Design And Implementation Of Intelligent State Monitoring System For Electric Vehicle Charging Pile

With the rapid large-scale development of the new energy electric vehicle industry,the market demand for charging equipment such as charging piles is constantly increasing,and the charging infrastructure and the charging process of electric vehicles are usually large-scale processes with very high power and current requirements.,And is easily affected by the external environment such as temperature and traffic conditions,which has led to an increase in safety accidents in the charging process of electric vehicles in recent years.Therefore,online monitoring and safety assessment of charging equipment has become the focus of research and attention..This article analyzes and judges the various data of charging facilities for charging cars based on related backgrounds,uses data mining methods to evaluate the status and fault prediction of the charging process of charging facilities,and checks and repairs the charging piles that may fail in advance.To prevent safety accidents during the charging process.A key in the intelligent monitoring system for the operating status of electric vehicle charging facilities is to establish a state assessment model and a fault prediction model for charging equipment,use data mining technology to analyze and process the collected data,and call decision trees,random forests,and LSTM short-term The learner based on the memory cycle establishes the model,inputs the processed data set to the model for training and learning,and continuously optimizes to improve the accuracy of condition assessment and fault prediction,and realizes intelligent monitoring and early warning of the operating status of the charging equipment,thereby Conducive to ensuring the charging safety of electric vehicles.This topic is based on an in-depth understanding of the actual needs and business functions of the system,and after understanding and analyzing the system development background and current research status at home and abroad,it chooses to use the Django framework to complete the development and design of the system,and uses the model to communicate with users in a systematic way.Interaction and feedback,through the system to evaluate the status of the charging device charging process and early warning of failure,by calling the established model,analysis and get the status of the charging pile and early warning of the failure,so that users can obtain the status of the charging device in time and take measures avoid risk.