Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty

• المؤلفون الرئيسيون: Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.
• مؤلفون آخرون: 59055914200
• التنسيق: مقال
• منشور في: Institute of Electrical and Electronics Engineers Inc. 2025
• الموضوعات: Brain; Digital storage; Forecasting; Learning algorithms; Lithium-ion batteries; Long short-term memory; NASA; Particle swarm optimization (PSO); Accuracy; Battery; Capacity prediction; Gravitational search algorithm; Optimisations; Prediction algorithms; Predictive models; Remaining useful lives; Search Algorithms; Uncertainty; Deep neural networks

An accurate estimation of the remaining useful life (RUL) and capacity of lithium-ion batteries (LIBs) can guarantee safe and reliable operation and help to make wise replacement decisions. This paper presents an improved approach for predicting the RUL and capacity of LIB using a long short-term me...