Data-driven design of a cascaded observer for battery state of health estimation

Abstract

The design of an observer for battery state of charge (SoC) and state of health (SoH) using data-driven models is addressed. SoH estimation is an important issue in battery management system design for (hybrid) electrical vehicles. Without SoH correction, the accuracy of the SoC indication system will decrease progressively with battery age/degradation. In order to take the battery degradation into account, ageing data analysis using data-driven models and the associated model adaptation is addressed. Furthermore, a cascaded observer structure for combined SoC and SoH estimation is presented and preliminary results using real measurement data demonstrate the performance of the proposed concepts.