Abstract
This paper presents a battery monitoring system using a multilayer neural network (MNN) for state of charge (SOC) estimation and state of health (SOH) diagnosis. In this system, the MNN utilizes experimental discharge voltage data from lithium battery operation to estimate SOH and uses present and previous voltages for SOC estimation. From experimental results, we know that the proposed battery monitoring system performs SOC estimation and SOH diagnosis well.
| Original language | English |
|---|---|
| Pages (from-to) | 206-213 |
| Number of pages | 8 |
| Journal | EPiC Series in Computing |
| Volume | 69 |
| DOIs | |
| State | Published - 9 Mar 2020 |
| Event | 35th International Conference on Computers and Their Applications, CATA 2020 - San Francisco, United States Duration: 23 Mar 2020 → 25 Mar 2020 |
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