Electric & Hybrid Vehicle Technology International
  • News
    • A-F
      • Battery Technology
      • Buses & Commercial Vehicles
      • Charging Technology
      • Concept Vehicle
      • Electrification Strategies
      • Fuel-cell Technology
    • G-K
      • Hybrid Powertrain
      • Hybrid/electric Architecture
      • ICE Hybrids
      • Industry News
      • Joint Ventures
    • L-Q
      • Manufacturing
      • Materials Research
      • Motor Technology
      • Motorsport Electrification
      • NVH
      • OEM News
      • Powertrain Components
      • Pure-electric Powertrain
    • R-Z
      • Range Extender
      • Solid-state Battery Technology
      • Testing
      • Transmissions
  • Features
  • Online Magazines
    • March 2025
    • November/December 2024
    • July 2024
    • March 2024
    • November 2023
    • July 2023
    • March 2023
    • Archive Issues
    • Subscribe Free!
  • Technical Articles
  • Opinion
  • Videos
  • Supplier Spotlight
  • Webinars
  • Events
LinkedIn YouTube X (Twitter)
Subscribe to Magazine SUBSCRIBE TO EMAIL NEWSLETTER MEDIA PACK
LinkedIn
Electric & Hybrid Vehicle Technology International
  • News
      • Battery Technology
      • Buses & Commercial Vehicles
      • Charging Technology
      • Concept Vehicle
      • Electrification Strategies
      • Fuel-cell Technology
      • Hybrid Powertrain
      • Hybrid/electric Architecture
      • ICE Hybrids
      • Industry News
      • Joint Ventures
      • Manufacturing
      • Materials Research
      • Motor Technology
      • Motorsport Electrification
      • NVH
      • OEM News
      • Powertrain Components
      • Pure-electric Powertrain
      • Range Extender
      • Solid-state Battery Technology
      • Testing
      • Transmissions
  • Features
  • Online Magazines
    1. March 2025
    2. November/December 2024
    3. July 2024
    4. March 2024
    5. November 2023
    6. July 2023
    7. March 2023
    8. November 2022
    9. July 2022
    10. Archive Issues
    11. Subscribe Free!
    Featured
    March 24, 2025

    New issue available now! March 2025

    News By Web Team
    Recent

    New issue available now! March 2025

    March 24, 2025

    New issue available now! November/December 2024

    December 2, 2024

    In this issue – July 2024

    July 19, 2024
  • Technical Articles
  • Opinion
  • Videos
  • Supplier Spotlight
  • Webinars
  • Events
LinkedIn
Electric & Hybrid Vehicle Technology International
Battery Technology

MIT, Stanford and Toyota using AI to predict battery lifespan

Matt RossBy Matt RossMarch 27, 20193 Mins Read
Share LinkedIn Twitter Facebook Email

Scientists at MIT, Stanford University and the Toyota Research Institute (TRI) have published research detailing a system to predict the useful life of lithium-ion batteries before their capacities begin to decline.

After the researchers trained their machine learning model (a combination of comprehensive experimental data and artificial intelligence) with a few hundred million datapoints, the algorithm predicted how many more cycles each battery would last, based on voltage declines and a few other factors among the early cycles. The predictions were within 9% of the actual cycle life.

Separately, the algorithm categorized batteries as either long or short life expectancy based on just the first five charge/discharge cycles. Here, the predictions were correct 95% of the time. This machine learning method could accelerate R&D for new battery designs, and reduce the time and cost of production.

“The standard way to test new battery designs is to charge and discharge the cells until they die. Since batteries have a long lifetime, this process can take many months and even years,” said co-lead author Peter Attia, Stanford doctoral candidate in materials science and engineering. “It’s an expensive bottleneck in battery research.”

The work was carried out at the Center for Data-Driven Design of Batteries. The Stanford researchers, led by William Chueh, assistant professor in materials science and engineering, conducted the battery experiments. MIT’s team, led by Richard Braatz, professor in chemical engineering, performed the machine learning work. Kristen Severson is co-lead author of the research. She completed her PhD in chemical engineering at MIT last spring.

Study co-authors Muratahan Aykol and Patrick Herring brought TRI’s experience with big data to the project (and their own expertise in battery development) to enable effective management and seamless flow of battery data, which was essential in the creation of accurate machine-learning models for the early prediction of battery failure.

The research has many potential applications according to Attia. It could, for example, shorten the validation time for new chemistries. Manufacturers could also use the sorting technique to grade batteries – those with longer lifetimes could be used in more demanding applications (such as electric vehicles) and therefore sold at higher prices. Recyclers could use the technology to assess cells in used EV battery packs, determining if they have enough life for secondary uses.

The research is part of TRI’s Accelerated Materials Design and Discovery (AMDD) program. Led by program director Brian Storey, the US$35m initiative collaborates with research entities, universities and companies to use artificial intelligence to accelerate the design and discovery of advanced materials.

Share. Twitter LinkedIn Facebook Email
Previous ArticleFord to unveil mild hybrid Fiesta and Focus models
Next Article GM to invest US$300m in Michigan plant for new EV production
Matt Ross

Matt joined UKi Media & Events in 2014 after seven years of living and working in Dubai. He has been a journalist for over a decade and has worked for a wide range of publications, including Rolling Stone, Time Out, iQ and Loaded. After starting out on the automotive team as deputy editor of Engine Technology International, Electric & Hybrid Vehicle Technology International and Transmissions Technology International, he began editing Electric & Hybrid Vehicle Technology International in 2016, and took over as editor of Tire Technology International in 2018.

Related Posts

Battery Technology

BMW and Solid Power achieve milestone with first ASSB road test

May 20, 20252 Mins Read
Battery Technology

Altilium successfully tests EV batteries made with recycled materials

May 15, 20252 Mins Read
Battery Technology

24M Technologies urges battery redesign to prevent costly EV fire recalls

May 8, 20252 Mins Read
Latest Posts

The right laser optic for every weld

May 22, 2025

Tesla loses European market lead to BYD amid shifting EV landscape

May 22, 2025

BMW and Solid Power achieve milestone with first ASSB road test

May 20, 2025
Our Social Channels
  • YouTube
  • LinkedIn
Getting in Touch
  • Free Email Newsletters
  • Meet the Editors
  • Contact Us
  • Media Pack
FREE WEEKLY NEWS EMAIL!

Get the 'best of the week' from this website direct to your inbox every Thursday


© 2023 Mark Allen Group Ltd | All Rights Reserved
  • Cookie Policy
  • Privacy Policy
  • Terms & Conditions

Type above and press Enter to search. Press Esc to cancel.