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研究生:徐嘉章
研究生(外文):Chia-Chang Hsu
論文名稱:鉛酸電池充電及殘餘電量估測之研究
論文名稱(外文):Study on the charge and residual capacity estimation of lead-acid batteries
指導教授:趙貴祥
指導教授(外文):Kuei-Hsiang Chao
學位類別:碩士
校院名稱:國立勤益科技大學
系所名稱:資訊與電能科技研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:120
中文關鍵詞:鉛酸電池均勻充電殘餘電量估測可拓理論
外文關鍵詞:lead-acid batterycharge equalizationresidual capacity estimationextension theory
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  • 被引用被引用:4
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本論文主要係就鉛酸電池之均勻充電及其容量估測從事研究及探討。首先,在電池均勻充電方面,採三階層中性點箝位交流/直流轉換器對串聯之蓄電池組進行充電。所提之均勻充電電路不但可調控輸入端功因,並可使其直流鏈串聯充電之蓄電池組之電壓達到平衡。同時亦以模擬結果驗證了所提之均勻充電方法的可行性。接著,在電池容量估測方面,以常見之電量估測法中之庫倫計法配合可程式化系統晶片(Programmable system-on-chip, PSoC)研製一鉛酸電池放電器,此放電器在放電同時亦可透過可程式系統晶片設定放電電流,並準確的計算出蓄電池當時之殘餘電量狀態。經由實測結果得知,所提之放電器深具實用性。最後,本論文提出具智慧型之電量狀態估測方法,此法由實際鉛酸蓄電池充放電時所量測之開路電壓及內部電阻分別以可拓理論與可拓類神經網路演算法進行蓄電池殘餘電量之估測。所提兩種演算法皆具有學習時間短及辨識率極高之優點。由模擬結果亦證明了所提之智慧型電量估測法的可行性及準確性。
The main purpose of this thesis is to study the charge equalization and capacity estimation of the lead-acid batteries. First, a three-level neutral point clamped AC/DC converter is adopted to charge the series batteries for obtain the charge equalization. The proposed charge equalization circuits can not only regulate the input power factor, but also make the voltage balance between the series batteries. Some simulation results are made to verify the effectiveness of proposed charger. As to the battery capacity estimation, the coulometric measurement method with Programmable system-on-chip (PSoC) are used to develop a lead-acid battery discharger. The discharger is not only used for battery discharge, but also can control discharging current via PSoC during discharging time and then calculates the residual capacity of the batteries. Finally, an intelligent capacity estimation method based on Extension theory and Extension neural network is developed for a lead-acid battery. Both of the two developed algorithms are with less learning time and high recognition. Some simulation results have been made to demonstrate the effectives of the proposed intelligent capacity estimation of lead-acid batteries.
目 錄

中文摘要 ------------------------------------------ i
英文摘要 ------------------------------------------ ii
致謝 ---------------------------------------------- iii
目錄 ---------------------------------------------- iv
表目錄 -------------------------------------------- vii
圖目錄 -------------------------------------------- viii
第一章 簡介---------------------------------------- 1
1.1 研究背景與動機-------------------------------- 1
1.2 國內外相關研究-------------------------------- 3
1.3 研究方法-------------------------------------- 5
1.4 論文大綱-------------------------------------- 6
第二章 鉛酸電池之介紹-------------------------------- 7
2.1 前言------------------------------------------ 7
2.2 鉛酸電池的構造與原理-------------------------- 8
2.2.1 鉛酸電池之構造--------------------------- 8
2.2.2 鉛酸電池之工作原理----------------------- 12
2.2.3 鉛酸電池充放電特性----------------------- 14
2.3 蓄電池相關術語-------------------------------- 18
2.4 鉛酸電池等效電路之建立------------------------ 20
第三章 鉛酸電池均勻充電器---------------------------- 24
3.1 既有均勻充電方式探究-------------------------- 24
3.2 所提之均勻充電電路---------------------------- 30
3.2.1 所提均勻充電電路架構-------------------- 30
3.2.2 所提均勻充電電路之工作原理--------------- 32
3.3 模擬結果-------------------------------------- 42
第四章 鉛酸電池容量測試器之研製---------------------- 48
4.1 電池容量之定義-------------------------------- 48
4.2 既有鉛酸電池之容量檢測方法-------------------- 48
4.2.1 電池內部電阻之測定方式------------------- 54
4.3 所提之鉛酸電池放電器-------------------------- 58
4.3.1 所提鉛酸電池放電器之架構原理------------- 58
4.3.2 系統操作功能需求------------------------- 59
4.3.3 以PSoC實現之放電器系統電路------------- 62
4.4 實測結果-------------------------------------- 67
第五章 鉛酸電池之智慧型殘餘電量估測------------------ 76
5.1 前言------------------------------------------ 76
5.2 可拓理論-------------------------------------- 76
5.2.1 可拓物元概念----------------------------- 77
5.2.2 可拓數學--------------------------------- 79
5.3 所提可拓理論殘餘電量估測法-------------------- 86
5.3.1 電池殘餘電量可拓物元模型----------------- 86
5.3.2 可拓殘餘電量估測法之估測程序------------- 89
5.3.3 可拓理論殘餘電量估測法之測試結果--------- 95
5.4 可拓類神經網路殘餘電量估測法------------------ 97
5.4.1 可拓類神經網路之架構--------------------- 98
5.4.2 可拓類神經網路監督式學習訓練程序--------- 99
5.4.3 可拓類神經網路之辨識演算程序------------- 106
5.4.4 所提之可拓類神經殘餘電量檢測法----------- 107
5.4.5 測試結果--------------------------------- 108
第六章 結論---------------------------------------- 112
6.1 總結------------------------------------- 112
6.2 未來研究方向------------------------------ 113
參考文獻 ------------------------------------------ 114
作者簡歷 ------------------------------------------ 121
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