Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments

Abstract The demand for high-capacity lithium-ion batteries (LIB) in electric vehicles has increased. In this study, optimization to maximize the specific energy density of a cell is conducted using the LIB electrochemical model and sequential approximate optimization (SAO). First, the design of exp...

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Main Authors: Ji-San Kim, Dong-Chan Lee, Jeong-Joo Lee, Chang-Wan Kim
Format: Article
Language:English
Published: Nature Publishing Group 2020-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-020-72442-4
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spelling doaj-7e3593a1190042d4a804485dec338ace2021-09-26T11:25:15ZengNature Publishing GroupScientific Reports2045-23222020-09-0110111110.1038/s41598-020-72442-4Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experimentsJi-San Kim0Dong-Chan Lee1Jeong-Joo Lee2Chang-Wan Kim3Graduate School of Mechanical Design and Production Engineering, Konkuk UniversitySchool of Mechanical Engineering, Konkuk UniversityGraduate School of Mechanical Design and Production Engineering, Konkuk UniversitySchool of Mechanical Engineering, Konkuk UniversityAbstract The demand for high-capacity lithium-ion batteries (LIB) in electric vehicles has increased. In this study, optimization to maximize the specific energy density of a cell is conducted using the LIB electrochemical model and sequential approximate optimization (SAO). First, the design of experiments is performed to analyze the sensitivity of design factors important to the specific energy density, such as electrode and separator thicknesses, porosity, and particle size. Then, the design variables of the cell are optimized for maximum specific energy density using the progressive quadratic response surface method (PQRSM), which is one of the SAO techniques. As a result of optimization, the thickness ratio of the electrode was optimized and the porosity was reduced to keep the specific energy density high, while still maintaining the specific power density performance. This led to an increase in the specific energy density of 56.8% and a reduction in the polarization phenomenon of 11.5%. The specific energy density effectively improved through minimum computation despite the nonlinearity of the electrochemical model in PQRSM optimization.https://doi.org/10.1038/s41598-020-72442-4
collection DOAJ
language English
format Article
sources DOAJ
author Ji-San Kim
Dong-Chan Lee
Jeong-Joo Lee
Chang-Wan Kim
spellingShingle Ji-San Kim
Dong-Chan Lee
Jeong-Joo Lee
Chang-Wan Kim
Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments
Scientific Reports
author_facet Ji-San Kim
Dong-Chan Lee
Jeong-Joo Lee
Chang-Wan Kim
author_sort Ji-San Kim
title Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments
title_short Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments
title_full Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments
title_fullStr Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments
title_full_unstemmed Optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments
title_sort optimization for maximum specific energy density of a lithium-ion battery using progressive quadratic response surface method and design of experiments
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2020-09-01
description Abstract The demand for high-capacity lithium-ion batteries (LIB) in electric vehicles has increased. In this study, optimization to maximize the specific energy density of a cell is conducted using the LIB electrochemical model and sequential approximate optimization (SAO). First, the design of experiments is performed to analyze the sensitivity of design factors important to the specific energy density, such as electrode and separator thicknesses, porosity, and particle size. Then, the design variables of the cell are optimized for maximum specific energy density using the progressive quadratic response surface method (PQRSM), which is one of the SAO techniques. As a result of optimization, the thickness ratio of the electrode was optimized and the porosity was reduced to keep the specific energy density high, while still maintaining the specific power density performance. This led to an increase in the specific energy density of 56.8% and a reduction in the polarization phenomenon of 11.5%. The specific energy density effectively improved through minimum computation despite the nonlinearity of the electrochemical model in PQRSM optimization.
url https://doi.org/10.1038/s41598-020-72442-4
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