Ultra-Fast Health Estimation of Li-ion Batteries Applying Online Internal Impedance Measurement

Lithium-ion (Li-ion) batteries have become the dominant energy storage technology of transportation and various industrial products in recent years. Despite the rapid growth in popularity, Li-ion battery usage faces several challenges such as safety and waste management difficulty. Safe and reliable use of Li-ion batteries depends on accurate state-of-health (SOH) estimation. While studies have shown various techniques of battery health estimation, most require either high computational effort or high cost of implementation. Battery state estimation based on impedance spectroscopy have gained traction in recent years due to many attractive benefits such as direct indication of battery performance and non-destructive measuring approach. Furthermore, online impedance measurement techniques based on broadband perturbations have been shown as a fast and cost-effective alternative to traditional impedance spectroscopy. This paper demonstrates the use of discrete-interval binary sequence (DIBS) method in developing an efficient SOH estimation algorithm for Li-ion batteries based on least-square techniques. Experimental results based on several commercial Li-ion battery cells at various conditions are presented and analyzed. A health prediction error of less than 1% was achieved from the experimental work.