一个扩展的非线性双电容模型的两步识别方法
Jose Genario de Oliveira1, Cisel Aras2, Pankaj Pallewar3
1Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems, Vienna, Austria.
Heliyon
|September 23, 2024
概括
这项研究增强了用于汽车应用的离子电池模型,提高了在不同负载下放电能力预测的准确性. 新型号在动态测试中提供了更好的性能和更容易的参数化.
科学领域:
- 电化学 电化学 电化学
- 计算机建模 计算建模
- 汽车工程 汽车工程
背景情况:
- 相当电路模型是汽车应用中的离子电池的标准.
- 现有的模型在不同的负载,动态测试和参数化中难以准确预测放电能力.
研究的目的:
- 为离子电池提出一个扩展的非线性双电容模型.
- 为了提高汽车应用的精度,计算速度和参数化方便性.
主要方法:
- 增加了依赖模型顺序和C率的参数.
- 开发了一种识别程序,利用伪线性问题的特征.
- 利用与单粒子模型的类比来减少搜索空间并增强可解释性.
主要成果:
- 扩展模型准确地捕捉了不同负载下的电池放电容量.
- 在LiFePO4数据集和现实的驱动周期上,获得了平均绝对平均误差约20mV.
- 与最先进的模型相比,表现出卓越的性能.
结论:
- 拟议的模型扩展有效地解决了传统等效电路模型的局限性.
- 在动态的汽车环境中为离子电池建模提供了强大的和可解释的解决方案.
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