From Aging-Aware Operation to Circular Value Retention: A Circular Battery Digital Twin for Electric Bus Fleets

The electrification of public transport has introduced new challenges in managing lithium-ion battery degradation, operational efficiency, and lifecycle sustainability. While battery digital twins (BDTs) have emerged as a promising solution for monitoring and prediction, most existing approaches remain limited to short-term state estimation and do not exploit lifecycle data for circular decision-making. This paper proposes a Circular Battery Digital Twin (CBDT) framework that in-tegrates aging-aware operation, predictive lifecycle modeling, and circular value retention within a unified architecture. The framework combines real-world oper-ational, environmental, and maintenance data to continuously calibrate a semi-empirical degradation model supporting multiple use cases, including route reas-signment and second-life assessment. The framework is demonstrated using a multi-year dataset from a real electric bus operating in Sweden. The bus operates with a 60 kWh LFP battery pack and relies exclusively on pantograph charging at terminus stops. The results show that CBDT enables consistent degradation esti-mation, supports cost-aware operational decisions, and provides a pathway to-ward circular battery management. The framework successfully identified an op-timal reassignment threshold at 70% load that extends operational life by 45%. The study demonstrates how integrating multi-source data and lifecycle intelli-gence enables the transition from reactive battery management to proactive and circular decision-making.