一个基于混合贝叶斯物理学信息的神经网络的离子电池预后框架
Renato G Nascimento1, Felipe A C Viana1, Matteo Corbetta2
1Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL, 32816, USA.
Scientific reports
|August 24, 2023
概括
我们开发了一种新的混合物理知情机器学习模型,用于可靠的离子电池 (Li-ion) 健康状况监测. 这种方法通过准确的电池性能预测,提高了电动汽车和飞机的安全性.
科学领域:
- 材料科学 材料科学 材料科学
- 电气工程 电气工程
- 计算机科学 计算机科学
背景情况:
- 离子电池 (Li-ion) 对于电力推进至关重要,要求准确的充电状态和健康监测可靠性.
- 传统的基于物理学的模型是计算密集型的,不适合实时预后和健康管理.
- 现有的机器学习方法往往难以捕捉复杂的电化学动态和不确定性.
研究的目的:
- 为准确的离子电池预测提出混合物理信息机器学习 (PIML) 方法.
- 解决电池管理系统中纯数据驱动或基于物理的模型的局限性.
- 通过先进的电池分析,提高电动推进系统的可靠性和安全性.
主要方法:
- 实现了一个PIML框架,使用循环神经网络 (RNN) 来直接数值集成管理方程.
- 使用多层感知子 (MLP) 来建模形式不确定性和变异MLP用于电池对电池的异常不确定性.
- 采用贝叶斯的方法,将整个车队的数据 (priors) 与电池特定的放电周期相结合.
主要成果:
- 拟议的混合PIML模型有效地模拟了离子电池的动态反应.
- 该框架准确地捕捉了电池性能中的模型形式和随机不确定性.
- 使用美国宇航局预测数据库电池数据集证明了有效性.
结论:
- 混合PIML方法为离子电池预后提供了一个计算效率高,准确的解决方案.
- 这种方法显著提高了电池监控电动推进应用的可靠性.
- 该框架为管理不同操作条件下的电池健康提供了一个强大的工具.
更多相关视频
10:41The Effect of Charging and Discharging Lithium Iron Phosphate-graphite Cells at Different Temperatures on Degradation
Published on: July 18, 2018
15.5K
11:25Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway
Published on: March 7, 2022
4.6K
相关概念视频
03:12Batteries and Fuel Cells
27.6K
A battery is a galvanic cell that is used as a source of electrical power for specific applications. Modern batteries exist in a multitude of forms to accommodate various applications, from tiny button batteries such as those that power wristwatches to the very large batteries used to supply backup energy to municipal power grids. Some batteries are designed for single-use applications and cannot be recharged (primary cells), while others are based on conveniently reversible cell reactions that...
27.6K
01:26Linear Approximation in Frequency Domain
110
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
110
01:20Maxwell-Boltzmann Distribution: Problem Solving
1.6K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.6K