A Novel SOH Prediction Framework for the Lithium-ion Battery Using Echo State Network
暂无分享,去创建一个
Xiao Li | Zhe Li | Jianmin Wang | Youyi Zhao
[1] R. Gouriveau,et al. Fuel Cells prognostics using echo state network , 2013, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society.
[2] Dirk Uwe Sauer,et al. Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data , 2012 .
[3] Sun Zechang,et al. A new SOH prediction concept for the power lithium-ion battery used on HEVs , 2009, 2009 IEEE Vehicle Power and Propulsion Conference.
[4] IL-Song Kim,et al. A Technique for Estimating the State of Health of Lithium Batteries Through a Dual-Sliding-Mode Observer , 2010, IEEE Transactions on Power Electronics.
[5] Yu Peng,et al. Data-driven prognostics for lithium-ion battery based on Gaussian Process Regression , 2012, Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing).
[6] K. Goebel,et al. Prognostics in Battery Health Management , 2008, IEEE Instrumentation & Measurement Magazine.
[7] Bhaskar Saha,et al. Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework , 2009, IEEE Transactions on Instrumentation and Measurement.
[8] Jorge F. Silva,et al. Particle-Filtering-Based Prognosis Framework for Energy Storage Devices With a Statistical Characterization of State-of-Health Regeneration Phenomena , 2013, IEEE Transactions on Instrumentation and Measurement.