牵引电池循环性能预测的电化学模型研究进展:Ni-MH的实验研究与仿真

J. Bernard, A. Sciarretta, Y. Touzani, V. Sauvant-Moynot
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引用次数: 12

摘要

用于模拟电池循环性能的严格电化学模型已经成功开发并在文献中报道。与其他方法相比,它们构成了一种非常有前途的基于电池物理特性的充电状态(SoC)估计方法,因为SoC是这些物理模型的内部参数。然而,求解在线应用的电化学电池模型所需的计算时间要求开发一个简化的基于物理的电池模型。在这项工作中,我们的目标是提出并验证一个先进的Ni-MH电池的0d电化学模型,作为一个例子。该集总参数模型将用于设计扩展卡尔曼滤波器来预测镍氢电池的SoC。随后,对镍氢电池进行了广泛的实验研究,以更好地了解在两个电极上发生的物理化学现象的机制,并支持模型的发展。论文的最后一部分侧重于对该模型进行评估,并根据在镍氢密封电池上获得的实验结果以及相关的商用混合动力电池组进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in Electrochemical Models for Predicting the Cycling Performance of Traction Batteries: Experimental Study on Ni-MH and Simulation
Rigorous electrochemical models to simulate the cycling performance of batteries have been successfully developed and reported in the literature. They constitute a very promising approach for State-of-Charge (SoC) estimation based on the physics of the cell with regards to other methods since SoC is an internal parameter of these physical models. However, the computational time needed to solve electrochemical battery models for online applications requires to develop a simplified physics-based battery model. In this work, our goal is to present and validate an advanced 0D-electrochemical model of a Ni-MH cell, as an example. This lumped-parameter model will be used to design an extended Kalman filter to predict the SoC of a Ni-MH pack. It is presented, followed by an extensive experimental study conducted on Ni-MH cells to better understand the mechanisms of physico-chemical phenomena occurring at both electrodes and support the model development. The last part of the paper focuses on the evaluation of the model with regards to experimental results obtained on Ni-MH sealed cells but also on the related commercial HEV battery pack.
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