Workshop on Prognostics and Health Monitoring of Lithium-ion Batteries

9 September 2011 City University of Hong Kong

workshop

Batteries are critical to the health and functional capabilities of many electronic products and systems. Lithium-ion batteries in particular are commonly found in consumer electronics and electric vehicles. The failure of a Li-ion battery can lead to reduced performance, faulty operation, and even catastrophic failure. An efficient method for battery monitoring would greatly improve the reliability of Li-ion batteries and the systems that depend on them.

A workshop on Prognostics and Health Monitoring of Lithium-ion Batteries was held on 9 September 2011 at the City University of Hong Kong (CityU). This workshop was co-organized by CityU PHM Centre, the Hong Kong Productivity Council, and the Hong Kong Automotive Parts and Accessory Systems (APAS) R&D Centre. Over 110 representatives from industry and academia attended this workshop.

The Vice President of Research and Technology at City University of Hong Kong, Prof. Gregory B. Raupp, gave the opening remarks. Seven experts then presented their work. Prof. Michael Pecht, Director of the Prognostics and Systems Health Management Centre, gave a presentation titled "Introduction to Electric Vehicles and Battery Management Systems." Mr. Anthony Shum from APAS presented on "Electric Vehicles Battery Management Systems." Mr. Terry Lo from Linear Technology Corporation shared his work on "High Performance BMS Design in Electronic Vehicles." Dr. Xiaojun Tan from Sun Yat-sen University presented his research on "Optimized Charge Control for Power Batteries in Vehicles." Dr. Eden Ma from the CityU PHM Centre gave a presentation on "Battery Management Systems: Their Problems and Solutions." Dr. Jonathan C. Y. Chung from the Department of Physics and Materials at CityU presented on "Failure Mechanisms of Lithium-ion Batteries." And Prof. Peng Yu from Harbin Institute of Technology gave a presentation on the topic of "Remaining Useful Life Estimation for Batteries: Data-driven Methods."

workshop workshop