近年來鋰離子電池在可攜式產品、電動車及再生能源系統之能量儲存上扮演相當重要之角色。為了使鋰離子電池發揮最大性能，一個快速又精準的容量估測技術變得相當重要。
本文提出以交流阻抗為測試基礎對鋰離子電池進行殘餘容量估測(State of Charge, SOC)，運用類神經網路以所測試之交流阻抗以及不同充電電流和電池溫度作為輸入，進入學習訓練而得到電池殘餘容量。本文使用Bio-Logic VMP3恆電位/恆電流儀作量測以取得上述輸入資料，搭配MATLAB類神經網路軟體方塊進行訓練。
根據訓練之結果，本文類神經網路之效能在隱藏層中神經元數分別採用15、25以及35時，所估測到之SOC平均誤差值小於6%、5%以及2%。因此本文之技術可以被用來精確估算鋰離子之SOC。最後，將受訓練之類神經網路實現於 Microchip低成本微控器dsPIC33FJ16GS502，以驗證此方法的正確性。

Lithium ion (Li-ion) batteries play an important role in applications such as portable electronic, electrical vehicles and renewable energy systems. To maximize the performance of the Li-ion batteries, an accurate and fast battery state of charge (SOC) estimation technique is essential. In this thesis, an AC impedance based technique is proposed to estimate the SOC of Li-ion batteries. The proposed technique includes an artificial neural network (ANN) which can be used to calculate the SOC according to the AC impedance values, battery current and battery temperature data. In this thesis, these input data is obtained using the Bio-Logic VMP3 potentiostats/galvanostats device, and the ANN is trained using the Neural Network Toolbox in MATLAB.
According to the trained results, the performance of the utilized ANN is related to the number of neurons in the hidden layer. The averages SOC estimation error is lower than 6 %, 5% and 2% when the number of neurons in the hidden layer is set as 15, 25 and 35, respectively. Therefore, the proposed technique can be utilized to estimate the SOC of Li-ion battery precisely. Finally, the trained ANN is implemented using a low cost microcontroller dsPIC33FJ16GS502 from Microchip to validate the correctness of the proposed method.

[1] S. Lee, J. Kim, J. Lee, and B. H. Cho, “State-of-charge and capacity estimation of lithium-ion batteryusing a new open-circuit voltage versus state-of-charge,” J. Power Sources,vol. 185, no. 2, pp. 1367–1373, Dec. 2008.
[2] J. Lee, O. Nam, and B.H. Cho, “Li-ion battery SOC estimation method based on the reducedorder extended Kalman filtering,” J. Power Sources,vol. 174, no. 1, pp. 9–15, Nov. 2007.
[3] Y. C. Chuang and Y. L. Ke, “High-efficiency and low-stress ZVT–PWM DC-to-DC converter for battery charger,” IEEE Trans. on Industrial Electronics, vol. 55, no. 8, pp.3030–3037, Aug. 2008.
[4] I. S. Kim, “Nonlinear state of charge estimator for hybrid electric vehicle battery,” IEEE Trans. on Power Electronics, vol. 23, no. 4, pp. 2027–2034, Jul. 2008.
[5] M. A. Alahmad and H. L. Hess, “Evaluation and analysis of a new solid-state rechargeable microscale lithium battery,” IEEE Trans. on Industrial Electronics, vol. 55, no. 9, pp.3391–3401, Sep. 2008.
[6] M. Dubarry, N. Vuillaume, and B. Y. Liaw, “From single cell model to battery pack simulation for Li-ion batteries,” J. Power Sources, vol. 186, no. 2, pp. 500–507, Jan. 2009.
[7] L. R. Chen, “PLL-based battery charge circuit topology,” IEEE Trans. on Industrial Electronics, vol. 51, no. 6, pp. 1344–1346, Dec. 2004.
[8] S. S. Zhang, “The effect of the charging protocol on the cycle life of a Li-ion battery,” J. Power Sources,vol. 161, no. 2, pp. 1385–1391, Oct. 2006.
[9] B. P. McGrath, D. G. Holmes, P. J. McGoldrick, and A. D. McIver, “Design of a soft-switched 6-kW battery charger for traction applications,” IEEE Trans. on Power Electronics, vol. 22, no. 4, pp. 1136–1144, Jul. 2007.
[10] 朱順益，「鋰電池快速充電波形設計」，義守大學電機工程研究所論文，2004年6月。
[11] 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，2004年第62卷第4期。
[12] 吳敏旭，「串聯電池組電池管理系統之開發」，長庚大學電機工程研究所論文，2004年5月。
[13] 李嘉猷，「應用DSP於電動車充電站快充控制系統之研究」，國立成功大學電機工程系碩士學位論文，2001年6月。
[14] 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。
[15] 羅一峰，「運用田口方法之鋰電池最佳化快速充電波形搜尋」，台灣科技大學電機工程博士論文，2006年8月。
[16] 李孜賾，「以模糊控制為基礎之五階段鋰電池充電機」，台灣科技大學電機工程研究所論文，2009年6月。
[17] M. Coleman, C. K. Lee, C. Zhu, and W. G. Hurley, “State-of-Charge Determination from EMF Voltage Estimation Using Impedance, Terminal Voltage,and Current for Lead-Acid and Lithium-Ion Batteries,” IEEE Trans. on Industrial Electronics, vol. 54, no. 5, pp. 2550-2557, Oct. 2007.
[18] Caumont O., et. al., “Energy Gauge for Lead-Acid Batteries in Electric Vehicles,” IEEE Trans. on Energy Conversion, vol. 15, No. 3, pp.354-360, Sep. 2000.
[19] G. Alber, and M. W. Migliaro, “Impedance testing-is it a substitute for capacity test?,” Telecommunications Energy Conference, pp. 245-249, 1994.
[20] L. M. Hofland, E. J. Stofel, and R.K. Taenaka, “Galileo probe Li-SO2 battery cell life testing,” IEEE Aerosp. Electron. Syst., pp. 14-18,1996.
[21] Pang, S., Farrell, J., Du, J., Barth, M., “Battery state-of-charge estimation,” Proceedings of the American Control Conference, vol. 2, pp. 1644 –1649, Jun. 2001.
[22] 賴世榮，「智慧型鋰離子電池殘存電量估測之研究」，中山大學電機工程學系碩士論文，民國2004年10月。
[23] Pop. V and Bergveld, H.J. and Notten, P.H.L and Regtien, P.P.L “State-of-the-Art of battery State-of-Charge determination” Measurement Science and Technology, vol. 16, no12, Oct. 2005.
[24] Y. S. Lee, W. Y. Wang, and T. Y. Kuo, “Soft computing for battery state-of-charge (BSOC) estimation in battery string systems,” IEEE Trans. on Industrial Electronics, vol. 55, no. 1, pp. 229–239, Jan. 2008.
[25] Sabine Piller, Marion Perrin, and Andreas Jossen, “Methods for state-of-charge determination and their applications, ” Journal of Power Source, vol.96, pp.113-120 , 2001
[26] Valer Pop, Henk Jan Bergveld, Dmitry Danilov, Paul P.L. Regtien, Peter H.L. Notten, Battery Management Systems_Accurate State-of-Charge Indication for Battery-Powered Applications (Philips Research Book Series), Springer, pp.87, May 2008
[27] G. Nagasubramanian, E. P. Roth, and D. Ingersoll, “Electrical and electrochemical performance characteristics of small commercial Li-ion cells,” Battery Conference on Applications and Advances, pp. 91-96,1999
[28] S. Piller, M. Perrin, A. Jossen, “Methods for state-of-charge determination and their applications,” J. Power Sources, vol. 96, no. 1, pp. 113-120, Jun. 2001.
[29] 羅一峰，「主動式即時電池殘量估測 Active Online Detection for Sate of Charge Analysis for Li-ion Battery」，101年資通所晶片次領域學研合作成果交流會。
[30] bidm.stat.fju.edu.tw:81/2013.../DM2013-0430/類神經網路觀念.doc
[31] 葉怡成，「類神經網路模式應用與實作」，儒林圖書出版，2003。
[32] M. C. Mabel and E. Fernandez, “Estimation of Energy Yield From Wind Farms Using Artificial Neural Networks,” IEEE Trans. Energy Convers., vol. 24, no. 2, pp. 459–464, Jun. 2009.
[33] O. S. Ebrahim, M. A. Badr, A. S. Elgendy,and P. K. Jain, “ANN-Based Optimal Energy Control of Induction Motor Drive in Pumping Applications,” IEEE Trans. Energy Convers., vol. 25, no. 3, pp. 652–660, Sep. 2010.
[34] K. Y. Lee, J. H. V. Sickel, J. A. Hoffman, W. H. Jung,and S. H. Kim, “Controller Design for a Large-Scale Ultrasupercritical Once-Through Boiler Power Plant,” IEEE Trans. Energy Convers., vol. 25, no. 4, pp. 2629–2637, Dec. 2010.
[35] S. V. Puranik, A. Keyhani, F. Khorrami, W. H. Jung,and S. H. Kim, “Neural Network Modeling of Proton Exchange Membrane Fuel Cell,” IEEE Trans. Energy Convers.,vol. 25, no. 2, pp. 474–483, Jun. 2010.
[36] G. Capizzi, F. Bonanno,and G. M. Tina, “Recurrent Neural Network-Based Modeling and Simulation of Lead-Acid Batteries Charge–Discharge,” IEEE Trans. Energy Convers.,vol. 26, no. 2, pp. 435–443, Jun. 2011.
[37] 朱凱、王正林，「精通MATLAB神經網絡」，電子工業出版，2010年1月。
[38] M. M. Gupta, L. Jin, and N.Homma, “Static and Dynamic Neural Networks”, Wiley, 2003.
[39] 黃嘉偉，「適用於快速變動環境之太陽能最大功率追蹤技術研究」，台灣科技大學電機工程博士論文，2012年7月。
[40] M. Yu, Y. Barsukov, and M. Vega,“Theory and Implementation of Impedance Track™ Battery Fuel-Gauging Algorithm in bq2750x Family,” TI. Application Report, Jan. 2008