- 學位論文
以查表方式建模之鋰離子電池卡爾曼濾波器電量估測
State of Change Estimation of lithium-ion battery by Kalman Filter with Table-Look-up Modeling
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摘要
在本論文中，我們利用等效電路來表示鋰離子電池電化學反應，等效電路中的參數則是以電池充放電測試數據辨識得到，並以模擬充放電計算結果與測試數據比較，以確認參數辨識的可信度。等效電路內之電容(C)參數是否可以忽略不計以簡化模型，進而可簡化以卡曼濾波電量估測的計算，亦為本論文研究項目之一。因此，我們將使用下列三種方法來進行卡曼濾波電量估測：(1)查表法。(2)簡化ECM建模方式。(3)完整ECM建模方式。比較從各式不同充放電情境得到的模擬結果與電池測試數據，驗證了我們所提出方法的可行性；在動態充放電模擬結果顯示，完整的ECM，亦即不忽略電容，確實可得到較佳的電量估測結果。
關鍵字
鋰離子電池電量估測並列摘要
In this thesis, we will utilize the equivalent circuit to represent the electrochemical reaction of lithium-ion battery from which the characteristics can be realized by simulation and capacity level of batteries can be estimated. The impact of the equivalent circuit of the capacitance(C) parameters can be taken into consideration. In other words, the goal of this research is to effectively improve the overall model simulation results in lithium-ion batteries. The implementation of model simulation works quite closely to the actual measured data. There are three different approaches to research: (1) Table Look-up Modeling. (2) Simplified equivalent circuit modeling. (3) Integrity equivalent circuit modeling. The above three modeling techniques are based upon the Kalman filter recursive operation in order to simulate lithium-ion battery charging and discharging experiments in which taking advantage of the ability of filter to optimize automatic data processing feedback and to recursively eliminate measurement errors and processing noise. By comparing massive model simulation and experimental results it is shown satisfactory results and fair performance which in turns validate our proposed state of charge estimation method.
參考文獻
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