An Intelligent Energy Management and Control System for Electric Vehicle

被引:0
作者
Chellaswamy, C. [1 ]
Ramesh, R. [2 ]
机构
[1] St Peterss Univ, St Peters Inst Higher Educ & Res, Dept ECE, Madras, Tamil Nadu, India
[2] Saveetha Engn Coll, Dept ECE, Madras, Tamil Nadu, India
来源
2014 INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES (ICACCCT) | 2014年
关键词
extended Kalman filtering (EKF); state of charge; electric vehicle; energy management;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an intelligent energy management for electric vehicles (EVs) which contains automatic charging mechanism. Nowadays EVs charging the battery pack by using road side stations, park stations etc. are increase the travel time. To overcome this problem we have proposed an automatic charging with an intelligent energy management system using Kalman filtering (IEMK) capable for estimating and controlling the battery packs. Energy and battery management in EV is difficult and important under driving condition. This paper mainly focuses to estimate different parameters such as available power, state of charge, and thermal management. The algorithm has been implemented for the battery packs to maintain charging by both the solar and wind energy systems. IEMK provides optimal mean for estimating the parameters of battery pack and accurate under running condition. Simulation results show that the proposed method is stable, state of charge with 1 % error, and robust compared with other systems.
引用
收藏
页码:180 / 184
页数:5
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