Simulating Success with oorja: The Ultimate Playground for Battery Modelling -

Simulating Success with oorja:
The Ultimate Playground for
Battery Modelling

Aditya Pandav

Founders Office Associate

Simulating Success with oorja: The Ultimate Playground for Battery Modelling

Introduction

“The industry is shifting— and OEMs are at the forefront of the change, feeling the transition strain.”

For the last century, automotive OEMs have built their business models around internal combustion engine (ICE) vehicles. However, the market is rapidly shifting towards electrification to meet future sustainability goals. This transition has put OEMs under unprecedented pressure to evolve into software-first companies. One of the most significant challenges in this shift is the development of better batteries that are reliable, accurate, and safe. Many companies still lack a deep understanding of batteries, leading to several issues. Firstly, OEMs often over-engineer batteries, resulting in higher costs and suboptimal performance. Secondly, this knowledge gap can lead to problems that cause costly recalls and lost revenue. Thirdly, there is the challenge of inaccurate warranty estimation.

Battery Simulation is Key to Speeding Up EV Development

Today’s biggest bottleneck to electrification is the OEMs’ heavy reliance on physical experimentation and testing. This approach is expensive and time-intensive, often requiring 12 to 18 months to complete. This slows innovation and the ability to bring new, efficient battery technologies to market quickly. However, in recent years, simulation has emerged as a transformative alternative. By providing cost-effective and efficient solutions, simulation has significantly reduced the need for physical testing, particularly in computational fluid dynamics (CFD), crash testing, and structural design.

Key Battery Design Challenges

Over-engineering of batteries
Knowledge gap
Inaccurate warranty estimation

Digital Twins Are the Future

The most promising advancement within CAE simulation is the digital twinning of batteries. Creating a virtual replica of a physical battery system allows for real-time monitoring, analysis, and optimization. Although the field of digital twinning is still in its early stages, it is rapidly evolving and shows immense potential to revolutionize battery development. By leveraging digital twins, OEMs can predict performance, identify potential issues, and make data-driven decisions without requiring extensive physical testing. This is where oorja steps in— an extremely capable suite of applications running proprietary hybrid technology— refreshing the idea of battery simulation.

How Simulation & Digital Twins Help

Reduce the need for physical testing
Predict performance, identify potential issues, and make data-driven decisions

Digital Twinning of Batteries with oorja

“oorja is designed to be an engineer’s best friend. The focus is on providing the user with simplicity— while at the same time giving them maximum control.”

Traditionally, most digital twinning software is physics-based. Physics-based approaches are powerful—the idea is to identify electrochemical patterns within the battery and fit them into empirical equations. Like any complex mathematical equation, their Achilles heel is determining the values of the variables, of which there are many. The issue is further exacerbated because these variables— more fittingly known as parameters— constantly change with the battery’s state. So, in principle, the equations used to model a battery today may no longer be relevant tomorrow as the battery pack has undergone electrochemical changes.

Key Benefits of oorja

Minimal Data Requirement: Generate meaningful results with minimal data.
Optimise parameters: Hybrid Algorithms provide optimised parameters
Virtual playground: test, simulate, and iterate.
Faster Time to Market: Cost and time-effective.
Accurate, insight-based warranty estimation.

oorja combats this problem through our hybrid approach— where we wed the best of physics-based modelling with the versatility of machine learning. An instant advantage of this approach is that we erase the bottleneck of data availability— a significant constraint holding back conventional battery simulations. With oorja, the user can use minimal data to generate meaningful results in a fraction of the time and cost it takes to procure such data physically. Another advantage of our approach is that oorja can calculate and constantly optimise the parameters needed for modelling based on user inputs.

Figure 1: Benefits of hybrid modelling with oorja.

One of the significant benefits of oorja is that it essentially acts as a virtual playground for battery engineers. Users can log onto the cloud-based interface from anywhere in the world, test multiple real-world scenarios, and optimize their battery pack designs to fulfil their objectives best. This can include tweaking pack configurations, experimenting with different cell chemistries, and different thermal management strategies— all to study and improve the efficacy of the battery pack. This allows them to make informed decisions upfront, potentially saving months of physical testing and costly design iterations. Moreover, oorja enables better-informed decisions around warranty planning, potentially saving companies millions in service recalls.

By leveraging battery simulation with oorja, companies design optimal battery solutions and drastically reduce the timelines and costs associated with EV development— proving that digital twinning with oorja is the way to develop cost-competitive EVs.

To explore how you can use oorja, contact us at info@oorja.energy