Modeling and Simulation of Integrated Solar PV/Battery/Hydrogen Hybrid System for Enhanced System

This paper describes an ongoing engineering project and outlines the modeling and simulation of a Hybrid Energy Storage System (HESS) of an electric vehicle using fuel cells and batteries with the aid of MATLAB/Simulink. The key purpose of this research is to develop and demonstrate the hybridization compatibility between both devices to ensure overall system stability and minimize transient effects. At present, researchers have proposed several types of nonhybrid Energy Storage System (ESS) which mostly involves batteries, also referred to as Battery Energy Storage System (BESS). The problem with this conventional system is that the system itself is jeopardizing and not efficient enough to lower the rate of transient, resulting in a longer response time. On that account, the hybridization between two types of sources, which in this case is the fuel cell and battery, is required along with the presence of a network controller. The network controller proposed for the HESS is Artificial Neural Network (ANN) as it is suitable for capturing complex and nonlinear relationships data. In general, this research aims to increase the stability and reliability of the entire system performance.

Authors

Institutions

Publication Details

Journal
Semarak International Journal of Mechanical Precision Engineering
Published
2025-06-30
DOI
https://doi.org/10.37934/sijmpe.3.1.1931
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling and Simulation of Integrated Solar PV/Battery/Hydrogen Hybrid System for Enhanced System

Shanti Faridah Salleh, Norhuzaimin Julai, Yonis M. Buswig, Al-Khalid Oth­man et al.
Semarak International Journal of Mechanical Precision Engineering
Advanced Battery Technologies Research
article

Modeling and Simulation of Integrated Solar PV/Battery/Hydrogen Hybrid System for Enhanced System

Shanti Faridah Salleh, Norhuzaimin Julai, Yonis M. Buswig, Al-Khalid Oth­man, Kasumawati Lias, A Azhar, Nur Aida Ariffah Kamis
article en

Abstract

This paper describes an ongoing engineering project and outlines the modeling and simulation of a Hybrid Energy Storage System (HESS) of an electric vehicle using fuel cells and batteries with the aid of MATLAB/Simulink. The key purpose of this research is to develop and demonstrate the hybridization compatibility between both devices to ensure overall system stability and minimize transient effects. At present, researchers have proposed several types of nonhybrid Energy Storage System (ESS) which mostly involves batteries, also referred to as Battery Energy Storage System (BESS). The problem with this conventional system is that the system itself is jeopardizing and not efficient enough to lower the rate of transient, resulting in a longer response time. On that account, the hybridization between two types of sources, which in this case is the fuel cell and battery, is required along with the presence of a network controller. The network controller proposed for the HESS is Artificial Neural Network (ANN) as it is suitable for capturing complex and nonlinear relationships data. In general, this research aims to increase the stability and reliability of the entire system performance.

Semarak International Journal of Mechanical Precision EngineeringVol. 3(1)
Universiti Malaysia Sarawak (MY)
Universiti Malaysia Sarawak, Research Institute of Electrical Communication, Tohoku University
Affordable and clean energy
Openalex Percentile: Top 79%
Advanced Battery Technologies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.