<![CDATA[This research aims to address challenges in efficient energy storage in electric vehicles, particularly those using lithium-ion batteries. The research focuses on voltage imbalances in battery packs with cells connected in series, which can reduce the battery pack's lifespan. We investigated active balancing charging methods using bidirectional fly-back converters in both pack-to-cell and cell-to-pack modes. Current charging methods face limitations such as prolonged balancing times, circuit complexity, and low efficiency. To overcome these challenges, this research proposes integrating an artificial intelligence approach using adaptive neuro-fuzzy inference system (ANFIS) control. This approach allows for dynamic adjustment of duty cycles, expediting the balancing process. Experimental results show that employing ANFIS control can significantly reduce balancing times. In pack-to-cell mode, balancing time decreased from 660 seconds to 600 seconds, while in cell-to-pack mode, it decreased from 660 seconds to 580 seconds. This research makes a significant contribution to the development of more efficient charging technology for lithium-ion batteries in electric vehicles. Its potential implications include improved battery lifespan and electric vehicle performance in the future.]]>
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