Showing 57–60 of 79 results

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    Passive Mitigation of Thermal Runaway Propagation in Dense 18650 Lithium Ion Cell Assemblies

    Utilization of lithium ion batteries (LIBs) in various applications has been growing exponentially. LIBs offer some distinct advantages including high energy density, outstanding efficiency, long lifespan, and fast charging capability. Probably, the main disadvantage of LIBs is that a small deviation from normal operating condition may result in rapid self-heating accompanied by ejection of large quantities of flammable materials, which can cause fire or explosion. The failure process becomes more dramatic when many cells are arranged in large arrays in order to fulfill the power requirements by most of applications. Failure of a single cell can release sufficient energy to trigger failure into adjacent cell, which subsequently propagates throughout the entire array. In this webinar, a set of passive strategies to mitigate failure propagation will be presented. The dynamics, heating rates, gaseous emissions, and energetics of thermally induced thermal runaway propagation in dense arrays consisting of 12-15 fully charged 18650 lithium ion cells have been quantified to determine the effectiveness of these passive mitigation strategies.

    This webinar will focus on the following key topics:

    • Thermal runaway in lithium ion batteries
    • Thermal runaway propagation in lithium ion battery packs
    • Hazards associated with failure propagation
    • Passive mitigation strategies

    Presenter
    Ahmed Said – Postdoc Fellow, Worcester Polytechnic Institute

    Ahmed Said is a post-doctoral fellow in the Department of Fire Protection Engineering at Worcester Polytechnic Institute. He Obtained his PhD from the Department of Mechanical Engineering at the University of Maryland, College Park, in 2020. He is broadly interested in fire and combustion science problems. More specifically, his research is centered on thermal and fire safety of energy storage systems, material flammability, fire spread on façade systems, and wildland fires.

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    Electrode Damage Characterization in Li-Ion Batteries Using Raman Spectroscopy

    While Li-Ion battery technology has continually advanced to provide cells that are smaller and more powerful, compromised safety concerns due to physical damage are always present. Physical damage to a Li-Ion battery can significantly affect its operational performance, causing accelerated degradation and capacity fade. Damage to electrodes and removal of active material lead to microstructural changes in electrode material and unbalanced current distribution, causing polarization in cells. This work focuses on characterizing the effects of partial nail penetrations on electrodes in cells that continue cycling after being damaged by using Raman spectroscopy and incremental capacity analysis. This helps to determine the type and extent of damage to the electrodes over the course of their abbreviated lifetime.

    This webinar will focus on the following key topics:

    • Dynamic impact testing of prismatic Li-Ion cells
    • Raman spectroscopy analysis for anode damage characterization
    • Increased polarization due to unbalanced current distribution
    • Accelerated degradation caused by physical damage
    • Incremental capacity analysis to determine mechanisms of aging

    Presenter
    Casey Jones – Ph.D. Candidate at Purdue University

    Casey Jones is a PhD student in the School of Aeronautics and Astronautics at Purdue University, where he works in the Interfacial Multiphysics Laboratory for Dr. Vikas Tomar. His research focuses on destructive testing of Li-ion batteries and the characterization of the effects on cell operation and is funded by the Office of Naval Research. Prior to studying at Purdue he served in the US Navy as a nuclear electronics technician aboard a fast-attack submarine based in Pearl Harbor, and received his BS in Mechanical Engineering from the University of Hawai’i at Manoa.

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    Low Data Machine Learning for Predicting Lithium-ion Battery Aging

    Meeting the demand for reliable energy storage, this work presents a machine-learning model for precise cycle life prediction in lithium-ion batteries (LIB). It explores battery aging features, utilizes data-driven methods for health assessment, and applies machine learning to predict cycle life. To address data limitations, synthetic data generation is employed, enhancing prediction accuracy. The presentation concludes by demonstrating the practical deployment of the proposed ML model on a battery management system, showcasing its potential impact on power usage efficiency. Discussions cover crucial aspects such as battery aging, data-driven health measurement, and the model’s versatility in handling accidental effects during operation.

    This webinar will focus on the following key topics:

    • Unveiling Battery Aging: identifying key aging features
    • Data-Driven Insights: machine learning for battery state of health assessment
    • Cycle Life Precision: machine learning in Lithium-Ion battery predictions
    • Addressing Data Gaps: synthetic data for enhanced prediction accuracy
    • Real-World Impact: practical deployment of ML on battery management systems

    Presenter
    Meghana Sudarshan – Ph.D. Candidate at Purdue University

    Meghana Sudarshan is currently pursuing a Ph.D. from the School of Aeronautics and Astronautics at Purdue University. Her research focuses on developing data-driven models agnostic battery management systems in UAVs and electric vehicles for predicting degradation of COTS (Commercial Off-The-Shelf) Li-ion Batteries as a function of operation parameters.

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    IP Landscape, Strategies & Protection for Li-Ion Battery Solid-State Electrolytes and Silicon-Based Anodes

    The audience will learn about recent key inventions in the areas of solid electrolytes and silicon anodes for Li-ion batteries that constitute the state of the art. Exemplified by a look at two new-comers (startups) and two incumbents, attendees will further learn about how to approach IP strategy & protection for their R&D programs.

    This webinar will focus on the following key topics:

    • IP landscape, strategies & protection
    • Solid-state electrolytes for Li-ion batteries
    • Silicon-based anodes

    Presenters
    Howard Lim – Associate Attorney, Fenwick & West LLP
    Pirmin Ulmann – Co-Founder & CEO, B-Science.net

    Howard represents technology-based clients in patent litigation matters and postgrant proceedings, such as inter partes reviews. He has technical experience in the area of lithium-ion batteries, electric vehicles, semiconductors, semiconductor manufacturing equipment, and LCD and OLED display technologies. Prior to becoming a lawyer, Howard had a substantial career in the lithium-ion battery industry working for Panasonic and Sanyo Electric Company developing new products in the areas of electric vehicle and energy storage technologies.

    Pirmin is co-founder and CEO of b-science.net, a battery innovation & patent monitoring service that is based on a novel machine learning approach. He obtained a diploma in chemistry from ETH Zurich (Switzerland) in 2004 and a PhD from Northwestern University (USA) in 2009. Thereafter, he was a JSPS Foreign Fellow at the University of Tokyo (Japan). From 2010 to 2016, while working at a major battery materials manufacturer in Switzerland, he was a coinventor of 7 patent families related to lithium-ion batteries. He holds the credential Stanford Certified Project Manager (SCPM) and has co-authored scientific publications with more than 1,600 citations.

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