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Battery Ageing – How Modeling is Used to Predict Battery Life
Battery modeling and simulation makes it possible to analyze multiple operating conditions and design parameters for batteries and other electrochemical systems and processes. By developing mathematical models you can begin to understand the interaction of electrochemical and chemical processes in the battery and how these processes affect the performance and life of the battery.
In this presentation, we will take a look at the benefits of modeling and simulation in the design, selection, and operation of a lithium-ion battery. We will especially take a look at how modeling can be used together with testing. These results provide manufacturers and application experts with the data to not only predict battery life but to analyze the implications of design parameters and operating conditions to better understand the limitation of the battery.
This webinar will focus on the following key topics:
• Benefits of modeling and simulations in the design, selection, and operation of a lithium-ion battery
• Implications of design parameters and operating conditions with respect to experimental observations of battery performance, aging, and battery safety
• How battery modeling can be used together with testing
Presenter
Tom O’Hara – Global Business Manager, Intertek
Tom O’Hara is the global business manager / advisory services for Intertek’s energy storage programs. Aside from his consulting role, Tom supports U.S. and European marketing and sales efforts and APAC CTIA certification efforts. As a 30-year veteran of the battery technology field, Tom has worked in Energizer Battery’s R&D sector and consulted with several start-up battery companies. He is also the co-inventor of the world’s first successful mercury-free zinc air button cell and holds seven U.S. patents. He obtained both a B.S. and M.S. in chemistry from Wake Forest University in North Carolina.
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Adding Intelligent Battery Management to Lead-Acid Energy Storage Systems
Lead batteries are resilient and have a low likelihood of catastrophic failure. However, their lifespan can be significantly reduced when operated outside of manufacturer specifications. The extension of lead battery life through active battery management is becoming a compelling value proposition for vendors of lead-based energy storage systems.
The evolving regulatory environment governing energy storage safety is also impacting how both lead and lithium chemistries are to be managed moving forward. Join Nuvation CEO Michael Worry to explore the reasons why active battery management is becoming adopted in large-scale lead battery applications, and how the changing regulatory environment is impacting lead-based energy storage.
This webinar will focus on the following key topics:
• Controlling off-gassing in vented and VRLA lead batteries
• Emerging functional safety regulations and UL 1973
• Using a BMS to reduce the levelized cost of energy
• Automating stack connection sequencing in a multi-stack ESS
• Lead-based energy storage system deployments
Presenter
Michael Worry – CEO at Nuvation Energy
Michael Worry founded Nuvation in 1997 and has grown the company into a thriving electronic products and engineering services firm with offices in Sunnyvale, California and Waterloo, Ontario Canada. He is the CEO of Nuvation Energy, a provider of battery management systems and engineering services for large-scale energy storage systems.
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Energy Storage RTE Tutorial Course 1/3: What is Round Trip Efficiency (RTE)? Why is it Important? How Much Does it Cost?
In the first of this three-part webinar series, a definition of RTE will be presented along with simple system equations that are important to its understanding, determination and management. RTE for some popular battery systems i.e. Lead Acid, Lithium Ion, Vanadium Redox and Nickel Zinc will be computed as examples, and their variation with common variables such as rate, capacity variability & SOC swing will be discussed. The costs of Round Trip inefficiency can be significant, and are experienced by customers either in higher energy generating capital costs and/or higher operating expenses. The calculation of these higher costs will be reviewed, and there will be a discussion on the key industry variables that influence them. Different geographic and customer markets will be considered.
This webinar will focus on the following key topics:
• The Importance of RTE to battery selection decisions
• How does RTE impact CAPEX and/or OPEX for energy storage
• How is RTE defined and how can it be derived – comparison of different systems
• An introduction to ancillary equipment energy losses
Presenter
Dr. Halle Cheeseman – Founder/President at Energy Blues LLC
Dr. Halle Cheeseman earned a PhD in Electrochemistry & Corrosion from the University of Nottingham in UK, graduating in 1985. She has held several executive positions in the battery industry over the past 32 years, including Sr. VP of R&D at Spectrum Brands and VP of R&D at Exide Technologies. Her specific battery experience includes Lithium Ion, Zinc Air, Nickel Metal Hydride, Nickel Iron, Alkaline and Lead Acid, focusing on Consumer, Industrial, Automotive & Renewable Energy applications. In July 2017, Dr. Cheeseman founded Energy Blues LLC, an energy storage consulting cooperative comprising 20+ subject matter experts.
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Battery Analytics Tutorial Course 3/3: Predictive Modelling, Machine Learning, and AI
This one-hour webinar is Part 3 of a 3-part series. It moves from a discussion of data capture and trend reporting explored in Part 2 to predictive modeling, machine learning, and artificial intelligence as the next levels of battery analytics.
We will examine how machine learning and artificial intelligence can be implemented to identify hidden correlations between disparate data and energy storage system performance, and also independently take pre-emptive action to increase ESS reliability and battery life.
Real-life examples will be shared where predictive models could have flagged anomalous behaviors that were experienced in the field, and led to corrective actions to mitigate unplanned costs and labor.
This webinar will focus on the following key topics:
• Coming to Terms – Understanding the differences between machine learning, artificial intelligence, deep learning, and rule-based systems
• Predictive Modeling Approaches – using data mining and probability to forecast outcomes
• What’s Next – How AI and Machine Learning will impact large-scale battery energy storage
Presenter
Michael Worry – CEO at Nuvation Energy
Michael Worry founded Nuvation in 1997 and has grown the company over 21 years into a thriving electronic products and engineering services firm with offices in Sunnyvale, California and Waterloo, Ontario Canada. He is the CEO of Nuvation Energy, a provider of battery management systems and engineering services for large-scale energy storage systems.
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