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CN-122017617-A - Storage battery remote monitoring method and system based on 5G communication

CN122017617ACN 122017617 ACN122017617 ACN 122017617ACN-122017617-A

Abstract

The application relates to the technical field of battery fault monitoring, in particular to a storage battery remote monitoring method and system based on 5G communication, wherein the method comprises the steps of collecting electric parameters of a storage battery in a charging and discharging process in real time based on 5G communication; the method comprises the steps of carrying out smoothing treatment on electric parameters at each moment, analyzing numerical value differences of the electric parameters before and after the smoothing treatment to determine first characteristic values of the electric parameters at each moment, identifying each change phase of the electric parameters at the current moment and historical local moments thereof through the first characteristic values, evaluating overall distribution and evolution trend of data length of each change phase, calculating optimization phase length of a storage battery, correcting smoothing coefficients of an EMA algorithm, predicting the electric parameters at the current moment and the historical local moments thereof by utilizing the corrected EMA algorithm, and remotely monitoring working states of the storage battery according to the deviation of the predicted electric parameters and actual electric parameters. Thereby improving the accuracy of remote monitoring of the storage battery.

Inventors

  • GENG YONG
  • ZHU BINGKUN
  • WANG KEMIN
  • HU ZHOU
  • HU BIAO

Assignees

  • 深圳市泰科通信科技有限公司

Dates

Publication Date
20260512
Application Date
20260402

Claims (10)

  1. 1. The remote monitoring method for the storage battery based on the 5G communication is characterized by comprising the following steps of: Acquiring electric parameters of the storage battery in the charging and discharging processes in real time based on 5G communication; smoothing the electric parameters at each moment, analyzing the numerical value difference of the electric parameters before and after the smoothing, and determining a first characteristic value of the electric parameters at each moment; Evaluating the overall distribution and evolution trend of the data length of each change phase, calculating the optimized phase length of the storage battery, and correcting the smoothing coefficient of the EMA algorithm; and predicting the electric parameters in the current moment and the historical local moment thereof by utilizing the corrected EMA algorithm, and remotely monitoring the working state of the storage battery according to the deviation between the predicted electric parameters and the actual electric parameters.
  2. 2. The battery remote monitoring method based on 5G communication of claim 1, wherein the electrical parameter comprises at least one of a voltage, a current, and an SOC of the battery.
  3. 3. The battery remote monitoring method based on 5G communication according to claim 1, wherein the determination of the first characteristic value includes: Calculating the difference of the electric parameters of each moment and the adjacent moment before and after the smoothing treatment, and marking the difference as a second difference; And determining the first characteristic value based on the first difference and the second difference, wherein the first characteristic value is positively correlated with both the first difference and the second difference.
  4. 4. The method for remote monitoring of a battery based on 5G communication according to claim 1, wherein the identifying each phase of change of the electrical parameter in the current time and the historical local time thereof by the first characteristic value comprises: And detecting each peak value in the time sequence formed by the first characteristic values of the current moment and the historical local moment thereof, and taking the corresponding time period between adjacent peak values as each change stage of the electrical parameter.
  5. 5. The method for remote monitoring of a battery based on 5G communication according to claim 1, wherein the calculating the optimization phase length of the battery comprises: Forward fusion is carried out on the data lengths of all the change phases of the electric parameters at the current moment and the historical local moment of the current moment, and linear fitting is carried out on the data lengths of all the change phases of the electric parameters, so that the slope of a fitting straight line is obtained; And calculating the optimization stage length of the storage battery based on the forward fusion result and the slope.
  6. 6. The battery remote monitoring method based on 5G communication according to claim 5, wherein the calculation of the optimization stage length of the battery includes: and obtaining an addition value of the forward fusion result and the absolute value of the slope, rounding the addition value, and determining the optimization stage length of the storage battery by utilizing the rounding result.
  7. 7. The method for remote monitoring of a battery based on 5G communication according to claim 1, wherein the modified EMA algorithm has a smoothing coefficient expressed as: In the formula (I), in the formula (II), And (3) modifying the smoothing coefficient for the EMA algorithm, wherein L is the optimization stage length of the storage battery.
  8. 8. The method for remote monitoring of a battery based on 5G communication according to claim 1, wherein a difference between a predicted electrical parameter and an actual electrical parameter is calculated and is noted as a third difference, and the difference is a ratio of the third difference to the actual electrical parameter.
  9. 9. The method for remotely monitoring the storage battery based on 5G communication according to claim 1, wherein the remotely monitoring the operating state of the storage battery comprises: if the deviation of the existing electric parameters is larger than a preset threshold value, judging that the storage battery has faults, otherwise, judging that the storage battery works normally.
  10. 10. Battery remote monitoring system based on 5G communication, comprising a memory, a processor and a computer program stored in the memory and running on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1-9 when executing the computer program.

Description

Storage battery remote monitoring method and system based on 5G communication Technical Field The application relates to the technical field of battery fault monitoring, in particular to a storage battery remote monitoring method and system based on 5G communication. Background The storage battery is an energy storage device for bidirectionally converting chemical energy and electric energy, and consists of positive and negative polar plates, electrolyte and a diaphragm, and is silent and energy-storage at ordinary times, once alternating current is lost for station use, direct current electric energy is instantly released, and the storage battery is continuously used for key loads such as relay protection, breaker tripping, communication transmission, emergency lighting and the like. After the 5G communication module is embedded, the electric parameters of the storage battery are uploaded to the cloud end with millisecond-level time delay, so that remote centralized management of the storage battery is realized. In periodic charge and discharge inspection of the storage battery, the fault state of the battery can be dynamically obtained through prediction of the electrical parameters, so that potential faults or performance degradation problems can be found in time. Because of the continuity of the discharge and charge states of the storage battery, the data with continuity and trend are conventionally predicted by adopting an EMA algorithm (Exponential Moving Average). However, due to the attenuation of the battery, the electrical parameters of each discharging and each charging of the battery are different, so that the electrical parameters of the next moment cannot be accurately predicted by the traditional EMA algorithm through the smooth coefficient calculated by the fixed equivalent window, the deviation between the predicted result and the actual measured result affects the subsequent judgment of the failure of the battery, and the failure recognition precision of the battery is low. Disclosure of Invention In order to solve the technical problems, the application aims to provide a storage battery remote monitoring method and system based on 5G communication, and the adopted technical scheme is as follows: in a first aspect, an embodiment of the present application provides a method for remotely monitoring a battery based on 5G communication, including the steps of: Acquiring electric parameters of the storage battery in the charging and discharging processes in real time based on 5G communication; smoothing the electric parameters at each moment, analyzing the numerical value difference of the electric parameters before and after the smoothing, and determining a first characteristic value of the electric parameters at each moment; Evaluating the overall distribution and evolution trend of the data length of each change phase, calculating the optimized phase length of the storage battery, and correcting the smoothing coefficient of the EMA algorithm; and predicting the electric parameters in the current moment and the historical local moment thereof by utilizing the corrected EMA algorithm, and remotely monitoring the working state of the storage battery according to the deviation between the predicted electric parameters and the actual electric parameters. In one embodiment, the electrical parameter includes at least one of a voltage, a current, and an SOC of the battery. In one embodiment, the determining of the first characteristic value includes: Calculating the difference of the electric parameters of each moment and the adjacent moment before and after the smoothing treatment, and marking the difference as a second difference; And determining the first characteristic value based on the first difference and the second difference, wherein the first characteristic value is positively correlated with both the first difference and the second difference. In one embodiment, the identifying, by the first characteristic value, each phase of change of the electrical parameter in the current time and the historical local time thereof includes: And detecting each peak value in the time sequence formed by the first characteristic values of the current moment and the historical local moment thereof, and taking the corresponding time period between adjacent peak values as each change stage of the electrical parameter. In one embodiment, the calculating the optimized phase length of the battery includes: Forward fusion is carried out on the data lengths of all the change phases of the electric parameters at the current moment and the historical local moment of the current moment, and linear fitting is carried out on the data lengths of all the change phases of the electric parameters, so that the slope of a fitting straight line is obtained; And calculating the optimization stage length of the storage battery based on the forward fusion result and the slope. In one embodiment, the calculation of the optimizat