利用模糊理論估測電池殘餘電量之系統設計

Estimating Battery State-of-Charge Using Fuzzy Theory Applied to Battery Management System

李政芳(Cheng-Fang Lee)

指導教授 ： 王仲淳

元智大學/電機通訊學院/電機工程學系/碩士(2011年)

摘要

本論文研究在於如何提升電池管理系統(Battery Management System)對於估測單元電池或電池組殘餘電量(State-of-Charge)上的準確度，因電池管理系統初始設計時對於電池殘餘電量的並未考慮電池本身與外在環境因素等影響，所以對於估測精確度有一定的誤差，且此誤差會因外在環境的不確定性導致其量測誤差值同樣呈現其不穩定的狀態，最終給與使用者錯誤的數據將會影響其輸出效能，甚至損害到電池與電池組。
經過策劃後的模糊理論系統(Fuzzy Theory System)在此估測方面可以提升此重要數據的準確度並考慮到外在環境溫度等變數，此為少數使用於磷酸鋰鐵系列電池的一種系統，且可套用其他種類的鋰電池。

關鍵字

電池管理系統 ； 電池殘餘電量 ； 模糊理論 ； 磷酸鋰鐵電池

並列摘要

This thesis mainly proposes an embedded Fuzzy Control system to a typical Battery Management System (BMS) that improves the accuracy and stability of its measured battery pack State-of-Charge (SoC) value. SoC is the equivalent of a fuel gauge in many battery systems. Due to the early design of the BMS, there exists a reasonable amount of miscalculation or estimation errors in this prototype system, therefore such inaccuracy will result an unstable situation when the batteries continue to operate. Users could receive inaccurate information from the BMS; as a result it may affect the performance of BMS not only to the battery packs but also to the load, and may even damage the battery system.
Embedded Fuzzy Logic system scheme is implemented as one of the solutions to counter this inaccuracy of the battery SoC value and also to improve its stability of the BMS while real-time SoC recalibration would maintain stable values for long-term performance.
This proposed method is not only an early implementation particularly for LiFePO4 battery or battery packs, but maybe also usable in other types of Li-ion batteries as well.

並列關鍵字

Battery Management System ； Battery State-of-Charge ； Fuzzy Theory ； LiFePO4 battery

參考文獻

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