Fuzzy-Rule-Based Failure Detection and Early Warning System for Lithium-ion Battery

• Main Author: Wu, Meng
• Other Authors: Chen, Yaobin
• Language: en_US
• Published: 2013
• Subjects: Lithium ion batteries; Electric vehicles; Hybrid electric vehicles; Storage batteries > Design and construction; Motor vehicles > Energy conservation; Fuzzy systems; Electric power system stability; Real-time control; Sustainable engineering > Research; Reliability (Engineering) > Mathematical models; Electric power systems > Control; Electrical engineering > Safety measures
• Online Access: http://hdl.handle.net/1805/3522

Indiana University-Purdue University Indianapolis (IUPUI) === Lithium-ion battery is one kind of rechargeable battery, and also renewable, sustainable and portable. With the merits of high density, slow loss of charge when spare and no memory effect, lithium-ion battery is widely used in portable electronics and hybrid vehicles. Apart from its advantages, safety is a major concern for Lithium-ion batteries due to devastating incidents with laptop and cell phone batteries. Overcharge and over-discharge are two of the most common electrical abuses a lithium-ion battery suffers. In this thesis, a fuzzy-rule-based system is proposed to detect the over-charge and over-discharge failure in early time. The preliminary results for the failure signatures of overcharged and over-discharged lithium-ion are listed based on the experimental results under both room temperature and high temperature. A fuzzy-rule-based model utilizing these failure signatures is developed and validated. For over-charge case, the abnormal increase of the surface temperature and decrease of the voltage are captured. While for over discharge case, unusual temperature increase during overcharge phases and abnormal current decrease during overcharge phases are obtained. The inference engine for fuzzy-rule-based system is designed based on these failure signatures. An early warning signal will be given by this algorithm before the failure occurs. This failure detection and early warning system is verified to be effective through experimental validation. In the validation test, the proposed methods are successfully implemented in a real-time system for failure detection and early warning. The result of validation is compatible with the design expectation. Finally an accurate failure detection and early warning system is built and tested successfully.