本論文研究目的為基於鋰離子電池 (Lithium-­ion Battery) 之等效電路模型、熱動態模型、以及所建構之參數老化模型為基礎，應用無跡卡爾曼濾波器建立一含老化效應之估測器進行鋰離子電池溫度電壓響應、荷電狀態 (State of Charge, SOC)、健康狀態 (State of Health, SOH) 及剩餘使用壽命 (Remaining Useful Life, RUL) 之即時估測。參數老化模型鑑別為透過電化學阻抗頻譜之分析實驗 (Electrochemical Impedance Spectroscopy, EIS)，利用最小平方法 (Least Squares Method) 求得鋰離子電池在不同荷電狀態 (State Of Charge, SOC) 與不同操作溫度下所建構的加速老化實驗下之各等效電路參數老化趨勢。各參數包含等效串聯電阻 (Internal Resistance, Ri )、極化電阻(Polarization Resistance, Rp )、極化電容 (Polarization Capacitance, Cp )、擴散電阻 (Diffusion Resistance, Rd )、擴散電容 (Diffusion Capacitance, Cd )、下壓因子 (Depression Factor)，並將各式數學模型所描述之參數老化趨勢結果進行比較，建構符合鋰離子電池參數老化趨勢之模型。最後分別以不同荷電狀態以及不同等效老化時間之電池以不同充放電行程實驗做驗證，比較含老化效應之估測器與老化數學模型模擬之結果進行比較，藉由實驗驗證結果顯示，可發現含老化效應之估測器在非線性系統問題的處裡上，其精準度較模型之模擬更為良好。

Based on the equivalent circuit model, thermal dynamic model and the constructed aging model of lithium­-ion battery. This thesis uses unscented kalman filter to establish an estimator with aging effect for lithium-­ion battery real-­time estimation of temperature and voltage response, State of Charge (SOC), State of Health (SOH) and Remaining Useful Life (RUL). The parametric aging model is identified by the analysis experiment of electrochemical impedance spectroscopy (EIS), and the least square method is used to obtain aging parameters from the accelerated aging experiment of the lithium-­ion battery model under different state of charge and different operating temperatures. Each parameter includes equivalent series resistance (Ri), polarization resistance (Rp), polarization capacitance (Cp), diffusion resistance (Rd), diffusion capacitance (Cd) and depression factor. Then use different aging mathematical models to describe the aging trend of the parameters, and establish a lithium­-ion battery aging model. Finally, the batteries with different states of charge and different equivalent aging times are tested by different charge and discharge experiments. The estimator with aging effect is compared with the results of the mathematical model simulation. The experimental verification results show that it can be found that the estimator with aging effect is more accurate than the model simulation in the nonlinear system problem.

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