運用數學演算法預測鋰電池之價格研究探討

Research and Discussion on Using Mathematical Algorithms to Predict the Price of Lithium Batteries

10.6459/JCM.202409_21(2).0003

莊閔淇(M. Q. Zhuang)；黃祥熙(H. H. Huang)

鋰電池價格預測 ； 影響因素 ； 機器學習模型 ； Lithium Battery Price Prediction ； Influencing Factors ； Machine Learning Model

危機管理學刊

21卷2期（2024 / 09 / 01）

23 - 34

繁體中文;英文

本研究探討電動汽車鋰電池價格預測的關鍵因素和方法。收集過去歷史相關之鋰電池價格數據和技術分析，依據全球電動車趨勢進行綜合分析。本研究收集相關影響鋰電池價格之因素，包含:材料成本、生產技術、需求和供應動態等。本研究運用數學演算法模型結合及時統計數據並和統計模型，建立鋰電池價格預測的模型。藉由本研究模型之驗證和準確性評估，於本研究提出了一種可行及時預測之框架，藉由預測電動汽車鋰電池的價格走向。最後，我們討論了該預測模型的應用和未來不確定性，希望通過這項研究幫助相關產業建立即時的成本控制方法，以提升工廠產值和應對未來的不確定性。我們還提出了未來研究的方向，旨在更準確地預測和理解電動汽車鋰電池價格的變動趨勢。

This study explores the key factors and methods for price prediction of lithium batteries for electric vehicles. Collect historical lithium battery price data and technical analysis in the past, and conduct a comprehensive analysis based on global electric vehicle trends. This study collects relevant factors that affect lithium battery prices, including: material costs, production technology, demand and supply dynamics, etc. This study uses mathematical algorithm models combined with real-time statistical data and statistical models to establish a lithium battery price prediction model. Through the verification and accuracy evaluation of this research model, this study proposes a feasible and timely prediction framework to predict the price trend of lithium batteries for electric vehicles. Finally, we discuss the application of this prediction model and future uncertainties, hoping that through this research, we can help related industries establish immediate cost control methods to improve factory output and cope with future uncertainties. We also propose directions for future research aimed at more accurately predicting and understanding the price trends of electric vehicle lithium batteries.