Industry Insights

Using AI in battery energy storage: how data is key

We spoke to our Head of Data Services, Frazer Wagg, about how data and machine learning can enhance second life battery energy storage system performance, safety and efficiency.

09/08/2023

While AI used for writing and creating art has stirred up some controversy, it is an invaluable tool for many technologies. And it is now integral to the success of a fast-growing segment of the cleantech sector: second life battery energy storage systems (BESS).

Connected Energy is an innovator in battery energy storage, as we create our systems uniquely from second life electric vehicle (EV) batteries. This makes our BESS the most environmentally friendly on the market, as they repurpose these assets using circular economy principles.

We embarked on a groundbreaking journey to harness the power of machine learning to revolutionise the second-life battery landscape. Our goal has been to use AI to optimise performance, extend battery life and enhance safety, paving the way for a more circular and sustainable energy ecosystem.

Cutting edge techniques

Our team worked closely with the UK’s National Innovation Centre for Data to explore cutting-edge techniques being developed in the field of machine learning. From a 24-month project, we created a model that can aggregate over 2.5 million data points each day. These range from information on power outputs, temperature readings, telemetry data, state of charge and health.

The ability to collate, interrogate and analyse these millions of data points provides new levels of insights into the battery’s condition, enabling us to track second life performance with unprecedented accuracy:

Optimising performance

Through AI, we are able to predict any noticeable issues in state of health that may impact an overall system’s performance. This enables us to maximise the value within each battery and ensures our systems are optimised for our customer’s individual use cases.

Extended battery life

By accurately making these necessary changes, we can implement efficiency strategies which in turn can lead to an extension of a second life battery’s usable life.

Enhanced safety

We are breaking new ground with second life batteries, as there are not yet any Government or industry standards for their safe use. We, therefore, created our own and use AI extensively in our testing regimes.

Customer confidence

Monitoring in this way also enables us to identify when maintenance or replacement of batteries is required. This not only prevents real-time failures, but it gives our customers the confidence to choose second-life systems.

“Just as we are driven by maximising the value of the resources within a battery, we have identified a way to maximise the data in our possession. The result is the development of a technical solution to drive forward the use of second life batteries as energy storage, helping to promote sustainability, efficiency and cost-effectiveness in battery reuse.”

Frazer Wagg, Head of Data Services, Connected Energy

Continuous improvement

With machine learning, we have a model that is constantly learning and drawing out new insights to further improve efficiency.

Providing valuable insights

We have much more informed insights into the true-life cycle of the batteries that can provide major intelligence to our automotive OEM partners, because we are collating and analysing data after the batteries have left their vehicles. By sharing our knowledge of the life cycle of our batteries, partners can better manage their pipeline of second life batteries. This work will become increasingly valuable as more OEM partners seek to find a second life use for their batteries.

Assessing a third life

Furthermore, because AI helps us identify and track batteries through their second life in energy storage, it also has the potential to help find a third life for those batteries. When they come to the end of their useful life in a BESS, we can provide accurate data on their state of health.

Moving forward

As Connected Energy moves into the development of utility scale systems later this year, utilising the batteries of a number of different OEM partners, our data-gathering and interrogation capabilities will be of increasing importance.

Our pioneering use of machine learning marks a significant milestone in the second life energy storage industry. Just as we are driven by maximising the value of the resources within a battery, we have identified a way to maximise the data in our possession. The result is the development of a technical solution to drive forward the use of second life batteries as energy storage, helping to promote sustainability, efficiency and cost-effectiveness in battery reuse.

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Industry Insights

Using AI in battery energy storage: how data is key

Cutting edge techniques

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