CN-121973668-A - Intelligent operation and maintenance management method, system and medium for battery exchange cabinet

CN121973668ACN 121973668 ACN121973668 ACN 121973668ACN-121973668-A

Abstract

The invention relates to the technical field of intelligent operation and maintenance of charging and replacing infrastructure, and discloses an intelligent operation and maintenance management method, system and medium of a power-replacing cabinet. According to the technical scheme, through collecting multidimensional operation data of the battery changing cabinet and constructing a temperature grading monitoring, demand prediction and risk fusion analysis model, the problems that the traditional operation and maintenance rely on manual inspection and passive response and lack of real-time safety monitoring and intelligent early warning are solved, and the charging safety dynamic management and control, the resource allocation optimization and the operation efficiency improvement are realized.

Inventors

HUANG JIANTA
Zhu Huimo
SU TIANQING
LIU ZHAOFENG

Assignees

深圳即刻换电数字信息有限公司

Dates

Publication Date: 20260505
Application Date: 20260303

Claims (10)

1. The intelligent operation and maintenance management method for the battery exchange cabinet is characterized by comprising the following steps of: The method comprises the steps of collecting multidimensional operation data of each battery changing cabinet in a battery changing cabinet network, wherein the multidimensional operation data comprise battery temperature data, charger operation parameters, user battery changing behavior records, equipment load data and environment monitoring data, and the user battery changing behavior records and the equipment load data are obtained through state inquiry in a battery changing cabinet management system and operation logs of a battery filling system; inputting the battery temperature data and the charger operation parameters into a preset temperature grading monitoring model, outputting a thermal runaway risk assessment grade, and generating a charging control instruction matched with the thermal runaway risk assessment grade; According to the user power change behavior record and the equipment load data, a time sequence prediction model is utilized for processing, and a power change demand prediction result and a load pressure prediction result of each power change cabinet in the power change cabinet network in a future preset period are generated; according to the environment monitoring data and the equipment load data, calculating the comprehensive operation risk level of each power conversion cabinet in the power conversion cabinet network under the severe weather condition through a risk evaluation rule base; And according to the thermal runaway risk assessment level, the charging control instruction, the power change demand prediction result, the load pressure prediction result and the comprehensive operation risk level, performing fusion analysis through a strategy generation engine, and outputting an operation and maintenance strategy aiming at a corresponding power change cabinet in a power change cabinet network, wherein the operation and maintenance strategy comprises a charging power regulation scheme, a standby battery scheduling scheme and a device capacity expansion early warning scheme, and the operation and maintenance strategy is used for displaying and executing driving on an interactive interface of a power change cabinet management system.
2. The intelligent operation and maintenance management method of a battery-changing cabinet according to claim 1, wherein the temperature grading monitoring model divides a plurality of discrete risk assessment grades including normal, early warning, alarming and emergency cutting through real-time coupling of an instantaneous value and a change trend of the battery temperature data and a real-time load rate in the charger operation parameters.
3. The intelligent operation and maintenance management method of a battery cabinet according to claim 2, wherein the charging control command matched with the alarm level includes a step-down power command, and the charging control command matched with the emergency shutdown level is an immediate power-off command.
4. The battery cabinet intelligent operation and maintenance management method according to claim 2, wherein the quantification of the change trend is based on a weighted combination of standard deviation and linear fit slope of the battery temperature data within a sliding time window.
5. The intelligent operation and maintenance management method of a battery exchange cabinet according to claim 1, wherein when calculating the comprehensive operation risk level, the risk assessment rule base performs association mapping on a weather early warning level in the environment monitoring data and the equipment load data.
6. The intelligent operation and maintenance management method of a battery exchange cabinet according to claim 1, wherein the policy generation engine adopts a fuzzy reasoning-based decision fusion method to carry out fusion analysis on the thermal runaway risk assessment level, the battery exchange demand prediction result, the load pressure prediction result and the comprehensive operation risk level.
7. The intelligent operation and maintenance management method of a battery cabinet according to claim 5, wherein the calculation of the comprehensive operation risk level is based on a dynamic environment load risk index, and the calculation formula of the dynamic environment load risk index is as follows: Wherein, the Representing the dynamic environmental load risk index; The weather severity score representing comprehensive judgment according to the wind speed, the rainfall intensity and the lightning early warning information in the environment monitoring data is a preset normalized value; representing real-time active power in the device load data; Representing the preset maximum allowable active power of the power conversion cabinet; representing an ambient temperature in the ambient monitoring data; Representing a preset environmental temperature risk threshold; 、 And Parameters are adjusted for a preset model, and 。
8. The intelligent operation and maintenance management method of a battery cabinet according to claim 3, wherein each stage of adjustment power value corresponding to the step-down power instruction Is determined by the following formula: Wherein, the Represents the first Target charging power after step adjustment; Representing a base rated charge power in the charger operating parameters; representing the current step-down number of steps; representative and the first The preset attenuation coefficient corresponding to the step ladder; Representative of the first A step of evaluating an average rate of change of the battery temperature data over a time window; Representative of the first The step evaluates the average efficiency of the charger operation parameters in a time window; representing the nominal efficiency of the charger.
9. An intelligent operation and maintenance management system for a battery exchange cabinet, which is characterized by comprising: The system comprises an acquisition module, a battery charging cabinet management system, a battery charging filling system, a battery charging cabinet management system, a battery charging management system and a battery charging management system, wherein the battery charging management system is used for acquiring multi-dimensional operation data of each battery charging cabinet in the battery charging cabinet network, the multi-dimensional operation data comprises battery temperature data, charger operation parameters, user charging behavior records, equipment load data and environment monitoring data; The generation module is used for inputting the battery temperature data and the charger operation parameters into a preset temperature grading monitoring model, outputting a thermal runaway risk assessment level and generating a charging control instruction matched with the thermal runaway risk assessment level; the prediction module is used for recording the power change behavior of the user and the equipment load data, processing the data by using a time sequence prediction model and generating a power change demand prediction result and a load pressure prediction result of each power change cabinet in the power change cabinet network within a preset future period; the calculation module is used for calculating the comprehensive operation risk level of each power conversion cabinet in the power conversion cabinet network under the severe weather condition through a risk evaluation rule base according to the environment monitoring data and the equipment load data; The output module is used for carrying out fusion analysis through the strategy generation engine according to the thermal runaway risk assessment level, the charging control instruction, the power change demand prediction result, the load pressure prediction result and the comprehensive operation risk level, and outputting an operation and maintenance strategy aiming at the corresponding power change cabinet in the power change cabinet network, wherein the operation and maintenance strategy comprises a charging power regulation scheme, a standby battery scheduling scheme and a device capacity expansion early warning scheme, and the operation and maintenance strategy is used for displaying and executing driving on an interactive interface of a power change cabinet management system.
10. A computer readable storage medium, wherein at least one computer program is stored in the computer readable storage medium, and when the at least one computer program is executed by a processor, the intelligent operation and maintenance management method of the power conversion cabinet according to any one of claims 1 to 8 is implemented.

Description

Intelligent operation and maintenance management method, system and medium for battery exchange cabinet Technical Field The invention relates to the technical field of intelligent operation and maintenance of charging and replacing infrastructure, in particular to an intelligent operation and maintenance management method, system and medium of a power-replacing cabinet. Background As the holding amount of electric bicycles continues to rise, intelligent power conversion cabinets are rapidly popularized in cities as a key infrastructure for solving the charging difficulty and potential safety hazards. However, the operation and maintenance management of the existing power conversion cabinet generally depends on manual periodic inspection and passive fault response modes, and lacks a systematic intelligent monitoring and early warning mechanism. In the aspect of battery charging safety management, a real-time grading monitoring system of the temperature of a charger and a battery cannot be established, and when the temperature is abnormally increased, a charging strategy cannot be dynamically adjusted or a power supply cannot be timely cut off, so that the risk of thermal runaway is increased, and a fire accident is easily caused. Meanwhile, the prior art has insufficient mining depth for the operation data of the battery-changing cabinet, is difficult to comprehensively analyze based on environmental factors such as user battery-changing behaviors, equipment load, bad weather and the like, cannot actively predict equipment capacity expansion requirements and optimize resource allocation, can be passively processed after user complaints, and seriously affects operation efficiency and service quality. The technical bottlenecks severely restrict the safe and stable operation and the large-scale development of the power conversion cabinet network. Accordingly, there is a need to provide a solution to the above-mentioned problems. Disclosure of Invention In order to solve the technical problems, the invention provides an intelligent operation and maintenance management method, system and medium for a battery-changing cabinet. In a first aspect, the invention provides an intelligent operation and maintenance management method for a battery exchange cabinet, which has the following technical scheme: The method comprises the steps of collecting multidimensional operation data of each battery changing cabinet in a battery changing cabinet network, wherein the multidimensional operation data comprise battery temperature data, charger operation parameters, user battery changing behavior records, equipment load data and environment monitoring data, and the user battery changing behavior records and the equipment load data are obtained through state inquiry in a battery changing cabinet management system and operation logs of a battery filling system; inputting the battery temperature data and the charger operation parameters into a preset temperature grading monitoring model, outputting a thermal runaway risk assessment grade, and generating a charging control instruction matched with the thermal runaway risk assessment grade; According to the user power change behavior record and the equipment load data, a time sequence prediction model is utilized for processing, and a power change demand prediction result and a load pressure prediction result of each power change cabinet in the power change cabinet network in a future preset period are generated; according to the environment monitoring data and the equipment load data, calculating the comprehensive operation risk level of each power conversion cabinet in the power conversion cabinet network under the severe weather condition through a risk evaluation rule base; And according to the thermal runaway risk assessment level, the charging control instruction, the power change demand prediction result, the load pressure prediction result and the comprehensive operation risk level, performing fusion analysis through a strategy generation engine, and outputting an operation and maintenance strategy aiming at a corresponding power change cabinet in a power change cabinet network, wherein the operation and maintenance strategy comprises a charging power regulation scheme, a standby battery scheduling scheme and a device capacity expansion early warning scheme, and the operation and maintenance strategy is used for displaying and executing driving on an interactive interface of a power change cabinet management system. In an alternative mode, the temperature grading monitoring model divides a plurality of discrete risk assessment grades including normal, early warning, alarming and emergency cutting through real-time coupling of the instantaneous value and the change trend of the battery temperature data and the real-time load rate in the charger operation parameters. In an alternative manner, the charge control command matched to the alarm level includes a step-down command, an