In this article, a real-time fault prediction method combining cost-sensitive logistic regression (CS-LR) and cost-sensitive support vector machine classification (CS-SVM)
AI Customer ServiceThis paper mainly studies the open circuit fault diagnosis of power components of electric vehicle DC charging piles; the faults are divided into 16 types, as shown in Table 2.
AI Customer ServiceSince the smart charging piles are generally deployed in complex environments and prone to failure, it is significant to perform efficient fault diagnosis and timely maintenance
AI Customer ServiceWith the increasing density of charge and discharge service network, various faults that occur frequently in the process of charge and discharge will cause great harm and loss to electric
AI Customer Servicecharging piles [31]. In view of the above situation, in the Section2of this paper, energy storage technology is applied to the design of a new type charging pile that integrates charging,
AI Customer ServiceSince the smart charging piles are generally deployed in complex environments and prone to failure, it is significant to perform efficient fault diagnosis and timely maintenance
AI Customer ServiceDuring the operation of DC charging pile, faults are easy to occur, mainly including communication faults, charging gun faults, charging module faults, etc. Among the
AI Customer ServiceWith an increasing number of lithium‐ion battery (LIB) energy storage station being built globally, safety accidents occur frequently. Diagnosing faults accurately and quickly
AI Customer ServiceThe battery energy storage technology is applied to the traditional EV (electric vehicle) charging piles to build a new EV charging pile with integrated charging, discharging,
AI Customer Servicecharging voltage and current can be adjusted in real time, and the charging time can be significantly shortened when the charging current are large, which is a more widely used
AI Customer ServiceThis type of product is actually not very meaningful for most individual users, because when sharing your own private charging pile with others, you need to consider many
AI Customer ServiceAbstract: With the application of the Internet of Things (IoT), smart charging piles, which are important facilities for new energy electric vehicles (NEVs), have become an
AI Customer ServiceThis paper proposes an error detection procedure of charging pile founded on ELM method. Different from the traditional charging pile fault detection model, this method constructs data
AI Customer ServiceTMS faults include compressor faults, pump faults, fan faults, communication faults, sensor faults, power supply alarming, humidity alarming, and high temperature
AI Customer ServiceThis paper proposes an error detection procedure of charging pile founded on ELM method. Different from the traditional charging pile fault detection model, this method constructs data
AI Customer ServiceThe construction of public-access electric vehicle charging piles is an important way for governments to promote electric vehicle adoption. The endogenous relationships
AI Customer ServiceThis paper mainly studies the open circuit fault diagnosis of power components of electric vehicle DC charging piles; the faults are divided into 16 types, as shown in Table 2.
AI Customer ServiceIn this paper, the battery energy storage technology is applied to the traditional EV (electric vehicle) charging piles to build a new EV charging pile with integrated charging,...
AI Customer ServiceAn arc fault is the most common cause of charging pile fire. The series arc fault current is usually lower than the short‐circuit fault current and is challenging to detect,...
AI Customer ServiceIn this article, a real-time fault prediction method combining cost-sensitive logistic regression (CS-LR) and cost-sensitive support vector machine classification (CS-SVM)
AI Customer Serviceand the fault maintenance of charging piles has gradually become a problem. Aiming at the prob- lems that convolutional neural networks (CNN) are easy to overfit and the low localization
AI Customer ServiceIn this paper, the battery energy storage technology is applied to the traditional EV (electric vehicle) charging piles to build a new EV charging pile with integrated charging,
AI Customer ServiceSince the smart charging piles are generally deployed in complex environments and prone to failure, it is significant to perform efficient fault diagnosis and timely maintenance for them.
However, traditional fault detection methods are still used in charging piles, which makes the detection efficiency low. This paper proposes an error detection procedure of charging pile founded on ELM method.
In this paper, the battery energy storage technology is applied to the traditional EV (electric vehicle) charging piles to build a new EV charging pile with integrated charging, discharging, and storage; Multisim software is used to build an EV charging model in order to simulate the charge control guidance module.
In this article, a real-time fault prediction method combining cost-sensitive logistic regression (CS-LR) and cost-sensitive support vector machine classification (CS-SVM) is proposed. CS-LR is first used to classify the fault data of smart charging piles, then the CS-SVM is adopted to predict the faults based on the classified data.
On the one hand, the energy storage charging pile interacts with the battery management system through the CAN bus to manage the whole process of charging.
Abstract: With the application of the Internet of Things (IoT), smart charging piles, which are important facilities for new energy electric vehicles (NEVs), have become an important part of the smart grid.
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