Evaluation of Electric Vehicle Integrated Charging Safety State Based on Fuzzy Neural Network

Hui Gao,Lei Sun,Binbin Zang,Liangliang Chen

doi:10.3390/app12010461

Abstract

Electric vehicles have been promoted worldwide because of their high energy efficiency and low pollution. However, frequent charging safety accidents have to a certain extent restricted the development of electric vehicles. Therefore, it is extremely important to accurately evaluate the safety state of EV charging. The paper presents an integrated safety assessment method for electric vehicle charging safety based on fuzzy neural network. The integrated fault model was established by analyzing the correlation between truck–pile–grid. Then the integrated evaluation index was analyzed and sorted out, and the comprehensive fuzzy evaluation method used to evaluate. Following this, the improved GA_BP neural network algorithm was used to calculate the weight. Compared with the evaluation effect before and after the improvement, the simulation results show that the GA_BP neural network has higher accuracy and smaller error than the ordinary BP neural network. Finally, the feasibility and effectiveness of the evaluation method was verified by a case study.

Highlights

In order to promote a global carbon balance, countries have formulated their own “carbon reduction” targets [1]
The inevitable performance degradation of the power battery in use will lead to the decrease of the vehicle driving range, the deterioration of the power performance and the shortening of service life, which will cause an increase in the safety risks
In the actual operation of electric vehicles, many factors such as electromagnetic interference, road conditions, and driving habits can lead to battery system failures, and complex, nonlinear, or multi-parameter coupling

Summary

Introduction

In order to promote a global carbon balance, countries have formulated their own “carbon reduction” targets [1]. In the promotion process of electric vehicles, power battery failure and charging equipment safety problems have become obstacles to the rapid development of electric vehicles [4]. Accurate prediction and diagnosis of power battery faults is an important guarantee to improve the safety and reliability of electric vehicles [7]. By studying the integrated safety assessment system of electric vehicle charging, an early warning of the integrated charging safety of battery, charging, and power supply is derived. This will play an effective supporting role in improving the evaluation effect of the charging safety system, ensuring the safety of vehicle charging, and promoting the development of electric vehicles.

Multistage Fault Correlation Analysis

Conclusions