基于探索性数据分析的电动矿卡动力电池故障影响因素研究  

Research on the Influencing Factors of Electric Mining Truck Power Battery Failure Based on Exploratory Data Analysis

作　　者：郑明芽 郑晓东 王薇薇 阙忠灏 陶海豹 彭倩 ZHENG Mingya;ZHENG Xiaodong;WANG Weiwei;QUE Zhonghao;TAO Haibao;PENG Qian(Fujian Xinhuadu Engineering Co.,Ltd.,Xiamen 361000,China;School of Mechanical and Automotive Engineering,Xiamen University of Technology,Xiamen 361024,China)

机构地区：[1]福建省新华都工程有限责任公司,福建厦门361000 [2]厦门理工学院机械与汽车工程学院,福建厦门361024

出　　处：《煤矿机电》2025年第1期91-95,共5页Colliery Mechanical & Electrical Technology

摘　　要：露天电动矿卡载重量大、工作环境恶劣、行驶坡度变化较大,相比其他应用场景,矿卡动力电池故障原因更为复杂。为了提升动力电池的可靠性与环境适应性,提出一种基于探索性数据分析(Exploratory Data Analysis, EDA)的电动矿卡动力电池故障影响因素分析方法。采集真实工况下的电动矿卡行驶数据并构建动力电池故障数据集;通过可视化分析和皮尔逊相关性分析等探索性分析技术,深入挖掘电动矿卡动力电池故障的影响因素。结果表明:坡度、载重、动力电池的电池组总电流、电池组总电压、电池电量状态SOC和电芯温度是导致电动矿卡电池故障的主要影响因素,通过EDA分析动力电池故障情况,为后期的故障诊断工作奠定了基础。The open-pit electric mining truck has a large load capacity,harsh working environment,and significant changes in driving slope.Compared to other application scenarios,the causes of power battery failures in mining trucks are more complex.In order to improve the reliability and environmental adaptability of power bateries,a fault influencing factor analysis method for electric mining truck power batteries based on Exploratory Data Analysis(EDA)was proposed.Driving data of electric mining trucks under real working conditions was collected and a dataset of power battery faults were constructed.Through exploratory analysis techniques such as visual analysis and Pearson correlation analysis,we aim to explore the influencing factors of power battery failures in electric mining trucks.The results indicated that slope,load capacity,total current and voltage of the power battery pack,battery state of charge(SOC),and cell temperature were the main influencing factors causing faults in electric mining truck batteries.Power battery faults analyzed by EDA lays the foundation for later fault diagnosis work.

关 键 词：电动矿卡 探索性数据分析 皮尔逊相关性分析 可视化 

分 类 号：TD57[矿业工程—矿山机电]