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CN-121973659-A - Electric automobile wisdom management system that charges based on thing networking

CN121973659ACN 121973659 ACN121973659 ACN 121973659ACN-121973659-A

Abstract

The invention relates to an intelligent management system for electric vehicle charging based on the Internet of things, which comprises a sensing layer, a network layer, a platform layer and an application layer, wherein the sensing layer is used for acquiring charging pile running state data, electric vehicle battery state data and power grid load data and comprises a charging pile sensor group, a battery state acquisition unit and a power grid load monitoring unit. By means of a trinity data acquisition and global scheduling mechanism and combining an improved genetic algorithm and a self-adaptive scheduling strategy of a fuzzy neural network, dynamic balanced distribution of charging pile resources in an area is achieved, the LSTM neural network load prediction module is used for accurately predicting the power grid load change trend for 1-24 hours in future, and the charging pile charging power is dynamically adjusted by combining a power grid load balancing sub-algorithm, so that the fluctuation amplitude of the power grid load is reduced, the problems of power grid overload, unstable voltage and the like caused by centralized charging of a large number of electric vehicles are avoided, safe and stable operation of a power distribution network is guaranteed, and the operation and maintenance cost of the power grid is reduced.

Inventors

  • Request for anonymity

Assignees

  • 江西鸿充大数据科技有限公司

Dates

Publication Date
20260505
Application Date
20260327

Claims (10)

  1. 1. Electric automobile wisdom management system that charges based on thing networking, its characterized in that includes perception layer, network layer, platform layer and application layer, each layer communication connection in proper order: The sensing layer is used for acquiring the running state data of the charging pile, the battery state data of the electric automobile and the power grid load data and comprises a charging pile sensor group, a battery state acquisition unit and a power grid load monitoring unit; the network layer is used for realizing data interaction between the perception layer and the platform layer, and comprises a local communication module, a wide area communication module and gateway equipment, and supports multi-protocol data conversion and transmission; the platform layer comprises a data processing module, an intelligent scheduling module, a safety early warning module and a database unit: The data processing module is used for denoising, normalizing and multisource data fusion analysis on the acquired data; The intelligent scheduling module generates a charging control instruction through a self-adaptive scheduling algorithm based on the fusion data, the power grid load predicted value and the user charging demand; The safety early warning module is used for detecting and early warning the safety risk in the charging process in real time based on a preset threshold value and an abnormal feature library; the database unit is used for storing historical data, real-time data, scheduling strategies and early warning rules; The application layer comprises a user interaction terminal, a management monitoring platform and a state display module and is used for realizing charging reservation, progress inquiry, remote management and control and data visualization.
  2. 2. The intelligent management system for charging the electric automobile based on the internet of things according to claim 1, wherein the charging pile sensor group comprises a current sensor, a voltage sensor, a temperature sensor, a humidity sensor, a plugging state sensor and a fault diagnosis sensor, and is used for collecting charging pile output current, output voltage, equipment temperature, ambient humidity, charging gun connection state and fault codes.
  3. 3. The intelligent management system for electric vehicle charging based on the internet of things according to claim 1, wherein the battery state acquisition unit is connected with the electric vehicle through an OBD interface or a wireless communication mode, and acquires battery SOC value, SOH value, battery temperature, single voltage balance and battery pack pressure data.
  4. 4. The intelligent management system for charging the electric automobile based on the internet of things according to claim 1, wherein the local communication module of the network layer adopts a LoRa or ZigBee protocol, the wide area communication module adopts NB-IoT, 5G or ethernet protocol, and the gateway device has functions of protocol conversion, data encryption and breakpoint continuous transmission.
  5. 5. The intelligent management system for charging an electric vehicle based on the internet of things of claim 1, wherein the adaptive scheduling algorithm of the intelligent scheduling module comprises: Grid load balancing sub-algorithm based on improved genetic algorithm, and optimizing charging pile charging power distribution by taking the minimum fluctuation of grid load as a target; and determining the charging service priority by combining the user reservation time, the battery SOC value and the charging pile idle state based on a charging priority ordering sub-algorithm of the fuzzy neural network.
  6. 6. The intelligent management system for electric automobile charging based on the internet of things according to claim 1, wherein the early warning types of the safety early warning module comprise overcurrent early warning, overvoltage early warning, overheat early warning, battery bulge early warning, insulation descent early warning and illegal plug early warning, and the early warning modes comprise local audible and visual warning, APP pushing and management platform popup window prompt.
  7. 7. The intelligent management system for electric vehicle charging based on the internet of things according to claim 1, wherein the platform layer further comprises a load prediction module, and the LSTM neural network model is adopted to predict the power grid load change trend in the future of 1-24 hours based on historical power grid load data, time period characteristics, weather data and charging reservation data.
  8. 8. The intelligent management system for electric vehicle charging based on the Internet of things is characterized in that a user interaction terminal of the application layer is a mobile phone APP or an applet, and supports functions of charging pile query, remote reservation, charging start-stop control, cost payment and early warning information receiving, and a management monitoring platform supports functions of charging pile state monitoring, fault remote diagnosis, scheduling strategy configuration and data statistics analysis.
  9. 9. The intelligent management system for charging electric vehicles based on the internet of things according to claim 1, further comprising an intelligent management method applied to the system according to any one of claims 1 to 8, comprising the following steps: The method comprises the following steps that S1, a sensing layer collects charging pile operation data, electric vehicle battery state data and power grid load data in real time and transmits the data to a platform layer through a network layer; S2, denoising and normalizing the acquired data by a data processing module, and adopting a D-S evidence theory to perform multi-source data fusion and remove abnormal data; S3, the load prediction module predicts the future power grid load trend based on the fusion data, and the intelligent scheduling module generates a charging control instruction through an adaptive scheduling algorithm by combining the prediction result, the user charging demand and the charging pile state; S4, the network layer issues a charging control instruction to the corresponding charging pile to control charging power, charging duration and start-stop state; S5, the safety early warning module monitors the fusion data in real time, immediately generates early warning information and pushes the early warning information to an application layer if the data is detected to exceed a preset threshold or match an abnormal feature library, and simultaneously triggers a charging pile protection mechanism; and S6, the application layer updates the charging progress, the early warning state and the power grid load data in real time, and provides an interactive interface for users and management personnel.
  10. 10. The intelligent management system for charging electric vehicles based on the internet of things according to claim 9, wherein the charging pile protection mechanism in S5 comprises charging power limitation, emergency stop, fault locking and automatic power-off functions, and the protection action log is uploaded to the database unit in real time.

Description

Electric automobile wisdom management system that charges based on thing networking Technical Field The invention relates to the technical field of new energy automobile charging, in particular to an intelligent electric automobile charging management system based on the Internet of things. Background The new energy automobile adopts unconventional automobile fuel as a power source, integrates advanced technology in the aspects of power control and driving of the automobile, forms an automobile with advanced technical principle, new technology and new structure, and along with the rapid increase of the conservation quantity of the electric automobile, the construction and management requirements of charging infrastructure are increasingly urgent. The existing electric vehicle charging system is mainly in a fixed power charging mode, global scheduling of an idle state of a charging pile in an area is lacked, so that part of the charging pile is blocked in a queuing way and part of the charging pile is idle, resource waste is serious, a large number of electric vehicles are charged simultaneously and easily to cause overload of a power grid load, the existing system does not fully consider dynamic change of the power grid load, lacks a targeted load balancing strategy and influences the stable operation of the power grid, the existing system is mainly used for monitoring basic parameters such as current, voltage and the like of the charging pile, lacks effective monitoring means for potential safety risks such as abnormal temperature, bulge and insulation drop of a battery, has great potential safety hazards, management personnel need to check the fault of the charging pile on site, remote diagnosis and maintenance cannot be realized, comprehensive analysis capability of charging data is lacked, operation strategies are difficult to optimize, users cannot acquire the idle state and charging progress of the charging pile in real time, and convenient reservation and remote control functions are lacked. The internet of things technology has the advantages of multi-equipment interconnection, data real-time transmission, remote control and the like, and can effectively solve the problems when being applied to electric automobile charging management, but a mature multidimensional sensing, intelligent scheduling and safety early warning integrated system is not formed in the prior art. Therefore, research and development of the intelligent management system for charging the electric automobile based on the Internet of things has important practical significance. Disclosure of Invention Aiming at the defects of the prior art, the invention provides an intelligent management system for charging an electric automobile based on the Internet of things, which solves the technical problems of low resource utilization rate, poor power grid load adaptation, single safety monitoring, low management efficiency and poor user experience of the conventional electric automobile charging system. In order to achieve the aim, the intelligent management system for charging the electric automobile based on the Internet of things comprises a sensing layer, a network layer, a platform layer and an application layer, wherein the layers are sequentially in communication connection: The sensing layer is used for acquiring the running state data of the charging pile, the battery state data of the electric automobile and the power grid load data and comprises a charging pile sensor group, a battery state acquisition unit and a power grid load monitoring unit; the network layer is used for realizing data interaction between the perception layer and the platform layer, and comprises a local communication module, a wide area communication module and gateway equipment, and supports multi-protocol data conversion and transmission; the platform layer comprises a data processing module, an intelligent scheduling module, a safety early warning module and a database unit: The data processing module is used for denoising, normalizing and multisource data fusion analysis on the acquired data; The intelligent scheduling module generates a charging control instruction through a self-adaptive scheduling algorithm based on the fusion data, the power grid load predicted value and the user charging demand; The safety early warning module is used for detecting and early warning the safety risk in the charging process in real time based on a preset threshold value and an abnormal feature library; the database unit is used for storing historical data, real-time data, scheduling strategies and early warning rules; The application layer comprises a user interaction terminal, a management monitoring platform and a state display module and is used for realizing charging reservation, progress inquiry, remote management and control and data visualization. Further, the charging pile sensor group comprises a current sensor, a voltage sensor, a temperature sensor, a humi