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 * Home
 * Team
 * About
 * Product
 * Battery Aging Overview
 * Technology
 * Application to Second Use
 * Contact







A BATTERY HEALTH DIAGNOSTICS
PLATFORM ENABLING BATTERY CIRCULARITY

Seamlessly Monitor and Evaluate the Impact of Aging on a

Battery’s Performance and Economic Value on the Cloud





ABOUT




MISSION:

Extending the life of a Battery Using Sophisticated Active Monitoring,
Diagnostics and Estimation Models


WHO WE ARE:

We are energy technologists leveraging advances in Artificial Intelligence and
Machine Learning coupled with Physics-based Modeling to effectively monitor and
predict battery aging. We work with leading Battery Scientists and Researchers
to Mathematically Model Complex Battery properties.

Beyond battery ageing, our team has experience in renewable energy, investing,
software, hardware and policy working with private sector and regulators.




WHERE WE OPERATE:





AFTER USE
CIRCULARITY: 


RECYCLING AND REPURPOSING





DURING USE
HEALTH MONITORING: 


PERFORMANCE AND RELIABILITY


PRODUCT




Rapid Active Monitoring and Maintenance




Revenue
Optimization




Reduced Cost
To Deploy




Performance

Warranty




MEETING ALL YOUR SAFETY AND PREDICTIVE MAINTENANCE NEEDS IN ONE PLATFORM

By leveraging our proprietary digital twin and active testing models, we bring
transparency on the state of health of your battery. This in turn allows its
capacity to be optimally utilized.


BATTERY AGING OVERVIEW



WHAT IS BATTERY AGING?

Batteries age in highly unique ways based on a variety of internal and external
factors. As such, this makes estimating their remaining useful life (RUL)
complex. While various battery management systems can control a battery’s
operating conditions in a way to force a state of health outcome, the industry
needs non-invasive solutions that can dynamically assess the impact of a
battery’s aging.



WHAT FACTORS AFFECT BATTERY AGING?

A few key factors that affect battery aging and performance include: 

(1) Operating Voltage

(2) Temperature or thermal management

(3) Charge transfer kinetics or C-rating



WHY DOES AGING MATTER?

By understanding a battery’s profile, we can operate it to its full capacity
without compromising on reliability and safety.  As a battery ages, its
remaining useful life and degradation curve become incredibly complex and
unpredictable.

Similarly, with new battery chemistry derivations, charging conditions, and
operating environments, our industry needs adaptive models that can effectively
predict and monitor battery aging and its impact. This is particularly true
given the increased focus on battery circularity and sustainability. 


TECHNOLOGY


HOW WE DO IT?

Because a battery is effectively a closed system, there are physics-based
properties that can be accurately modeled. The thermodynamic laws and outcomes
hold true.

Our solution is built to operate as a digital twin operating a cloud-based
virtual copy of the battery. By leveraging physics-based models we capture the
relationship between materials and their stress factors. In doing so, we can
build and monitor systems that mimic the behavior of a battery.  

Our model is fed with real-time usage data. Using this data, it can predict and
optimize the aging behavior for different battery profiles with a high degree of
fidelity making predictive maintenance possible.





APPLICATION TO SECOND USE

There is a realization that the industry needs to promote battery circularity by
extending a battery’s life and enabling the reuse of its remaining capacity in
alternative applications. By understanding a battery’s state of health and
remaining useful life, our diagnostics platform can play an important role in
promoting battery circularity.



In modeling a battery's path of aging, our platform can effectively determine
whether a battery is a good candidate for materials recycling or a second use
after its first mission. By actively estimating a battery's state of health
throughout its lifetime, we create the necessary data to enable this promising
market.


Furthermore, we can extend our models to offer effective predictive maintenance
to batteries that have a highly unpredictable and unconventional aging process.





CONTACT

Name

Email

Phone

Massege

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