本文提出一種新的尋找最佳化五階段定電流充電法之充電電流設定值的方法，本方法首先透過使用交流阻抗分析來建立鋰離子電池等效電路模型，並據以推導充電時間及充電電能損失條件下之數學模型。接著使用灰狼演算法在同時考量充電時間及充電電能損失來尋找最佳化充電電流設定。本文充電器功率級電路採用基於模型預測控制之同步降壓轉換器，並使用TI C2000 系列微控制器實現數位控制和五階段定電流充電法功能。
根據實驗結果顯示，所提之充電方具法有最低的充電溫升及最佳的充電效率；相較於傳統1C 定電流-定電壓充電法(CC-CV)，充電時間、最大充電溫升、平均充電溫升及充電效率分別可改善5.33%、25.99%、19.59%及0.48%；相較於僅考慮充電時間的最佳化方法，最大充電溫升、平均充電溫升及充電效率分別可改善12.54%、5.74%及0.21%。此外，經過循環壽命測試後，相較於傳統1C CC-CV 充電法與僅考慮充電時間的最佳化方法，本文所提方法之循環壽命可分別改善79.6%及40.2%。

In this dissertation, a novel method is proposed to search for the optimal charging pattern of the five-stage constant current charging method. Firstly, a detailed equivalent circuit model of the lithium-ion battery obtained by Electrochemical Impedance Spectroscopy analysis is utilized to derive the mathematical expression of the charging time and the charging loss of the battery. Next, the grey wolf optimization method is employed to find the optimal charging pattern (OCP), which simultaneously takes the charging time and charging loss into account. In the dissertation, the power stage of the charger is implemented by using the synchronous-rectified buck converter based on model predictive control. The digital peripheral module, and five-stage charging method using OCP are implemented by using the C2000 digital signal controller from Texas
Instruments(TI) Corporation.
According to the experimental results, the obtained OCP has the lowest temperature rise and the best charging efficiency. Compared with the conventional constant current-constant voltage charging technique with 1C charging current, the charging time, maximum temperature rise, average temperature rise, and charging efficiency are improved by 5.33%, 25.99%, 19.59%, and 0.48%, respectively. Comparing with the results obtained by the optimization method, which only takes the charging time into account, the maximum temperature rise, average temperature rise, and charging efficiency are improved by 12.54%, 5.74%, and 0.21%, respectively. In addition, cycling results also show that the life cycle can be improved by 79.6% and 40.2% compared with the CC-CV charging method and the optimization result obtained by considering only the charging time.

[1] K.M. Tsang and W.L. Chan, “Current sensorless quick charger for lithium-ion batteries,” Energy Conversion and Management, vol. 52, pp.1593-1595, March 2011.
[2] Guan-Chyun Hsieh, Liang-Rui Chen, and Kuo-Sun Huang, “Fuzzy controlled lithium-Ion battery charge system with active state of charge controller,” IEEE Transactions on Industrial Electronics, vol. 48, no. 3, June 2001.
[3] Liang-Rui Chen, Roy Chaoming Hsu and Chuan-Sheng Liu, “A design of a grey-predicted lithium-ion battery charge system,” IEEE Transactions on Industrial Electronics, vol. 51, no. 6, June 2008.
[4] Liang-Rui Chen, “PLL-based battery charge circuit topology,” IEEE Transactions on Industrial Electronics, vol. 48, no. 3, June 2001.
[5] L. R. Chen, J. J. Chen, N. Y. Chu, and G. Y. Han, ”Current pumped battery charger,” IEEE Transactions on Industrial Electronics, vol. 55, no. 6, pp. 2482- 2488, June 2008.
[6] Jun Li, Edward Murphy, Jack Winnick, and Paul A. Kohl, “The effects of pulse charging on cycling characteristics of commercial lithium-ion batteries,” Journal of Power Sources, vol. 102, pp. 302-309, December 2001.
[7] P.E. De Jongh and P.H.L. Notten, “Effect of current pulses on lithium intercalation batteries,” Solid State Ionics 148, pp. 259-268, June 2002.
[8] L. R. Chen, “A design of an optimal battery pulse charge system by frequency-varied technique”, IEEE Transactions on Industrial Electronics, vol. 54, no. 1, pp.398-405, February 2007.
[9] L. R. Chen, “A design of duty-varied voltage pulse charger for improving lithium-ion battery-charging response”, IEEE Transactions on Industrial Electronics, vol. 56, no. 2, pp.480-487, February 2009.
[10] S. M. Isuru Niroshana and Siriroj Sirisukprasert, “An adaptive pulse charging algorithm for lithium batteries”, 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), June 2017
[11] S. M. Isuru Niroshana and Siriroj Sirisukprasert, “Adaptive pulse charger for li-ion batteries”, 8th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES), May 2017
[12] Huazhen Fang, Christopher Depcik and Vadim Lvovich, “Optimal pulse-modulated lithium-ion battery charging algorithms”, Journal of Energy Storage, vol. 15, pp.359-367, February 2018.
[13] Shun-Chung Wang, Guan-Jhu Chen and Yi-Hua Liu, “Adaptive charging strategy with temperature rise mitigation and cycle life extension for li-ion batteries”, CPSS Transactions on Power Electronics and Applications, vol. 3, pp.202-212, September 2018.
[14] Yizhao Gao , Xi Zhang , Bangjun Guo, Chong Zhu, Jochen Wiedemann, Lin Wang, and Jianhua Cao,“Health-aware multiobjective optimal charging strategy with coupled electrochemical-thermal-aging model for lithium-ion battery”, IEEE Transactions on Industrial Informatics, vol. 16, no.5, pp.3417-3429, May 2020.
[15] Gao‐Long Zhu, Chen‐Zi Zhao, Jia‐Qi Huang, Chuanxin He, Jian Zhang, Shaohai Chen, Lei Xu, Hong Yuan, and Qiang Zhang,“Fast Charging Lithium Batteries: Recent Progress and Future Prospects”, Small, vol. 15, no.15, 1805389, March 2019.
[16] Chien-Hsing Lee, Ming-Yang Chen and Shih-Hsien Hsu, Joe-Air Jiang, “Implementation of a SOC-based four-stage constant current charger for Li-ion batteries”, Journal of Energy Storage, vol. 18, pp.528-537, August 2018.
[17] Thanh Tu Vo, Xiaopeng Chen and Weixiang Shen, Ajay Kapoor, “New charging strategy for lithium-ion batteries based on the integration of Taguchi method and state of charge estimation”, Journal of Power Sources, vol. 273, pp.413-422, January 2015.
[18] Chien-Hsing Lee, Ting-Wei Chang and Shih-Hsien Hsu, Joe-Air Jiang, “Taguchi-based PSO for searching an optimal four-stage charge pattern of Li-ion batteries”, Journal of Energy Storage, vol. 21, pp.301-309, February 2019.
[19] Shunli Wang, Carlos Fernandez, Yongcun Fan, Juqiang Feng, Chunmei Yu, Kaifeng Huang, and Wei Xie, “A novel safety assurance method based on the compound equivalent modeling and iterate reduce particle‐adaptive Kalman filtering for the unmanned aerial vehicle lithium ion batteries”, Energy Science & Engineering, vol. 8, no. 5, pp.301-309, January 2020.
[20] Shun-Li Wang, Carlos Fernandez, Wen Cao, Chuan-Yun Zou, Chun-Mei Yu, and Xiao-Xia Li, “An adaptive working state iterative calculation method of the power battery by using the improved Kalman filtering algorithm and considering the relaxation effect”, Energy Science & Engineering, vol. 428, no. 15, pp.67-75, July 2019.
[21] Wen Cao, Shun‐Li Wang, Carlos Fernandez, Chuan‐Yun Zou, Chun‐Mei Yu, and Xiao‐Xia Li, “A novel adaptive state of charge estimation method of full life cycling lithium‐ion batteries based on the multiple parameter optimization”, Energy Science & Engineering, vol. 7, no. 5, May 2019.
[22] Shun‐Li Wang, Chun‐Mei Yu, Carlos Fernandez, Chen, Ming-Jie, Li, Gui-Lin, Liu, and Xiao-Han “Adaptive State-of-Charge Estimation Method for an Aeronautical Lithium-ion Battery Pack Based on a Reduced Particle-unscented Kalman Filter”, Journal of Power Electronics, vol. 18, no. 4, pp.1127-1139, July 2018.
[23] Lan-Ron Dung, and Jieh-Hwang Yen,” ILP-based algorithm for lithium-Ion battery charging profile,” IEEE International Symposium on Industrial Electronics (ISIE), pp. 2286-2291, July 2010.
[24] Y. H. Liu, J. H. Teng, and Y. C. Lin, “Search for an optimal rapid charging pattern for li-ion batteries using ant colony system algorithm,” IEEE Transactions on Industrial Electronics, vol. 52, no. 5, pp. 1328-1336, October 2005.
[25] Y. H. Liu and Y. F. Luo, “Search for an optimal rapid charging pattern for Li-ion batteries using Taguchi approach,” IEEE Transactions on Industrial Electronics, vol. 57, no. 12, pp. 3963-3971, December 2010.
[26] Y. H. Liu, C. H. Hsieh, and Y. F. Luo, “Search for an optimal rapid charging pattern for Li-ion batteries using consecutive orthogonal arrays,” IEEE Transactions on Industrial Electronics, vol. 26, no. 2, pp. 654-661, January 2011.
[27] Shun-Chung Wang and Yi-Hua Liu, “A PSO-Based fuzzy-Controlled searching for the optimal charge pattern of Li-ion Batteries,” IEEE Transactions on Industrial Electronics, vol. 62, pp. 2983-2993, May 2015.
[28] Peter M. Attia, Aditya Grover, Norman Jin, Kristen A. Severson, Todor M. Markov, Yang-Hung Liao, Michael H. Chen, Bryan Cheong, Nicholas Perkins, Zi Yang, Patrick K. Herring, Muratahan Aykol, Stephen J. Harris, Richard D. Braatz, Stefano Ermon, and William C. Chueh, “Closed-loop optimization of fast-charging protocols for batteries with machine learning”, Nature, vol. 578, pp. 397-402, February 2020.
[29] Abdul Basit Khan and Woojin Choi, ”Optimal charge pattern for the high-performance multistage constant current charge method for the li-Ion batteries,” IEEE Transactions on Energy Conversion, pp. 1132-1140, September 2018.
[30] P. H. L. Notten, J. H. G. Op het Veld, and J. R. G. van Beek, “Boostcharging Li-ion batteries: A challenging new charging concept,” Journal of power Source, vol. 145, no. 1, pp. 89-94, July 2005.
[31] Seyedali Mirjalili, Seyed Mohammad Mirjalili, Andrew Lewis,” Grey wolf optimizer”, Advances in Engineering Software, vol. 69, pp.46-61, March 2014.
[32] 孫清華，「可充電電池技術大全」，全華科技圖書股份有限公司，2003年9月。
[33] 屠海令、吳伯榮、朱磊，「先進電池－電化學電源導論」，工業出版社冶金，2006年5月。
[34] 陳羿廷、陳玉惠，「高分子電解質在鋰二次電池上之應用研究現況」，中原大學化學研究所專題報導，民國九十三年第六十二卷第四期。
[35] B. Schweighofer, K. M. Raab, and G. Brasseur, “Modeling of high power automotive batteries by the use of an automated test system,” IEEE Transactions on Instrumentation and Measurement, vol. 52, no. 4, pp. 1087-1091, August. 2003.
[36] Z. M. Salameh, M. A. Casacca, andW. A. Lynch, “A mathematical model for lead-acid batteries,” IEEE Transactions on Energy Conversion, vol. 7, no. 1, pp. 93-98, March 1992.
[37] 劉峰其，「非線性鋰電池之充放電模型」，國立中央大學電機工程碩士論文，民國九十九年六月。
[38] Samsung Inc., “Lithium-ion battery-INR18650-25R,” Specification of product, 2014.
[39] Z. Chen, B. Xia, C. C. Mi, and R. Xiong,“Loss-Minimization-Based Charging Strategy for Lithium-Ion Battery,” IEEE Transactions on Industrial Applications, vol. 51, no. 5, pp. 4121-4129, September 2015.
[40] 王順忠，「電力電子學」，臺灣東華書局股份有限公司，2001年。
[41] R. W. Erickson and D. Maksmovic, “Fundamentals of Power Electronics,” 2rd Edition, 2000.
[42] 鄭力仁，「雙向升降壓直流-直流轉換器研製」，國立臺灣科技大學電機工程碩士論文，民國一零四年七月。
[43] Texas Instruments, “TMS320F28004x Piccolo Microcontrollers,” Available at http://www.ti.com/.
[44] Liuping,“Model Predictive Control System Design and Implementation Using MATLAB, ” 2009.
[45] 林哲綱，「以模型預測控制為基礎之鋰離子電池充電演算法」，國立臺灣科技大學電機工程碩士論文，民國一零八年七月。
[46] Tobias Geyer, Georgios Papafotiou, Roberto Frasca, and Manfred Morari,“Constrained Optimal Control of the Step-Down DC–DC Converter,” IEEE Transactions on Power Electronics, vol. 23, no. 5, pp. 2454-2464, September 2008.
[47] 許育豪，「多步預測型控制器達成無轉軸偵測元件磁通切換電動機驅動系統的研製」，國立臺灣科技大學電機工程碩士論文，民國一零八年七月。
[48] 劉元凱，「以電池等效模型為基礎之五階段定電流充電法最佳充電電流值搜尋」，國立臺灣科技大學電機工程碩士論文，民國一零七年七月。
[49] 林俊偉，「使用粒子群演算法之數位同步整流返馳式轉換器PID參數最佳化技術」，國立臺灣科技大學電機工程碩士論文，民國一零八年七月。
[50] 許富昱，「基於模型預測控制之新型鋰離子電池充電演算法」，國立臺灣科技大學電機工程碩士論文，民國一零六年七月。
[51] 鍾瑋芯，「鋰離子電池充電方法之評估」，國立臺灣科技大學電機工程碩士論文，民國一零九年六月。
[52] 劉俊良，「以模糊田口為基礎之新型電池充電機」，國立臺灣科技大學電機工程博士論文，民國一零三年七月。
[53] 羅一峰，「運用田口方法之鋰電池最佳化快速充電波形搜尋」，國立臺灣科技大學電機工程博士論文，民國九十九年八月。
[54] 陳蓉賢，「以模糊控制為基礎之鋰離子電池模組充電技術開發」，國立臺灣科技大學電機工程碩士論文，民國一零一年七月。
[55] J.W. Huang, Y.H. Liu, S.C. Wang, Z.Z. Yang, “Fuzzy-Control-Based Five-Step Lithium-Ion Battery Charger,” IEEE International Conference on Power Electronics and Drive Systems (PEDS), 2009.