Modelling and Control by Neural Network of Electric Vehicle Traction System

被引：8

作者：

Kanchev, Hristiyan ^{[1
]}

Hinov, Nikolay ^{[1
]}

Gilev, Bogdan ^{[2
]}

Francois, Bruno ^{[3
]}

机构：

[1] Tech Univ Sofia, Fac Elect Engn & Technol, 8 St Kliment Ohridski Blvd, Sofia 1000, Bulgaria

[2] Tech Univ Sofia, Fac Appl Math & Informat, 8 St Kliment Ohridski Blvd, Sofia 1000, Bulgaria

[3] Ecole Cent Lille, Lab Electrotech & Elect Puissance, F-59650 Villeneuve Dascq, France

来源：

ELEKTRONIKA IR ELEKTROTECHNIKA | 2018年 / 24卷 / 03期

关键词：

Electric vehicle; Neural network; Regenerative braking; Ultracapacitor; HYBRID;

D O I：

10.5755/j01.eie.24.3.20974

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Modelling and control by neural network of hybrid electric vehicle traction system is presented in this paper. The electric drive is composed by a battery bank and an ultracapacitor connected in parallel through bidirectional DC converters and a Brushless DC Motor driven by a three-phase inverter. In the electric drive control loop is implemented a NARMA neural network. The mechanical model comprises a gearbox and a model of the road-wheel friction force and vehicle aerodynamics. All the masses and inertia are expressed relative to the rotor of the motor. The model is studied by simulations with two driving cycles and an assessment of the available energy from regenerative braking is performed. The percentage of recycled energy from regenerative braking is assessed.

引用

页码：23 / 28

页数：6

共 15 条

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