In an era where sustainability is at the forefront of energy innovation, it’s no surprise that discussions surrounding the utilization of used, or second-life, lithium-ion batteries have been making the rounds in energy industry circles. Even our own Battery Experts have embarked on pioneering projects, reimagining used lithium-ion batteries from electric vehicles to create multi-MWh battery energy storage systems (BESS). These projects not only promote sustainability but also demonstrate how decommissioned electric vehicle modules can be given a second life.
In this article, we delve into the challenges associated with second-life batteries and explore how predictive battery analytics offers a comprehensive solution to address these issues.
In this case, the name “second-life battery” is self-explanatory. These are batteries, and/or their parts that are re-used for different applications once their first lifecycle comes to an end. Battery recycling is not only more cost effective than solely relying on first-life batteries, but it also reduces waste and avoids further depletion of naturally occurring minerals, making the transition to renewable energy more sustainable.
Most second-life batteries come from electric vehicle (EV)applications. Once the battery reaches the end of its first-life, it could be repurposed, refurbished, or recycled. Each option involves a different process outlined below:
While the process of recycling batteries seems to be straightforward, the implementation of these second-life batteries is not without challenges.
The concept of second-life batteries holds immense promise, but it’s not without unique challenges for system manufacturers and integrators in planning. Unlike first-life batteries, the actual state of second-life batteries cannot be understood from a simple datasheet. Instead, the lasting impacts of the conditions in their first life must be taken into account.
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Operating a grid-scale BESS with a mix of second-life battery modules can be demanding. Each module's quality and performance can vary significantly, making commissioning and ongoing maintenance more complex. Stable operation must be maintained to ensure the battery facility functions efficiently.
Inhomogeneities between modules can lead to performance discrepancies and imbalances in terms of extractable power and energy. If these imbalances lead to unplanned interruptions in the grid supply, it can result in penalties and financial losses.
Selling used batteries can be profitable for OEMs but comes with a growing risk of quality claims as sales volume rises, leading to operational challenges. Being able to perform a health and safety check on batteries intend to be used in a second life helps to manage these risks for both the OEMs and the second-life provider.
Second-life batteries are a viable and reliable option for energy storage if these challenges are addressed proactively. To do that, you need predictive battery analytics. This is a comprehensive solution that provides in-depth field data analysis throughout the entire lifecycle of a battery storage facility avoiding time-intensive and costly lab tests which would render the whole idea of second-life usage inefficient.
Breathing new life into battery modules hinges on a precise understanding of second-life storage system requirements. This entails specifying module and rack details based on use cases, encompassing safety standards, current rates, temperature resilience, nominal capacity, and energy.
To determine the best system configuration, we follow a concise three-step process with the available modules.
Once the battery storage facility is operational, predictive battery analytics provide ongoing support to maintain stable operation. Regular maintenance and monitoring are essential to ensure reliable operation of the BESS and minimize the risk of performance issues and safety-critical incidents.
Second-life lithium-ion batteries hold significant potential for enhancing sustainability in the energy sector by saving resources. However, the implementation of second-life batteries comes with its set of unique challenges, from planning and safety concerns to maintenance and performance risks.
To unlock the full potential of second-life batteries, it is essential to proactively address these challenges. Advanced battery analytics offers a comprehensive solution by leveraging first-life data analysis for better planning and construction, expert commissioning support, and ongoing operational assistance. By increasing predictability through in-depth field data analyses, battery analytics ensures that the promise of second-lifebatteries becomes a reality, contributing to a more sustainable and reliable energy ecosystem.
In conclusion, the key to minimizing uncertainty in second-life battery implementation lies in expert analysis and support. With a holistic approach as seen in our collaboration with various vendors, the future of sustainable energy storage becomes brighter, making the vision of a greener, more eco-friendly world one step closer to reality.
After completing his mechanical engineering studies and holding several positions at the largest German OEMs, Valentin shifted his focus to battery technologies around five years ago. As a product owner at ACCURE, Valentin excels at bringing interdisciplinary teams together, ensuring that the platform is finely tuned to the rapidly-evolving market and customer demands. Outside of work, you can often find Valentin riding on his road bike.
ACCURE helps companies reduce risk, improve performance, and maximize the business value of battery energy storage. Our predictive analytics solution simplifies the complexity of battery data to make batteries safer, more reliable, and more sustainable. By combining cutting-edge artificial intelligence with deep expert knowledge of batteries, we bring a new level of clarity to energy storage. Today, we support customers worldwide, helping optimize the performance and safety of their battery systems. Visit us at accure.net.