TY - JOUR T1 - Sizing of Power Train and Cooling of the Battery Systems of Hybrid Electric Vehicles by using Genetic Algorithm TT - Sizing of Power Train and Cooling of the Battery Systems of Hybrid Electric Vehicles by using Genetic Algorithm AU - Paşaoğlu, Ali PY - 2025 DA - April Y2 - 2025 DO - 10.30931/jetas.1621733 JF - Journal of Engineering Technology and Applied Sciences JO - JETAS PB - Muhammet KURULAY WT - DergiPark SN - 2548-0391 SP - 45 EP - 61 VL - 10 IS - 1 LA - en AB - Nowadays, the development of HEVs is done from three approaches: emission, fuel consumption, and vehicle performance. Due to the expansion of the use of HEVs around the world, optimal performance of the power train and power supply in the vehicle system has become an important issue. In this paper, in the first step, an optimal cooling attempt was made during power transfer in batteries by designing battery modules and their optimal configuration. The optimal design of the components of the transmission system and their optimized sizing have been performed in such a way that, while reducing emissions and fuel consumption, the dynamic performance of the vehicle is maintained at the standard level of passenger ones. The characteristics of class B passenger vehicle were utilized for modeling and simulation of the HEV and its optimization carried out by the constrained multi-objective genetic algorithm. It has been depicted that with the simultaneous sizing of power transmission components and optimal cooling of the battery system, fuel consumption and emission can be reduced by 5% and 8%, respectively, in various cycles of driving and traffic conditions. KW - Fuel consumption KW - emissions KW - power transmission structure KW - hybrid electric vehicle N2 - Nowadays, the development of HEVs is done from three approaches: emission, fuel consumption, and vehicle performance. Due to the expansion of the use of HEVs around the world, optimal performance of the power train and power supply in the vehicle system has become an important issue. In this paper, in the first step, an optimal cooling attempt was made during power transfer in batteries by designing battery modules and their optimal configuration. The optimal design of the components of the transmission system and their optimized sizing have been performed in such a way that, while reducing emissions and fuel consumption, the dynamic performance of the vehicle is maintained at the standard level of passenger ones. The characteristics of class B passenger vehicle were utilized for modeling and simulation of the HEV and its optimization carried out by the constrained multi-objective genetic algorithm. It has been depicted that with the simultaneous sizing of power transmission components and optimal cooling of the battery system, fuel consumption and emission can be reduced by 5% and 8%, respectively, in various cycles of driving and traffic conditions. CR - [1] Ruan, J., Walker, P.D., Zhang, N., Wu, J., “An investigation of hybrid energy storage system in multi-speed electric vehicle”, Energy 140 (2017) : 291-306. CR - [2] Ruan, J., Walker, P., Zhang, N., “A comparative study energy consumption and costs of battery electric vehicle transmissions”, Applied energy 165 (2016) : 119-134. CR - [3] Ahmadi, S., Bathaee, S.M.T., Hosseinpour, A.H., “Improving fuel economy and performance of a fuel-cell hybrid electric vehicle (fuel-cell, battery, and ultra-capacitor) using optimized energy management strategy”, Energy Conversion and Management 160 (2018) : 74-84. CR - [4] Madanipour, V., Montazeri-Gh, M., Mahmoodi-k, M., “Optimization of the component sizing for a plug-in hybrid electric vehicle using a genetic algorithm”, Proceedings of the institution of mechanical engineers, Part D: journal of automobile engineering 230(5) (2016) : 692-708. CR - [5] Mazouzi, A., Hadroug, N., Alayed, W., Hafaifa, A., Iratni, A., Kouzou, A. “Comprehensive optimization of fuzzy logic-based energy management system for fuel-cell hybrid electric vehicle using genetic algorithm”, International Journal of Hydrogen Energy 81 (2024) : 889-905. CR - [6] Tran, D.D., Vafaeipour, M., El Baghdadi, M., Barrero, R., Van Mierlo, J., Hegazy, O., “Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies”, Renewable and Sustainable Energy Reviews 119 (2020) : 109596. CR - [7] Nguyen-Minh, T., Nguyễn, B.H., Vo-Duy, T., Ta, M.C., Trovão, J.P.F., Antunes, C.H., “A universal optimal sizing for hybrid energy storage system of electric vehicles”, Journal of Energy Storage 92 (2024) : 112128. CR - [8] Chen, S.Y., Wu, C.H., Hung, Y.H., Chung, C.T., “Optimal strategies of energy management integrated with transmission control for a hybrid electric vehicle using dynamic particle swarm optimization”, Energy 160 (2018) : 154-170. CR - [9] Nainggolan, N., Maghsoudlou, E., AlWadi, B.M., Atamurotov, F., Kosov, M., Putra, W., “Advancements in Optimization for Automotive Manufacturing: Hybrid Approaches and Machine Learning”, International Journal of Industrial Engineering and Management 15(3) (2024) : 254-263. CR - [10] Liu, H., Han, L., Cao, Y., “Improving transmission efficiency and reducing energy consumption with automotive continuously variable transmission: A model prediction comprehensive optimization approach”, Applied Energy 274 (2020) : 115303. CR - [11] Luo, Y., Chen, T., Zhang, S., Li, K. “Intelligent hybrid electric vehicle ACC with coordinated control of tracking ability, fuel economy, and ride comfort”, IEEE Transactions on Intelligent Transportation Systems 16(4) (2015) : 2303-2308. CR - [12] Das, H.S., Tan, C.W., Yatim, A.H.M., “Fuel cell hybrid electric vehicles: A review on power conditioning units and topologies”, Renewable and Sustainable Energy Reviews 76 (2017) : 268-291. CR - [13] Montazeri-Gh, M., Mahmoodi-K, M., “Optimized predictive energy management of plug-in hybrid electric vehicle based on traffic condition”, Journal of cleaner production 139 (2016) : 935-948. CR - [14] Montazeri-Gh, M., Pourbafarani, Z., Mahmoodi-k, M., “Comparative study of different types of PHEV optimal control strategies in real-world conditions”, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 232(12) (2018) : 1597-1610. CR - [15] Anselma, P.G., Niutta, C.B., Mainini, L., Belingardi, G., “Multidisciplinary design optimization for hybrid electric vehicles: component sizing and multi-fidelity frontal crashworthiness”, Structural and Multidisciplinary Optimization 62 (2020) : 2149-2166. CR - [16] Park, S., Ahn, C., “Power management controller for a hybrid electric vehicle with predicted future acceleration”, IEEE Transactions on Vehicular Technology 68(11) (2019) : 10477-10488. CR - [17] Huang, Y., Wang, H., Khajepour, A., Li, B., Ji, J., Zhao, K., Hu, C., “A review of power management strategies and component sizing methods for hybrid vehicles”, Renewable and Sustainable Energy Reviews 96 (2018) : 132-144. CR - [18] Cai, Y., Ouyang, M.G., Yang, F., “Impact of power split configurations on fuel consumption and battery degradation in plug-in hybrid electric city buses”, Applied Energy 188 (2017) : 257-269. CR - [19] Mayyas, A.R.O., Kumar, S., Pisu, P., Rios, J., Jethani, P., “Model-based design validation for advanced energy management strategies for electrified hybrid power trains using innovative vehicle hardware in the loop (VHIL) approach”, Applied Energy 204 (2017) : 287-302. CR - [20] Yang, R., Yang, X., Huang, W., Zhang, S., “Energy management of the power-split hybrid electric city bus based on the stochastic model predictive control”, IEEE Access 9 (2020) : 2055-2071. CR - [21] Dindar, S., “A Comprehensive Analysis of Strategies, Challenges and Policies on Turkish Sustainable Energy Development”. Journal of Engineering Technology and Applied Sciences 7(3) (2022) : 231-250. UR - https://doi.org/10.30931/jetas.1621733 L1 - https://dergipark.org.tr/en/download/article-file/4528751 ER -