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  • 學位論文

電動車用鋰離子電池壽命評估模型之建構與可靠度分析

Life Modeling and Reliability Analysis of Lithium-ion Batteries Used in Electric Vehicles

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摘要


鋰離子電池因具有能量密度高、使用壽命長等優點,已成為電動車電池的主流。本研究旨在建構一個考慮不確定性、以可靠度為基礎的數學模型來描述鋰離子電池的退化現象,並藉以評估電池壽命與可靠度。本研究首先依據實際電池測試數據,考慮不同操作環境下的電池性能退化狀況,並考慮各電池退化之不確定性,依據電池儲存及使用狀態,分別提出其電容量損失模型,以描述電池電容量隨時間或充放電循環次數下降的趨勢,而後據以分析前述電池壽命分布與可靠度,求得電池在任意時間下的失效機率。本研究也將車輛每日行駛距離分布轉換為隨機放電深度分布,探討不同行駛習慣與充電方式對電池退化的影響。研究結果顯示電池荷電狀態(state of charge, SOC)為影響電池退化主要因素之一,而降低電池充電上限、避免在高SOC下頻繁地淺放電(shallow discharge)則能大幅延長電池使用壽命並提升其可靠度。

並列摘要


Lithium-ion batteries have gradually become the mainstream of batteries used in electric vehicles due to their advantages such as high energy density and long lifetime. This research aims to establish a reliability-based mathematical model that considers uncertainties of the degradation of lithium-ion batteries. The model can be used to evaluate the lifetime distribution and reliability of a selected type of lithium-ion battery. Based on the actual battery test data, this research considers battery performance under different operational environments as well as the uncertainty existed for each battery and proposes two capacity loss formulas to describe respectively the declines of battery capacity along with time when it is in storage and charge-and-discharge cycle when it is in use. According to the model, the battery lifetime distribution and reliability can be evaluated, and the failure probability of the battery at any time can be obtained. This research also converts a vehicle's daily driving distance into a random depth of discharge, and explores the impact of different driving habits and charging methods on battery degradation. Research results show that state of charge (SOC) is one of the main factors affecting battery degradation. It is also found that selecting a lower battery charging limit and avoiding frequent shallow discharge under high SOC can slow down the degradation, and greatly extend the lifetime and improve the reliability of the battery.

參考文獻


[1] 謝育錚、閻大維,國際電動車產業發展現況與商機,財團法人車輛研究測試中心,2019。
[2] R. Xiong and W. Shen, Advanced Battery Management Technologies for Electric Vehicles, Hoboken, NJ: Wiley, 2018.
[3] C. Lyu, Y. Song, J. Zheng, W. Luo, G. Hinds, J. Li, and L. Wang, "In situ monitoring of lithium-ion battery degradation using an electrochemical model," Applied Energy, Vol. 250, pp. 685-696, 2019.
[4] T.R. Tanim and C.D. Rahn, "Aging formula for lithium-ion batteries with solid electrolyte interphase layer growth," Journal of Power Sources, Vol. 294, pp. 239-247, 2015.
[5] J. Brand, Z. Zhang, and R.K. Agarwal, "Extraction of battery parameters of the equivalent circuit model using a multi-objective genetic algorithm," Journal of Power Sources, Vol. 247, pp. 729-737, 2014.

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