A key challenge in the widespread deployment and use of retired electric vehicle (EV) batteries for second-life (SL) applications is accurately estimating and monitoring their state of health (SOH). One of the main obstacles is the lack of knowledge about the historical usage of these battery packs, which can come from different sources.
However, a new online adaptive health estimation strategy has been introduced in this paper, aiming to overcome these challenges. This method relies solely on real-time operational data from SL batteries, allowing for on-the-field use. One of the key features of this strategy is that it guarantees bounded-input-bounded-output (BIBO) stability, ensuring reliable and accurate estimations.
In laboratory experiments using aged EV batteries, the proposed adaptive strategy has demonstrated its effectiveness. The estimator gains in this approach are dynamically adapted to suit the unique characteristics of each individual battery cell. This adaptability makes it a promising candidate for future SL battery management systems (BMS2).
This research is significant because it addresses a crucial issue in the second-life battery market. By providing accurate and real-time estimation of battery health, it enables better decision-making regarding the use and viability of retired EV batteries in various applications, such as energy storage systems or electric vehicle charging infrastructure.
In the future, it is possible that this online adaptive health estimation strategy could be further refined and integrated into battery management systems (BMS) used in electric vehicles. This would enhance the ability to assess the health and performance of EV batteries throughout their entire lifecycle, leading to improved efficiency and potentially extending their overall lifespan.
Furthermore, this research has the potential to contribute to the development of a circular economy for EV batteries. By utilizing retired batteries in second-life applications, their value and lifespan can be extended, reducing waste and promoting sustainability in the electric vehicle industry.