{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T18:19:36Z","timestamp":1765995576906,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T00:00:00Z","timestamp":1748390400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"technology project about the development and application of hydrogen\u2013lithium hybrid zero-carbon power generation system equipment for long-term emergency supply","award":["JC2024115"],"award-info":[{"award-number":["JC2024115"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Proton exchange membrane fuel cell (PEMFC) hybrid vehicles offer a long driving range but are heavily dependent on energy management strategies (EMS). Traditional EMS methods, such as rule-based approaches and optimization-based methods like model predictive control (MPC), either lack flexibility or are computationally complex and rely on prior driving experience. To overcome these limitations, this study proposes a semi-empirical approach that combines state machine (SM) and MPC in a novel hybrid EMS (SM-MPC) to optimize power distribution in a 100 kW PEMFC hybrid vehicle. The SM-MPC strategy uses SM to handle fast power fluctuations and MPC to manage slow variations, balancing real-time adaptability and efficiency. Simulation results based on the NEDC and HWFET driving cycles show that compared to the traditional MPC method, SM-MPC significantly reduces hydrogen consumption by 7.11 g (NEDC) and 1.89 g (HWFET). Additionally, the proposed method effectively maintains the state of charge (SOC) of the lithium-ion battery using a PID controller and ensures the PEMFC stack temperature remains within \u00b15.8 \u00b0C. Overall, the SM-MPC strategy improves energy efficiency, reduces fuel consumption, and enhances the stability of the hybrid power system, offering a promising solution for real-time energy optimization in fuel cell vehicles.<\/jats:p>","DOI":"10.3390\/a18060322","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T10:21:13Z","timestamp":1748427673000},"page":"322","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Modelica-Based Energy Management of PEMFC Hybrid Power System of Vehicle"],"prefix":"10.3390","volume":"18","author":[{"given":"Keshu","family":"Zhang","sequence":"first","affiliation":[{"name":"Changzhou Changgong Electric Power Design Institute Co., Ltd., Changzhou 213200, China"}]},{"given":"Jiandong","family":"Jia","sequence":"additional","affiliation":[{"name":"Changzhou Changgong Electric Power Design Institute Co., Ltd., Changzhou 213200, China"}]},{"given":"Xiaodan","family":"Shangguan","sequence":"additional","affiliation":[{"name":"Changzhou Changgong Electric Power Design Institute Co., Ltd., Changzhou 213200, China"}]},{"given":"Jing","family":"Dong","sequence":"additional","affiliation":[{"name":"Changzhou Changgong Electric Power Design Institute Co., Ltd., Changzhou 213200, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alaswad, A., Omran, A., Sodre, J.R., Wilberforce, T., Pignatelli, G., Dassisti, M., and Olabi, A.G. 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