基于LightGBM的电动汽车动力电池故障双层诊断模型  

Double-layer Diagnosis Model for Electric Vehicle Power Battery Faults Based on LightGBM

作　　者：伍毅平 杨傲然 陈家源 荣建 马俊 宋鹏 WU Yiping;YANG Aoran;CHEN Jiayuan;RONG Jian;MA Jun;SONG Peng(Beijing Key Laboratory of Traffic Engineering,Beijing University of Technology,Beijing 100124,China;College of Metropolitan Transportation,Beijing University of Technology,Beijing 100124,China;School of Civil Engineering,Guangzhou University,Guangzhou 510006,China)

机构地区：[1]北京工业大学交通工程北京市重点实验室,北京100124 [2]北京工业大学城市交通学院,北京100124 [3]广州大学土木工程学院,广州510006

出　　处：《北京工业大学学报》2025年第2期183-191,共9页Journal of Beijing University of Technology

基　　金：国家自然科学基金资助项目(52102403)。

摘　　要：动力电池是电动汽车的能量之源,需要准确预测动力电池故障并识别其故障类型以保障电动汽车的安全性和可靠性。基于10辆纯电动汽车6个月的实车监测数据,提取16个特征数据为输入,以电池故障类型为输出,通过模型训练和参数调优,建立了基于LightGBM的电动汽车动力电池故障双层诊断模型。上层模型用于判断车辆动力电池是否存在故障,下层模型对具体故障类型进行诊断分析。结果表明:该模型能够完全正确预测电动汽车动力电池是否发生故障,诊断故障类型的准确率达94.05%。同时,根据模型结果特征值排序筛选出了影响动力电池是否发生故障的主要特征。研究成果为识别电动汽车动力电池状态、分析故障类型以及诊断故障原因提供了方法支撑。Power battery is the energy source for electric vehicles.It is of great significance to ensure the safety and reliability of electric vehicles by accurately predicting power battery failures and identifying their fault types.Based on the 6-month actual vehicle monitoring data of 10 pure electric vehicles,16 feature data were extracted as input and the battery fault type was used as the output.A double-layer diagnosis model for electric vehicle power battery faults based on LightGBM was established through model training and parameter tuning.The upper-layer model was used to determine whether the vehicle power battery is fault.The lower-layer model diagnosed and analyzed the specific fault type.Results show that whether the electric vehicle power battery will be fault can be correctly predicted.The accuracy of diagnosing the fault type is 94.05%.Meanwhile,the main features that affect the failure of the power battery are screened out according to the ranking of the eigenvalues of the model results.This study provides an approach for identifying the state of electric vehicle power battery,analyzing the fault type and diagnosing the cause of the fault.

关 键 词：电动汽车 动力电池 故障诊断 LightGBM 双层模型 特征排序 

分 类 号：U491[交通运输工程—交通运输规划与管理]