电子测量与仪器学报

郑雪莹,邓晓刚,曹玉苹.基于能量加权高斯过程回归的锂离子电池健康状态预测[J].电子测量与仪器学报,2020,34(6):63-69

基于能量加权高斯过程回归的锂离子电池健康状态预测

State of health prediction of lithium-ion batteries based on energy-weighted Gaussian process regression

DOI：

英文关键词:Gaussian process regression empirical mode decomposition capacity recovery phenomena lithium-ion battery state of health

基金项目:国家自然科学基金 ( 61403418, 21606256 )、中央高校基本科研业务费专项资金 ( 17CX02054 )、山东省重点研发计划(2018GGX101025)、山东省自然科学基金(ZR2016FQ21,ZR2016BQ14)资助项目

作者	单位
郑雪莹	1.中国石油大学(华东)信息与控制工程学院
邓晓刚	1.中国石油大学(华东)信息与控制工程学院
曹玉苹	1.中国石油大学(华东)信息与控制工程学院

Author	Institution
Zheng Xueying	1.College of Information and Control Engineering,China University of Petroleum(East China)
Deng Xiaogang	1.College of Information and Control Engineering,China University of Petroleum(East China)
Cao Yuping	1.College of Information and Control Engineering,China University of Petroleum(East China)

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中文摘要:

针对容量再生现象影响锂离子电池健康状态预测(SOH)建模精度的问题,提出一种经验模态分解(EMD)的能量加权高斯过程回归(EWGPR)方法。该方法将容量再生现象看作是锂离子电池容量衰减过程的能量凸现,利用 EMD 分解获得样本的能量分布情况,根据能量情况计算每个样本的权重,进而建立基于能量加权高斯过程回归的锂离子电池 SOH 预测模型。基于 NASA 锂电池数据集的仿真实验结果表明,EWGPR 方法比基本 GPR 算法具有更高的精度和适应性,单步预测和多步预测的均方根误差(RMSE)分别减少了 3%和 10%。

英文摘要:

Aiming at the problem that the capacity regeneration phenomenon affects the state of health ( SOH) prediction accuracy of lithium-ion batteries, an energy-weighted Gaussian process regression (EWGPR) of empirical mode decomposition (EMD) method is proposed. This method regards the capacity recovery phenomenon as the energy projection of the capacity decay process of lithium-ion battery. The energy distribution is obtained by EMD decomposition and the sample weights are calculated according to the energy distributions. Then the SOH prediction model of lithium-ion battery based on EWGPR is established. The experimental simulation results on the NASA lithium-ion battery datasets show that the EWGPR algorithm has higher accuracy and adaptability than the basic GPR algorithm, and the root mean square error (RMES) for single-step and multi-step predictions are decreased by more than 3% and 10%, respectively.

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