Yi Wu 1,2, Youren Wang 1, Winco K.C. Yung 3, and Michael Pecht 2
1 College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2 CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA
3 Department of Industrial and System Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
Because of the complex physiochemical nature of the lithium-ion battery, it is difficult to identify the internal changes that lead to battery degradation and failure. This study develops an ultrasonic sensing technique for monitoring the commercial lithium-ion pouch cells and demonstrates this technique through experimental studies. Data fusion analysis is implemented using the ultrasonic sensing data to construct a new battery health indicator, thus extending the capabilities of traditional battery management systems. The combination of the ultrasonic sensing and data fusion approach is validated and shown to be effective for degradation assessment as well as early failure indication.