Browsing by Author "Wu, Meng"

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    Failure Detection for Over-Discharged Li-Ion Batteries
    (Office of the Vice Chancellor for Research, 2012-04-13) Xiong, Jing; Banvait, Harpreetsingh; Li, Lingxi; Chen, Yaobin; Xie, Jian; Liu, Yadong; Wu, Meng; Chen, Jie
    Li-ion batteries are high density, slow loss of charge when not in use and no memory effect. Vast research on Li-ion batteries has been focusing on increasing the energy density, durability, and cost. Due to its advantages it has been widely used in consumer electronics and electric vehicles. Apart from its advantages, safety is a major concern for Li-ion batteries. The Li-ion safety issues have been widely publicized due to devastating incidents with laptop and cell phone batteries. Despite of much research towards the safety of Li-ion battery, it remains as a major concern related to Li-Ion batteries. A failure of Li-ion battery may result in thermal runaway. Li-ion battery failure may be due to overcharge, over-discharge, short circuits, particles poisoning, mechanical or thermal damage [1, 2]. Short circuit, overcharge, and over-discharge are the most common electrical abuses a battery suffers. This poster presents preliminary results for the failure signatures of over-discharged Li-ion batteries, and proposes a rule-based method and a probabilistic method for failure detection. The two methods Rule-based method and Probabilistic method are verified using experimental results for a Li-ion battery. The proposed methods were successfully implemented in a real-time system for failure detection and early warning.
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    Fuzzy-Rule-Based Failure Detection and Early Warning System for Lithium-ion Battery
    (2013-09-05) Wu, Meng; Chen, Yaobin; Li, Lingxi; Rovnyak, Steven; King, Brian
    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.