Modelling and Control by Neural Network of Electric Vehicle Traction System

Hristiyan Kanchev, Nikolay Hinov, Bogdan Gilev, Bruno Francois

Abstract


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.

DOI: http://dx.doi.org/10.5755/j01.eie.24.3.20974


Keywords


Electric vehicle; Neural network; Regenerative braking; Ultracapacitor.

Full Text: PDF

Refbacks

  • There are currently no refbacks.


Print ISSN: 1392-1215
Online ISSN: 2029-5731