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Improved Modeling of Lithium-Ion Battery Capacity Degradation Using an Individual-State Training Method and Recurrent Softplus Neural Network

机译：利用单个状态训练方法和经常性软多网络改进锂离子电池容量劣化建模

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Jianxiang Wang; Xuesong Feng; Xiaokun Zhang; Yong Xiang;
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年度 2021
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1. Improved Modeling of Lithium-Ion Battery Capacity Degradation Using an Individual-State Training Method and Recurrent Softplus Neural Network [J] . Jianxiang Wang, Xuesong Feng, Xiaokun Zhang, Quality Control, Transactions . 2021,第1期

机译：利用单个状态训练方法和经常性软多网络改进锂离子电池容量劣化建模
2. Data Preparation and Training Methodology for Modeling Lithium-Ion Batteries Using a Long Short-Term Memory Neural Network for Mild-Hybrid Vehicle Applications [J] . Daniel Jerouschek, ?mer Tan, Ralph Kennel, Applied Sciences . 2020,第21期

机译：使用长短短期记忆神经网络进行锂离子电池进行锂离子电池的数据准备和培训方法，用于轻度混合动力车辆应用
3. A multi-scale fusion prediction method for lithium-ion battery capacity based on ensemble empirical mode decomposition and nonlinear autoregressive neural networks [J] . Pei Wang, Xue Dan, Yong Yang International Journal of Distributed Sensor Networks . 2019,第3期

机译：基于集成经验模态分解和非线性自回归神经网络的锂离子电池容量多尺度融合预测方法
4. A data-driven method based on recurrent neural network method for online capacity estimation of lithium-ion batteries [C] . Sahar Khaleghi, S. Hamidreza Beheshti, Maitane Berecibar, IEEE Vehicle Power and Propulsion Conference . 2020

机译：一种基于锂离子电池在线容量估计的复发神经网络方法的数据驱动方法
5. State-of-Charge Estimation of the Lithium-Ion Battery Using Neural Network Based on an Improved Thevenin Circuit Model [D] . Zhang, Haoliang. 2018

机译：基于改进的戴维南电路模型的神经网络锂离子电池充电状态估计
6. Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas [O] . Lizhi Wang, Yusheng Sun, Xiaohong Wang, 2019

机译：基于回归模型和Copulas的考虑电池退化相关性的锂离子电池组可靠性建模方法
7. State-of-Charge Estimation of Lithium-Ion Batteries in the Battery Degradation Process Based on Recurrent Neural Network [O] . Shuqing Li, Chuankun Ju, Jianliang Li, 2021

机译：基于经常性神经网络的电池劣化过程中锂离子电池的充电状态估算

Improved Modeling of Lithium-Ion Battery Capacity Degradation Using an Individual-State Training Method and Recurrent Softplus Neural Network

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