In the design of electric vehicle battery packs, the optimal selection of parameters such as the number of series and parallel cells, the arrangement of cells, and their distance from the battery walls have a direct impact on the system performance. This paper presents a framework for the optimal design of battery packs that considers objectives such as minimizing cooling system consumption, controlling the maximum cell temperature, and optimizing the available space. This design is considered one of the key challenges in the production of electric vehicles due to its direct impact on the performance of the entire system and its importance in reducing weight, volume, cost, and increasing efficiency. The main innovation of this research is the use of the combination of the MOSOA algorithm to determine the optimal number of series and parallel cells and the MOGA algorithm to optimize the cell arrangement. Simulation results show that the proposed method reduces the battery volume by 22%, reduces the cost by 18%, increases the output power by 15%, and improves the temperature distribution by 10% compared to previous methods. This research can be a useful guide for the design and optimization of battery packs in electric vehicles.
G. Oskouei, N. Abdolmaleki, A. Bouyer, B. Arasteh, and K. Shirini, “Efficient Superpixel-based Brain MRI Segmentation Using Multi-scale Morphological Gradient Reconstruction and Quantum Clustering,”Biomedical Signal Processing and Control, vol. 100, p. 107063, 2025. doi: 10.1016/j.bspc.2024.107063.
Napa, M. K. Agrawal, B. Tamma, “Development of Electro-thermal Model for Air Cooling Study of Electric Vehicle Lithium-ion Battery Module Operating in Indian Conditions and Drive Cycle” Applied Thermal Engineering, Vol. 240, 122233, 2024. https://doi.org/10.1016/j.applthermaleng.2023.122233
Shirini, M. B. Kordan, and S. S. Gharehveran, “Impact of Learning Rate and Epochs on LSTM Model Performance: A Study of Chlorophyll-a Concentrations in the Marmara Sea,”Journal of Supercomputing, vol. 81, p. 265, 2025. https://doi.org/10.1007/s11227-024-06806-2
S. Gharehveran, K. Shirini, S. C. Khavar,et al., “Deep Learning-based Demand Response for Short-term Operation of Renewable-based Microgrids,”Journal of Supercomputing, vol. 80, pp. 26002–26035, 2024. https://doi.org/10.1007/s11227-024-06407-z
Shirini, H. S. Aghdasi, and S. Saeedvand, “Multi-objective Aircraft Landing Problem: A Multi-population Solution Based on Non-dominated Sorting Genetic Algorithm-II,”Journal of Supercomputing, vol. 80, pp. 25283–25314, 2024. https://doi.org/10.1007/s11227-024-06385-2
Shirini, H. S. Aghdasi, and S. Saeedvand, “A Comprehensive Survey on Multiple-runway Aircraft Landing Optimization Problem,”International Journal of Aeronautical and Space Sciences, vol. 25, no. 4, pp. 1574–1602, 2024. https://doi.org/10.1007/s42405-024-00747-z
Taherihajivand, A. , Shirini, K. and Samadi Gharehveran, S. (2024). An Overview of Product Performance Prediction Using Artificial Algorithms. Journal of Agricultural Mechanization, 9(3), 1-14. doi: 10.22034/jam.2024.61899.1276
Samadi Gharehveran, S., N. Najafpour, and K. Shirini, “A Hybrid Approach for Vehicle Detection and Tracking in Low-Visibility Conditions Based on AWBLP, YOLOv8, and GM-PHD Algorithms,” Journal of Machine Vision and Image Processing, pp. 1–11, 2025 (In Persian).
Scrosati, J. Hassoun, Y. K. Sun, “Lithium-ion batteries. A look into the future”, Energy & Environmental Science, Vol. 4, No. 9, pp. 3287-3295, 2011. https://doi.org/10.1039/C1EE01388B
C. Smart, B. V. Ratnakumar, L. D. Whitcanack, F. J. Puglia, S. Santee, R. Gitzendanner, “Life Verification of Large Capacity Yardney Li-ion Cells and Batteries in Support of NASA Missions”, International Journal of Energy Research, Vol. 34, No. 2, pp. 116-132, 2010. https://doi.org/10.1002/er.1653
Shirini, H. S. Aghdasi, and S. Saeedvand, “Modified Imperialist Competitive Algorithm for Aircraft Landing scheduling problem,” Journal of Supercomputing, vol. 80, pp. 13782–13812, 2024. https://doi.org/10.1007/s11227-024-05999-w
Zaki Dizaji, K. Shirini, A. Taheri Hajivand, and N. Monjezi, “Modelling Variables Affecting the Yield of Sugarcane Fields Using Deep Recurrent Neural Network,”Iranian Journal of Biosystems Engineering, vol. 55, no. 2, pp. 93–108, 2024. doi: 10.22059/ijbse.2025.378958.665557
Shirini and S. Samadi Gharehveran, “Balancing Time and Cost in Resource-Constrained Project Scheduling Using Meta-Heuristic Approach,”Journal of Agricultural Machinery, vol. 14, no. 2, 2024. https://doi.org/10.22067/jam.2023.81735.1157
Mirsadeghi and R. Ghaffarpour, "Improving the Resilience of Power Grids in the Face of Focused Attacks Using the Contingency Analysis," Passive Defense, vol. 13, no. 3, pp. 1-10, 2022 (In Persian). 20.1001.1.20086849.1401.13.3.1.8
Feng, J. Sun, M. Ouyang, F. Wang, X. He, L. Lu, H. Peng, “Characterization of Penetration Induced Thermal Runaway Propagation Process Within a Large Format Lithium-ion Battery Module”, Journal of Power Sources, Vol. 275, pp. 261-273, 2015. https://doi.org/10.1016/j.jpowsour.2014.11.017
Ghaffarpour and S. Zamanian, "The Coordinated Scheduling of Emerging Energy Resources to Improve the Resilience of Island Microgrids with a Two-Stage Decision-Making Approach," Passive Defense, vol. 12, no. 3, pp. 37-46, 2021(In Persian). doi: 10.1109/PD.2021.2965978.
M. T. Sattari, K. Shirini, and S. Javidan, “Evaluating the Efficiency of Dimensionality Reduction Methods in Improving the Accuracy of Water Quality Index Modeling in Qizil-Uzen River Using Machine Learning Algorithms,”Water and Soil Management and Modelling, vol. 4, no. 2, pp. 89–104, 2024.doi: 10.22098/mmws.2023.12434.1241
J. Kelly, M. Mihalic, M. Zolot, “Battery Usage and Thermal Performance of the Toyota Prius and Honda Insight During Chassis Dynamometer Testing”, Annual Battery Conference on Applications and Advances, Proceedings of Conference, pp. 247-252, 2002. doi: 10.1109/BCAA.2002.986408.
Taheri Hajivand, K. Shirini, and S. Samadi Gharehveran, “Weed Detection in Fields Using Convolutional Neural Network Based on Deep Learning,”Agricultural Engineering, vol. 47, no. 1, pp. 129–142, 2024. doi: 10.22055/agen.2024.45327.1688
Ahrari, K. Shirini, S. S. Gharehveran, M. G. Ahsaee, S. Haidari, and P. Anvari, “A Security-constrained Robust Optimization for Energy Management of Active Distribution Networks with Presence of Energy Storage and Demand Flexibility,”Journal of Energy Storage, vol. 84, p. 111024, 2024. https://doi.org/10.1016/j.est.2024.111024
Zahiri, K. Shirini, and S. Samadi Gharehveran, “Network Traffic Analysis with Machine Learning for Faster Detection of Distributed Denial of Service Attack,”Journal of Advanced Defense Science & Technology, 2024.
Samadi Gharehveran, S., “A Review of Energy Management of Multi-microgrid Power Systems in the Presence of Uncertainty of Distributed Generation Resources,” Power, Control, and Data Processing Systems, vol. 2, no. 4, pp. 46–58, 2025. https://doi.org/30511/pcdp.2025.2072671.1046
Gheibi, K. Shirini, S. N. Razavi,et al., “CNN-Res: Deep Learning Framework for Segmentation of Acute Ischemic Stroke Lesions on Multimodal MRI Images,”BMC Medical Informatics and Decision Making, vol. 23, p. 192, 2023. https://doi.org/10.1186/s12911-023-02289-y
Shirini, A. Taheri Hajivand, and S. Samadi Gharehveran, “A Review of Algorithms for Solving the Project Scheduling Problem with Resource-constrained Considering Agricultural Problems,”Journal of Agricultural Mechanization, vol. 8, no. 1, pp. 1–14, 2023. doi: 10.22034/jam.2023.55751.1227
F. da Silva, J. J. Eckert, F. L. Silva, L. C. Silva, F. G. Dedini, "Multi-objective Optimization Design and Control of Plug-in Hybrid Electric Vehicle Powertrain for Minimization of Energy Consumption, Exhaust Emissions and Battery Degradation," Energy Conversion and Management, vol. 234, pp. 113909, 2021. https://doi.org/10.1016/j.enconman.2021.113909
Gholinavaz, S., N. Saeedi, and S. S. Gharehveran, “Robustness Analysis of YOLO and Faster R-CNN for Object Detection in Realistic Weather Scenarios with Noise Augmentation,” Scientific Reports, vol. 15, p. 44888, 2025. https://doi.org/10.1038/s41598-025-28737-5
F. da Silva, J. J. Eckert, F. L. Silva, L. C. Silva, and F. G. Dedini, "Multi-objective Optimization Design and Control of Plug-in Hybrid Electric Vehicle Powertrain for Minimization of Energy Consumption, Exhaust Emissions, and Battery Degradation," Energy Conversion and Management, vol. 234, pp. 113909, 2021. https://doi.org/10.1016/j.enconman.2021.113909
S. Gharehveran, K. Shirini, and A. Abdolahi, “Optimizing Energy Storage Solutions for Grid Resilience: A Comprehensive Overview,” 2025. https://doi.org/ 10.5772/intechopen.1006499
Deb, K.; Jain, H. “An Evolutionary Many-objective Optimization Algorithm Using Reference-point-based Nondominated Sorting approach, Part I: Solving Problems with Box Constraints”: IEEE transactions on evolutionary computation, Vol. 18(4), pp. 577-601, 2023. doi: 10.1109/TEVC.2013.2281535
Samadi Gharehveran, S. (2026). Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization. Passive Defense, 16(4), 17-33. doi: 10.47176/PD.2026.1490
MLA
Sina Samadi Gharehveran. "Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization", Passive Defense, 16, 4, 2026, 17-33. doi: 10.47176/PD.2026.1490
HARVARD
Samadi Gharehveran, S. (2026). 'Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization', Passive Defense, 16(4), pp. 17-33. doi: 10.47176/PD.2026.1490
VANCOUVER
Samadi Gharehveran, S. Optimization of the Number of Batteries and their Arrangement in Electric Vehicles Based on Multi-Objective Optimization. Passive Defense, 2026; 16(4): 17-33. doi: 10.47176/PD.2026.1490
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