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Review of adaptive systems for lithium batteries State-of-Charge and State-of-Health estimation

机译:锂电池自适应系统的审查充电状态和健康状态估计

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High energy battery systems have recently appeared as an alternative Internal-Conbustion-Engine (ICE) based vehicle's powertrains. As a conquence, over the last few years, automotive manufacturers focused their research on electrochemical storage for electric (EV) and hybrid electric vehicles (HEV). In a lot of hybrid or electric applications, Lithium based batteries are used. To protect Lithium batteries and optimize their utilisation, a good State-of-Charge determiation is necessary. So three adaptive system used in the literature are presented in this article, the Kalman Filter, the Artificial Neural Network and the Fuzzy Logic systems.
机译:高能电池系统最近已成为替代基于内燃机(ICE)的车辆动力总成。作为结果,在过去的几年中,汽车制造商将研究重点放在了电动汽车(EV)和混合电动汽车(HEV)的电化学存储上。在许多混合动力或电动应用中,都使用了锂基电池。为了保护锂电池并优化其利用率,必须确定一个良好的荷电状态。因此,本文提出了文献中使用的三种自适应系统,即卡尔曼滤波器,人工神经网络和模糊逻辑系统。

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