Review of Fusion Prognostics for Lithium-Ion Batteries - Current State and Future Challenges

The rapid increase in deployment of Lithium-ion (Li-ion) batteries across a wide range of applications such as automotive, robotics, energy networks and consumer products, present specific challenges to the optimal performance and reliability of Li-ion batteries. Charge-discharge cycles are the main factors degrading Li-ion battery capacity, thus directly affecting their lifetime. Studies on prognostic approaches for predicting state of health (SOH) and remaining useful life (RUL) of batteries aim at supporting their optimal operation and well-managed usage. This paper presents a review of state-of-the-art hybrid/fusion prognostics methods for assessing the SOH/RUL of Li-ion batteries, aiming to leverage the advantage of each to achieve a more accurate and/or more computationally efficient model. The respective underpinning fusion prognostics methods and algorithms for predicting SOH/RUL of Li-ion battery are outlined and discussed. A comparative analysis outlines their capabilities with respect to critical criteria, such as error and uncertainty handling capacity. The benefits and challenges of using these approaches are highlighted, as well as opportunities for continuing research into fusion prognostics approaches for Li-ion batteries posed by emerging applications.