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Lithium-ion batteries are increasingly used in industry as an energy storage system for applications ranging from portable electronics to high-energy electric vehicle systems. Their reliability and performance in the field can be affected by variations in environmental and loading conditions. Performance characterization testing provides health and performance features that can be used to assess a...
Lithium-ion batteries are popular for a wide variety of applications owing to their high energy/power density, long cycle life, and low self-discharge rate. A battery management system (BMS) can ensure the reliability and safety of batteries. As an important part of a BMS, prognostics and health management (PHM) can predict the failure time of batteries. This paper presents a new approach for battery...
In this work, we apply the projection-based model-reduction framework for PDEs of [1] to the diffusion process governing the intercalation of lithium ions into spherical particles that appears in electrochemical models of Li-ion batteries. We first invoke the projection framework with different projections (the so-called natural—i.e. Galerkin—and volume-averaging projections—NP and VAP, respectively)...
This paper presents an investigation into the reliability and physical degradation mechanisms associated with the loss of battery performance. Cells from two different manufactures underwent cycle life testing until failure (defined as a 20% decrease in nominal capacity). Designated samples from each battery type were subjected to one of two different discharge methods, one at a constant discharge...
The research of the energy source of online condition monitoring devices for transmission line is a current interest. An energy capture system using both current transformer (CT) and lithium batteries is proposed in this paper. Through this system, the CT with variable turns transmits energy of transmission lines to devices and lithium batteries. The latter works only if line current is inadequate...
A method for remaining useful performance (RUP) analysis for lithium-ion batteries is presented using Dempster-Shafer theory (DST) and Bayesian Monte Carlo (BMC). First, an empirical model is developed, which can provide a good fit to the battery fade data. Then, the parameters of the empirical model are initialized by combining sets of training data based on DST. When data become available through...
Improved RBF neural network arithmetic is mainly characterized by using TI's Impedance Track TM technology for reference which predict the status of charge (SOC) of lithium battery, and in accordance with the chemistry characteristics of lithium batteries, use varied pulse charge method for their rapid and efficient charging. The results show that the SOC which is predicted by improved RBF arithmetic...
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