Method for self-adapting compensation of metering accuracy based on thermal characteristics of communication module, electric energy meter

Abstract

The application provides a method for self-adaptive compensation of metering accuracy based on thermal characteristics of a communication module, and an electric energy meter, comprising: pre-storing a thermal characteristic parameter table recording thermal characteristic parameters corresponding to each type of communication module; querying the thermal characteristic parameter table according to the type identification of the current access communication module, if the corresponding thermal characteristic parameter cannot be matched, starting a self-adaptive thermal characteristic identification process, modeling by using a first-order inertia lag model, and then using recursive least squares (RLS) to online identify the thermal characteristic parameter of the unknown communication module according to the real-time power consumption of the unknown communication module under different working conditions and the real-time temperature of the equivalent thermal node of the metering chip, completing self-learning of the model within a few minutes, and obtaining the thermal characteristic parameter of the unknown communication module. The method has self-adaptive compensation capability covering all working conditions, and the steady-state thermal power consumption difference and thermal time constant difference of different communication modules can be accurately compensated by dynamically loading the corresponding thermal characteristic parameter.

Description

Technical Field

[0001] This invention relates to the field of electricity metering technology, and in particular to a method for adaptive compensation of metering accuracy based on the thermal characteristics of a communication module, and an electricity meter. Background Technology

[0002] Multi-mode communication energy meters refer to energy meters that support hot-swappable replacement of multiple communication standard modules on a single base meter hardware architecture. Compatible communication modules cover mainstream communication standards such as power line carrier (PLC), 4G / 5G wireless public network, Wi-SUN, NB-IoT, and LoRa. This modular communication design greatly improves the flexibility of energy meter field networking: the same base meter can be equipped with the optimal communication module according to the differences in the field communication environment, facilitating inventory management and operation and maintenance upgrades.

[0003] However, the hot-swappable nature of communication modules also brings about a deeper problem: dynamic drift in electricity metering accuracy. Different types of communication modules have significantly different operating power consumption, heat generation characteristics, and heat dissipation structures, resulting in drastically different impacts on electricity meter accuracy. For example, a 4G module can consume over 2W of power instantaneously during full-power transmission, far exceeding the typical operating power consumption of a low-power narrowband carrier module (typically around 0.5W). When a 4G module is connected to an electricity meter, the heat generated by its operation is transferred to core metering components such as the metering chip and sampling resistor through heat conduction, radiation, and convection, causing temperature changes in these components. Since the sampling resistor exhibits temperature drift characteristics (the temperature coefficient of copper is approximately +3900ppm / ℃), and the ADC reference voltage and operational amplifier bias current of the metering chip both change with temperature, the temperature rise of the communication module directly translates into electricity metering error. Experimental data shows that before and after the 4G module is connected, the maximum temperature rise in the core metering area of ​​the electricity meter can reach 5°C, which corresponds to a metering error of up to 0.2%. This level of error is unacceptable for precise billing scenarios.

[0004] More significantly, the communication module operates not as a constant power load, but as a dynamic variable power load, which further exacerbates the uncertainty in metering accuracy. Taking the 4G module as a typical example, its operating states can be divided into standby, receive, and transmit modes, and the transmit power can be dynamically adjusted according to the signal strength (dynamically adjusted within the range of -40dBm to +23dBm). The instantaneous power consumption during operation varies greatly when switching operating states (standby power consumption is only about 10mA, while full-load transmit power consumption can exceed 600mA). This means that the thermal interference generated by the communication module is not a fixed static deviation, but changes dynamically in real time with the operating state, causing the energy meter's measurement error to exhibit dynamic drift characteristics, significantly increasing the difficulty of compensation.

[0005] Existing technologies for automatic identification of communication modules include, for example, a combined adaptive smart meter and its automatic module identification method. This method incorporates dedicated identification pins in the pin interfaces between the base meter and each communication module, enabling the base meter to automatically detect the type of the inserted communication module and switch operating modes accordingly. However, existing solutions only focus on communication protocol compatibility, addressing only the communication matching issues between different communication modules. They completely neglect the characteristic differences resulting from communication module replacements and fail to design corresponding compensation mechanisms for metering accuracy deviations caused by thermal interference.

[0006] Furthermore, existing thermal compensation technologies for electricity meters are all based on the premise that the hardware configuration of the electricity meter equipment is fixed, and do not consider the application scenarios of replacing multi-mode communication modules. Even if some technologies adopt multi-heat source separation modeling, they still assume that the heat source structure is fixed and cannot identify or adapt to the changes in heat source parameters caused by the addition or replacement of communication modules, and do not have the ability to dynamically adapt to the thermal characteristics of different modules for compensation.

[0007] In summary, there is an urgent need for an adaptive thermal compensation scheme for energy meters that can dynamically adjust based on the thermal characteristics of the communication module. This would solve the problem of dynamic drift in metering accuracy caused by the plugging and unplugging of multi-mode communication modules, and ensure the metering accuracy and stability of multi-mode communication energy meters in scenarios with full module compatibility. Summary of the Invention

[0008] The technical problem to be solved by this invention is to provide a method and an energy meter for adaptive compensation of metering accuracy based on the thermal characteristics of the communication module, so that the self-heating compensation parameters can be automatically and smoothly updated after the multi-mode communication module is plugged in and replaced, thereby ensuring the metering accuracy and stability across the entire operating range.

[0009] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: Methods for adaptive compensation of measurement accuracy based on the thermal characteristics of communication modules include: A pre-stored thermal characteristic parameter table is provided; the thermal characteristic parameter table records the thermal characteristic parameters corresponding to each type of communication module; the thermal characteristic parameters include thermal power consumption parameters, thermal time constant, thermal coupling coefficient, and additional error model parameters; The thermal feature parameter table is queried based on the type identifier of the currently accessed communication module. If no matching thermal feature parameter is found, the adaptive thermal feature identification process is initiated. The adaptive thermal feature identification process includes: The entire system consisting of the electricity meter and the unknown communication module is considered as a thermodynamic dynamic system to be identified, and a first-order inertial hysteresis model is selected for modeling; the first-order inertial hysteresis model is as follows: τ_c·dT_c / dt = - (T_c - T_env) + γ·P_mod(t); Where τ_c is the thermal time constant; dT_c / dt is the temperature change rate of the equivalent thermal node of the metering chip; T_c is the predicted temperature of the equivalent thermal node of the metering chip output by the model; T_env is the ambient reference temperature; γ is the thermal coupling coefficient; and P_mod(t) is the real-time power consumption of the unknown communication module input by the model. Real-time power consumption of the unknown communication module under different working conditions and real-time temperature of the corresponding equivalent thermal node of the metering chip were collected respectively. Based on the real-time power consumption and corresponding real-time temperature collected at the moment, the model is updated online using the recursive least squares (RLS) method until the model converges and the data collection operation is stopped. Based on the converged established model, obtain the thermal characteristic parameters corresponding to the unknown communication module; The acquired thermal characteristic parameters are loaded into the self-heating compensation model of the main control unit of the electricity meter.

[0010] Optionally, an intermittent acquisition strategy is used to collect the real-time power consumption of the unknown communication module under different working states and the real-time temperature of the corresponding equivalent thermal node of the metering chip. The intermittent acquisition strategy includes: When the unknown communication module switches its working state, the real-time continuous acquisition mode is triggered; When the duration for which an unknown communication module maintains the same working state reaches a preset threshold, the data acquisition operation is temporarily suspended.

[0011] Optionally, before obtaining the thermal characteristic parameters corresponding to the unknown communication module, the method further includes: The converged model is evaluated by residual analysis. If the root mean square error calculated from the predicted temperature of the equivalent thermal node of the metering chip output by the model and its corresponding measured temperature is lower than the preset error threshold, the converged model is deemed to be valid and the process of obtaining the thermal feature parameters corresponding to the unknown communication module is executed. Otherwise, the converged model is deemed to be invalid and the adaptive thermal feature identification process is restarted.

[0012] Optionally, if the root mean square error calculated from the predicted temperature of the equivalent thermal node of the metering chip output by the established model and its corresponding measured temperature is lower than a preset error threshold, it specifically includes: If the root mean square error calculated from the predicted temperature of the equivalent thermal node of the metering chip output by the established model and its corresponding measured temperature is lower than the preset error threshold, and the goodness of fit is greater than or equal to the preset lower limit threshold of goodness of fit, then the established model is deemed to have converged and is valid.

[0013] Optionally, after querying the thermal characteristic parameter table based on the type identifier of the currently accessed communication module, the method further includes: If a matching thermal characteristic parameter is found, the matched thermal characteristic parameter will be loaded into the self-heating compensation model of the main control unit of the electricity meter.

[0014] Optionally, it also includes: When a communication module disconnection event is detected, the compensation value currently output by the self-heating compensation model of the main control unit of the electricity meter is obtained and marked as the initial heat contribution compensation value when the communication module is disconnected. Based on the initial thermal contribution compensation value and the preset attenuation time constant, the attenuation compensation value at time t after the communication module is unplugged is calculated in real time using an exponential attenuation algorithm until the calculated attenuation compensation value is zero. Based on the attenuation compensation value at time t after the communication module is unplugged, calculated in real time, the compensation value output by the self-heating compensation model at the corresponding time is compensated.

[0015] Optionally, it also includes: When a communication module access event is detected, the compensation value currently output by the self-heating compensation model of the main control unit of the electricity meter is obtained and marked as the target heat contribution compensation value after the communication module access; Based on the target thermal contribution compensation value, the preset establishment time constant and the thermal time constant of the communication module, the establishment compensation value at time t after the communication module is connected is calculated in real time using an exponential establishment algorithm until time t equals the preset steady-state time threshold. Based on the established compensation value at time t after the communication module is connected, calculated in real time, the compensation value output by the self-heating compensation model at the corresponding time is compensated.

[0016] Optionally, it also includes: If there are two or more independent heat sources inside the electricity meter, the heat compensation values ​​of each independent heat source are added together to obtain the total heat compensation value of the electricity meter. The independent heat source is a sampling resistor, a metering chip, or a communication module.

[0017] Optionally, it also includes: The electricity meter remotely receives the thermal characteristic parameter upgrade package sent by the master station. The thermal characteristic parameter upgrade package encapsulates the thermal characteristic parameters corresponding to the type identifier of the new communication module, and / or the new thermal characteristic parameters corresponding to the type identifier of the existing communication module. The electricity meter updates the locally stored thermal characteristic parameter table according to the thermal characteristic parameter upgrade package.

[0018] Another technical solution provided by this invention is: An electricity meter includes a main control unit and a computer-readable storage medium; the computer-readable storage medium stores a computer program; when executed by the main control unit, the computer program can implement the method of adaptive compensation of metering accuracy based on the thermal characteristics of the communication module.

[0019] The beneficial effects of this invention are as follows: This invention possesses adaptive thermal feature identification capabilities for unknown communication modules. Specifically, it employs a first-order inertial hysteresis model for modeling, and then, based on the real-time power consumption of the unknown communication module under different operating states and the real-time temperature of the corresponding equivalent hot node of the metering chip, it uses recursive least squares (RLS) to identify the thermal feature parameters of the unknown communication module online. The model completes self-learning within minutes, acquiring the thermal feature parameters of the unknown communication module. Simultaneously, it also possesses adaptive compensation capabilities covering all operating conditions. Differences in steady-state thermal power consumption and thermal time constants between different communication modules can be accurately compensated by dynamically loading the corresponding thermal feature parameters. Furthermore, it features seamless precision switching during hot-swapping of communication modules. Specifically, through a smooth transition mechanism of gradual attenuation and gradual establishment, it controls the jump variables in metering values ​​during communication module replacement, ensuring metering accuracy while achieving complete user-unnoticed accuracy. Attached Figure Description

[0020] Figure 1 A flowchart illustrating a method for adaptive compensation of metering accuracy based on the thermal characteristics of a communication module, provided in an embodiment of the present invention; Figure 2 This is a complete flowchart illustrating a method for adaptive compensation of measurement accuracy based on the thermal characteristics of a communication module, provided for a specific embodiment of the present invention. Detailed Implementation

[0021] To explain in detail the technical principles, specific implementable solutions, possible application scenarios, and achievable objectives and effects of the present invention, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. It is understood that the embodiments described herein and the embodiments shown in the accompanying drawings are only used to more clearly illustrate the technical solutions of the present invention, and are therefore only examples intended to explain the present invention, and should not be construed as limiting the present invention. It should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0022] Please see Figure 1 This invention provides a method for adaptively compensating for measurement accuracy based on the thermal characteristics of a communication module.

[0023] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for adaptive compensation of measurement accuracy based on the thermal characteristics of a communication module, comprising the following steps: S1: Pre-stored thermal characteristic parameter table.

[0024] The thermal characteristic parameter table records a set of thermal characteristic parameters corresponding to each type of communication module. Each set of thermal characteristic parameters includes thermal power consumption parameters, thermal time constant, thermal coupling coefficient, and additional error model parameters, which are used to describe the heating characteristics of the corresponding communication module under different communication (operating) states and its impact on the electricity meter metering system.

[0025] For example, the thermal characteristic parameters of each communication module are shown in Table 1 below: Table 1 In some specific implementations, the thermal characteristic parameters of various types of communication modules are calibrated offline through standardized tests under laboratory conditions. The calibration apparatus includes a constant temperature chamber, a data acquisition system, and a reference thermometer.

[0026] (1) The calibration method for thermal power consumption parameters is as follows: place the communication module in a constant temperature environment, measure the voltage and current under different communication (working) states, and calculate the power consumption corresponding to each state.

[0027] (2) The thermal time constant is calibrated by applying a step power input (such as switching from standby to full power transmission) to the communication module, recording the temperature response curve, and then fitting it using a first-order RC thermal response model: T(t) = T0 + (T∞ - T0)·(1 - e^{-t / τ}); where T(t) is the temperature at time t; T0 is the initial temperature (when time t=0); T∞ is the final / steady-state temperature (when time approaches infinity); t is time; and τ is the time constant.

[0028] Therefore, the thermal time constant of the communication module itself, namely the module thermal time constant τ_mod, is calculated. This parameter determines the lower limit of the response speed of thermal compensation: the larger τ_mod is, the slower the thermal equilibrium process is, and the longer the transition period is required for the compensation parameters.

[0029] (3) Calibration method of thermal coupling coefficient: Under the condition of complete machine assembly, the temperature rise ΔT_met of the metering chip of the communication module under different thermal power consumption states is measured, and a linear regression model is established: ΔT_met = γ_static·ΔT_mod; Therefore, the static compliance coefficient γ_static of the communication module can be calculated.

[0030] (4) Calibration method of additional error model parameters: Use a standard power source to measure the measurement error of the communication module under different thermal power consumption conditions, and establish a polynomial regression model of error and module temperature rise ΔT_mod.

[0031] In some specific embodiments, the thermal characteristic parameter table is stored in the non-volatile memory (Flash / EEPROM) of the electricity meter base and supports remote online upgrades.

[0032] Preferably, in the thermal characteristic parameter table organized using a table structure, each type of communication module corresponds to one thermal characteristic parameter record.

[0033] S2: The communication module is plugged into the energy meter. After the base meter successfully identifies the type of the currently connected communication module, it queries the thermal characteristic parameter table based on the type identifier.

[0034] In some specific implementations, a standardized plug-in interface is used between the electricity meter base and the communication module. The communication module type identification process after the base is powered on or a plug-in event is detected is as follows: S21 detects the presence of the communication module: The base table periodically scans the power pin current or identifies the pin status of the communication module interface, and triggers the identification process when a communication module insertion event is detected. S22 Read Communication Module Type Identifier: The base table reads the module type identifier (Type ID) by identifying the pins. S23 Reads Communication Module Information Descriptor: The base table can read the descriptor information of the EEPROM stored internally in the communication module via the communication bus I²C, including extended information such as module model, hardware version, rated power consumption, and thermal characteristic parameters. This step provides an additional data source for the rapid loading of thermal characteristic parameters.

[0035] S24 Confirmation of Identification Result: The base table and the communication module perform a two-way handshake confirmation, and the communication module replies with an identification confirmation frame.

[0036] S3: If a corresponding thermal characteristic parameter is successfully matched in the thermal characteristic parameter table, the matched thermal characteristic parameter will be loaded into the self-heating compensation model of the main control unit of the electricity meter.

[0037] S4: If the corresponding thermal feature parameter cannot be matched in the thermal feature parameter table, the currently accessed communication module is determined to be an unknown type of communication module, referred to as an unknown communication module, and the adaptive thermal feature identification process is started.

[0038] The adaptive thermal feature identification process mainly obtains its thermal feature parameters by measuring the temperature rise curves of the communication module under different operating states and fitting them online. Specifically, it includes the following steps: 1. Verify the status of the electricity meter system and set the initial default parameters for the recursive least squares (RLS) method.

[0039] The status of the electricity meter system that needs to be verified includes, but is not limited to, whether the communication module is stable, whether the sensors are working properly, and whether the main control unit (MCU) is idle; if all conditions are met, proceed to the next step.

[0040] 2. Construct the thermodynamic dynamic system to be identified.

[0041] The entire system consisting of the electricity meter and the unknown communication module is regarded as a thermodynamic dynamic system to be identified. Its input is the real-time thermal power consumption state sequence P_mod(t) of the unknown module, which is obtained by the base meter through the interface of the unknown communication module to query the working status of the module; its output is the measured value of the temperature sensor near the metering chip.

[0042] The state-space model of the thermodynamic dynamic system to be identified is a first-order inertial hysteresis model; the first-order inertial hysteresis model is as follows: τ_c·dT_c / dt = - (T_c - T_env) + γ·P_mod(t); Where τ_c is the thermal time constant (parameter to be identified); dT_c / dt is the temperature change rate of the equivalent thermal node of the metering chip; T_c is the predicted temperature of the equivalent thermal node of the metering chip output by the model; T_env is the ambient reference temperature; γ is the thermal coupling coefficient (parameter to be identified); and P_mod(t) is the real-time power consumption of the unknown communication module input to the model.

[0043] In this embodiment, a first-order inertial hysteresis model is selected to construct the state-space model of the thermodynamic dynamic system to be identified. The working principle for subsequently obtaining the thermal characteristic parameters to be identified through online recursion is as follows: Given a set of two unknown physical parameters (i.e., two eigenvalues ​​to be identified) [τ_c, γ The nonlinear differential equation is transformed into a standard linear regression equation for intermediate parameters [a,b] through forward Euler discretization and algebraic transformation. This equation can then be solved online using the RLS algorithm, and finally the physical parameters can be derived back.

[0044] Its core derivation chain can be summarized as follows: Physical differential equation → Forward Euler discretization → Parameter transformation (a,b) → Standard RLS linear regression form → RLS recursive identification → Inverse deduction of physical parameters [τ_c, γ ].

[0045] For example, the specific derivation process is as follows: (1) Primitive continuous domain differential equation (i.e., first-order inertial hysteresis equation): τ_c·dT_c / dt = - (T_c - T_env) + γ·P_mod(t); (2) Forward Euler discretization (Δt=1 second): Using the difference approximation to replace the differential: dT_c dt≈T_c (k+1) T_c (k)Δt; Substitute into the original equation: τ_c T_c (k+1) T_c (k)Δt= T_c (k) + T_env +γ Pmod(k); Organize into recursive form: T_c (k+1)=(1 Δtτ_c) T_c (k)+Δt γτ_c Pmod(k)+Δt τ_c T_env; (3) Parameter transformation (converting to linear regression form): Define two intermediate variables, which will be the physical parameters [τ_c, γ ] [τ_c, γ The mapping is [a,b]: a=1 Δt τ_c; b=Δt γ τ_c; Because of 1 Substituting a = Δt / τc into the recurrence relation: T_c (k+1)=a T_c (k)+b Pmod(k)+(1 a) T_env; Rearrange the terms, using the temperature rise ΔT_c (k) = T_c (k) T_env expression: ΔT_c (k+1)=a ΔT_c (k)+b Pmod(k); (4) RLS standard format: Let y(k) = ΔT_c(k), (k 1)=[ΔT_c (k 1), Pmod(k 1)]T,θ= : y(k)= T(k 1) θ+e(k); Expanding into algebraic form: ΔT_c (k)=a ΔT_c (k 1)+b Pmod(k 1)+e(k); Where e(k) is the modeling error (residual); y(k) is the system output at time k = ΔT_c(k); (k 1) is a data vector containing the temperature rise and power consumption of the previous time step; (5) After identification, the physical parameters are deduced: RLS identification obtained , Then, the physical parameters are deduced back: τ_c= Δt / ln( ); γ= τ_c / Δt; in, Temperature retention coefficient identified for RLS; The power consumption-temperature rise gain coefficient identified by RLS; τ_c is the equivalent thermal time constant obtained by back-reasoning; γ is the comprehensive thermal coupling coefficient obtained by back-reasoning.

[0046] 3. During the operation of the electricity meter, the thermal characteristic parameters of the unknown communication module are adaptively identified using the thermodynamic dynamic system to be identified.

[0047] First, the real-time power consumption of the unknown communication module under different working conditions and the real-time temperature of the corresponding equivalent thermal node of the metering chip were collected.

[0048] In some specific implementations, an intermittent acquisition strategy is adopted during the identification process in order to minimize the impact of the identification process on the measurement accuracy.

[0049] The intermittent acquisition strategy includes: (1) When the unknown communication module switches its working state (such as from standby state to transmission state), the real-time continuous acquisition mode is triggered; that is, the power consumption of the unknown communication module and the real-time temperature of the corresponding metering chip equivalent thermal node are collected in real time.

[0050] (2) When the duration of the unknown communication module maintaining the same working state reaches the preset threshold duration (e.g., 3-20 minutes), the data acquisition operation is temporarily suspended to reduce the load.

[0051] Secondly, based on the currently collected real-time power consumption and corresponding real-time temperature, the recursive least squares (RLS) method is used to update the model of the thermodynamic dynamic system to be identified online until the model converges, at which point the data acquisition operation stops.

[0052] In some specific implementations, the general process of using recursive least squares (RLS) to update the model of the thermodynamic dynamic system to be identified online is as follows: (1) Let the parameter vector to be identified be θ = [τ_c, γ] Construct the measurement matrix; (2) Execute the recursive least squares (RLS) update equation, data preprocessing → RLS recursive update (prior error, Kalman gain, parameters, covariance) → reverse calculation of physical parameters; (3) Comprehensively judge convergence (parameter change rate, RMSE, covariance trace, duration). Only when all four conditions are met can it be judged as convergence; if it does not converge, continue to collect data.

[0053] For example, the specific processes of (1) and (2) above are as follows: (1) Model: ΔT_c (k)=a ΔT_c (k 1)+b Pmod(k 1); RLS standard form: y(k) = (k 1) θ; Where y(k) = ΔT_c(k) is the current temperature rise; (k 1)= θ = temperature rise + power consumption at the previous moment; , which are the parameters to be identified.

[0054] (2) Perform the recursive least squares (RLS) update equation: initialization; make (0)= P(0) = 1000 I,λ=0.98; The process is repeated every second (5 steps in total, ①-⑤). ①Prediction error e(k) (measured) predict): e(k)=y(k) (k 1) (k 1); ② Kalman gain (correction strength): K(k) = P(k) 1) (k 1) / λ+ (k 1)P(k 1) (k 1); ③ Parameter update (correction in the opposite direction of error): (k)= (k 1)+K(k) e(k); ④ Covariance update (reducing uncertainty): P(k) = 1 / λ[P(k) 1) K(k) (k 1)P(k 1)]; ⑤ Back-engineer physical parameters (executed after convergence): τ_c = 1ln / ( ),γ= τ_c.

[0055] After each data acquisition, the model of the thermodynamic dynamic system to be identified is updated online based on the real-time power consumption and corresponding real-time temperature, gradually approximating the actual system parameters (i.e., thermal characteristic parameters). Since the thermal time constant of the communication module is usually in the range of tens of seconds to minutes, collecting 100 to 200 data points (with a sampling period of 1 second) is sufficient to obtain a relatively stable parameter estimate, and the identification process takes only about 2 to 3 minutes.

[0056] In some specific implementations, residual analysis is used to evaluate the convergence of the model of the thermodynamic dynamic system to be identified in order to assess the confidence level of the identification results.

[0057] Specifically, the residual analysis includes: (1) Calculation of root mean square error (RMSE); If the root mean square error calculated from the predicted temperature of the equivalent thermal node of the metering chip output by the established model and its corresponding measured temperature is lower than the preset error threshold, the converged model identification is deemed valid; otherwise, the converged model identification is deemed invalid, and the adaptive thermal feature identification process is restarted.

[0058] Here, the root mean square error (RMSE) is used to assess the absolute deviation between the predicted and actual values. Only when the deviation is below the error threshold is the model considered valid.

[0059] Preferably, before determining that the converged model identification is valid, the process further includes: (2) Calculation of goodness-of-fit R²; The goodness of fit R² is calculated based on the predicted temperature of the equivalent thermal node of the metering chip output by the established model and its corresponding measured temperature. If the calculated goodness of fit R² is greater than or equal to the preset lower limit threshold of goodness of fit, the established model is deemed to have converged and is valid.

[0060] For example, the preset goodness-of-fit lower limit threshold is 0.85.

[0061] In other words, the model's identification results are considered highly confident and effective only if the root mean square error (RMSE) is acceptable and the goodness of fit (R²) meets the standard. If the RMSE is acceptable but the goodness of fit (R²) is too low, it means that the model can guarantee single-point error but cannot reproduce dynamic changes, resulting in poor dynamic identification performance.

[0062] Here, the root mean square error (RMSE) of the residuals meeting the error threshold requirement is used as the core judgment condition for residual analysis, supplemented by the goodness of fit (R²) meeting the index requirement as a constraint condition, to construct a dual identification effectiveness evaluation criterion, ensuring the accuracy of the identification results of the thermodynamic dynamic system model to be identified.

[0063] S5: Based on the converged and validly identified thermodynamic dynamic system model to be identified, obtain the thermal characteristic parameters corresponding to the unknown communication module. That is, the parameter vector to be identified mentioned above θ=[τ_c, γ]. .

[0064] S6: Load the thermal characteristic parameters (thermal power consumption parameters, thermal time constant, thermal coupling coefficient, and additional error model parameters) corresponding to the unknown communication module into the self-heating compensation model of the main control unit of the electricity meter.

[0065] For example, a thermal characteristic parameter package is generated based on the thermodynamic dynamic system model to be identified, and then written into RAM for immediate effect, while simultaneously being written into Flash for persistence (preferably marked as "local learning").

[0066] When the base meter identifies a communication module type not included in the thermal characteristic parameter table, directly using the default compensation parameters cannot effectively guarantee metering accuracy. This embodiment, through the adaptive thermal characteristic identification process, can adaptively identify the thermal characteristic parameters of unknown communication modules during normal operation of the energy meter, enabling the base meter to autonomously learn the thermal characteristics of unknown modules and dynamically adjust compensation parameters. Furthermore, the implementation of the adaptive thermal characteristic identification process also satisfies the following engineering constraints: (1) Uninterrupted metering: The identification process runs as a background task and does not affect the accumulation calculation of electrical energy.

[0067] (2) No special testing equipment is required: identification can be completed using the built-in sensors (temperature, current, voltage) of the electricity meter.

[0068] (3) It has adaptive convergence characteristics: After multiple rounds of data collection and calculation, the model parameters gradually converge to the range near the true value.

[0069] Please see Figure 2 Another embodiment of the present invention further extends the above embodiments and can achieve compensated smooth switching based on the hot-plugging status detection of the communication module.

[0070] Combination Figure 2 To understand further, the method for adaptive compensation of measurement accuracy based on the thermal characteristics of a communication module provided in this embodiment also includes: The system monitors the presence of the communication module in real time. When a communication module is unplugged, a gradual attenuation compensation process is executed. When a communication module is connected, a gradual establishment compensation process is executed.

[0071] In some specific implementations, the base station of the electricity meter determines whether the communication module is in place through one, two, or three of the following detection mechanisms.

[0072] (1) Pin level detection mechanism: The detection method is to read the pin status change by MCU GPIO interrupt; the response time is less than 1ms; it has the highest real-time performance and can respond immediately after the plugging and unplugging event is detected; (2) Communication link heartbeat detection mechanism: The detection method is to periodically send query commands to the base table and wait for the response; the response time is 200ms~1000ms; it can effectively distinguish between two states: the communication module is online but communication is abnormal and the communication module is disconnected; (3) Power supply current monitoring mechanism: The detection method is to monitor the current value of the power supply path of the communication module interface; the response time is less than 10ms; it is confirmed through the physical layer and is not affected by protocol layer faults.

[0073] In this embodiment, the gradual attenuation compensation process when the communication module is unplugged is mainly based on the thermal state of the communication module before it is unplugged and the preset attenuation time constant. The contribution of the communication module in the gradual attenuation self-heating compensation model avoids parameter jumps and ensures metering continuity through simulation and smooth transition.

[0074] The gradual attenuation compensation process specifically includes the following steps: (1) When the communication module is unplugged, the compensation value currently output by the self-heating compensation model of the main control unit of the electricity meter is obtained and marked as the initial heat contribution compensation value C_mod(t0) when the communication module is unplugged; (2) Based on the initial thermal contribution compensation value C_mod(t0) and the preset attenuation time constant τ_decay, the attenuation compensation value C_mod(t) at time t after the communication module is unplugged is calculated in real time using the exponential attenuation algorithm until the calculated attenuation compensation value C_mod(t) is zero. The exponential decay algorithm is as follows: C_mod(t) = C_mod(t0)·e^{-t / τ_decay}; Where e is the natural constant, approximately equal to 2.718281828; the decay time constant τ_decay ranges from 30 to 90 seconds.

[0075] (3) Based on the attenuation compensation value at time t after the communication module is unplugged, calculated in real time, the compensation value output by the self-heating compensation model at the corresponding time is compensated.

[0076] In this embodiment, the progressive compensation process after the communication module is inserted can gradually increase the compensation value from zero to the target compensation value C_target under the steady state of the communication module, so as to achieve a smooth transition of the compensation value and ensure the continuity of measurement.

[0077] The gradual establishment of the compensation process specifically includes the following steps: (1) When a communication module access event is detected, the compensation value currently output by the self-heating compensation model of the main control unit of the electricity meter is obtained and marked as the target heat contribution compensation value C_target after the communication module is accessed; (2) Based on the target thermal contribution compensation value C_target, the preset establishment time constant τ_build and the thermal time constant τ_mod of the communication module, the establishment compensation value at time t after the communication module is connected is calculated in real time by the exponential establishment algorithm until time t is equal to the preset steady-state time threshold. The algorithm for establishing the index is as follows: C_mod(t) = C_target·(1 - e^{-t / τ_build}) (when t<T_threshold); C_mod(t) = C_target (when t ≥ T_threshold); wherein, e is the natural constant, approximately equal to 2.718281828; T_threshold is the steady-state time threshold, which is the time threshold for reaching steady state; the preferred value of the establishment time constant τ_build is 0.5 to 1 time of the thermal time constant τ_mod of the communication module.

[0078] (3) According to the real-time calculated establishment compensation value at time t after the communication module is accessed, compensate the compensation value output by the self-heating compensation model at the corresponding time.

[0079] Please refer to Figure 2 , another embodiment of the present invention is further expanded on the basis of the above embodiments. For the situation where there are multiple independent heat sources inside the electric energy meter, compensation is performed by constructing a multi-source fusion compensation model.

[0080] in combination with Figure 2 for understanding, the method for adaptively compensating metering accuracy through thermal characteristics of a communication module provided in this embodiment further includes: if there are two or more independent heat sources inside the electric energy meter, the thermal compensation values of each independent heat source are superimposed to obtain the total thermal compensation value of the electric energy meter.

[0081] independent heat sources include but are not limited to: sampling resistors, metering chips and communication modules.

[0082] in some specific implementation modes, after modeling each independent heat source separately, a multi-source fusion compensation model is constructed.

[0083] the multi-source fusion compensation model is: C_total = C_shunt + C_metrology + C_module; wherein: C_shunt is the Joule heat compensation value of the sampling resistor, which is proportional to the square of the current, and the error has a linear relationship with ΔT_shunt; C_metrology is the self-heating compensation value of the metering chip, whose error has a non-linear relationship (quadratic curve) with ΔT_met; C_module is the thermal contribution compensation value of the communication module, which is jointly determined by the thermal characteristic parameters of the currently activated communication module and the real-time working state.

[0084] the acquisition mode of the real-time working state of the currently activated communication module is: The base table queries the module's working status in real time through the currently active communication interface, and the query frequency is adaptively adjusted. Stable state (standby or continuous sending and receiving): query cycle 5 seconds.

[0085] State transition event (launch start / end): Update immediately.

[0086] Since the different heat sources inside the electricity meter have different mechanisms of influence on metering error, this embodiment adopts the method of modeling them separately and then superimposing them to obtain the total heat compensation value. This method can accurately characterize the independent temperature rise contribution and error characteristics of different heat sources, avoid the coupling deviation caused by a single centralized thermal model, and improve the accuracy of heat compensation in scenarios with wide operating conditions and dynamic changes of multiple heat sources.

[0087] Please see Figure 2 Another embodiment of the present invention further extends the above embodiments and enables OTA remote upgrade of the thermal characteristic parameter table stored locally in the electricity meter.

[0088] Combination Figure 2 To understand further, the method for adaptive compensation of measurement accuracy based on the thermal characteristics of a communication module provided in this embodiment also includes: Perform OTA remote upgrades on the thermal characteristic parameter table stored locally on the electricity meter.

[0089] Specifically, when a new communication module is launched, or when the thermal characteristic parameters of an existing communication module are updated, the master station pushes a thermal characteristic parameter upgrade package to the lower-level energy meter via 4G or Ethernet; the thermal characteristic parameter upgrade package encapsulates the thermal characteristic parameters corresponding to the type identifier of the new communication module, and / or the new thermal characteristic parameters corresponding to the type identifier of the existing communication module. After receiving the thermal characteristic parameter upgrade package from the master station remotely, the electricity meter updates the locally stored thermal characteristic parameter table according to the thermal characteristic parameter upgrade package.

[0090] With the continuous evolution of communication module types and specifications, this embodiment can realize OTA remote upgrade of the internal thermal characteristic parameter table of the electricity meter without the need for on-site operation and maintenance upgrade work, effectively saving manpower and material costs and improving the convenience of operation and maintenance.

[0091] In some specific implementations, the thermal characteristic parameter upgrade package is packaged according to a preset format, including a module type code, version number, checksum, and signature. It is then transmitted via the communication channel (wireless public network or power line carrier) of the electricity information collection system, encrypted with AES-128, to the target electricity meter for secure transmission. Upon receiving the thermal characteristic parameter upgrade package, the electricity meter performs integrity verification and signature authentication. After successful authentication, the package is written to the thermal characteristic database area of ​​non-volatile memory, updating the thermal characteristic parameter table. After the upgrade is completed, the base meter is reset or hot-rebooted to load the updated thermal characteristic parameter table, which is then used for compensation the next time the communication module is inserted.

[0092] Another embodiment of the present invention provides an electricity meter based on any of the above embodiments.

[0093] The electricity meter provided in this embodiment includes a main control unit and a computer-readable storage medium; the computer-readable storage medium stores a computer program; when the computer program is executed by the main control unit, it can implement the method for adaptive compensation of metering accuracy based on the thermal characteristics of the communication module as described in any of the above embodiments. The specific steps of the method have been described in detail in the corresponding embodiments and will not be repeated here. Please refer to the description in the above embodiments for details.

[0094] Those skilled in the art will understand that all or part of the processes in the above technical solutions can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the methods described above. After being executed by a processor, the program can also achieve the beneficial effects of the corresponding methods.

[0095] The storage medium can be a disk, optical disc, read-only memory (ROM), or random access memory (RAM), etc.

[0096] In summary, the method and energy meter based on adaptive compensation of metering accuracy using the thermal characteristics of communication modules provided by this invention completely solve the problem of metering accuracy degradation caused by hot-swapping of communication modules in multi-mode communication energy meters, eliminating the need for manual recalibration after module replacement. Through dynamic loading of thermal characteristic parameters and a gradual smooth transition mechanism, it achieves adaptive and accurate compensation covering all operating conditions, ensuring continuous and stable metering data throughout the hot-swapping process. It possesses adaptive thermal characteristic identification capabilities for unknown communication modules, completing self-learning and establishing effective compensation within minutes. It supports OTA remote upgrades of thermal characteristic parameter upgrade packages, eliminating the need for on-site calibration and upgrade procedures, while ensuring compatibility with new communication modules.

[0097] Although preferred embodiments of the invention have been described, those skilled in the art, upon understanding the basic inventive concept, can make other changes and modifications to the embodiments. Therefore, the appended claims are intended to cover the preferred embodiments and all equivalent modifications falling within the scope of protection defined by the claims and their equivalents. Clearly, those skilled in the art can make various alterations and variations to the invention without departing from its spirit and scope. If such modifications and variations fall within the scope of protection defined by the claims and their equivalents, the invention also intends to include them.

[0098] It should be noted that any reference signs placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware.

[0099] In this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "multiple" means two or more, unless otherwise explicitly specified. The term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone.

[0100] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0101] In this specification, the use of terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refers to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. The illustrative expressions of the above terms in this specification should not be construed as necessarily referring to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0102] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for adaptive compensation of measurement accuracy based on the thermal characteristics of a communication module, characterized in that, include: Pre-stored thermal characteristic parameter table; The thermal characteristic parameter table records the thermal characteristic parameters corresponding to each type of communication module; The thermal characteristic parameters include thermal power consumption parameters, thermal time constant, thermal coupling coefficient, and additional error model parameters; The thermal feature parameter table is queried based on the type identifier of the currently accessed communication module. If no matching thermal feature parameter is found, the adaptive thermal feature identification process is initiated. The adaptive thermal feature identification process includes: The entire system consisting of the electricity meter and the unknown communication module is considered as a thermodynamic dynamic system to be identified, and a first-order inertial hysteresis model is selected for modeling; the first-order inertial hysteresis model is as follows: τ_c·dT_c / dt = - (T_c - T_env) + γ·P_mod(t); Where τ_c is the thermal time constant; dT_c / dt is the temperature change rate of the equivalent thermal node of the metering chip; T_c is the predicted temperature of the equivalent thermal node of the metering chip output by the model; T_env is the ambient reference temperature; γ is the thermal coupling coefficient; and P_mod(t) is the real-time power consumption of the unknown communication module input by the model. Real-time power consumption of the unknown communication module under different working conditions and real-time temperature of the corresponding equivalent thermal node of the metering chip were collected respectively. Based on the real-time power consumption and corresponding real-time temperature collected at the moment, the model is updated online using the recursive least squares (RLS) method until the model converges and the data collection operation is stopped. Based on the converged established model, obtain the thermal characteristic parameters corresponding to the unknown communication module; The acquired thermal characteristic parameters are loaded into the self-heating compensation model of the main control unit of the electricity meter.

2. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 1, characterized in that, An intermittent acquisition strategy was adopted to collect the real-time power consumption of the unknown communication module under different working conditions and the real-time temperature of the corresponding equivalent thermal node of the metering chip. The intermittent acquisition strategy includes: When the unknown communication module switches its working state, the real-time continuous acquisition mode is triggered; When the duration for which an unknown communication module maintains the same working state reaches a preset threshold, the data acquisition operation is temporarily suspended.

3. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 1, characterized in that, Prior to obtaining the thermal characteristic parameters corresponding to the unknown communication module, the process also includes: The converged model is evaluated by residual analysis. If the root mean square error calculated from the predicted temperature of the equivalent thermal node of the metering chip output by the model and its corresponding measured temperature is lower than the preset error threshold, the converged model is deemed to be valid and the process of obtaining the thermal feature parameters corresponding to the unknown communication module is executed. Otherwise, the converged model is deemed to be invalid and the adaptive thermal feature identification process is restarted.

4. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 3, characterized in that, If the root mean square error calculated from the predicted temperature of the equivalent thermal node of the metering chip output by the established model and its corresponding measured temperature is lower than a preset error threshold, specifically including: If the root mean square error calculated from the predicted temperature of the equivalent thermal node of the metering chip output by the established model and its corresponding measured temperature is lower than the preset error threshold, and the goodness of fit is greater than or equal to the preset lower limit threshold of goodness of fit, then the established model is deemed to have converged and is valid.

5. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 1, characterized in that, After querying the thermal characteristic parameter table based on the type identifier of the currently accessed communication module, the method further includes: If a matching thermal characteristic parameter is found, the matched thermal characteristic parameter will be loaded into the self-heating compensation model of the main control unit of the electricity meter.

6. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 1, characterized in that, Also includes: When a communication module disconnection event is detected, the compensation value currently output by the self-heating compensation model of the main control unit of the electricity meter is obtained and marked as the initial heat contribution compensation value when the communication module is disconnected. Based on the initial thermal contribution compensation value and the preset attenuation time constant, the attenuation compensation value at time t after the communication module is unplugged is calculated in real time using an exponential attenuation algorithm until the calculated attenuation compensation value is zero. Based on the attenuation compensation value at time t after the communication module is unplugged, calculated in real time, the compensation value output by the self-heating compensation model at the corresponding time is compensated.

7. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 1, characterized in that, Also includes: When a communication module access event is detected, the compensation value currently output by the self-heating compensation model of the main control unit of the electricity meter is obtained and marked as the target heat contribution compensation value after the communication module access; Based on the target thermal contribution compensation value, the preset establishment time constant, and the thermal time constant of the communication module, the establishment compensation value at time t after the communication module is connected is calculated in real time using an exponential establishment algorithm until time t equals the preset steady-state time threshold. Based on the established compensation value at time t after the communication module is connected, calculated in real time, the compensation value output by the self-heating compensation model at the corresponding time is compensated.

8. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 1, characterized in that, Also includes: If there are two or more independent heat sources inside the electricity meter, the heat compensation values ​​of each independent heat source are added together to obtain the total heat compensation value of the electricity meter. The independent heat source is a sampling resistor, a metering chip, or a communication module.

9. The method for adaptive compensation of measurement accuracy based on thermal characteristics of a communication module as described in claim 1, characterized in that, Also includes: The electricity meter remotely receives the thermal characteristic parameter upgrade package sent by the master station. The thermal characteristic parameter upgrade package encapsulates the thermal characteristic parameters corresponding to the type identifier of the new communication module, and / or the new thermal characteristic parameters corresponding to the type identifier of the existing communication module. The electricity meter updates the locally stored thermal characteristic parameter table according to the thermal characteristic parameter upgrade package.

10. An electricity meter, characterized in that, It includes a main control unit and a computer-readable storage medium; the computer-readable storage medium stores a computer program; when the computer program is executed by the main control unit, it can implement the method for adaptive compensation of measurement accuracy of thermal characteristics of the communication module as described in any one of claims 1 to 9.

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