摘要
电驱桥作为新能源工程车辆的核心零部件,在面对企业数字化变革时,研发目标除了传统的减重、降本和性能提升外,还应该加入数据采集、大数据分析的软硬件应用,并在此基础上建立属于自己的大数据库及数据智能提炼分析工具,从而依靠先发优势占领未来工程车辆大数据平台的领导地位。基于数据管理知识体系(DMBOK)的数据科学过程迭代模型,结合公司新能源工程车辆电驱桥业务实际发展需要,通过增加一系列传感器进行数据采集,再经过车载终端和企业云平台对数据进行分析提炼,最后通过算法挖掘单个数据以及各数据组合背后的价值并进行反馈。该技术不但可以对现有服役产品进行实时监控、寿命预警和故障诊断,还可以为研发及时提供准确的客户痛点和设计优化方向,减少设计冗余和规避设计风险,真正达到提质降本的目的。
Electric drive axle is the core component of new energy engineering vehicles.In the face of the digital transformation of enterprises,in addition to the traditional weight reduction,cost reduction and performance improvement,the software and hardware applications of data acquisition and big data analysis should also be added to the research and development goals.On the basis,the own big database and intelligent data extraction and analysis tools were establish,so as to occupy the leading position of the future engineering vehicle big data platform by relying on the first-mover advantage.Based on the iterative model of data science process of DMBOK,combined with the actual development needs of the company’s new energy engineering vehicle electric drive axle business,data was collected by adding a series of sensors,and then the data was analyzed and refined through the vehicle terminal and enterprise cloud platform.Finally,the algorithm was used to mine the value behind a single data and each data combination and feedback.It can not only carry out real-time monitoring,failure warning and fault diagnosis of existing service products,but also provide accurate customer concerns and design optimization directions for R&D in time,reduce design redundancy and avoid design risks,and truly achieve the purpose of improving quality and reducing cost.
作者
宋锋
李家扩
魏永祥
武帅
Song Feng;Li Jiakuo;Wei Yongxiang;Wu Shuai(Business School of Hunan University,Changsha 410082,China;Sany Heavy Industry Co.,Ltd.,Changsha 430100,China)
出处
《机电工程技术》
2023年第5期159-162,227,共5页
Mechanical & Electrical Engineering Technology
