Abstract
Lithium-ion (Li-ion) batteries have increasingly been used in diverse applications. Accurate estimation of the state of health (SOH) of the Li-ion batteries is vital for all stakeholders and critical in various applications such as electric vehicles (EVs). The electrical equivalent circuit (EEC) 2-RC model is often used to model the battery operation but has not been used to capture the degradation of battery cells over time. This paper uses the 2-RC model to capture the degradation of the Li-ion battery. The proposed model is not only time-dependent but also captures the effect of temperature on battery degradation. The proposed approach estimates the SOH accurately and is also considerably flexible for diverse cells of different chemistry. We further generalize an N-RC model approach to evaluate the SOH of the battery. We compare the proposed model (2-RC) with the 1-RC model, and through numerical results, we show that the 2-RC model outperforms 1-RC and reduces the computational cost significantly. Similarly, the 2-RC model outperforms 3-RC and higher-order circuits. We also show that the proposed approach can capture the battery dynamics better for specific smaller orders of the polynomial (associated with Arrhenius equation) when compared with the 1-RC approach with considerably reduced (up to 60%) root mean square error (RMSE). Lastly, the average testing RMSE for 2-RC is 52.4%.
Highlights
B ATTERIES are ubiquitous in 21st century; from personal computers to residential storage units, from storage for renewable energy sources to high power electric vehicles (EVs), batteries are used as sources of energy and storage
VALIDATION AND EVALUATION We evaluated our algorithm on the University of Maryland (UMD) Center for Advanced Life Cycle Engineering (CALCE) dataset, and National Aeronautics and Space Administration (NASA) Ames Research Center dataset
In this paper, a dynamic model based on a Thevenin equivalent circuit (EEC) (2RC) lumped with the Arrhenius equation is used to estimate the state of health (SOH)
Summary
B ATTERIES are ubiquitous in 21st century; from personal computers to residential storage units, from storage for renewable energy sources to high power electric vehicles (EVs), batteries are used as sources of energy and storage. The electrochemical model can capture the state of the electrode at a given instance This approach has its drawbacks, such as requiring the computation of a large number of complex parameters and having a high computational cost and so would not be suitable for real-time applications such as in EVs. Li-ion batteries are modelled as equivalent circuits comprising basic circuit elements like resistors and capacitors (RC) in the EEC model. A model which can capture this degradation as well to enhance the accuracy of estimated SOH is a challenge Differential methodologies such as incremental capacity analysis (ICA) and differential voltage analysis (DVD) are used to study the degradation of the Li-ion battery [39]–[41]. The RMSE for both models are compared for different values of m where m is the polynomial degree
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