Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude Regions
Proton exchange membrane fuel cells (PEMFCs), as a clean energy technology, show remarkable potential for a wide range of applications. However, high altitude regions pose significant challenges for PEMFC system operation due to thin air and low oxygen partial pressure. Existing logic judgement-base...
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| Format: | Article |
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MDPI AG
2025-01-01
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| Series: | Eng |
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| Online Access: | https://www.mdpi.com/2673-4117/6/1/19 |
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| author | Lei Gao Xuechao Wang |
| author_facet | Lei Gao Xuechao Wang |
| author_sort | Lei Gao |
| collection | DOAJ |
| description | Proton exchange membrane fuel cells (PEMFCs), as a clean energy technology, show remarkable potential for a wide range of applications. However, high altitude regions pose significant challenges for PEMFC system operation due to thin air and low oxygen partial pressure. Existing logic judgement-based controls exhibit defects such as poor robustness and poor adaptability, which seriously restrict PEMFC system operation. In order to address this issue, this paper puts forth an intelligent control of a PEMFC system air compressor (AC) and back pressure valve (BPV) using an asynchronous advantage actor-critic (A3C) algorithm and systematically compares it with the logic judgement-based control. The application of an A3C-based control under three distinct high altitude test conditions demonstrated a notable enhancement in dynamic responsiveness, with an improvement of up to 40% compared to the results for the logic judgement-based control. Additionally, an improvement of 5.8% in electrical efficiency was observed. The results demonstrate that the A3C-based control displays significant robustness and control precision in response to altitude alterations. |
| format | Article |
| id | doaj-art-fc58eb167ca9499bb4bc39f91432039d |
| institution | Kabale University |
| issn | 2673-4117 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Eng |
| spelling | doaj-art-fc58eb167ca9499bb4bc39f91432039d2025-01-24T13:31:36ZengMDPI AGEng2673-41172025-01-01611910.3390/eng6010019Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude RegionsLei Gao0Xuechao Wang1School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing 100811, ChinaChina Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, ChinaProton exchange membrane fuel cells (PEMFCs), as a clean energy technology, show remarkable potential for a wide range of applications. However, high altitude regions pose significant challenges for PEMFC system operation due to thin air and low oxygen partial pressure. Existing logic judgement-based controls exhibit defects such as poor robustness and poor adaptability, which seriously restrict PEMFC system operation. In order to address this issue, this paper puts forth an intelligent control of a PEMFC system air compressor (AC) and back pressure valve (BPV) using an asynchronous advantage actor-critic (A3C) algorithm and systematically compares it with the logic judgement-based control. The application of an A3C-based control under three distinct high altitude test conditions demonstrated a notable enhancement in dynamic responsiveness, with an improvement of up to 40% compared to the results for the logic judgement-based control. Additionally, an improvement of 5.8% in electrical efficiency was observed. The results demonstrate that the A3C-based control displays significant robustness and control precision in response to altitude alterations.https://www.mdpi.com/2673-4117/6/1/19proton exchange membrane fuel cellsair compressorback pressure valvehigh altitude regionsdeep reinforcement learning |
| spellingShingle | Lei Gao Xuechao Wang Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude Regions Eng proton exchange membrane fuel cells air compressor back pressure valve high altitude regions deep reinforcement learning |
| title | Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude Regions |
| title_full | Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude Regions |
| title_fullStr | Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude Regions |
| title_full_unstemmed | Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude Regions |
| title_short | Intelligent Control of the Air Compressor (AC) and Back Pressure Valve (BPV) to Improve PEMFC System Dynamic Response and Efficiency in High Altitude Regions |
| title_sort | intelligent control of the air compressor ac and back pressure valve bpv to improve pemfc system dynamic response and efficiency in high altitude regions |
| topic | proton exchange membrane fuel cells air compressor back pressure valve high altitude regions deep reinforcement learning |
| url | https://www.mdpi.com/2673-4117/6/1/19 |
| work_keys_str_mv | AT leigao intelligentcontroloftheaircompressoracandbackpressurevalvebpvtoimprovepemfcsystemdynamicresponseandefficiencyinhighaltituderegions AT xuechaowang intelligentcontroloftheaircompressoracandbackpressurevalvebpvtoimprovepemfcsystemdynamicresponseandefficiencyinhighaltituderegions |