• Circular Energy Storage's lifecycle data is together with the forecast of batteries placed on the market the backbone of Circular Energy Storage's battery volume forecasts. The data defines how much batteries that remain in the market, reach end of life and how much that will be reused and recycled.

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• The data consist of three different types of datasets: lifecycle data, reuse rates and application export rates.

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• The lifecycle data is the aggregated estimates of the time different types of batteries deployed during one year on average will remain in their original host products. Removal from the original host product is classified as end of life.​​​​The measure indicates how long each battery on average will power its original host product and at what point it will reach the end-of-life market. The data is based on research on how different types of batteries perform in their individual applications, how these or equivalent applications are used and what values they have over the lifetime as well as when the applications reach end of life. The background data will be further discussed in our analytical section.

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• The reuse rate defines how much of the batteries from the EOL volume that will be reused in either the same or in a new application. This varies by battery type, application and age of battery and is defined individually by application and in some cases by model (for light and heavy EV). The data is based on research of how batteries are reused, on prices of used batteries and the activities and capacity in the reuse market.​​

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• The application export rate defines how much of a year's deployment of applications that will be exported from their home markets with the batteries inside. Estimates are today produced for vehicles and the largest categories of portable applications as well as for personal mobility. The data is based on research on trade data, scraping and analysis of data from used product sales platforms as well as contacts with players in the market.

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• The data is continuously updated to adjust for changes in expectations, adjustments based on new historic data or errors.

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• The chart above describes the average lifecycle rate in 2010, 2020 and 2030 adjusted for the share varioius applications had/will have at the time they were placed on the market and shows the effect of an increasing share of applications that will remain in use for a long time.