Quantifying Electric Vehicle Lithium‐Ion Battery Performance Using Fuzzy Analytic Hierarchy Process

ABSTRACT The progress of lithium‐ion battery performance and production technology has promoted the rapid development of electric vehicles (EVs) for these years. However, people are still used to driving EVs in the way as traditional internal combustion engine automobiles. Cruising range, acceleration ability, charging time, and safety have become the first issues that people should consider when purchasing EVs, and most of these functions depend on the performance of the battery. Therefore, this work used a multi‐factor evaluation method for the performance of lithium‐ion batteries used in EVs, with the help of the fuzzy analytic hierarchy process. The article focuses on the performance of the batteries that deserve the most quantified evaluation, which are the overall performance, charging performance, discharging performance, safety performance, and the sub‐factors of each performance. The criteria performance rating of EV batteries is obtained, and the performance of two distinct commercially available battery packs with different functional focuses is analyzed through a case study, which assigns the battery packs performance ratings of II and III. The factors of energy density and fast charging time are with greater weights (0.558 and 0.451, respectively), which should be the direction of key research and development of EV batteries.

Authors

Institutions

Publication Details

Journal
Energy Storage
Published
2025-09-12
DOI
https://doi.org/10.1002/est2.70269
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

Quantifying Electric Vehicle Lithium‐Ion Battery Performance Using Fuzzy Analytic Hierarchy Process

Shichen Chen, Yingzhou Hu, Yan Zhao, Sainan Chen
Energy Storage
Advanced Battery Technologies Research
article

Quantifying Electric Vehicle Lithium‐Ion Battery Performance Using Fuzzy Analytic Hierarchy Process

Shichen Chen, Yingzhou Hu, Yan Zhao, Sainan Chen
article en

Abstract

ABSTRACT The progress of lithium‐ion battery performance and production technology has promoted the rapid development of electric vehicles (EVs) for these years. However, people are still used to driving EVs in the way as traditional internal combustion engine automobiles. Cruising range, acceleration ability, charging time, and safety have become the first issues that people should consider when purchasing EVs, and most of these functions depend on the performance of the battery. Therefore, this work used a multi‐factor evaluation method for the performance of lithium‐ion batteries used in EVs, with the help of the fuzzy analytic hierarchy process. The article focuses on the performance of the batteries that deserve the most quantified evaluation, which are the overall performance, charging performance, discharging performance, safety performance, and the sub‐factors of each performance. The criteria performance rating of EV batteries is obtained, and the performance of two distinct commercially available battery packs with different functional focuses is analyzed through a case study, which assigns the battery packs performance ratings of II and III. The factors of energy density and fast charging time are with greater weights (0.558 and 0.451, respectively), which should be the direction of key research and development of EV batteries.

Energy StorageVol. 7(7)
Nanjing Institute of Railway Technology (CN)
Openalex Percentile: Top 71%
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.

Quantifying Electric Vehicle Lithium‐Ion Battery Performance Using Fuzzy Analytic Hierarchy Process — Shichen Chen, Yingzhou Hu, et al. · Energy Storage (2025) | TGRS Research Map | TGRS