摘要
由机器人与机器学习每日新闻的新闻记者兼工作人员新闻编辑-人工智能的新数据在一份新的报告中呈现。根据NewsRx记者来自新加坡新阿波雷的新闻报道，研究表明，"电池管理系统(BMSs)在电动汽车(EVs)中发挥着关键作用，严重依赖两个基本因素：充电状态(SOC)和健康状态(SOH)。"这项研究的资助机构包括中国奖学金委员会。新闻编辑们从新加坡纽卡斯尔大学的研究中获得了一句话：“然而，准确估计锂离子电池(li-i on)的SOC和SOH仍然是一个挑战。为了解决这个问题，许多研究人员转向了机器学习(ML)技术。这项研究全面概述了BMSs和ML，回顾了最近流行的ML方法估计SOC和SOH的研究。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting originating from Sing apore, Singapore, by NewsRx correspondents, research stated, “Battery management systems (BMSs) play a critical role in electric vehicles (EVs), relying heavily on two essential factors: the state of charge (SOC) and state of health (SOH).” Financial supporters for this research include China Scholarship Council. The news editors obtained a quote from the research from Newcastle University in Singapore: “However, accurately estimating the SOC and SOH in lithium-ion (Li-i on) batteries remains a challenge. To address this, many researchers have turned to machine learning (ML) techniques. This study provides a comprehensive overvi ew of both BMSs and ML, reviewing the latest research on popular ML methods for estimating the SOC and SOH.”
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