论文标题
使用深度学习和随机优化对锂离子电池的最先进估计
State-of-charge Estimation of a Li-ion Battery using Deep Learning and Stochastic Optimization
论文作者
论文摘要
本文介绍了一项新颖的经验研究，用于估计锂离子（锂离子）电池的电荷状态（SOC），该电池使用了带有三个隐藏层的深度学习模型。我们对一系列应用于Panasonic 18650pf锂离子电池进行建模。我们的结果表明，优化算法的选择会影响模型性能。所提出的模型能够在所有驱动周期中实现小于1.0％的误差。
This article presents a novel empirical study for the estimation of the State of Charge (SOC) of a lithium-ion (Li-ion) battery which uses a deep learning model with three hidden layers. We model a series of ten vehicle drive cycles that were applied to a Panasonic 18650PF Li-ion cell. Our results show that the choice of the optimization algorithm affects the model performance. The proposed model was able to achieve an error smaller than 1.0% in all drive cycles.
