Modelling and Control by Neural Network of Electric Vehicle Traction System

Authors

  • Hristiyan Kanchev
  • Nikolay Hinov
  • Bogdan Gilev
  • Bruno Francois

DOI:

https://doi.org/10.5755/j01.eie.24.3.20974

Keywords:

Electric vehicle, Neural network, Regenerative braking, Ultracapacitor.

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

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Published

2018-06-26

How to Cite

Kanchev, H., Hinov, N., Gilev, B., & Francois, B. (2018). Modelling and Control by Neural Network of Electric Vehicle Traction System. Elektronika Ir Elektrotechnika, 24(3), 23-28. https://doi.org/10.5755/j01.eie.24.3.20974

Issue

Vol. 24 No. 3 (2018)

Section

ELECTRONIC MEASUREMENTS

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