is operating normally.

[0107] S6.2 Multi-Dimensional Status Control: ① Power Consumption Status Control: Based on the output of the dynamic power consumption scheduling algorithm, switch the 4G module operating mode and eSIM chip working status to ensure that the module power consumption is within a reasonable range. ② Network Status Control: Based on the network adaptation optimization results, switch the eSIM redundancy profile and fix the adjusted 4G module network parameters. ④ Alarm Status Control: When configuration verification failure, multiple data transmission failures, abnormal module operating parameters, etc. are detected, trigger a local alarm, and simultaneously report alarm information and relevant operating logs to the power master station for further processing.

[0108] To address the problems in the prior art, this application also provides a 4G communication module system for an energy meter integrating eSIM, which is integrated into the main control chip of the eSIM-4G module, including:

[0109] Data acquisition unit 1: used to collect the operating status parameters of the eSIM-4G module, the operating parameters of the 4G network, and the electricity meter service data in real time, and transmit the collected data to each functional module;

[0110] Power consumption coordination scheduling module 2: It has a built-in dynamic power consumption scheduling algorithm, which dynamically adjusts the 4G module operation mode and eSIM chip working status based on the operation status parameters transmitted by the data acquisition unit 1.

[0111] Remote security configuration module 3 includes a configuration file encryption submodule 30, a device identity authentication submodule 31, a configuration integrity verification submodule 32, and an encryption / decryption processing submodule 33. It is used to implement two-way authentication between the 4G module and the master station, decrypt information sent by the master station, and encrypt electricity meter information. It also integrates a secure transmission module 34 to ensure secure transmission of eSIM configuration files and secure uploading of electricity meter data. Relying on the ESAM interface class, it provides hardware security support for device identity binding, two-way identity authentication, and encrypted transmission of configuration files, achieving collaborative reinforcement of software and hardware security, ensuring secure data transmission across all interfaces, and ensuring reliable execution of configuration updates and data protection.

[0112] Among them, the ESAM interface is the communication interface between the eSIM-4G module and the ESAM hardware security chip built into the energy meter, which is used to call hardware-level encryption operation, identity authentication and key secure storage capabilities.

[0113] ESAM (Embedded Secure Access Module): This is a standard hardware security chip inside electricity meters, equivalent to a "hardware security lock" for the meter. It is specifically responsible for hardware-level key storage, identity authentication, and data encryption / decryption. It is the core hardware in the power industry to ensure the security of meter communication and prevent unauthorized access.

[0114] ESAM Interface Class: This refers to a set of standard interfaces used in this embodiment for communication between the eSIM-4G module and the ESAM hardware security chip inside the electricity meter. These interfaces are used to access the meter's hardware security capabilities, allowing the 4G module's secure authentication and encrypted transmission to be directly reinforced by the meter's hardware security lock. Steps S4 to S6 involve device identity binding, two-way authentication, and configuration file encryption. Pure software encryption is insecure; by using the ESAM interface to access the meter's hardware security chip, software security is transformed into hardware-level, unbreakable security. This allows the eSIM-4G module and the electricity meter to share a single hardware security root, achieving integrated trusted access for both the module and the meter.

[0115] Dynamic network adaptation module 4: Built-in scene awareness algorithm, based on the 4G network operation parameters transmitted by the data acquisition unit 1, triggers eSIM redundancy profile switching and 4G module network parameters optimization;

[0116] Business data processing module 5: As the core data interaction carrier between the eSIM-4G module and the main control chip, it integrates data classification submodule 50, batch upload scheduling submodule 51 and communication function adaptation submodule 52. Through layered design, it realizes differentiated and efficient transmission of power business data, and has the ability to integrate preset communication functions and adapt to multiple types of interfaces.

[0117] The preset communication functions cover the entire process of communication interaction capabilities, including connection, read and write operation, operation reporting and secure transmission protection functions, covering all business scenarios of remote communication for electricity meters;

[0118] The interface adaptation capability is fully compatible with the core business interfaces of the electricity meter, including basic business interfaces and event objects, frozen data, file transfer, device management, ESAM, and wireless public / private network communication interfaces. It can realize multi-dimensional power data compatible acquisition, standardized encapsulation and stable transmission, and ensure seamless connection between the eSIM-4G module and different models of electricity meters.

[0119] Storage Unit 6: Used to cache collected electricity meter service data, preset parameters, operation logs, and eSIM configuration files.

[0120] To enable those skilled in the art to better understand this solution, a specific application scenario is used as an example to illustrate the solution in detail below: This embodiment takes an electricity meter connected to a 4G module with an integrated eSIM chip as an example. This module uses eSIM technology to replace the traditional physical SIM card. The eSIM chip is embedded inside the 4G module and communicates with the 4G module's main control chip through a standard interface. The electricity meter has power and communication interfaces, and its specific supported power service scenarios and collaborative control strategies are implemented through the software layer.

[0121] Reference Figure 1 As shown, after the electricity meter is powered on, the multi-dimensional collaborative control component of the 4G module with integrated eSIM chip starts operating.

[0122] Initialization (corresponding to step S1): The component loads the pre-stored finite state machine model (including IDLE idle state, COLLECT data acquisition state, CONFIG configuration state, ALERT alarm state), weighted comprehensive scoring algorithm model and device status evaluation model, and initializes the unified interface abstraction layer. This abstraction layer encapsulates the eSIM chip interface, 4G module main control interface and energy meter service interface through standardized interfaces, shielding the underlying hardware differences.

[0123] Multi-source data acquisition (corresponding to step S1): The component collects three types of data in real time through the unified interface abstraction layer: (1) eSIM-4G module operating status parameters, including battery power (collected once every 60 seconds, through piecewise linear calibration) and service scenario status (based on finite state machine definition, identified through the task scheduling status of the main control chip); (2) 4G network operating parameters, including signal strength RSRP (collected once every 30 seconds), packet loss rate (statistically counted once every 5 minutes), and latency (obtained through test message round-trip time); (3) electricity meter service data, including fault alarm data (collected in real time), real-time electricity consumption data (collected every 15 minutes), and monthly report data (collected at fixed times every day).

[0124] Reference Figure 2 As shown, the construction of the 3D collaborative model (corresponding to step S2) includes the following steps:

[0125] First, the component assesses the device status into three levels based on the collected battery power: high power (≥70%), medium power (30%-70%), and low power (≤30%). At the same time, based on a finite state machine, it identifies the current business scenario status according to timer triggers (IDLE→COLLECT, 15-minute cycle), master station command triggers (COLLECT→CONFIG), fault alarm event triggers (arbitrary state→ALERT), and task completion triggers (arbitrary state→IDLE).

[0126] Second (Weighted Overall Score): The component uses a weighted overall score algorithm to calculate the overall network quality score. The scoring formula is as follows: , where S_RSRP, S_loss, and S_delay are the standardized scores of signal strength, packet loss rate, and delay, respectively.

[0127] Third (Dynamic Weight Adjustment): The component dynamically adjusts the weight coefficients ω1, ω2, and ω3 according to the business scenario status: When the business scenario is in alarm state (ALERT), the packet loss rate weight ω2 increases to 0.5 (emphasizing packet loss rate to ensure the reliability of fault alarm transmission), the signal strength weight ω1=0.3, and the latency weight ω3=0.2; When the business scenario is in configuration state (CONFIG), the signal strength weight ω1 increases to 0.5 (emphasizing signal strength to ensure configuration file download speed), the packet loss rate weight ω2=0.2, and the latency weight ω3=0.3; When the business scenario is in idle state (IDLE), the latency weight ω3 increases to 0.4 (emphasizing latency to allow for lower power consumption), the signal strength weight ω1=0.3, and the packet loss rate weight ω2=0.3; When the business scenario is in data acquisition state (COLLECT), ω1=0.4, ω2=0.3, and ω3=0.3 (for balanced consideration).

[0128] Fourth (Three-dimensional collaborative decision-making): The component queries the collaborative decision-making matrix based on three dimensions: business scenario, comprehensive network quality score, and device status, and outputs the optimal 4G module operation mode (PSM power saving mode, eDRX extended discontinuous reception mode, normal operation mode, and high power mode).

[0129] Reference Figure 3 As shown, dynamic power consumption scheduling and state synchronization (corresponding to step S3) includes the following steps:

[0130] First: Based on the output of the 3D collaborative model, the component adjusts the 4G module's operating mode and eSIM's working state through a dynamic power consumption scheduling algorithm. The power consumption prediction formula is as follows: Where P0 is the module's basic power consumption, α is the business scenario coefficient (IDLE=0.2, COLLECT=0.6, CONFIG=1.0, ALERT=0.8), and β is the device status coefficient (high power β=1.0, medium power β=0.8, low power β=0.5).

[0131] Second (Mode Switching): Based on the power consumption prediction results, the component performs 4G module operation mode switching: PSM mode is triggered when the battery level is ≤30% and the service scenario is in idle state, with an average power consumption of ≤1mA; eDRX mode is triggered when the battery level is 30%~70% and the service scenario is in idle state, or when the battery level is ≤30% and the service scenario is in data acquisition state, with the eDRX period dynamically adjusted as T_eDRX=max(20s,min(600s,T_base×Score / 60)), and an average power consumption of ≤10mA; Normal mode is triggered when the battery level is ≥70% and the service scenario is in data acquisition state, with an average power consumption of 150mA; High power mode is triggered when the service scenario is in configuration state or alarm state, with a transmit power of 23dBm and an average power consumption of 500mA. Where T_eDRX is the actual reception period (in seconds) of the eDRX extended discontinuous reception mode; T_base is the base reception period of the eDRX mode (preset initial value); and Score is the overall network quality score (0-100 points).

[0132] Third (Event-Driven State Synchronization): The component adopts an event-driven mechanism to achieve coordinated switching between the eSIM working state and the 4G module operating mode. This mechanism is triggered by a hardware interrupt, with an interrupt response time of ≤1ms; the real-time mapping table between the eSIM working state and the 4G module operating mode is stored in shared memory, with a query latency of ≤1ms; the total state synchronization latency is ≤5ms.

[0133] Reference Figure 4 As shown, device identity association and trusted authentication (corresponding to steps S4-S5) include the following steps:

[0134] First (Identity Association): The component establishes a device identity association based on the eSIM chip's EID identifier and the 4G module's IMEI identifier. This association is written into the module's secure storage area and permanently fixed at the factory, and cannot be modified through external interfaces. The component extracts the eSIM chip's EID and generates a device fingerprint as "device unique identifier (electricity meter number) + eSIM_EID". This fingerprint is then used to generate a 256-bit identity credential using the SM3 hash algorithm and is pre-stored synchronously on the main station. The eSIMEID (eUICCIdentifier, Embedded Universal Integrated Circuit Card Identifier) ​​is a globally unique, tamper-proof, and indelible hardware-level electronic serial number that is burned into the chip's secure storage area by the manufacturer at the time of manufacture.

[0135] Second (Two-way Authentication): The component employs a challenge-response mechanism for two-way authentication with the power master station. The specific process is as follows: The component sends an authentication request to the master station containing the device fingerprint, timestamp, and random number Nonce_A; after verifying the device fingerprint, the master station generates an authentication key K_auth=HMAC-SHA256EID (master station private key) and returns K_auth(Nonce_A), the timestamp, and the random number Nonce_B encrypted using SM4; the component decrypts and verifies K_auth, generating a response K_resp=HMAC-SHA256Nonce_B (device private key); after verifying K_resp, the master station establishes a secure session. Through this invention, device identity requires simultaneous impersonation of both eSIM_EID and the device's unique identifier, and the cracking of the SM3 hash and HMAC-SHA256 authentication mechanisms, significantly increasing the difficulty of impersonation and enhancing the security of trusted device access. Nonce_A is randomly generated by the eSIM-4G module (client) when initiating an authentication request. It is used by the module to verify the legitimacy of the master station: the master station must be able to correctly encrypt Nonce_A with its own private key, and the module must decrypt it and compare the results to confirm that the master station is not a fake base station. Nonce_B is randomly generated by the power master station (server) after verifying the module's identity. It is used by the master station to verify the legitimacy of the module: the module must be able to correctly encrypt Nonce_B with its own private key, and the master station must decrypt it and compare the results to confirm that the module is not an illegal counterfeit device.

[0136] Third (Security Configuration Update): Under a secure session, the component employs the TLS 1.3 protocol and SM4-CBC algorithm to achieve end-to-end encrypted transmission and updates of the eSIM configuration file. The transport layer uses the TLS 1.3 protocol with the TLS_AES_128_GCM_SHA256 suite; the application layer uses SM4-CBC encryption, with the key derived from the session key, and the IV using a random number plus a timestamp; integrity protection uses HMAC-SHA256 to generate the message authentication code; replay protection uses a 64-bit sequence number carried in each configuration packet, with the master station maintaining a sliding window for detection; after receiving the configuration file, its integrity is verified using the CRC32 checksum algorithm.

[0137] Reference Figure 5 As shown, scene-aware network adaptation (corresponding to step S6) includes the following steps:

[0138] First (Network Quality Assessment): The component continuously monitors the overall network quality score. When the overall score Score ≤ 60 or any parameter reaches the preset threshold (signal ≤ -105dBm, packet loss rate ≥ 5%, latency ≥ 300ms), the adaptation process is triggered.

[0139] Second (Profile handover): The component filters redundant operator profiles stored in the eSIM, prioritizes the profile with the best signal strength, and performs profile handover. Thanks to the optimized coordination mechanism at the software layer, the profile handover process is streamlined and efficient, with a handover latency of ≤2 seconds, which is 60-80% shorter than the 5-10 seconds of existing technologies.

[0140] Third (Network Parameter Optimization): The component dynamically adjusts the network parameters of the 4G module, including: transmit power adjustment P_tx=max{10dBm,min(23dBm,P_base+(60-Score) / 10)}, with an adjustment range of 10dBm~23dBm; channel selection automatically selects the optimal channel based on signal strength; receive time window adjustment T_rx=max{10ms,min(50ms,T_base×(100-Score) / 40)}, with an adjustment range of 10ms~50ms.

[0141] Fourth (cyclic detection): The component re-evaluates the network quality until the score is >60; if the score is still ≤60 after 3 consecutive adjustments, an alarm is triggered and reported to the main station.

[0142] Multi-level buffering and closed-loop verification (corresponding to step S7) includes the following steps:

[0143] First (Multi-level Buffering): The component uses multi-level circular buffers to perform hierarchical caching and management of electricity meter business data. BUF_A (High-speed Buffer) has a capacity of 1MB and stores real-time fault alarm data, using a cyclic overwrite strategy, with a data retention time of ≥5 minutes; BUF_B (Business Buffer) has a capacity of 4MB and stores data to be uploaded, including data collection and report data, using a first-in-first-out strategy, with a data retention time of ≥24 hours; BUF_C (Persistent Buffer) has a capacity of 128MB and uses non-volatile storage to store historical operation logs, configuration file backups, and abnormal event records, with a data retention time of ≥30 days.

[0144] Second (Multi-dimensional Closed-Loop Verification): The component verifies configuration execution, data transmission, and operational status through a multi-dimensional closed-loop verification mechanism, triggering alarms when anomalies occur. Specifically, this includes: configuration verification closed loop (configuration command signature verification HMAC-SHA256 → execution verification parameter comparison → main station comparison and confirmation, closed loop time ≤ 10 seconds); data transmission verification closed loop (data frame verification CRC16 → transmission verification TLS encryption + packet loss detection → receiver ACK response, closed loop time ≤ 30 seconds); operational status verification closed loop (real-time monitoring every 60 seconds → anomaly judgment threshold comparison → recovery verification status comparison, closed loop time ≤ 60 seconds).

[0145] Through this invention, a 4G module, which is conventionally used only as a "transparent channel," is deeply analyzed into an intelligent communication unit capable of three-dimensional collaborative control of service scenarios, network environment, and device status. It not only automatically adapts to standard protocols (DL / T698.45, Q / GDW1376.2) but also establishes a quantitative coupling relationship between service scenarios, network environment, and device status. Through dynamic weight adjustment and three-dimensional collaborative decision-making, it achieves precise allocation of network resources. An event-driven state synchronization mechanism ensures real-time collaboration and shortens the response time of power consumption scheduling strategies. Ultimately, its capabilities are securely and efficiently scheduled, maximizing the value of communication resources and rapidly supporting power IoT services. This invention demonstrates significant advancements in realizing "scenario perception, real-time synchronization, and multi-dimensional collaboration" in smart meter eSIM-4G modules.

[0146] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and incorporate common knowledge or customary techniques in the art disclosed herein. The specification and examples are to be considered exemplary only, and the true scope of this application is indicated by the claims.

[0147] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The embodiments of this application described above do not constitute a limitation on the scope of protection of this application.

Claims

1. A collaborative control method for a 4G communication module of an energy meter integrating eSIM, characterized in that, The eSIM chip replaces the physical SIM card, and the eSIM chip is embedded inside the 4G module to form an eSIM-4G module. It communicates with the main control chip of the eSIM-4G module through a standard interface. The control method includes: S1: The eSIM-4G module's operating status parameters, 4G network operating parameters, and electricity meter service data are collected in real time through a unified interface abstraction layer. The operating status parameters include battery power and service scenario status. The service scenario status is defined based on a finite state machine and includes idle state, data acquisition state, configuration state, and alarm state. S2: Based on the aforementioned operating status parameters, 4G network operating parameters, and electricity meter service data, a three-dimensional collaborative model of service scenario, network environment, and device status is constructed. This three-dimensional collaborative model uses a weighted comprehensive scoring algorithm to calculate a comprehensive network quality score. The scoring formula for the weighted comprehensive scoring algorithm is as follows: S_RSRP, S_loss, and S_delay are the standardized scores of signal strength, packet loss rate, and latency, respectively, and the weight coefficients ω1, ω2, and ω3 are dynamically adjusted according to the business scenario status. S3: Based on the output of the three-dimensional collaborative model, the operating mode of the 4G module and the working state of the eSIM chip are adjusted using a dynamic power scheduling algorithm. The 4G module operating modes include PSM power-saving mode, eDRX extended discontinuous reception mode, normal operating mode, and high-power mode. The dynamic power scheduling algorithm uses a power prediction formula. Where P0 is the module's basic power consumption, α is the service scenario coefficient, and β is the device state coefficient. The coordinated switching between the 4G module's operating mode and the eSIM chip's operating state is achieved through an event-driven mechanism, which is triggered by a hardware interrupt. The real-time mapping table between the eSIM chip's operating state and the 4G module's operating mode is stored in shared memory, and the state synchronization latency is ≤5ms. S4: Establish a one-to-one correspondence between the eSIM chip's EID identifier and the 4G module's IMEI identifier for device identity. Use the IMEI identifier + EID identifier as a unique device fingerprint, and perform hash operation using the national cryptographic SM3 hash algorithm to generate a 256-bit fixed-length, tamper-proof, unique device identity credential. S5: Based on the device identity credentials, a challenge-response mechanism is used to perform two-way identity authentication with the power master station. The authentication key K_auth is generated by calculating the HMAC-SHA256 algorithm with the master station's private key and eSIM_EID as parameters. After successful authentication, a secure session is established. S6: Under the secure session, the TLS1.3 protocol and SM4-CBC algorithm are used to implement the end-to-end encrypted transmission and update of the eSIM configuration file. Each configuration packet carries a 64-bit serial number. The main station maintains a sliding window to detect replay attacks. S7: When the overall network quality score is lower than a preset threshold, trigger eSIM redundancy profile switching and dynamic optimization of 4G module network parameters, with eSIM redundancy profile switching latency ≤2 seconds; S8: The electricity meter business data is cached and managed hierarchically through a multi-level ring buffer. The multi-level ring buffer includes a high-speed buffer with a capacity of 1MB, a business buffer with a capacity of 4MB, and a persistent buffer with a capacity of 128MB. The configuration execution, data transmission and operation status are verified through a multi-dimensional closed-loop verification mechanism, and an alarm is triggered when an anomaly occurs.

2. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 1, characterized in that, The parameter standardization logic of the weighted comprehensive scoring algorithm described in step S2 is as follows: S_RSRP is calculated with -115dBm as 0 points and -90dBm as 100 points. The formula is S_RSRP={RSRP−(−115)} / {−90−(−115)}×100. The standardized score of network packet loss rate, S_loss, is calculated with 10% as 0 points and 0% as 100 points. The formula is S_loss = (10% - loss_rate) / 10% × 100. Where loss_rate is the actual measured network packet loss rate; The standardized score for network transmission delay, S_delay, is calculated with 500ms as 0 points and 100ms as 100 points. The formula is S_delay=(500-delay) / (500-100)×100. Here, delay is the actual measured network transmission delay.

3. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 1, characterized in that, The weighting coefficients of the weighted comprehensive scoring algorithm described in step S2 are dynamically adjusted according to the business scenario status as follows: When the business scenario is in an idle state, ω3 increases to 0.4, ω1=0.3, and ω2=0.3; When the business scenario is data acquisition, ω1=0.4, ω2=0.3, ω3=0.3; When the business scenario is in configuration mode, ω1 is increased to 0.5, ω2=0.2, and ω3=0.3; When the business scenario is in alarm state, ω2 increases to 0.5, ω1=0.3, and ω3=0.

2.

4. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 1, characterized in that, The business scenario coefficient α mentioned in step S3 is determined according to the business scenario status: idle state α=0.2, data acquisition state α=0.6, configuration state α=1.0, and alarm state α=0.

8. The device state coefficient β is determined based on the battery charge. When the battery charge is ≥70%, β=1.0; when the battery charge is 30% < 70%, β=0.8; and when the battery charge is ≤30%, β=0.

5.

5. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 1, characterized in that, In the 4G module operation modes described in step S3, the average power consumption of PSM power saving mode is ≤1mA, the average power consumption of eDRX extended discontinuous reception mode is ≤10mA, the average power consumption of normal operation mode is 150mA, and the average power consumption of high power mode is 500mA. The reception period of the eDRX extended discontinuous reception mode is dynamically adjusted, and the adjustment formula is T_eDRX=max{20s,min(600s,T_base×Score / 60)}; Where T_eDRX is the actual reception period (in seconds) of the eDRX extended discontinuous reception mode; T_base is the baseline reception period of the eDRX mode; and Score is the overall network quality score. The eSIM chip's operating states include active and sleep modes. The sleep mode corresponds to the PSM power-saving mode and the eDRX extended discontinuous reception mode, while the active mode corresponds to the normal operating mode and the high-power mode.

6. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 1, characterized in that, The device identity association mentioned in step S4 is written into the secure storage area by the system and fixed when the module leaves the factory, and cannot be modified through external interfaces; The device fingerprint is generated as a 256-bit identity credential by concatenating "electricity meter number + eSIM_EID" and then using the SM3 hash algorithm. The identity credential is compared and verified with the pre-stored credentials on the main station during each authentication.

7. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 1, characterized in that, The challenge-response mechanism described in step S5 includes: The 4G module sends an authentication request to the main station, which includes the device fingerprint, timestamp, and random number Nonce_A. Nonce_A is randomly generated by the eSIM-4G module when it initiates an authentication request. It is used by the module to verify the legitimacy of the master station: the master station must be able to correctly encrypt Nonce_A with its own private key. Only if the module decrypts and compares the results can it be confirmed that the master station is not a fake base station. After verifying the device fingerprint, the master station generates an authentication key K_auth using the HMAC-SHA256 algorithm, with the master station's private key and eSIM_EID as parameters. The authentication key, timestamp, and random number Nonce_B are then encrypted using the SM4 algorithm and returned. Nonce_B is randomly generated by the power station after verifying the module's identity. It is used by the power station to verify the module's legitimacy: the module must be able to correctly encrypt Nonce_B with its own private key. Only if the main station decrypts and compares the results can it be confirmed that the module is not an illegal counterfeit device. The 4G module decrypts and verifies K_auth, and uses the HMAC-SHA256 algorithm to calculate and generate a response key using the device private key and the random number Nonce_B as parameters to generate the response K_resp. After the main site verifies K_resp, a secure session is established.

8. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 7, characterized in that, In step S6, the key of the SM4-CBC algorithm is derived from the secure session key. The IV uses a random number plus a timestamp. Each configuration packet carries a 16-byte message authentication code, which is generated by the secure session key and the configuration packet content using the HMAC-SHA256 algorithm. This code is used to verify the integrity and source legitimacy of the configuration packet. After the configuration file is received, the overall integrity of the file is verified by the CRC32 check algorithm. Here, the IV represents the initialization vector.

9. The collaborative control method for the 4G communication module of an integrated eSIM energy meter according to claim 1, characterized in that, The preset thresholds mentioned in step S7 are: network quality comprehensive score ≤ 60 or signal strength ≤ -105dBm or packet loss rate ≥ 5% or latency ≥ 300ms. The 4G module network parameters include transmit power, channel selection and receive time window. The transmit power adjustment range is 10dBm~23dBm, and the adjustment formula is P_tx=max{10dBm,min(23dBm,P_base+(60-Score) / 10)}; The receiving time window is adjusted from 10ms to 50ms, and the adjustment formula is T_rx=max{10ms,min(50ms,T_base×(100-Score) / 40)}; if the overall network quality score is still ≤60 after 3 consecutive adjustments, an alarm is triggered and reported to the main station. Among them, Score is the comprehensive network quality score (0-100 points) calculated by the three-dimensional collaborative model, P_base is the factory preset reference transmit power (dBm) of the 4G module, and T_base is the preset reception time window reference period (ms) of the 4G module.

10. A 4G communication module system for an energy meter integrating eSIM, integrated into the main control chip of an eSIM-4G module, characterized in that, include: Data acquisition unit (1): used to collect the operating status parameters of the eSIM-4G module, the operating parameters of the 4G network and the service data of the electricity meter in real time, and transmit the collected data to the power consumption collaborative scheduling module, the remote security configuration module, the dynamic network adaptation module and the service data processing module respectively, and simultaneously store the data in the storage unit. Power consumption coordination scheduling module (2): Built-in dynamic power consumption scheduling algorithm, which dynamically adjusts the 4G module operation mode and eSIM chip working status based on the operation status parameters transmitted by the data acquisition unit (1); The remote security configuration module (3) includes a configuration file encryption submodule (30), a device identity authentication submodule (31), a configuration integrity verification submodule (32), and an encryption / decryption processing submodule (33). It is used to realize the two-way authentication between the 4G module and the master station, the decryption of information sent by the master station, and the encryption of electricity meter information. At the same time, it integrates a secure transmission module (34) to ensure the secure transmission of eSIM configuration files and the secure uploading of electricity meter data. It relies on the ESAM interface class to provide hardware security support for device identity binding, two-way identity authentication, and configuration file encryption transmission, realize the collaborative reinforcement of software security and hardware security, ensure the security of data transmission across all interfaces, and ensure the reliable execution of configuration updates and data protection. The ESAM interface is a communication interface between the eSIM-4G module and the ESAM hardware security chip built into the energy meter, used to call hardware-level encryption operations, identity authentication and key secure storage capabilities. Dynamic network adaptation module (4): Built-in scene perception algorithm, based on the 4G network operation parameters transmitted by the data acquisition unit (1), triggers eSIM redundancy profile switching and 4G module network parameters optimization; Business data processing module (5): As the core data interaction carrier between the eSIM-4G module and the main control chip, it integrates the data classification sub-module (50), the batch upload scheduling sub-module (51) and the communication function adaptation sub-module (52). Through layered design, it realizes the differentiated and efficient transmission of power business data, and at the same time has the ability to integrate preset communication functions and adapt to multiple types of interfaces. The preset communication functions cover the entire process of communication interaction capabilities, including connection, read and write operation, operation reporting and secure transmission protection functions, covering all business scenarios of remote communication for electricity meters; The interface adaptation capability is fully compatible with the core business interfaces of the electricity meter, including basic business interfaces and event objects, frozen data, file transfer, device management, ESAM, and wireless public / private network communication interfaces. It can realize multi-dimensional power data compatible acquisition, standardized encapsulation and stable transmission, and ensure seamless connection between the eSIM-4G module and different models of electricity meters. Storage unit (6): used to cache collected electricity meter service data, preset parameters, operation logs and eSIM configuration files.

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