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State of Health Estimation for Lithium-Ion Battery Based on Long Short
PDF | On Feb 4, 2019, Zheng Chen and others published State of Health Estimation for Lithium-Ion Battery Based on Long Short Term Memory Networks | Find, read and cite all the research
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To address the mentioned problems, this paper proposes a novel SOH estimation method with an attentional long short-term memory network for lithium-ion batteries. Firstly, the
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Request PDF | Lithium-ion battery state of health estimation with short-term current pulse test and support vector machine | State of Health (SOH) of Lithium-ion (Li-ion)
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This method can estimate the battery state. The method-based model is based on the lithium-ion battery degradation and failure mechanism to accomplish the SOH estimation and prediction, although able to represent the
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The battery SOH results can be obtained through each of the eight short-term voltage profiles, thus the flexibility and rapidity of estimation are enhanced. In addition, to make
6 FAQs about [Battery short-term storage test method]
Does short-term storage affect the thermal stability of lithium-ion batteries?
In practical applications, lithium-ion batteries inevitably encounter short-term exposure to high or low temperatures due to geographical climate variations and specific usage scenarios. This study explored the impact of short-term storage at temperatures ranging from −40 to 60 °C on the thermal stability of batteries.
Can attentional long short-term memory network estimate the SoH of lithium-ion batteries?
Then, considering the correlation scores of different features, the proposed attentional long short-term memory network is used to estimate the SOH of lithium-ion batteries. Finally, to comprehensively evaluate the performance of the proposed method, three metrics were used for error analysis.
How can a method based model estimate the battery state?
This method can estimate the battery state. The method-based model is based on the lithium-ion battery degradation and failure mechanism to accomplish the SOH estimation and prediction, although able to represent the aging condition of internal model attenuation rules of critical parameters to achieve the intention of the SOH estimation.
How can LSTM be used to estimate the SoH of lithium-ion batteries?
The correlation scores of different features are considered and quantified to allocate more computational resources for the important input features, and an improved LSTM network structure based on the attention mechanism is used to estimate the SOH of lithium-ion batteries.
How is short-term low-temperature storage achieved?
Similarly, short-term low-temperature storage was achieved using a low-temperature test chamber with a temperature range of -70-0 °C. Prior to the experiment, the constant temperature was preset to the desired temperature for 2 h to ensure that the temperature in the chamber remained constant.
What is the temperature range of a battery storage chamber?
The batteries in this study were subjected to short-term high-temperature storage using a high-temperature test chamber with a temperature range of 10–150 °C. Similarly, short-term low-temperature storage was achieved using a low-temperature test chamber with a temperature range of -70-0 °C.