A Novel Nonlinear Approach for State of Health Estimation of Li-Ion Batteries Based on the Hammerstein-Wiener Model

The state of health is essential for energy storage units’ long life and high-efficiency use. Two different approaches, experimental-based and model-based, are used for State of Health (SOH) estimation. Experimental-based methods need all the real-time data of the batteries, which is caused the requirement of a very long time and data storage. Furthermore, the nonlinear electrochemical structures of batteries make modeling and estimating with model-based methods difficult. This paper proposes a novel approach for the SOH estimation of batteries based on the nonlinear Hammerstein-Wiener model. The Hammerstein-Wiener model is a well-established technique combining the advantages of linear and nonlinear models to capture a system’s dynamic behavior accurately. In this approach, the battery’s parameters are modeled as a series of linear and nonlinear functions, which are then combined to estimate the SOH. The proposed approach is evaluated using experimental data obtained from a lithium-ion battery. The results demonstrate the effectiveness of the proposed method in accurately estimating the SOH of the battery. The proposed approach offers a promising alternative to existing methods for SOH estimation of batteries and has potential applications in electric vehicles and renewable energy systems.