臺灣博碩士論文加值系統

本研究以改良電動車感應馬達的效率、力矩漣波與功率密度為研究主軸。藉由Hairpin繞組設計增加佔槽率，進而減少馬達損失，並透過參數最佳化方法，達到性能提升之目的。
首先，對原型馬達進行實驗測試與模擬分析，藉由結果得到可以改良的目標。接下來，應用磁路分析軟體進行各參數探討，其中包含了解Hairpin設計對馬達造成的磁路影響，如渦流效應、磁飽和等，以及為了使Hairpin設計有更好的結果，針對定子槽型、定轉子槽數、氣隙大小等參數作改良影響的探討。之後導入最佳化軟體，並建立一套優化流程，對各參數進行最佳化分析，在符合限制條件下，得到最佳的參數匹配，達到磁路改良之目的。

The goal of this research is to improve the efficiency , torque ripple , and power density of induction motor for electric vehicle. By the design of Hairpin winding which is benefit for increasing slot fill factor and reducing the loss and through the parameter optimization method, to achieve the purpose of performance improvement.
First, experimenting and analyzing the prototype to discover improvable targets. Next, applying electromagnetic field simulation software to access all the factors including eddy effect and magnetic saturation, the magnetic impact from Hairpin. Moreover, reforming factors like slot shape of stator , slot number of stator and rotor ,and air gap for better results. Then, applying optimization software to find the best condition that fulfills the limitations and expectations for the purpose of reforming magnetic circuit.

摘要 I
ABSTRACT II
目錄 III
圖目錄 V
表目錄 VIII
符號說明 IX
第一章 緒論 1
1.1 前言 1
1.2 研究動機 2
1.3 論文架構 3
1.4 研究工具介紹 4
1.4.1 RMxprt 4
1.4.2 Maxwell 2D/3D 4
1.4.3 ANSYS Workbench 5
1.4.4 OPTIMUS [2] 5
第二章 理論背景與文獻回顧 6
2.1 感應馬達理論背景 6
2.1.1 磁場介紹[4] 7
2.1.2 動力特性[4] 8
2.1.3 馬達損失 11
2.2 文獻回顧 15
2.2.1 馬達趨勢 15
2.2.2 馬達性能目標 16
2.2.3 Hairpin 繞組 21
2.2.4 小結 27
第三章 原型馬達分析與驗證 28
3.1 分析與驗證流程及方法 28
3.2 RMXPRT特性分析 29
3.2.1 模型建立 29
3.2.2 輸出性能分析 32
3.2.3 參數分析 34
3.3 MAXWELL 2D性能分析 36
3.3.1 模型建立 36
3.3.2 2D磁路分析 40
3.4 實驗測試驗證 42
3.4.1 測試方法與測試設備介紹 42
3.4.2 測試項目及測試結果 44
3.4.3 模擬與實驗結果驗證 48
3.5 小結 50
第四章 馬達各參數磁路分析 51
4.1 HAIRPIN繞組之RMXPRT分析 51
4.1.1 模型建立 52
4.1.2 性能分析 52
4.1.3 功率密度之改良參數探討 55
4.1.4 功率密度改良分析 60
4.2 HAIRPIN設計之MAXWELL 2D分析 63
4.2.1 模型建立 63
4.2.2 效率之改良參數分析 65
4.2.3 力矩漣波之改良參數分析 71
4.3 HAIRPIN設計之MAXWELL 3D分析 73
4.3.1 繞線端部之改良參數分析 75
4.3.2 探討繞線方式 77
4.4 小結 79
第五章 馬達參數最佳化 80
5.1 模型建立與設定 80
5.1.1 軟體連結 81
5.2 最佳化方法與演算法 82
5.2.1 最佳化方法 82
5.2.2 演算法 88
5.3 最佳化分析 89
5.3.1 效率與力矩漣波的多目標最佳化 89
5.3.2 功率密度最佳化 95
5.4 小結 98
第六章：結論與未來方向 99
6.1 研究成果 99
6.2 未來趨勢與改進方向 100
參考文獻 101

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