Neural-network synthesis of integrated brake controller of electrical vehicle

2010 ◽  
Author(s):  
Hsien-Ping Chu ◽  
Bo-Rong Liang ◽  
Wei-Song Lin
Keyword(s):  
Neural Network ◽  
Network Synthesis ◽  
Electrical Vehicle

scholarly journals NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm

2019 ◽  
Vol 68 (10) ◽  
pp. 1487-1497 ◽  
Author(s):  
Xiaoliang Dai ◽  
Hongxu Yin ◽  
Niraj K. Jha
Keyword(s):  
Neural Network ◽  
Network Synthesis ◽  
Synthesis Tool

A Novel Design of SOC Prediction for an Electrical Vehicle Based on the Intelligent Algorithm

2012 ◽  
Vol 468-471 ◽  
pp. 601-606 ◽  
Author(s):  
Hao Qiu ◽  
Zheng Bao Lei ◽  
Tom Zi Ming Qi
Keyword(s):  
Neural Network ◽  
Electric Vehicles ◽  
Open Circuit Voltage ◽  
Open Circuit ◽  
Intelligent Algorithm ◽  
Electrical Vehicle ◽  
Fuzzy Neural ◽  
Intelligent Methods ◽  
Novel Design

This paper is to present a novel design to predict the State of charge (SOC) of the batteries for the Electric Vehicles (EV) using a voltage descent model which has been built based on the analysis of adaptive fuzzy neural intelligent algorithm (AFNIA) and the charge/discharge experimental data of Electric Vehicle. In this design, an improved BP neural network has also been proposed to indicate the correlation between open circuit voltage and SOC. An experiment employed a Lateral Moving and In Situ Steering EV built by Shenzhen Polytechnic. The test and simulation results showed that the intelligent methods can accurately predict the SOC of lithium batteries. The combination of fuzzy control and neural network can achieve an effective way of predicting the SOC of batteries.

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