本文融入河流匯聚尋優概念至最佳化求解，並進而應用至充電效能之強化。此演算法之建構，乃經由觀察多條河流可自然匯集建構成主河道，進而形成最佳流動路徑，故具有應用潛力，並可應用至有效搜尋充電電池於不同電壓層級下所對應之最佳充電電流，不僅可維持較佳之充電能力，兼以具有較穩定之靜置穩態電壓，因而展現較優質之電池續航力。而為說明本文所提方法之實務應用價值，本文已將所提方法與多種不同充電電流情形相互比較，測試結果輔以證實本文所提方法於電池電能儲存及充電應用，具有研究遠景價值。

In this thesis, an application of river clustering optimization to enhance the battery charging performance is proposed. This algorithm is motivated from the observation on the river clustered through several creeks, hence forming an optimal flow path. Such a concept can be equivalently deemed to search an optimal charging current under different voltage levels while maintaining the sufficient charging capability and a satisfactory amount of residual power. In order to solidify the practical value of this proposed approach, the thesis has compared the method with different charging current under several scenarios. Test results have shown the promising research values of the application that is investigated.

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