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Bor Yann Liaw

Researcher at Idaho National Laboratory

Publications -  153
Citations -  12077

Bor Yann Liaw is an academic researcher from Idaho National Laboratory. The author has contributed to research in topics: Battery (electricity) & Lithium. The author has an hindex of 45, co-authored 147 publications receiving 9213 citations. Previous affiliations of Bor Yann Liaw include Max Planck Society & Electrochemical Society.

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Micro-macroscopic coupled modeling of batteries and fuel cells: I. Model development

TL;DR: In this paper, a micro-macroscopic coupled model for advanced batteries and fuel cells is presented, which can be used to explore material and interfacial properties for desired cell performance.
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Identifying battery aging mechanisms in large format Li ion cells

TL;DR: In this article, two types of 10-Ah single cells (one prismatic and another cylindrical) from two manufacturers were tested at room temperature and 60°C. The results were analyzed using incremental capacity analysis (ICA) along with other electrochemical techniques.
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Incremental Capacity Analysis and Close-to-Equilibrium OCV Measurements to Quantify Capacity Fade in Commercial Rechargeable Lithium Batteries

TL;DR: In this paper, a quantitative approach is used to identify sources of contribution of capacity fade in commercial rechargeable lithium battery cells in laboratory evaluations, which can separate attributes to capacity fade due to intrinsic and extrinsic origins.
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Modeling of lithium ion cells: A simple equivalent-circuit model approach

TL;DR: In this paper, an equivalent circuit-based battery model capable of simulating charge and discharge behavior of lithium-ion batteries (LiB) is presented. But the model is not suitable for battery charging and discharge.
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From single cell model to battery pack simulation for Li-ion batteries

TL;DR: In this article, a universal modeling and simulation approach is presented to show that accurate battery pack simulation can be achieved if cell-to-cell variations were taken into account, using a single cell model, which was validated against experimental data and demonstrated with validity of high accuracy in predicting cell performance.