Modeling and Evaluation of Dynamical Properties of Different Energy Storage Systems Using Machine Learning Methods
Author:
Affiliation:
1. Chair of Dynamics and Control University of Duisburg-Essen,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10403113/10403114/10403390.pdf?arnumber=10403390
Reference13 articles.
1. Adaptation of an Electrochemistry-based Li-ion Battery Model to Account for Deterioration Observed Under Randomized Use;Bole
2. The method of determining PEMFC fuel cell stack performance decrease rate based on the voltage-current characteristic shift
3. Li-Ion Batteries Parameter Estimation With Tiny Neural Networks Embedded on Intelligent IoT Microcontrollers
4. Machine Learning-Based Lithium-Ion Battery Capacity Estimation Exploiting Multi-Channel Charging Profiles
5. Data Preparation and Training Methodology for Modeling Lithium-Ion Batteries Using a Long Short-Term Memory Neural Network for Mild-Hybrid Vehicle Applications
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