Power Allocation based on ANN for Hybrid Battery and Supercapacitor Storage System in EV
Abstract
Neural Network (ANN) approach to allocate power for a hybrid
energy storage system (HESS) in an Electric Vehicle (EV). The
HESS is comprised of a battery and supercapacitor, and the
ANN algorithm aims to optimize power allocation between these
two energy storage devices. The data for ANN training was
based on cost optimization-based power allocation from
previous research. While optimization can often take high
computational resource and time, it is expected that a welltrained ANN can allocate power for the EV HESS more quickly.
In this research, the inputs to the ANN are the required power
derived from the drive cycle, energy and power capacity of the
battery and supercapacitor, and state of charge (SoC) of the
battery and supercapacitor. The trained ANN was trained with
various inputs not used in the training and it shows satisfactory
performance.
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DOI: https://doi.org/10.12962/jaree.v8i2.385
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