Patent Analysis of the Electric Vehicle Battery Management Systems Based on the AHP and Entropy Weight Method

With the rapid development of the electric vehicle (EV) industry, the importance of battery management systems (BMS) in ensuring the safety, reliability, and efficiency of batteries has significantly increased. This study explores the technological development trends and market layout of EV BMS through patent analysis, focusing on patent quantity, geographic distribution, and technical classification. By integrating the analytic hierarchy process (AHP) and entropy weight method, a patent value evaluation model was constructed to identify key patents and assess their quality across four dimensions: technical, market, economic, and legal. The results reveal that BMS patents are primarily concentrated in China, the United States, and South Korea, with major contributors including LG Energy Solution, BYD, and Hyundai. While BMS patent applications grew rapidly from 2015 to 2020, the pace has slowed since 2021, indicating a possible shift in market focus. The analysis identified 14 high-quality patents, mainly focused on battery safety and compactness, while fewer patents addressed battery lifespan extension and anti-interference capabilities. The study suggests that although significant progress has been made in BMS technology, there is still substantial room for innovation, particularly in areas such as battery lifespan management, charging efficiency, and intelligent energy scheduling. This research provides valuable insights for future technological innovation and market decision-making in the EV BMS sector.

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Publication Details

Journal
World Electric Vehicle Journal
Published
2025-04-05
DOI
https://doi.org/10.3390/wevj16040218
Citations
1
Primary Topic
Engineering Applied Research
Type
article
Field-Weighted Citation Impact
0.95

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article

Patent Analysis of the Electric Vehicle Battery Management Systems Based on the AHP and Entropy Weight Method

Dan Wan, Hao Zhan, Ling Peng
1 citations
World Electric Vehicle Journal
Engineering Applied Research
0.95
article

Patent Analysis of the Electric Vehicle Battery Management Systems Based on the AHP and Entropy Weight Method

Dan Wan, Hao Zhan, Ling Peng
article en
1 citations

Abstract

With the rapid development of the electric vehicle (EV) industry, the importance of battery management systems (BMS) in ensuring the safety, reliability, and efficiency of batteries has significantly increased. This study explores the technological development trends and market layout of EV BMS through patent analysis, focusing on patent quantity, geographic distribution, and technical classification. By integrating the analytic hierarchy process (AHP) and entropy weight method, a patent value evaluation model was constructed to identify key patents and assess their quality across four dimensions: technical, market, economic, and legal. The results reveal that BMS patents are primarily concentrated in China, the United States, and South Korea, with major contributors including LG Energy Solution, BYD, and Hyundai. While BMS patent applications grew rapidly from 2015 to 2020, the pace has slowed since 2021, indicating a possible shift in market focus. The analysis identified 14 high-quality patents, mainly focused on battery safety and compactness, while fewer patents addressed battery lifespan extension and anti-interference capabilities. The study suggests that although significant progress has been made in BMS technology, there is still substantial room for innovation, particularly in areas such as battery lifespan management, charging efficiency, and intelligent energy scheduling. This research provides valuable insights for future technological innovation and market decision-making in the EV BMS sector.

World Electric Vehicle JournalVol. 16(4)
Hunan Normal University (CN), Xiamen University (CN)
Hunan Normal University
Openalex Percentile: Top 27%
Engineering Applied Research
0.95
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Patent Analysis of the Electric Vehicle Battery Management Systems Based on the AHP and Entropy Weight Method — Dan Wan, Hao Zhan, et al. · World Electric Vehicle Journal (2025) | TGRS Research Map | TGRS