Email this article Analisis Teknologi Manajemen Energi Pada Kendaraan Listrik Hibrida Berbasis Tinjauan Pustaka
Abstract
The application of hybrid electric vehicle technology has grown rapidly in recent years. This article aims to describe and discuss energy management strategies in hybrid electric vehicles. The research method is qualitative with a systematic literature review based on database searches on IEEE, Garuda SINTA, ArXiv, Preprints. The results obtained 13 articles from the IEEE database by describing the results of the energy management strategy of each article. The conclusion is that the technology used for energy management strategies includes algorithm settings, namely reinforcement learning and Q-learning combined with several control systems, namely predictive control models, Equivalent Consumption Minimization Strategy, and Dynamic Programming.
Keywords
Full Text:
PDFReferences
Y. Xiao dan M. Watson, Guidance on Conducting a Systematic Literature Review, J. Plan. Educ. Res., vol. 39, no. 1, hal. 93112, 2019, doi: 10.1177/0739456X17723971.
Y. Lin, J. McPhee, dan N. L. Azad, Co-Optimization of On-Ramp Merging and Plug-In Hybrid Electric Vehicle Power Split Using Deep Reinforcement Learning, hal. 111, 2022, [Daring]. Tersedia pada: http://arxiv.org/abs/2203.03113.
C. Z. Liu et al., The Bionics and its Application in Energy Management Strategy of Plug-in Hybrid Electric Vehicle Formation, IEEE Trans. Intell. Transp. Syst., vol. 22, no. 12, hal. 78607874, 2021, doi: 10.1109/TITS.2020.3017571.
Y. Wang, H. Tan, Y. Wu, dan J. Peng, Hybrid Electric Vehicle Energy Management with Computer Vision and Deep Reinforcement Learning, IEEE Trans. Ind. Informatics, vol. 17, no. 6, hal. 38573868, 2021, doi: 10.1109/TII.2020.3015748.
N. Yang, L. Han, C. Xiang, H. Liu, dan X. Hou, Energy Management for a Hybrid Electric Vehicle Based on Blended Reinforcement Learning with Backward Focusing and Prioritized Sweeping, IEEE Trans. Veh. Technol., vol. 70, no. 4, hal. 31363148, 2021, doi: 10.1109/TVT.2021.3064407.
H. Yu, F. Zhang, J. Xi, dan D. Cao, Mixed-Integer Optimal Design and Energy Management of Hybrid Electric Vehicles with Automated Manual Transmissions, IEEE Trans. Veh. Technol., vol. 69, no. 11, hal. 1270512715, 2020, doi: 10.1109/TVT.2020.3018445.
X. Gong, F. Dong, M. A. Mohamed, O. M. Abdalla, dan Z. M. Ali, A secured energy management architecture for smart hybrid microgrids considering PEM-Fuel cell and electric vehicles, IEEE Access, vol. 8, hal. 4780747823, 2020, doi: 10.1109/ACCESS.2020.2978789.
H. Lee, C. Kang, Y. Il Park, N. Kim, dan S. W. Cha, Online data driven energy management of a hybrid electric vehicle using model based Q-learning, IEEE Access, vol. 8, hal. 8444484454, 2020, doi: 10.1109/ACCESS.2020.2992062.
A. M. I. Fernandez, M. Kandidayeni, L. Boulon, dan H. Chaoui, An Adaptive State Machine Based Energy Management Strategy for a Multi Stack Fuel Cell Hybrid Electric Vehicle, IEEE Trans. Veh. Technol., vol. 69, no. 1, hal. 220 234, 2020, doi: 10.1109/TVT.2019.2950558.
J. Wu, Y. Zou, X. Zhang, G. Du, G. Du, dan R. Zou, A Hierarchical Energy Management for Hybrid Electric Tracked Vehicle Considering Velocity Planning with Pseudospectral Method, IEEE Trans. Transp. Electrif., vol. 6, no. 2, hal. 703716, 2020, doi: 10.1109/TTE.2020.2973577.
A. Rezaei, J. B. Burl, B. Zhou, dan M. Rezaei, A New Real-Time Optimal Energy Management Strategy for Parallel Hybrid Electric Vehicles, IEEE Trans. Control Syst. Technol., vol. 27, no. 2, hal. 830837, 2019, doi:
1109/TCST.2017.2775184.
D. Zhou, A. Al-Durra, I. Matraji, A. Ravey, dan F. Gao, Online Energy Management Strategy of Fuel Cell Hybrid Electric Vehicles: A Fractional-Order Extremum Seeking Method, IEEE Trans. Ind. Electron., vol. 65, no. 8, hal. 6787 6799, 2018, doi: 10.1109/TIE.2018.2803723.
H. I. Dokuyucu dan M. Cakmakci, Concurrent design of energy management and vehicle traction supervisory control algorithms for parallel hybrid electric vehicles, IEEE Trans. Veh. Technol., vol. 65, no. 2, hal. 555565, 2016, doi: 10.1109/TVT.2015.2405347.
Y. Zhang, H. Liu, dan Q. Guo, Varying-domain optimal management strategy for parallel hybrid electric vehicles, IEEE Trans. Veh. Technol., vol. 63, no. 2, hal. 603616, 2014, doi: 10.1109/TVT.2013.2276432.
A. Rezaei, An Optimal Energy Management Strategy for Hybrid Electric Vehicles. Michicgan Technology University, 2017, [Daring]. Tersedia pada: https://digitalcommons.mtu.edu/cgi/ viewcontent.cgi?article=1385&cont ext=etdr.
Y. Yang, Plug-In Hybrid Electric Vehicles, Adv. Electr. Drive Veh., no. October 2014, 2014, doi: 10.1201/b17506-15.
V. Franois-lavet et al., An Introduction to Deep Reinforcement Learning, Found. trends Mach. Learn., vol. II, no. 34, hal. 1140, 2018, doi: 10.1561/2200000071.
DOI: https://doi.org/10.33508/wt.v21i2.4531
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Widya Teknik is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License