Intelligent Battery-Aware Energy Management System for Electric Vehicles

被引：0

作者：

Mahmoud, Dina G. ^{[1
]}

Elkhouly, Omar A. ^{[1
]}

Azzazy, Muhammad ^{[1
]}

Alkady, Gehad I. ^{[1
]}

Adly, Ihab ^{[2
]}

Daoud, Ramez M. ^{[1
]}

Amer, Hassanein H. ^{[1
]}

ElSayed, Hany ^{[3
]}

Guirguis, Mark ^{[1
]}

Abdelshafi, Mohamed Gamal ^{[1
]}

机构：

[1] Amer Univ Cairo, Elect & Commun Engn Dept, Cairo, Egypt

[2] Tegrom, Cairo, Egypt

[3] Cairo Univ, Elect & Elect Commun Engn Dept, Cairo, Egypt

来源：

2019 24TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA) | 2019年

关键词：

electric vehicle; energy management; FPGA; driving cycle; neural networks; performability;

D O I：

10.1109/etfa.2019.8869496

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a system for intelligent energy management in electric vehicles. This system incorporates parameters relating to driving style of the car, trip information and battery states. The driving cycle classification subsystem is implemented in different scenarios, and the results of power, performance and utilization are reported. Finally, a performability analysis, utilizing the implementation scenarios for increasing the system reliability, is presented.

引用

页码：1635 / 1638

页数：4

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