4th July 2019
From Evolution to Application: How Digital Twin Technology Helps Improve Lithium Battery Life
As a concept, Digital Twin has been around since 2002. It was first introduced as the Mirrored Spaces Model by Michael Grieves at the University of Michigan in executive Product Life cycle Management courses. It was first implemented and practiced by NASA who used it to monitor and update machines that were physically present in outer space and hence, out of reach.
One of the first use cases was when the engineers and astronauts could use the Digital Twin technology to identify and remotely fix issues during the Apollo 13 mission. Since then, Digital Twin has proved to deliver remarkable outcomes in a wide range of applications and functions in varied industry verticals.
It has gained immense popularity only in the past two years as there were rapid advancements in digital technologies such as Artificial Intelligence, Machine Learning, Internet of Things, Big Data and Analytics. The benefits of these technologies, to name a few – improved cost-effectiveness, higher applicability, and cloud connectivity – enabled industries to explore the potential of the Digital Twin technology.
What is a Digital Twin?
As increasingly complex “things” are now built with the ability to connect, interact and produce data, a digital twin is a virtual simulation of a physical asset. It mimics the behavior of the asset throughout the product life cycle with the help of the asset’s sensor data. The compelling technology couples the real-time data with the ability of artificial intelligence to optimize the deployed asset’s behavior remotely, to achieve higher efficiency.
The emergence of the Digital Twin
The Digital Twin technology gained traction when Gartner named it as one of the top 10 strategic technology trends for 2017. As per Gartner – Organizations will use digital twins to proactively repair and plan for equipment service, to plan manufacturing processes, to operate factories, to predict equipment failure or increase operational efficiency, and to perform enhanced product development (Source).
A year later, Gartner’s Top 10 Strategic Technology Trends for 2018 highlighted the amplified interest and adoption of the Digital Twin technology. The report mentioned that – With an estimated 21 billion connected sensors and endpoints by 2020, digital twins will exist for billions of things in the near future. Potentially billions of dollars of savings in maintenance repair and operation (MRO) and optimized IoT asset performance are on the table (Source).
How does it work?
Essentially, the Digital Twin uses sensors to receive real-time operational data on the cloud. The technology provides an accurate, real-time, all-encompassing representation of the variables such as – usage patterns, environmental conditions, current performance, etc., thereby reducing manual inspections, that save a considerable amount of time and cost for the organization.
The virtual simulations then integrate and analyze past usage data. The insights help the user to understand any performance inefficiencies and offer solutions to identify and eliminate potential issues that may be critical to the product life.
Digital Twin and the Battery
With a consistent flow of information, Digital Twins are enabling manufacturing, design and supply chain companies to outperform and optimize outcomes. There exists an enormous untapped application potential of the technology for an advanced product market such as Lithium-ion batteries.
Digital Twin technology is the key to gaining complete control of the battery with easy information availability and accessibility. In a single view, it can help uncover historical data and real-time battery data. With the ability to use machine learning algorithms, the user can predict the life, overall performance, and critical issues that could prevent breakdowns. Digital Twin offers the insights, recommendations, and tools to optimize the battery behavior, in the virtual space that can enhance the battery life a great deal.
As batteries constitute 40% of the total cost of electric vehicles, it is a crucial time for a breakthrough in battery technology for OEMs and battery pack makers. The digital twin, along with AI and Big Data, can be an absolute game-changer for them all as it helps to prepare for challenges we may face towards a completely electric future. It can be used for can be testing and validating even during the production stage as it mimics the battery behavior and performance for accurate data extraction.
At ION, we are obsessed with battery life cycle management. We believe that intelligent battery analytics is the key to unlocking the next big breakthrough in battery technology. Hence, we’re really enthusiastic about building a Digital Twin platform with the predictive maintenance edge for high battery efficiency and operational reliability.
Edison Analytics: Battery Intelligence & Analytics Platform2nd December 2020/