针对目前我国电动汽车等领域使用的动力电池组寿命短、退货率高等问题，本项目提出了一种基于海量数据学习的动力电池智能成组方法。通过对电池充放电完整数据的自动采集，采用天线阵列空分接入技术完成数据的高效传输，进而对电池充放电海量数据进行非监督学习，研究其稀疏表示方法，抽取出能表征电池充放电特性和一致性的关键特征；然后，基于所抽取的一致性特征，采用稀疏图谱聚类方法完成充放电大规模数据的聚类；最终设计一套基于AGV小车的电池RFID高速可靠读写和多出口的动力电池自动成组分拣控制系统。通过本项目的研究，有望在密集节点无线传输、大规模数据学习理论与算法、动力电池智能配组控制技术与系统研究等方面取得突破；利用上述研究成果，可支撑我国动力电池生产过程的自动配组，大幅提升电池组内单体电池的一致性，延长整个电池组的使用寿命，同时提高电池成组生产效率。本项目对推动我国电动汽车产业也有十分重要的意义。

At present, many issues still exist in battery production in China, e.g., the rely of process control on the presence of experience, low-tech, labor-intensive, harsh production environment, etc., so that the return rate of battery packs is still high. This project will focus on the research on the key technologies to the automatic grouping of batteries as well as the intelligent control system for the grouping. The project intends to study the wireless data transmission technology for intensive nodes based on the antenna array space division access technology, and to construct the corresponding hardware system to acquire safely the battery charge and discharge big data and to transmit them efficiently; then unsupervised learning algorithms for the battery charge and discharge big data will be studied to obtain a sparse representation of them, which will be extracted as key features to characterize the power battery charge and discharge characteristics and battery consistency; The sparse representation of the battery charge/discharge big data will be then clustered using a graph spectral clustering algorithm, thereby improving the efficiency and effectiveness for battery grouping; An automatic sorting control system with multi-outputs will be built based on a RFID reader/writer installed on an automated guided vehicle . Breakthroughs are expected in a heterogeneous network of things, massive data learning theories and algorithms, control technologies and the system for intelligent grouping, etc. The research will promote the battery grouping technologies in China as well as the intelligentization for battery manufacturers, meanwhile certain significance is expected for Chinese electric vehicles manufacturer.