Utilizing an integrated AHP-COPRAS approach for battery selection in electric vehicles

Year 2023, Volume: 12 Issue: 4, 121 - 132, 30.12.2023

Aslı Abdulvahitoğlu , Gözde Ekmekçi Güçlüten

https://doi.org/10.18245/ijaet.1342516

Abstract

Internal combustion engine vehicles provide better performance and longer-range using fossil fuels such as gasoline and diesel. However, fossil fuels are non-renewable and cause environmental pollution, alternative fuels such as blends of ethanol and biodiesel, hydrogen etc have been sought for these vehicles. On the other hand, some researchers prefer to design alternative vehicles such as hybrid and electrical vehicles, instead of changing the fuel type. Among the studied topics for alternative vehicles, the battery is one of the most important components, especially in electrical vehicles. Batteries are diversified with different criteria such as battery life, nominal voltage, energy density, volumetric energy density, specific power, operating temperature, and production cost. In this study, the expert perspective was utilized when selecting the battery type to be employed for the energy source through utilizing the Integrated Analytical Hierarchy Process (AHP) - Complex Proportional Assessment (COPRAS), a multi-criteria decision-making approach. Various batteries such as Lead-acid (Pb-acid), Nickel-cadmium (Ni-Cd), Ni-MH, Sodium Nickel Chloride (Zero Emission Battery Research Activity-ZEBRA), Lithium –Ion (Li-Ion) Battery were evaluated in terms of different criterion. Among the alternatives the Li-ion battery type is chosen as the best option and the Ni-Cd battery is the least chosen alternative.

Keywords

Battery Selection, Electric Vehicle, AHP, COPRAS, Multi-Criteria Decision-Making

References

• Verma S., Mishra S., Gaur, A., Chowdhury S., Mohapatra S., Dwivedi G. and Verma P. A comprehensive review on energy storage in a hybrid electric vehicle. Journal of Traffic and Transportation Engineering (English Edition), 2021.
• Troy R. Hawkins, Ola Moa Gausen, Anders Hammer Strømman, Environmental impacts of hybrid and electric vehicles—a review, Int. J. Life Cycle Assess. 17(8), 997–1014, 2012.
• IEA, Global EV Outlook 2022, Technical Report, International Energy Agency, Paris, France, 2022, https://www.iea.org/reports/global-ev-outlook-2022, Accessed August 2023.
• TurkStadt https://www.tuik.gov.tr/ accessed August 223
• Özbay, H., Közkurt, C., Dalcalı, A., Tektaş, M. Geleceğin Ulaşım Tercihi: Elektrikli Araçlar. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 3 (1), 34-50, 2020.
• Sezen B. and İşler A.U. Elektrikli Araçların Mevcut Durumu, Tercih Edilme Ve Edilmeme Sebepleri. Turkish Journal of Marketing, 2(2), 82-103, 2017
• Winter M. and Brodd R.J. What are Batteries, Fuel Cells, and Supercapacitors? Chemical Reviews, 105 (3), 1021-1021, 2005
• Kerem, A. Elektrikli Araç Teknolojisinin Gelişimi ve Gelecek Beklentileri. Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 5 (1) , 1-13, 2014.
• Özcan, Ö. F., Karadağ, T., Altuğ, M., Özgüven, Ö. F. Elektrikli Araçlarda Kullanılan Pil Kimyasallarının Özellikleri ve Üstün Yönlerinin Kıyaslanması Üzerine Bir Derleme Çalışması. GU J Sci, Part A, 8(2), 276-298, 2021.
• Muratoğlu Y. and Alkaya A. Elektrikli Araç Teknolojisi ve Pil Yönetim Sistemi-İnceleme. Elektrik Mühendisliği, 458, 10-14, Eylül 2016.
• Budde-Meiwes H, Drillkens J, Lunz B, et al. A review of current automotive battery technology and future prospects. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 227(5):761-776. 2013
• Moralı, U. & Erol, S.,18650 lityum-iyon ve 6HR61 nikel-metal hidrit tekrar şarj edilebilir pillerinin elektrokimyasal empedans analizi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 35 (1) , 297-310. 2020.
• Miao Y, Hynan P, von Jouanne A, Yokochi A. Current Li-Ion Battery Technologies in Electric Vehicles and Opportunities for Advancements. Energies; 12(6):1074, 2019
• Demir G., Özyalçın A. T. Bircan H. Çok Kriterli Karar Verme Yöntemlerive ÇKKV Yazılımı ile Problem Çözümü, Nobel Yayınevi, 382 sf., Mayıs 2021.
• Alojaiman B., A Multi-Criteria Decision-Making Process for the Selection of an Efficient and Reliable IoT Application, Processes; 11(5):1313,2023.
• Halder S., Roy M.B., Roy P. K., Sedighi M., Groundwater vulnerability assessment for drinking water suitability using Fuzzy Shannon Entropy model in a semi-arid river basin, CATENA, Volume 229, 107206, 2023
• Geetha S., Jeon J.H., Stratified network mapping decision making technique based decision support framework for R&D budget allocation in South Korea, Socio-Economic Planning Sciences, Volume 87, Part B, 101579, 2023.
• Annamalai, P., Dhavamani, C. Experimental Investigation on Machining of Recycled Aluminum Alloy Metal Matrix Composite in ECMM. Trans Indian Inst Met 76, 1831–1839, 2023.
• Abdulvahitoglu A., Kilic M., A new approach for selecting the most suitable oilseed for biodiesel production; the integrated AHP-TOPSIS method, Ain Shams Engineering Journal, 13(3), 101604, 2022.
• Abdulvahitoğlu, A., Abdulvahitoğlu, A., Kılıç, M. Elektrikli Araç Bataryalarının Bütünleşik Swara-Topsis Metodu ile Değerlendirilmesi. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 37 (4), 1061-1076, (2022).
• Fossile, D.K.; Frej, E.A.; da Costa, S.E.G.; de Lima, E.P.; de Almeida, A.T. Selecting the most viable renewable energy source for Brazilian ports using the FITradeoff method. J. Clean. Prod., 260, 121107, 2020.
• Siksnelyte-Butkiene, I.; Zavadskas, E.K.; Streimikiene, D. Multi-Criteria Decision-Making (MCDM) for the Assessment of Renewable Energy Technologies in a Household: A Review. Energies, 13, 1164,2020.
• Ebbs-Picken T, Da Silva C. M., Amon C. H., Design optimization methodologies applied to battery thermal management systems: A review Journal of Energy Storage 67, 107460, 2023.
• Lamya Albraheem, Lama AlAwlaqi, Geospatial analysis of wind energy plant in Saudi Arabia using a GIS-AHP technique, Energy Reports, 9, 5878-5898, 2023.
• Brodny J., Tutak M., Assessing the energy security of European Union countries from two perspectives – A new integrated approach based on MCDM methods, Applied Energy, 347, 121443, 2023.
• Äkräs L., Vahvaselkä M., Silvenius F., Seppälä J., Ilvesniemi H., A multi-criteria decision-making framework and analysis of vegetable oils to produce bio-based plastics, Industrial Crops and Products, Volume 188, Part A, , 115584, 2022.
• Kang D., Jaisankar R., Murugesan V., Suvitha K., Narayanamoorthy S., Omar H. A, Arshad N. I., Ahmadian A., A novel MCDM approach to selecting a biodegradable dynamic plastic product: a probabilistic hesitant fuzzy set-based COPRAS method, Journal of Environmental Management, Volume 340, 17967, 2023.
• Daniel, M., Ahammed, M.M. & Shaikh, I.N. Selection of Greywater Reuse Options Using Multi-criteria Decision-making Techniques. Water Conserv Sci Eng 8, 2, 2023.
• Abdulvahitoğlu, A. Prioritization of risk factors causing juvenile delinquency with SWARA Method: A Case Study from Türkiye. Türk İdare Dergisi, 95(496):39-61, 2023
• Ecer F., Küçükönder H., Kaya S. K., Görçün Ö.F., Sustainability performance analysis of micro-mobility solutions in urban transportation with a novel IVFNN-Delphi-LOPCOW-CoCoSo framework, Transportation Research Part A: Policy and Practice, Volume 172, 103667, 2023.
• Deveci M., Pamucar D., Gokasar I., Zaidan B. B., Martinez L., Pedrycz W., Assessing alternatives of including social robots in urban transport using fuzzy trigonometric operators based decision-making model, Technological Forecasting and Social Change, 194, 122743, 2023.
• Can G. F., Toktaş P. and Pakdil F., Six Sigma Project Prioritization and Selection Using AHP–CODAS Integration: A Case Study in Healthcare Industry, in IEEE Transactions on Engineering Management, 70(10), 3587-3600, 2023.
• Akhoundi, B., Modanloo, V. A multi-criteria decision-making analysis on the extrusion-based additive manufacturing of ABS/Cu composites. Int J Interact Des Manuf 17, 1995–2003, 2023.
• Nayagam, V.L.G., Suriyapriya, K., Jagadeeswari, M. A Novel Similarity Measure Based on Accuracy Score of Conventional Type of Trapezoidal-Valued Intuitionistic Fuzzy Sets and Its Applications in Multi-criteria Decision-Making Problems. Int J Comput Intell Syst 16, 106, 2023.
• Lamrini, L., Abounaima, M.C. & Talibi Alaoui, M. New distributed-topsis approach for multi-criteria decision-making problems in a big data context. J Big Data 10, 97,2023.
• Loganathan M.K., Mishra B., Tan C.M., Kongsvik T. and Rai R.N. Multi-Criteria decision making (MCDM) for the selection of Li-Ion batteries used in electric vehicles (EVs). Materials Today: Proceedings 41, 1073-1077, 2021.
• Sonar H.C. and Kulkarni S.D. An Integrated AHP-MABAC Approach for Electric Vehicle Selection. Research in Transportation Business & Management, 41,100665, 2021.
• Chakraborty S., Saha A. K., Selection of optimal lithium ion battery recycling process: A multi-criteria group decision making approach, Journal of Energy Storage, 55, Part B, 105557, 2022.
• Wu Z., Khalilpour K., Hämäläinen R. P., A decision support tool for multi-attribute evaluation of demand-side commercial battery storage products, Sustainable Energy Technologies and Assessments, Volume 50, 2022, 101723.
• Zhao H., Guo S., Zhao H., Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences, Energy, 168, 450-461, 2019.
• Yücenurşen, A. & Samancı, A. Battery selection criteria for electric vehicles: techno-economic analysis. International Journal of Automotive Engineering and Technologies, 12(2), 65-74, 2023.
• Liang Y., Zhao C., Yuan H., Chen Y., Zhang W., Huang J., Yu D., Liu Y., Titirici M., Chueh Y., Yu H. and Zhang Q. A review of rechargeable batteries for portable electronic devices. Wiley Online Library, 1(1), 6-32, 2019.
• Ünal, Ö. F. Analitik Hiyerarşi Prosesi Ve Personel Seçimi Alanında Uygulamaları. Uluslararası Alanya İşletme Fakültesi Dergisi, 3 (2) , 18-38, 2011.
• Abdulvahitoğlu A. Using Analytic Hierarchy Process for Evaluating Different Biodiesels as an Alternative Fuel. Çukurova Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 33 (3), 177 – 186, 2018.
• Ishizaka A., Labib A. Review of the main developments in the analytic hierarchy process, Expert Systems with Applications, 38(11), 14336-14345, 2011.
• Alonso, J.A., Lamata, M.T. Consistency in the Analytic Hierarchy Process: A New Approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, (04), 445-459,2006.
• Davras, G. M. & Karaatlı, M., Otel İşletmelerinde Tedarikçi Seçimi Sürecinde Ahp Ve Bahp Yöntemlerinin Uygulanması. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi , 32 (1) , 87-112, 2014 .
• Awasthi, A., Satyaveer S. Chauhan. Using AHP and Dempster Shafer Theory for Evaluating Sustainable Transport Solutions, Environmental Modelling & Software 26(6):787-796, 2011.
• Hadjipaschalis, I., Poullikkas, A., & Efthimiou, V. Overview of current and future energy storage technologies for electric power applications. Renewable and Sustainable Energy Reviews, 13(6-7), 1513-1522, 2009.
• Cano, Z. P., Banham, D., Ye, S., Hintennach, A., Lu, J., Fowler, M. and Chen, Z. Batteries and fuel cells for emerging electric vehicle markets. Nature Energy, 3(4), 279-289, 2018.
• Perujo, A., Grootveld, G. V., and Scholz, H. Present and future role of battery electrical vehicles in private and public urban transport. In: Z. Stević (Eds), New Generation of Electric Vehicles (pp. 3-25). Intech, 2012.
• Khaligh, A. and Li, Z. Battery, ultracapacitor, fuel cell, and hybrid energy storage systems for electric, hybrid electric, fuel cell, and plug-in hybrid electric vehicles: State of the art. IEEE Transactions on Vehicular Technology, 59(6), 2806-2814, 2010.
• Soloveichik, G. L. Battery technologies for large-scale stationary energy storage. Annual Review of Chemical and Biomolecular Engineering, 2(1), 503-527, 2011.
• Vidyanandan, K. V. Batteries for Electric Vehicles. IEEE, 2019.
• S. M. Sundaram, M. Kulkarni and V. Diwakar, "Management of large format liion batteries," 2015 IEEE International Transportation Electrification Conference (ITEC), Chennai, India, 2015, pp. 1-7, doi: 10.1109/ITEC-India.2015.7386883.
• Hezer, S., Gelmez, E., & Özceylan, E. Comparative analysis of TOPSIS, VIKOR and COPRAS methods for the COVID-19 Regional Safety Assessment. Journal of infection and public health, 14(6), 775-786, 2021.