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    Title: 從動力電池專利看中國電動車的後進發展策略
    Examining China's Latecomer Development Strategy in the Electric Vehicle Industry through Power Battery Patents
    Authors: 劉奕
    Liu, Yi
    Contributors: 李浩仲
    李文傑

    Li, Hao-Chung
    Lee, Wen-Chieh

    劉奕
    Liu, Yi
    Keywords: 動力電池
    電動車電池
    專利文本分析
    技術進步率
    專利引用網絡
    Electric vehicle battery
    Patent text analysis
    Technological improvement rate
    Patent Citation Network
    Date: 2025
    Issue Date: 2025-09-01 15:46:30 (UTC+8)
    Abstract: 隨著全球暖化的問題日益嚴重,各國紛紛制定淨零碳排目標,並陸續推動禁售燃油車政策與規劃,進而加速電動車產業的發展。然而,電動車仍面臨價格高昂與續航力不足等挑戰,又電動車電池約佔電動車整車成本的30~40%,故動力電池為未來發展的關鍵核心技術之一。本研究以動力電池專利為研究對象,運用專利資料去探討其技術發展趨勢,進一步解析不同技術領域的發展潛力與路徑。研究方法包括詞頻與共現詞分析,從專利文本中萃取核心技術詞彙與研發趨勢,並依據Triulz等人(2020)所提的模型,計算各技術子領域的技術進步率,以評估其未來潛力,並以Park和Magee(2017)中的主路徑分析方法,建構技術知識發展路徑。資料來源涵蓋美國與中國專利局,自1990年至2022年共計數十萬筆專利資料,並將動力電池依產業鏈區分為上游(極板原物料、電解質、隔離膜)、中游(極板製造、電池芯組裝)與下游(電池模組組裝、電池管理系統、熱管理系統)技術子領域。研究結果顯示中國聚焦於製程優化與性能提升,上中游的技術布局集中在極板原材料與製造,發展重點包含複合材料、奈米結構材料及正極材料回收技術;下游則以電池管理系統為核心,發展智慧化監控與無線充電等應用,亦顯示其技術導向實作與應用能力。全球產業發展方面,上游的極板材料技術已趨於成熟,研發重點逐步轉向固態電解質,其具備高能量密度與高電壓穩定性等潛力,技術進步率逐年提升;中游領域則延續極板與塗佈材料創新,強調上中游整合;下游則處於相對成熟階段,電池管理系統架構穩定,並朝向無線充電技術與智慧化管理系統等應用面向積極拓展。
    In response to climate change, global net-zero targets and bans on fuel-powered vehicles are accelerating the electric vehicle (EV) industry. Despite this momentum, EVs still face challenges such as high costs and limited range. As the battery accounts for 30–40% of an EV’s cost, power batteries have become a core technology for future advancement. This study analyzes power battery patents to explore technological development trends and future trajectories across different domains. Using patent data from the USPTO and CNIPA (1990–2022), we classify technologies into upstream (e.g., electrode materials, electrolytes, separators), midstream (e.g., electrode manufacturing, cell assembly), and downstream (e.g., module assembly, battery management, thermal systems). Methods include term frequency and co-word analysis to identify key R&D trends, Triulz et al.’s (2020) model to calculate technological improvement rates, and main path analysis by Park and Magee (2017) to map knowledge flows. Findings indicate that China's upstream and midstream efforts prioritize process optimization and performance enhancement, with a particular emphasis on composite and nanostructured electrode materials and electrode recycling. Downstream efforts center on intelligent battery management and wireless charging, demonstrating strong integration and application capacity. Globally, upstream technologies are maturing, with growing interest in solid-state electrolytes. Midstream innovation stresses material advancement and vertical integration, while downstream technologies are relatively mature and shifting toward smart, wireless applications.
    Reference: 中文文獻
    李旭弘(2023)。七層開箱電動車動力電池系統。綠學院,取自 https://greenimpact.cc/Articles/detail?cid=1&id=486。
    林匯凱(2021)。電動車的心臟-電池產業鏈中的主要玩家有哪些?臺灣新創資訊平台,取自https://findit.org.tw/Res/1866。
    英文文獻
    Callon, M., Courtial, J.-P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co‑word analysis. Social Science Information, 22(2), 191–235.
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    Feng, S., & Magee, C. L. (2020). Technological development of key domains in electric vehicles: Improvement rates, technology trajectories and key assignees. Applied Energy, 260, 114264.
    Golembiewski, B., Vom Stein, N., Sick, N., & Wiemhöfer, H. D. (2015). Identifying trends in battery technologies with regard to electric mobility: evidence from patenting activities along and across the battery value chain. Journal of Cleaner Production, 87, 800-810.
    Gong, H., & Hansen, T. (2023). The rise of China’s new energy vehicle lithium-ion battery industry: The coevolution of battery technological innovation systems and policies. Environmental Innovation and Societal Transitions, 46, 100689.
    Hummon, N. P., & Doreian, P. (1989). Connectivity in a citation network: The development of DNA theory. Social Networks, 11(1), 39–63.
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    Lee, S., Lee, S., Seol, H., & Park, Y. (2008). Using patent information for designing new product and technology: Keyword-based technology roadmapping. R&D Management, 38(2), 169–188.
    Li, Y.-R., Wang, L.-H., & Hong, C.-F. (2009). Extracting the significant-rare keywords for patent analysis. Expert Systems with Applications, 36(3, 1), 5200–5204.
    Li, W., Yang, M., & Sandu, S. (2018). Electric vehicles in China: A review of current policies. Energy & Environment, 0(0), 1–13.
    Martinelli, A., & Nomaler, Ö. (2014). Measuring knowledge persistence: A genetic approach to patent citation networks. Journal of Evolutionary Economics, 24(3), 623–652.
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    Singh, A., Triulzi, G., & Magee, C. L. (2023). Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description. Research Policy, 50, 104249
    Tian, J., Wang, P., & Zhu, D. (2024). Overview of Chinese new energy vehicle industry and policy development. Green Energy and Resources, 2, 100075.
    Triulzi, G., Alstott, J., & Magee, C. L. (2020). Estimating technology performance improvement rates by mining patent data. Technological Forecasting and Social Change, 158, 120100.
    Tseng, Yuen‑Hsien; Lin, Chi‑Jen; Lin, Yu‑I. (2007). Text mining techniques for patent analysis. Information Processing & Management, 43(5), 1216–1247.
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    2024 EV and ESS Battery Sales Volume by Makers, Retrieved February 25 2025, from https://www.sneresearch.com/en/insight/release_view/381/page/0
    Description: 碩士
    國立政治大學
    經濟學系
    112258037
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0112258037
    Data Type: thesis
    Appears in Collections:[經濟學系] 學位論文

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