Comparative Analysis of the Performance of Batteries

This study presents a comparative modeling and performance analysis of four major battery chemistries Lead–acid, Lithium-ion, Solid-state, and Flow using MATLAB/Simulink and Simscape. A unified equivalent circuit model (ECM), comprising an open-circuit voltage source, ohmic resistance, and two RC branches, was implemented as a baseline framework to ensure consistency across chemistries. Chemistry-specific extensions were incorporated, including the Shepherd–Peukert model for Lead–acid, a Single-Particle Model (SPM) for Lithium-ion, an extended SPM with interfacial resistance for Solid-state, and coupled tank–stack–channel dynamics for Flow batteries. Experimental OCV–SOC (Open-Circuit Voltage vs. State of Charge) data, diffusion coefficients, and kinetic parameters were integrated to enhance fidelity, while degradation sub-models such as SEI growth, Peukert aging, interfacial resistance, and electrolyte imbalance enabled lifecycle projections. Standardized test protocols comprising constant-current discharges, dynamic load cycles, temperature sweeps, and cycling tests were applied to evaluate voltage–SOC behaviour, round-trip efficiency, thermal rise, and cycle life. Results indicated that Lithium-ion and Solid-state deliver superior energy density and efficiency, Lead–acid remains cost-effective but cycle-limited, and Flow batteries achieve exceptional lifetime with scalable power–energy decoupling. The unified framework provides a reproducible methodology for battery evaluation, offering valuable insights for mobility, stationary storage, and grid-scale applications.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-15
DOI
https://doi.org/10.5281/zenodo.18267961
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Analysis of the Performance of Batteries

Aniru Abudu Muhammed, Hibah Imuentinyanose Muhammed
Zenodo (CERN European Organization for Nuclear Research)
Advanced Battery Technologies Research
article

Comparative Analysis of the Performance of Batteries

Aniru Abudu Muhammed, Hibah Imuentinyanose Muhammed
article en

Abstract

This study presents a comparative modeling and performance analysis of four major battery chemistries Lead–acid, Lithium-ion, Solid-state, and Flow using MATLAB/Simulink and Simscape. A unified equivalent circuit model (ECM), comprising an open-circuit voltage source, ohmic resistance, and two RC branches, was implemented as a baseline framework to ensure consistency across chemistries. Chemistry-specific extensions were incorporated, including the Shepherd–Peukert model for Lead–acid, a Single-Particle Model (SPM) for Lithium-ion, an extended SPM with interfacial resistance for Solid-state, and coupled tank–stack–channel dynamics for Flow batteries. Experimental OCV–SOC (Open-Circuit Voltage vs. State of Charge) data, diffusion coefficients, and kinetic parameters were integrated to enhance fidelity, while degradation sub-models such as SEI growth, Peukert aging, interfacial resistance, and electrolyte imbalance enabled lifecycle projections. Standardized test protocols comprising constant-current discharges, dynamic load cycles, temperature sweeps, and cycling tests were applied to evaluate voltage–SOC behaviour, round-trip efficiency, thermal rise, and cycle life. Results indicated that Lithium-ion and Solid-state deliver superior energy density and efficiency, Lead–acid remains cost-effective but cycle-limited, and Flow batteries achieve exceptional lifetime with scalable power–energy decoupling. The unified framework provides a reproducible methodology for battery evaluation, offering valuable insights for mobility, stationary storage, and grid-scale applications.

Zenodo (CERN European Organization for Nuclear Research)
University of Science and Technology of Benin (BJ)
Affordable and clean energy
Openalex Percentile: Top 42%
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.