臺灣博碩士論文加值系統

摘要
隨著鋰離子電池技術與電動車產業的迅速發展，車用電池模組(battery module)之可靠度分析與設計逐漸成為備受注目的研究課題，原因在於電池模組昂貴，占現今電動車總成本三分之一以上，其失效所帶來的風險更不可輕忽。本研究將車用電池模組視為由多顆單電池(battery cell)組成的系統，先依計算流體力學之三維紊流模型，模擬獲得模組運作受熱時之溫度場，而後探討溫度場內不同位置所在各單電池之電量衰退情形。本研究考量單電池健康狀態評估之不確定性，將單電池與電池模組分別視為具有多狀態之隨機元件與隨機系統，藉由習知可靠度工程方法與通用生成函數，評估電池模組的可靠度。本研究特別探討離散多狀態隨機元件與系統通用生成函數之應用，比較離散狀態多寡對系統可靠度評估之影響。本研究最後以模組系統可靠度作為最佳化設計之目標函數，將各單電池在空間位置上之排列當作設計變數，透過粒子群演算法，獲得具最高可靠度之電池模組設計。本研究結果顯示，在有限空間限制下，將各單電池適當交錯排列並提供適度間隔，可有效提升模組的系統可靠度，最後達到最高可靠度之設計目標。

Abstract
Along with the rapid development of lithium-ion battery technology as well as the battery’s being used in electric vehicles (EVs), the reliability analysis and design of battery module have gradually become an important research issue. This study considers the battery module of an EV as a system consisting of multiple battery cells. When the EV is in cruise, spatial temperature distribution of the heated module is obtained by computational fluid dynamics (CFD) based on a 3D turbulence simulation model. The temperature affects the capacity degradation of individual cells located in different positions within the module. The uncertainty of capacity degradation is considered in particular and represented by multiple probability state of health (SOH) in this study. It results in multiple probability state of the battery module and hence its quantitative reliability. The universal generating function (UGF) is employed in the analysis, and how the discretization of UGF affects the estimation is investigated in detail. Within the framework of reliability-based design optimization (RBDO), this study also explores the most reliable spatial layout of battery cells within a module subject to certain given constraints. The result of case study indicates RBDO of battery module can really be achieved by the proposed method.

目錄
致謝 I
摘要 II
ABSTRACT III
目錄 IV
圖目錄 VII
表目錄 IX
1. 緒論 1
1.1 研究背景與動機 1
1.2 文獻回顧 2
1.3 論文架構 4
2. 電池模型與數值計算方法 5
2.1 電池基本理論 5
2.1.1 鋰電池工作原理 6
2.1.2 電池模組與電池組 8
2.2 電池模型與數值計算模型 9
2.2.1 熱生成模型 9
2.2.2 數值計算模型 10
3. 可靠度與最佳化理論 13
3.1 可靠度基本理論 13
3.1.1 定義 14
3.1.2 機率分布函數 16
3.1.3 系統可靠度 18
3.1.4 多狀態系統 22
3.2 通用生成函數 23
3.2.1 矩生成函數與z轉換 23
3.2.2 通用生成函數理論 27
3.3 最佳化方法 32
3.3.1 最佳化理論概述 32
3.3.2 粒子群演算法 36
4. 案例分析與結果討論 40
4.1 電池模組模型與散熱模擬 40
4.1.1 基本假設 40
4.1.2 電池模組幾何模型 41
4.1.3 CFD模型邊界條件設定 42
4.1.4 CFD散熱模擬 43
4.2 電池電量衰退模型 48
4.3 可靠度分析 49
4.3.1 單電池健康狀態不確定性 49
4.3.2 傳統可靠度方法 51
4.3.3 通用生成函數法 53
4.3.4 電池品質對可靠度影響 66
4.4 最佳化設計 68
4.4.1 粒子群最佳化 69
4.4.2 最佳化分析與結果討論 71
5. 結論 75
參考文獻 77

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