Building a robust battery recycling industry, one company at a time

Argonne model informs key technology decisions of two innovative recycling companies.

A model developed by the U.S. Department of Energy’s (DOE) Argonne National Laboratory informed the technology of two teams that won a prestigious battery recycling prize. These successful applications of the model, called EverBatt, demonstrate its potential to help shape a robust battery recycling industry.

The Lithium-Ion Battery Recycling Prize was a $5.5 million prize competition launched in 2019 by DOE’s Vehicle Technologies Office and Advanced Manufacturing Office. It was administered by the National Renewable Energy Laboratory. The competition aimed to incentivize American businesses to demonstrate processes to capture and recover battery materials.

“We used EverBatt to analyze automated sorting systems with different features and processing capacities. This helped us to optimize the system for maximum economic benefits to the recycling industry.” — Zheng Li, CEO of Li Industries

Rigorous analysis to guide a nascent industry

According to Argonne, annual electric vehicle (EV) sales in the U.S. grew from just a few thousand in 2011 to hundreds of thousands in 2020. Tens of millions of EVs are expected on U.S. roads by 2030.

With rapid EV adoption, there is likely to be an enormous increase in the volume of spent EV batteries soon. This points to an urgent need for widespread infrastructure to reuse, repurpose, and recycle batteries.

Argonne developed EverBatt to address this need. EverBatt is a free, publicly available Excel-based tool. It enables users to directly compare the costs and environmental impacts of recycling and other supply chain processes for EV batteries. Environmental impacts include energy use, water use, and air pollutant emissions.

EverBatt’s objective is to inform investment decisions in sustainable, cost-effective recycling infrastructure. As a simple example, EverBatt can help a user assess how a particular step in battery manufacturing might affect energy use during disassembly and recycling when the batteries are spent. A manufacturing step might be closing a battery pack with a bolt or a welded joint.

Since its 2019 release, EverBatt has been downloaded by more than 2,000 users. They include battery and vehicle manufacturers, recycling companies, researchers and others.

A key strength of the model is its flexibility. For instance, the model can adapt to different battery chemistries and production methods. Argonne often works with battery supply chain companies to customize the model to their specific needs. The changes are informed by extensive research to determine additional cost and environmental parameters. These collaborations can inform important technology decisions as companies grow.

“We encourage industry stakeholders to download the model and experiment with it,” said Jeff Spangenberger, Argonne’s Materials Recycling group leader. “They can reach out to us for help in maximizing its potential.”

Insights on recycling grid storage systems

Argonne customized EverBatt for Illinois-based Renewance. This company led one of the winning teams in the prize competition. Battery owners use Renewance’s digital platform to determine the most cost-effective, environmentally friendly reuse, repurposing and recycling options.

Many of Renewance’s customers have stationary grid storage systems at remote sites that need to be decommissioned. This involves dismantling the components before transporting them to a recycling or repurposing facility. Costs and greenhouse gas emissions associated with transportation can be significant.

Renewance can potentially lower logistics-related costs and emissions by holding the equipment in “interim storage” warehouses. When there is enough volume for transport of full truck loads, the equipment can be transported.

The public version of EverBatt focuses on EV batteries. As a result, it does not include analysis of decommissioning, interim storage and transportation activities associated with stationary storage. Argonne customized the model so that it could estimate greenhouse gas emissions for these activities in all 50 states.

The customized EverBatt model has helped Renewance demonstrate the benefits of interim storage to its customers.

“A key insight from the model was that costs and emissions from interim storage would usually be more than offset by the benefits of full truck shipments,” said Sander Jacobs, Renewance co-founder. “The model enables us to offer the most cost-effective, sustainable logistics to our clients.”

EverBatt revealed that greenhouse gas emissions from interim storage can vary significantly with the warehouse location. The variances are driven by differences in the local electricity mix.

“Careful planning is needed to account for distances between the warehouse, decommissioning site and recycling facilities,” said Qiang Dai, an Argonne sustainability analyst who developed EverBatt.

Renewance also uses EverBatt’s emissions estimates to inform customers on warehouse storage and transportation during a battery’s operating life. This includes activities associated with initial installation, commissioning and warranty-related replacements.

Making battery sorting smarter

Argonne also customized EverBatt for Virginia-based Li Industries, which won a prize for its Smart Battery Sorting System. This technology uses machine learning, cameras and other sensors to automate sorting and separation of end-of-life lithium-ion batteries. The system can sort by battery type and chemical composition.

Li Industries designed the technology to enable faster, more accurate and lower cost separation relative to traditional, manual sorting processes. Once separated, batteries are recycled to generate battery materials suitable for reuse.

Argonne customized EverBatt to evaluate the sorting system’s potential cost and environmental impacts on recycling supply chains. This effort included creating new cost models for automated and manual sorting technologies. Argonne also modified transportation parameters to account for sorting’s unique considerations.

Analysis with EverBatt revealed that the overall costs of an automated sorting plant are consistently lower than its manual counterpart. This is due to significantly lower labor costs. The model also showed that automated sorting has negligible environmental impacts relative to the overall recycling supply chain.

“EverBatt helped us to confirm that replacing manual sorting plants with automated ones will lower the overall supply chain costs,” said Zheng Li, CEO of Li Industries. “Our automated sorting line can help recyclers separate higher and lower value batteries more effectively. That capability can potentially improve recycling rates for more profitable battery materials.”

Another EverBatt insight: Co-locating the sorting plant with a pretreatment plant or a recycling plant can avoid additional transportation costs.

“We used EverBatt to analyze automated sorting systems with different features and processing capacities,” said Li. “This helped us to optimize the system for maximum economic benefits to the recycling industry.”

“The ability to customize EverBatt enabled both Li Industries and Renewance to gain insights on commercialization barriers and other challenges,” said Lauren Lynch, an NREL senior mechanical engineer. “This helped them optimize their concepts.” Lynch was an official reviewer and Prize Administrator for the recycling prize competition.

Building an integrated, national recycling ecosystem

EverBatt helps recycling stakeholders understand how various supply chain stages can be integrated most effectively.

“One of EverBatt’s biggest benefits is its ability to input decisions in one stage of the supply chain and see how they impact the entire industry,” said Li. “These insights can help policymakers create better regulations, incentives and infrastructure.”

“When we customize EverBatt for the recycling industry, the benefits go both ways,” said Argonne’s Dai. “Companies gain insights to inform their technology development. At the same time, Argonne researchers learn about additional, real-world aspects of recycling. That helps them make EverBatt a more comprehensive, accurate model.”