新一代电动汽车电池能量管理系统:人工智能概述

Nayan Kumar , Prabhansu
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引用次数: 0

摘要

本文全面概述了人工智能(AI)及其子集——机器学习(ML)和深度学习(DL)在下一代电动汽车电池能量管理系统(BEMS)中的潜力。下一代BEMS由于监测电压和电流、估计充放电、均衡和保护电池、管理温度条件以及管理电池数据分析而受到能源部门专业人士的密切关注。讨论还强调了与基于人工智能的BEMS相关的挑战和机遇,考虑到效率、能源管理、可靠性、控制和寿命因素。最后,本文讨论了支持ai的BEMSs对下一代电动汽车的其他几个潜在破坏性影响。文章还强调了关键挑战,批判性地分析了BEMS最近的研究成果和空白。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Next-generation battery energy management systems in electric vehicles: An overview of artificial intelligence
This article proposes a comprehensive overview of the potential of artificial intelligence (AI) and its subsets-machine learning (ML) and deep learning (DL) in next-generation battery energy management systems (BEMS) for electric vehicles (EVs). Next-generation BEMS has gained close attention from professionals in the energy sectors due to monitoring voltage and current, estimating charge and discharge, equalizing and protecting the battery, managing temperature conditions, and managing battery data analytics. The discussion also highlights the challenges and opportunities associated with AI-based BEMS, considering efficiency, energy management, reliability, control, and life factors. Finally, the article discusses several other potential disruptive impacts of AI-enabled BEMSs for next-generation EVs. The article also highlights key challenges and critically analyzes recent research efforts and open gaps in BEMS.
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