Lead-acid Battery Automatic Grouping System Based on Graph Cuts

Abstract

The inconsistent parameters of different lead-acid batteries in the same battery pack will result in the reduction of battery pack capacity and life. It is difficult to fundamentally solve the inconsistent parameters problem of lead-acid batteries. Battery grouping is a simple and effective approach for solving the performance inconsistency problem by packing batteries with close characteristic parameters. The traditional manual grouping method is labor intensive and prone to errors in measurement that will result in wrong grouping. In this article, a novel lead-acid battery automatic grouping system is developed based on graph cuts. This system consists of a PC server end, a wireless router, and several portable grouping devices. Based on embedded real-time operating, the proposed system realizes battery parameters characterization, data uploading, and automatic grouping processes. Using this battery automatic grouping system, batteries with close charge and discharge characteristics will be grouped into the same battery pack. Experimental results demonstrate that the proposed approach can provide superior performance over traditional manual methods.

Keywords:

• battery grouping
• graph cuts
• termination voltage
• static voltage

Additional information

Notes on contributors

Yu Zeng

Yu Zeng received his B.S. and M.S. in electronic engineering from Hangzhou Dianzi University of China in 2001 and 2015, respectively. He joined Hangzhou Dianzi University, China, in 2001, where he is currently an assistant professor in the Department of Electronic and Information. His research interests include software engineering with particular current focus on embedded systems.

Yuxiang Yang

Yuxiang Yang received his B.S. and Ph.D. in control science and engineering from University of Science and Technology of China in 2008 and 2013, respectively. He joined Hangzhou Dianzi University, China, in 2013, where he is currently an assistant professor in the Department of Electronic and Information. His research interests include signal processing and computer vision, with current emphasis on graph cuts and stereo vision.

Zhiwei He

Zhiwei He received the B.S. and Ph.D. in information and communication engineering from Zhejiang University, China, in 2001 and 2006, respectively. He joined Hangzhou Dianzi University, China, in 2006, where he is currently a professor in the Department of Electronic and Information. He is a member of IEEE. His current research interests are in the areas of non-linear signal processing, machine learning, and vehicle electronics; his special current focus is on time series clustering, computer vision, and deep learning.

Mingyu Gao

Mingyu Gao received his M.S. in power electronics from Zhejiang University, China, in 1993 and his Ph.D. from Wuhan University of Technology, China, in 2013, in information and communication engineering. He joined Hangzhou Dianzi University, China in 2001, where he is currently a professor in the Department of Electronic and Information. He is a member of IEEE. His current research interests are in the areas of machine vision, industrial electronics, and vehicle electronics.

Caisheng Wang

Caisheng Wang received his B.S. and M.S. from Chongqing University, China, in 1994 and 1997, respectively, and his Ph.D. from Montana State University, Bozeman, in 2006, all in electrical engineering. From August 1997 to May 2002, he worked as an electrical engineer and was a vice department chair in Zhejiang Electric Power Test & Research Institute, Hangzhou, China. Since August 2006, he has been with Wayne State University, where he is currently an associate professor at the Department of Electrical and Computer Engineering. His current research interests include modeling and control of power systems and electric vehicles, energy storage devices, distributed generation and microgrids, alternative/hybrid energy power generation systems, and fault diagnosis and on-line monitoring of electric apparatuses.

Ming Hong

Ming Hong received his B.S. in motor control engineering from Zhejiang University, China, in 1997 and his M.S. from Zhejiang University, China, in 2002, in biomedical engineering. He joined Hangzhou Dianzi University, China in 2002, where he is currently an associate professor in the Department of Electronic and Information. His current research interests are in the areas of industrial electronics.