Cross-collaborative research, data and knowledge sharing is essential to make relevant advances in lithium-ion battery reuse. Today, this is not taking place in the intensity and scale as it should be with a openness on access for everyone. Our goal here is to make contributions towards this goal.
| Project duration | 06/2020 – 03/2021 |
| Status | Completed |
| Battery type reused | Laptop batteries |
| Location | Berlin (Germany) & Bangalore (India) |
| Pilot partners | Technical University Berlin, Nunam |
| Contact people |
Felipe Salinas, Technical University Berlin (felipe.salinas@eet.tu-berlin.de)
Darshan Virupaksha, Nunam (darshan@nunam.com) |
Project description
Despite many advancements in the recent years, there are still hundreds of millions of people in India and other developing countries with less or no access to electricity. Concurrently, there is rapid penetration of battery-operated portable computing devices such as laptops, both in the developing and developed world. This generates a significant amount of electronic waste (e-waste), especially in the form of discarded Lithium-ion batteries which power such devices. Many of those batteries could be reused, which helps to reduce the overall environmental and e-waste footprint of these batteries.
However, it is uncertain how long will these cells continue to operate in a new environment. Lithium-ion cells lifespan is affected by temperature and charge/discharge profiles, and in different magnitudes depending on cell design. Moreover, few information about their previous life can be obtained, making it difficult to forecast their degradation when operating again. This complicates choosing a second life that would make a good use of their remaining life.
The present project will produce a model that forecasts capacity degradation of used 18650 Li-ion cells, using as inputs cell characteristics tested between the transition of these cells from first to second life. Such a model will be obtained from the relation between these characteristics to capacity degradation tested under controlled conditions. This regression model will be built by EET in Berlin, Germany, out from data obtained by Nunam in Bangalore, India.