Pu Yang1,*, Wanning Yan1, Rong Li1, Lei Chen2, Lijie Guo2
CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 699-725, 2025, DOI:10.32604/cmc.2025.064947
- 09 June 2025
Abstract Lithium-ion batteries (LIBs) have been widely used in mobile energy storage systems because of their high energy density, long life, and strong environmental adaptability. Accurately estimating the state of health (SOH) for LIBs is promising and has been extensively studied for many years. However, the current prediction methods are susceptible to noise interference, and the estimation accuracy has room for improvement. Motivated by this, this paper proposes a novel battery SOH estimation method, the Beluga Whale Optimization (BWO) and Noise-Input Gaussian Process (NIGP) Stacked Model (BGNSM). This method integrates the BWO-optimized Gaussian Process Regression (GPR)… More >
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