Smart Extreme Fast Portable Charger for Electric Vehicles-Based Artificial Intelligence
| العنوان: | Smart Extreme Fast Portable Charger for Electric Vehicles-Based Artificial Intelligence |
|---|---|
| المؤلفون: | Mahdi Mosayebi, Meysam Gheisarnejad, Hamed Farsizadeh, Bjorn Andresen, Mohammad Hassan Khooban |
| المصدر: | Mosayebi, M, Gheisarnejad Chirani, M, Farsizadeh, H, Andresen, B & Khooban, M H 2023, ' Smart Extreme Fast Portable Charger for Electric Vehicles-Based Artificial Intelligence ', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 70, no. 2, pp. 586-590 . https://doi.org/10.1109/TCSII.2022.3176863 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | machine learning, Electric vehicles, fast charger, sliding mode control, charger, Electrical and Electronic Engineering |
| الوصف: | Due to the increase in the number of electric vehicles (EVs) in the world, there is a need to design superior performance and lower operating costs of charging infrastructures to serve these vehicles. Merging extreme fast charging technology with the portable feature can provide a user-friendly and cost-effective structure for charging EVs. This brief proposes a Smart Extreme Fast Portable Charger (SEFPC) for Electric Vehicles which have several input ports (e.g., the power grid or Renewable Energy Sources (RESs)/Energy Storage Systems (ESSs)) and an output port with an optimal charging operation mode based on considering the condition of the available power sources and battery of EVs for saving the energy and time charging. Moreover, a model-free sliding mode controller-based machine learning algorithm is applied to find optimal charging operation mode based on the battery state and power of sources condition to increase battery life and overall system efficiency. Finally, real-time results based on the OPAL-RT are provided to validate the efficacy and feasibility of the proposed SEFPC and model-free sliding mode controller. |
| تدمد: | 1558-3791 1549-7747 |
| DOI: | 10.1109/tcsii.2022.3176863 |
| DOI: | 10.1109/TCSII.2022.3176863 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::742883ce8272ae9f5382afad41f7b22e https://doi.org/10.1109/tcsii.2022.3176863 |
| Rights: | RESTRICTED |
| رقم الانضمام: | edsair.doi.dedup.....742883ce8272ae9f5382afad41f7b22e |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15583791 15497747 |
|---|---|
| DOI: | 10.1109/tcsii.2022.3176863 |