鋰離子電池均衡控制=Equalization Control for Lithium-Ion Batteries(英文)

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書名:鋰離子電池均衡控制=Equalization Control for Lithium-Ion Batteries(英文)
ISBN:9787577209418
出版社:華中科技大學
著編譯者:陳劍 歐陽權 王志勝
叢書名:節能與新能源汽車關鍵技術研究叢書
頁數:208
所在地:中國大陸 *此為代購商品
書號:1655522
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【台灣高等教育出版社簡體書】 鋰離子電池均衡控制=Equalization Control for Lithium-Ion Batteries(英文) 787577209418 陳劍 歐陽權 王志勝
編輯推薦
《節能與新能源汽車關鍵技術研究叢書》聚焦國家節能減排和發展戰略性新興產業的需求,瞄準國際前沿科技,服務汽車產業轉型升級和國家經濟建設。叢書由清華大學歐陽明高院士擔任主編;作者由包含國家傑青、國家*專家在內的國內外一流學者親自領銜執筆,他們是國內外新能源汽車研究領域*高水平的代表,具有較高的權威性。著作內容為作者承擔國家重點研究項目成果的結晶,原創性強、學術水平高、體現自主知識產權。具有較高的學術價值、出版價值和產業應用價值。

內容簡介
鋰離子電池是市場上使用*廣泛的電池。其主要用途包括動力電池和儲能電池。在實際應用中,通常會串聯足夠多的電池以滿足高電壓需求,但電池組中的每個電池都不同,這會影響整個電池組的性能和壽命。如今,為了避免電池組中的不一致性,將採用電池均衡方法。電池均衡通常有兩種方法,包括保持電池之間的充電狀態一致和使電池之間的電壓相等。同時,均衡控制策略還包括主動小區均衡和被動小區均衡。與消耗能量的被動均衡策略相比,主動電池均衡方法在電池之間傳遞能量,效率更高,均衡時間更短。此外,由於主動細胞平衡策略的優勢,它們吸引了大量的研究和商業興趣。因此,主動均衡控制策略的設計對鋰離子電池組的安全和健康具有重要意義。現在,根據拓撲結構,所設計的均衡控制演算法可以分為三類:1)單元間均衡,2)基於模塊的單元均衡和3)基於電池組的充電均衡。

作者簡介
陳劍,浙江大學機械工程學院教授、博導,GJJ人才(青年),中國自動化學會控制理論專委會委員、TCCT新能源控制學組主任、車輛控制與智能化專委會委員、智慧教育專委會委員等。研究方向包括計算機視覺、機器人感知與控制,智能駕駛,氫電混合動力、燃料電池控制,非線性控制等。在機器人視覺伺服控制、非線性控制以及燃料電池系統建模與控制等領域取得了一些研究成果,合作發表了140餘篇SCI/EI論文。

目錄
Contents
1 Introduction - 1
1 1 Applications of Lithium-Ion Batteries - 1
1 1 1 The Crucial Role of Batteries - 1
1 1 2 Comparisons of Different Batteries - 4
1 2 Battery Inconsistency Phenomenon - 5
1 3 Crucial Role of Cell Equalization - 6
1 3 1 Voltage-Based Equalization - 7
1 3 2 SOC-Based Equalization - 7
References - 10
2 Overview of Cell Equalization Systems - 13
2 1 Classification and Comparisons of Cell Equalization Systems 13
2 1 1 Passive Cell Equalization Systems - 13
2 1 2 Active Cell Equalization Systems - 15
2 1 3 Comparisons of Cell Equalization Systems - 16
2 2 Commercial Equalizers - 17
2 2 1 Bidirectional Buck-Boost Converters - 17
2 2 2 Bidirectional Modified C?uk Converters - 19
2 3 Overview of Equalization Algorithms - 21
2 3 1 Cell-to-Cell Equalization Algorithms - 21
2 3 2 Cell-to-Pack-to-Cell Equalization Algorithms - 23
2 3 3 Charging Equalization Algorithms - 24
References - 25
3 Active Cell Equalization Topology - 29
3 1 Commonly Used Active Cell Equalization Topology - 29
3 1 1 Adjacent-Based Topology - 30
3 1 2 Non-adjacent-Based Topology - 35
3 1 3 Direct Cell-Cell Topology - 38
3 1 4 Mixed Topology - 40
3 2 Active Cell Equalization Topology Comparison - 41
3 2 1 Performance Comparison - 41
3 2 2 Economic Comparison - 45
3 2 3 Discussions - 48
References - 49
4 Optimal Active Cell Equalizing Topology Design - 55
4 1 Cell Equalizing System - 55
4 1 1 Equalizing System Model - 56
4 1 2 Consensus-Based Cell Equalizing Algorithm Design 57
4 2 Design of the Optimal Equalizing Topology - 59
4 2 1 Equalizing Time - 59
4 2 2 Traditional Cell Equalizing Topology - 61
4 2 3 Position Identification of the Added ICEs
for Reducing the Equalizing Time - 62
4 3 Simulation Results - 63
4 4 Experimental Results - 67
References - 72
5 Neural Network-Based SOC Observer Design for Batteries - 73
5 1 Battery Model - 73
5 2 RBF Neural Network Observer - 75
5 2 1 Neural Network Based Nonlinear Observer Design 75
5 2 2 Convergence Analysis - 77
5 3 Experiments and Simulations - 79
5 3 1 Experiment for Parameter Extraction - 79
5 3 2 Experiment for SOC Estimation - 81
References - 86
6 Active Cell-to-Cell Equalization Control - 89
6 1 Cell Equalizing System Model - 89
6 1 1 Battery Cell Model - 89
6 1 2 Bidirectional Modified C?uk Converter Model - 92
6 1 3 Cell Equalizing System Model - 93
6 2 Objective and Constraints of the Cell Equalizing Process - 95
6 2 1 Cell Equalizing Objective - 95
6 2 2 Cell Equalizing Constraints - 96
6 3 SOC Estimation Based Quasi-Sliding Mode Control
for Cell Equalization - 97
6 3 1 Adaptive Quasi-sliding Mode Observer Design
for Cells』 SOC Estimation - 97
6 3 2 Quasi-Sliding Mode-Based Cell Equalizing Control 99
6 4 Experiments - 102
6 4 1 Experimental Setup - 102
6 4 2 Experimental Results - 105
References - 107
7 Module-Based Cell-to-Cell Equalization Control - 109
7 1 Module-Based Cell-to-Cell Equalization Systems - 109
7 1 1 Equalizing Currents - 109
7 1 2 Cell Equalizing System Model - 112
7 1 3 Cell Equalizing Constraints - 113
7 2 Hierarchical Optimal Control Strategy - 114
7 2 1 Cell Equalizing Task Formulation - 115
7 2 2 Top Layer: Module-Level Equalizing Control - 116
7 2 3 Bottom Layer: Cell-Level Equalizing Control - 118
7 3 Results and Discussions - 119
7 3 1 Cell Equalizing Results - 120
7 3 2 Tests of Different Weight Selections - 121
7 3 3 Comparison With Decentralized Equalizing Control 123
7 3 4 Tests for Different Cells』 Initial SOCs - 124
References - 126
8 Module-Based Cell-to-Pack Equalization Control - 127
8 1 Improved Module-Based CPC Equalization System - 127
8 1 1 Equalizing Current Formulation - 128
8 1 2 Improved Module-Based CPC Equalization
System Model - 131
8 2 Two-Layer Model Predictive Control Strategy - 132
8 2 1 Cost Function Formulation - 132
8 2 2 Constraints - 133
8 2 3 Centralized MPC Design - 134
8 3 Two-Layer MPC for Cell Equalization - 134
8 3 1 Top-layer MPC: ML Equalizing Current Control - 135
8 3 2 Bottom-Layer MPC: CMC Equalizing
Current Control - 136
8 3 3 Computational Complexity Comparison With
Centralized MPC - 137
8 4 Results and Discussions - 139
8 4 1 Equalization Results - 140
8 4 2 Comparison With the Centralized MPC - 140
8 4 3 Comparison With a Commercial CPC-Based
Equalization Structure - 141

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