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Year 2020, Volume: 3 Issue: 1, 30 - 46, 30.06.2020

Abstract

References

  • Nitta, N., Wu, F., Lee, J. T., and Yushin, G., Li-ion battery materials: present and future. Materials Today, 2015, 18(5):252–264.
  • Nishi, Y., Lithium ion secondary batteries; past 10 years and the future, Journal of Power Sources, 2001, 100(1-2): 101-106.
  • Sarkar, A., Shrotriya, P., Chandra, A., Parametric Analysis of Electrode Materials on Thermal Performance of Lithium-Ion Battery: A Material Selection Approach Batteries and Energy Storage, J. Electrochem. Soc., 2018, 165(9): A1587-A1594.
  • Mishra, A., Mehta, A., Basu, S., Malode, S. J, Nagaraj P. Shetti, N. P., Shukla, S., Nadagouda, M. N., Aminabhavi, T. M., Electrode materials for lithium-ion batteries, Materials Science for Energy Technologies, 2018, 1(2): 182-187.
  • Panday, A. , and Bansal, H. O. , Multi-Objective Optimization in Battery Selection for Hybrid Electric Vehicle Applications. Journal of Electrical Systems, 2016, 12(2):325–343.
  • Kaa, G., Fens, T., Rezaei, J., Residential grid storage technology battles: a multi-criteria analysis using BWM, Technology Analysis and Strategic Management, 2019, 31(1):40-52.
  • Sangwan, S. K., Jindal, A., An integrated fuzzy multi-criteria evaluation of lithium-ion battery recycling processes, International Journal of Sustainable Engineering, 2013, 6(4): 359-371.
  • Warner, J. T., The Handbook of Lithium-Ion Battery Pack Design: Chemistry, Components, Types and Terminology, Elsevier, Grand Blanck, MI,, 2015, 1–80.
  • Graf, C., Cathode materials for lithium-ion batteries, Lithium-ion batteries: basics and applications. Edited by Korthauer, R., and Wuest, M., Springer, 2018, 29-40.
  • Deng, D., Li-ion batteries: Basics, Progress, and Challenges, Energy Science & Engineering, 2015, 3(5): 385–418.
  • Scrosati, B., and Garche, J., Lithium Batteries: Status, Prospects and Future. Journal of Power Sources, 2010, 195(9):2419–2430.
  • Gwon, H., Hong, J., Kim, H., Seo, D.-H., Jeon, S., and Kang, K., Recent Progress on Flexible Lithium Rechargeable Batteries. Energy Environ. Sci., 2014, 7(2):538-551.
  • Yuan, M., Erdman, J., Tang, C., and Ardebili, H., 2014, “High Performance Solid Polymer Electrolyte with Graphene Oxide Nanosheets,” RSC Adv., 4(103), pp. 59637–59642.
  • Doeff, M. M., Chapter 2: Battery Cathodes. Batteries for Sustainability: Selected Entries from the Encyclopedia of Sustainability Science and Technology. Edited by Brodd J. R., Springer, New York, NY, 2013, 5–49.
  • Manthiram, A., Materials Challenges and Opportunities of Lithium Ion Batteries. The Journal of Physical Chemistry Letters, 2011, 2(3):176–184.
  • Wang, Y., and Huang, H.-Y. S., An Overview of Lithium-Ion Battery Cathode Materials. MRS Proceedings, 2011, 1363.
  • Doughty, D. H., and Roth, E. P., A General Discussion of Li Ion Battery Safety. The Electrochemical Society Interface, 2012, 21(2):37–44.
  • Schmuch, R., Wagner, R., Hörpel, G., Placke, T., & Winter, M., Performance and cost of materials for lithium-based rechargeable automotive batteries. Nature Energy, 2018, 3(4): 267–278.
  • Al-Hallaj, S., Wilk, G., Crabtree, G., and Eberhard, M., Overview of distributed energy storage for demand charge reduction. MRS Energy & Sustainability, 2018, 5(1): 1–18.
  • Lazim, A., Norsyahida Z., Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: An application to human resource management, Expert Systems with Applications, 2015, 42(9): 4397-4409.
  • Ying-Chyi C., Chia-Chi S., Hsin-Yi Y., Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach, Applied Soft Computing, 2012, 12(1):64-71.
  • Marbini A.H. and Tavana M., An extension of the Electre I method for group decision-making under a fuzzy environment, Omega, 2011, 39 (4): 373-386.
  • Sen, C. G., Cinar, G., Evaluation and pre-allocation of operators with multiple skills: A combined fuzzy AHP and max–min approach, Expert Systems with Applications, 2010, 37 (3): 2043-2053.
  • Ling W., Jian C., Jun W., Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process, International Journal of Production Economics, 2007, 107(1): 151-163.
  • Yeap, J.A.L., Ignatius J., Ramayah, T., Determining consumers’ most preferred eWOM platform for movie reviews: A fuzzy analytic hierarchy process approach, Computers in Human Behavior, 2014, 31: 250-258.
  • Saaty, R.,The analytic hierarchy process–what it is and how it is used, Math. Model.,1987,9:161–176.
  • Dweiri, F., Al-Oqla, F. M., Material selection using analytical hierarchy process. Int. J. Comput. Appl. Technol., 2006, 26 (4):182-189.
  • Kiong, S. C., Lee, L. Y., Chong, S. H., Azlan, M. A., Nor, N. H. M., Decision Making with the Analytical Hierarchy Process (AHP) for Material Selection in Screw Manufacturing for Minimizing Environmental Impacts, Applied Mechanics and Materials, 2013, 315: 57-62.
  • Kühn, F., Rehra, J., May, D., Schmeer, S., Mitschang, P., Dry fiber placement of carbon/steel fiber hybrid preforms for multifunctional composites, Advanced Manufacturing: Polymer & Composites Science, 2019,5(1):37-49.
  • Zadeh, L., Fuzzy sets. Information and Control, 1965, 8:338- 353.
  • Zadeh, L., The consept of a linguistic variable and its applications to approximate reasoning. Inform Science, 1975, 8:199- 249.
  • Hagras, H., Type-2 flcs: A new generation of fuzzy controllers. IEEE Computational Intelligence Magazine, 2007, 2:30-43.
  • Greenfield, S., Chiclana, F., John, R., Coupland, S., The sampling method of defuzzification for type-2 fuzzy sets: Experimental evaluation, Information Sciences, 2012, 189: 77- 92.
  • Mendel, J.M., John, R., Liu, F., Interval type-2 fuzzy logic systems made simple. IEEE T. Fuzzy Systems, 2006, 14:808- 821.
  • Young, K., Wang,, C., Wang, L. Y., and Strunz, K., Electric Vehicle Battery Technologies. Electric vehicle integration into modern power networks. Edited by R. Garcia-Valle, and J.A.P. Lopes, SPRINGER-VERLAG NEW YORK, 2013, 15–56.
  • W. Reaugh, Larry. Re-Cycling Spent Electric Vehicle Batteries Potentially Recovers Significant Amounts of Lithium, Cobalt and Other Cathode Metals. American Manganese Inc., 19 Jan. 2017, https://americanmanganeseinc.com/re-cycling-spent-electric-vehicle-batteries-potentially-recovers-significant-amounts-of-lithium-cobalt-and-other-cathode-metals/.(accessed September 10, 2019).
  • Sen, C. G., Cinar, G., Evaluation and pre-allocation of operators with multiple skills: A combined fuzzy AHP and max–min approach, Expert Systems with Applications, 2010, 37 (3): 2043-2053.
  • Bhushan, N., & Rai, K. (2004). Strategic Decision Making: Applying the Analytic Hierarchy Process. Decision Engineering. Springer London.
  • Türk, S. John, R. and Özcan, E., Interval type-2 fuzzy sets in supplier selection, 14th UK Workshop on Computational Intelligence (UKCI), Bradford, 2014, pp. 1-7.
  • Chen, S., Lee, L., Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method, Expert Systems with Applications, 2010, 37 (4): 2790-2798.

COMPARISON OF AN INTERVAL TYPE-2 FUZZY SETS AND AHP METHODS FOR MATERİAL SELECTION PROBLEM ON LITHIUM-ION BATTERİES

Year 2020, Volume: 3 Issue: 1, 30 - 46, 30.06.2020

Abstract

Lithium-ion batteries have become one of the most commercially preferred energy storage devices because of their high energy density, low self-discharge rate, and the ability to be cycled many times with slow capacity fading in comparison with other rechargeable batteries. They have been applied on a wide variety of electrical devices and systems such as consumer electronics, power tools, electric vehicles and aerospace equipment. The characteristics of Li-ion batteries are mainly determined by the materials used for its components which can be categorized into four parts: anode and cathode electrodes, separator, and electrolyte. Over the last decade, there has been a significant increase in the number of studies evaluating battery performance based on various materials used in each battery component. However, few attempts have been made to evaluate materials of Lithium-ion batteries. Thus, in this study, we aim to evaluate different materials for cathode electrode in terms of four main criteria: cost, performance, safety and service life using two methods; AHP and interval type-2 fuzzy sets. It is shown that more reliable results are obtained for selecting the best cathode material of Li-ion battery and based on comparison of two methods, same rank is achieved for both approaches.

References

  • Nitta, N., Wu, F., Lee, J. T., and Yushin, G., Li-ion battery materials: present and future. Materials Today, 2015, 18(5):252–264.
  • Nishi, Y., Lithium ion secondary batteries; past 10 years and the future, Journal of Power Sources, 2001, 100(1-2): 101-106.
  • Sarkar, A., Shrotriya, P., Chandra, A., Parametric Analysis of Electrode Materials on Thermal Performance of Lithium-Ion Battery: A Material Selection Approach Batteries and Energy Storage, J. Electrochem. Soc., 2018, 165(9): A1587-A1594.
  • Mishra, A., Mehta, A., Basu, S., Malode, S. J, Nagaraj P. Shetti, N. P., Shukla, S., Nadagouda, M. N., Aminabhavi, T. M., Electrode materials for lithium-ion batteries, Materials Science for Energy Technologies, 2018, 1(2): 182-187.
  • Panday, A. , and Bansal, H. O. , Multi-Objective Optimization in Battery Selection for Hybrid Electric Vehicle Applications. Journal of Electrical Systems, 2016, 12(2):325–343.
  • Kaa, G., Fens, T., Rezaei, J., Residential grid storage technology battles: a multi-criteria analysis using BWM, Technology Analysis and Strategic Management, 2019, 31(1):40-52.
  • Sangwan, S. K., Jindal, A., An integrated fuzzy multi-criteria evaluation of lithium-ion battery recycling processes, International Journal of Sustainable Engineering, 2013, 6(4): 359-371.
  • Warner, J. T., The Handbook of Lithium-Ion Battery Pack Design: Chemistry, Components, Types and Terminology, Elsevier, Grand Blanck, MI,, 2015, 1–80.
  • Graf, C., Cathode materials for lithium-ion batteries, Lithium-ion batteries: basics and applications. Edited by Korthauer, R., and Wuest, M., Springer, 2018, 29-40.
  • Deng, D., Li-ion batteries: Basics, Progress, and Challenges, Energy Science & Engineering, 2015, 3(5): 385–418.
  • Scrosati, B., and Garche, J., Lithium Batteries: Status, Prospects and Future. Journal of Power Sources, 2010, 195(9):2419–2430.
  • Gwon, H., Hong, J., Kim, H., Seo, D.-H., Jeon, S., and Kang, K., Recent Progress on Flexible Lithium Rechargeable Batteries. Energy Environ. Sci., 2014, 7(2):538-551.
  • Yuan, M., Erdman, J., Tang, C., and Ardebili, H., 2014, “High Performance Solid Polymer Electrolyte with Graphene Oxide Nanosheets,” RSC Adv., 4(103), pp. 59637–59642.
  • Doeff, M. M., Chapter 2: Battery Cathodes. Batteries for Sustainability: Selected Entries from the Encyclopedia of Sustainability Science and Technology. Edited by Brodd J. R., Springer, New York, NY, 2013, 5–49.
  • Manthiram, A., Materials Challenges and Opportunities of Lithium Ion Batteries. The Journal of Physical Chemistry Letters, 2011, 2(3):176–184.
  • Wang, Y., and Huang, H.-Y. S., An Overview of Lithium-Ion Battery Cathode Materials. MRS Proceedings, 2011, 1363.
  • Doughty, D. H., and Roth, E. P., A General Discussion of Li Ion Battery Safety. The Electrochemical Society Interface, 2012, 21(2):37–44.
  • Schmuch, R., Wagner, R., Hörpel, G., Placke, T., & Winter, M., Performance and cost of materials for lithium-based rechargeable automotive batteries. Nature Energy, 2018, 3(4): 267–278.
  • Al-Hallaj, S., Wilk, G., Crabtree, G., and Eberhard, M., Overview of distributed energy storage for demand charge reduction. MRS Energy & Sustainability, 2018, 5(1): 1–18.
  • Lazim, A., Norsyahida Z., Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: An application to human resource management, Expert Systems with Applications, 2015, 42(9): 4397-4409.
  • Ying-Chyi C., Chia-Chi S., Hsin-Yi Y., Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach, Applied Soft Computing, 2012, 12(1):64-71.
  • Marbini A.H. and Tavana M., An extension of the Electre I method for group decision-making under a fuzzy environment, Omega, 2011, 39 (4): 373-386.
  • Sen, C. G., Cinar, G., Evaluation and pre-allocation of operators with multiple skills: A combined fuzzy AHP and max–min approach, Expert Systems with Applications, 2010, 37 (3): 2043-2053.
  • Ling W., Jian C., Jun W., Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process, International Journal of Production Economics, 2007, 107(1): 151-163.
  • Yeap, J.A.L., Ignatius J., Ramayah, T., Determining consumers’ most preferred eWOM platform for movie reviews: A fuzzy analytic hierarchy process approach, Computers in Human Behavior, 2014, 31: 250-258.
  • Saaty, R.,The analytic hierarchy process–what it is and how it is used, Math. Model.,1987,9:161–176.
  • Dweiri, F., Al-Oqla, F. M., Material selection using analytical hierarchy process. Int. J. Comput. Appl. Technol., 2006, 26 (4):182-189.
  • Kiong, S. C., Lee, L. Y., Chong, S. H., Azlan, M. A., Nor, N. H. M., Decision Making with the Analytical Hierarchy Process (AHP) for Material Selection in Screw Manufacturing for Minimizing Environmental Impacts, Applied Mechanics and Materials, 2013, 315: 57-62.
  • Kühn, F., Rehra, J., May, D., Schmeer, S., Mitschang, P., Dry fiber placement of carbon/steel fiber hybrid preforms for multifunctional composites, Advanced Manufacturing: Polymer & Composites Science, 2019,5(1):37-49.
  • Zadeh, L., Fuzzy sets. Information and Control, 1965, 8:338- 353.
  • Zadeh, L., The consept of a linguistic variable and its applications to approximate reasoning. Inform Science, 1975, 8:199- 249.
  • Hagras, H., Type-2 flcs: A new generation of fuzzy controllers. IEEE Computational Intelligence Magazine, 2007, 2:30-43.
  • Greenfield, S., Chiclana, F., John, R., Coupland, S., The sampling method of defuzzification for type-2 fuzzy sets: Experimental evaluation, Information Sciences, 2012, 189: 77- 92.
  • Mendel, J.M., John, R., Liu, F., Interval type-2 fuzzy logic systems made simple. IEEE T. Fuzzy Systems, 2006, 14:808- 821.
  • Young, K., Wang,, C., Wang, L. Y., and Strunz, K., Electric Vehicle Battery Technologies. Electric vehicle integration into modern power networks. Edited by R. Garcia-Valle, and J.A.P. Lopes, SPRINGER-VERLAG NEW YORK, 2013, 15–56.
  • W. Reaugh, Larry. Re-Cycling Spent Electric Vehicle Batteries Potentially Recovers Significant Amounts of Lithium, Cobalt and Other Cathode Metals. American Manganese Inc., 19 Jan. 2017, https://americanmanganeseinc.com/re-cycling-spent-electric-vehicle-batteries-potentially-recovers-significant-amounts-of-lithium-cobalt-and-other-cathode-metals/.(accessed September 10, 2019).
  • Sen, C. G., Cinar, G., Evaluation and pre-allocation of operators with multiple skills: A combined fuzzy AHP and max–min approach, Expert Systems with Applications, 2010, 37 (3): 2043-2053.
  • Bhushan, N., & Rai, K. (2004). Strategic Decision Making: Applying the Analytic Hierarchy Process. Decision Engineering. Springer London.
  • Türk, S. John, R. and Özcan, E., Interval type-2 fuzzy sets in supplier selection, 14th UK Workshop on Computational Intelligence (UKCI), Bradford, 2014, pp. 1-7.
  • Chen, S., Lee, L., Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method, Expert Systems with Applications, 2010, 37 (4): 2790-2798.
There are 40 citations in total.

Details

Primary Language English
Subjects Material Production Technologies
Journal Section Articles
Authors

Ahmet Aktürk

Seda Türk

Publication Date June 30, 2020
Acceptance Date May 9, 2020
Published in Issue Year 2020 Volume: 3 Issue: 1

Cite

APA Aktürk, A., & Türk, S. (2020). COMPARISON OF AN INTERVAL TYPE-2 FUZZY SETS AND AHP METHODS FOR MATERİAL SELECTION PROBLEM ON LITHIUM-ION BATTERİES. The International Journal of Materials and Engineering Technology, 3(1), 30-46.