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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.17214 |
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| _version_ | 1866914103853842432 |
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| author | Fei, Chenyan Zhang, Dalin Dang, Chen Melinda |
| author_facet | Fei, Chenyan Zhang, Dalin Dang, Chen Melinda |
| contents | Effective and accurate diagnosis of fuel cell health status is crucial for ensuring the stable operation of fuel cell stacks. Among various parameters, high-frequency impedance serves as a critical indicator for assessing fuel cell state and health conditions. However, its online testing is prohibitively complex and costly. This paper employs a deep sparse auto-encoding network for the prediction and classification of high-frequency impedance in fuel cells, achieving metric of accuracy rate above 92\%. The network is further deployed on an FPGA, attaining a hardware-based recognition rate almost 90\%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_17214 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Diagnosis of Fuel Cell Health Status with Deep Sparse Auto-Encoder Neural Network Fei, Chenyan Zhang, Dalin Dang, Chen Melinda Machine Learning Artificial Intelligence Effective and accurate diagnosis of fuel cell health status is crucial for ensuring the stable operation of fuel cell stacks. Among various parameters, high-frequency impedance serves as a critical indicator for assessing fuel cell state and health conditions. However, its online testing is prohibitively complex and costly. This paper employs a deep sparse auto-encoding network for the prediction and classification of high-frequency impedance in fuel cells, achieving metric of accuracy rate above 92\%. The network is further deployed on an FPGA, attaining a hardware-based recognition rate almost 90\%. |
| title | Diagnosis of Fuel Cell Health Status with Deep Sparse Auto-Encoder Neural Network |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2510.17214 |