Original Agenda

We are actively working with our speakers to confirm their availability for our new dates and will share the updated program once it is available. Initial response from our speakers has been very positive so we are quite optimistic the July agenda will be as valuable as the March. In fact, we are thrilled to share that all five Plenary Keynotes have already confirmed their participation!

 

Training Seminar*

Cambridge EnerTech is pleased to offer a skill-based Training Seminar to the International Battery Seminar & Exhibit. A Training Seminar offers in-depth training and instruction on a specific subject area that isn’t covered at this level during the main conference program or pre-conference and dinner tutorials. Our Training Seminar offers real-life case studies, problems encountered and solutions applied. Experienced Training Seminar instructors offer a mix of formal lectures, interactive discussions and activities to help attendees maximize their learning experiences.

NEW DATE - MONDAY, July 27, 2020 | 8:00 AM - 4:00 PM

TS1: Introduction to Big Data Analytics, Machine Learning (ML), and Artificial Intelligence (AI) and the Key Use Cases in Battery Development, Manufacturing, and Operations

INSTRUCTORS:

Gent_WillWilliam Gent, PhD, StorageX Staff Scientist, Materials Science & Engineering, Stanford University


Christianna LiningerChristianna Lininger, PhD, Application Engineer, Voltaiq


Martini_FabrizioFabrizio Martini, Co-founder and CEO, Electra Vehicles, Inc.


Austin SendekAustin Sendek, PhD, Founder and CEO, AIONICS


Sholklapper_TalTal Sholklapper, PhD, Co-Founder and CEO, Voltaiq


Warner_JohnJohn Warner, PhD, Chief Customer Officer, American Battery Solutions, Inc.


TOPICS WILL INCLUDE:

  • Review of use cases for Big Data Analytics, Machine Learning (ML), and Artificial Intelligence (AI)
    • R&D
      • Materials design
      • Materials selection
      • Life prediction
      • Accelerating development cycles and time-to-market
    • Production
      • Anomaly detection
      • Reduced costs through accelerated end-of-line testing
    • System Design
      • Lifetime prediction
      • System sizing
      • BMS algorithm design
    • Operations
      • Predictive maintenance
      • 2nd life application selection
      • Creating feedback loops to iteratively improve operations and battery design
  • Overview of key concepts
    • Full-lifecycle traceability and maintaining a batteries Digital Twin
    • Data harmonization and Battery Intelligence Systems
    • Introduction to battery data and feature selection
    • Review of Modern Machine Learning (ML) and Artificial Intelligence (AI) techniques
  • BMS
    • What is it?
    • Typologies
    • Controls integration into the battery system
    • Software – Base Layer and Application Layer
    • Use cases for data analytics/ML including system sizing and BMS algorithm optimization
  • Review of key data sources from across the lifecycle from materials and production parameters to operations 
    • What dare are important?
    • How much do you need?
    • What resolution do you need?
    • What are the important features?
  • Deep dive on use cases such as optimizing fast charge times

  • AGENDA:

    8:00 Organizer Remarks

    Cindy Crowninshield, RDN, LDN, Executive Event Director, Cambridge EnerTech

    8:15 Introduction to Machine Learning

    Austin Sendek, PhD, Founder and CEO, Aionics Technologies

    8:45 Review of Battery Specific Use Cases

    Christianna Lininger, PhD, Application Engineer, Voltaiq

    9:45 Features: Meta-data

    Tal Sholklapper, PhD, Co-Founder and CEO, Voltaiq

    10:15 Features: Performance

    Tal Sholklapper, PhD, Co-Founder and CEO, Voltaiq

    10:45 Features: BMS

    John Warner, PhD, Chief Customer Officer, American Battery Solutions, Inc.

    11:15 Explore Battery Data

    Tal Sholklapper, PhD, Co-Founder and CEO, Voltaiq

    11:45 Lunch

    1:00 Machine Learning Tutorial 1: Materials

    Austin Sendek, PhD, Founder and CEO, Aionics Technologies

    2:00 Machine Learning Tutorial 2: Life Prediction

    William Gent, PhD, StorageX Staff Scientist, Materials Science & Engineering, Stanford University

    3:00 Machine Learning Tutorial 3: System-Level Configuration

    Fabrizio Martini, Co-founder and CEO, Electra Vehicles, Inc.


    WHO SHOULD ATTEND:
    Engineers and scientists working for materials and component companies, battery developers, pack developers, and OEMS; data scientists; and business development and technical sales who are looking to gain a deeper understanding of the product and development process.

    What is a Training Seminar?
    Each Training Seminar offers 1.0 Day of instruction with start and stop times for each day shown above and on the Event-at-a-Glance published in the onsite Program & Event Guide. Training Seminars will include morning and afternoon refreshment breaks, as applicable, and lunch will be provided to all registered attendees on the full day of the class. Each person registered specifically for the Training Seminar will be provided with a hard copy handbook for the Seminar in which they are registered. A limited number of additional handbooks will be available for other delegates who wish to attend the Seminar, but after these have been distributed no additional books will be available. We ask that Training Seminars not be disturbed once they have begun. In the interest of maintaining a high-quality learning environment for these sessions, we ask that attendees commit to attending the entire program, rather than coming in and out of the room, as to not disturb the hands-on style instruction being offered to the other participants.

    *Best Value or separate registration required for Training Seminar