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Lityum iyon pillerde bulanık kurallara dayalı optimum şarj stratejisi

Yıl 2023, , 150 - 163, 16.01.2023

Fatih Kara , İbrahim Yücedağ , Muhsin Uğur Doğan

https://doi.org/10.25092/baunfbed.1056634

Öz

Bataryalar elektrik enerjisini elektrokimyasal enerjiye dönüştürerek depolayabilen yapılardır. Şarj akımının ayarlanması bataryalarda önemli bir husustur. Yüksek akımla şarj bataryaların kısa sürede şarj olmasını sağlar. Batarya şarj kapasitesi sıcaklığa ve akıma bağlı olarak değişmektedir. Batarya şarj akım değerini ayarlayan birçok çalışma arasında bulanık mantık kullanan çalışmalar da mevcuttur. Bu çalışmada, Lityum İyon pil şarjında bulanık mantığı kullanan bir yöntem önerilmektedir. Pil yüzey sıcaklığını ve ortam sıcaklığını giriş olarak alan ve çıkış akımını belirleyen bulanık bir denetleyici tasarlanmıştır. Panasonic NCR-18650B Lityum İyon pil üzerinde denemeler yapılmış ve sonuçlar bilgisayara ayarlanabilir akım gerilim cihazı ile aktarılmıştır. 5°C, 23°C ve 36°C ortam sıcaklığında test edilen pilin şarj kapasitesinde sırasıyla % 0,2; 2,5; 1,2 oranında kazanç sağlanmıştır.

Anahtar Kelimeler

Bulanık Kural lityum iyon pil şarj sıcaklık

Kaynakça

  • Sun, J., Qian, M., Tang, C., Wang, T., Jiang, T. ve Tang, Y., Research on optimization of charging strategy control for aged batteries, IEEE Transactions on Vehicular Technology, 69, 12, 14141-14149, (2020).
  • Han, H., Xu, H. ve Yuan, Z., Research of interactive charging strategy for electrical vehicles in smart grids, 2011 International Conference on Electrical Machines and Systems, Beijing, 1-6, (2011).
  • Wang, S. C., Chen, G. J. ve Liu, Y. H., Adaptive charging strategy with temperature rise mitigation and cycle life extension for li-ion batteries, CPSS Transactions on Power Electronics and Applications, 3, 3, 202-212, (2018).
  • Lin, F. J., Huang, M., Yeh, P. Y., Tsai, H. C. ve Kuan, C. H., DSP-Based probabilistic fuzzy neural network control for li-ion battery charger, IEEE Transactions on Power Electronics, 27, 8, 3782-3794, (2012).
  • Liu, C. L., Wang, S. C., Chiang, S. S., Liu, Y. H. ve Ho, C. H., PSO-based fuzzy logic optimization of dual performance characteristic indices for fast charging of lithium-ion batteries, 2013 IEEE 10th International Conference on Power Electronics and Drive Systems (PEDS), 474-479, (2013).
  • Preethi, A. A., Nesamalar, J. J. D., Suganya, S. ve Raja, C., Economic scheduling of plug-in hybrid electric vehicle considering various travel patterns, 2018 National Power Engineering Conference (NPEC), 1-7, (2018).
  • Geng B., Mills J. K. ve Sun D., Two-stage charging strategy for plug-in electric vehicles at the residential transformer level, IEEE Transactions on Smart Grid, 4, 3, 1442-1452, (2013).
  • Ghorai, S., Majumdar, D., Jash, T. ve Ray, S., PV assisted fuzzy based ev charge scheduling for demand side energy management: a case study, 2020 IEEE Calcutta Conference (CALCON), 486-492, (2020).
  • Liu, C. L., Wang, S. C., Liu, Y. H. ve Tsai, M. C., An optimum fast charging pattern search for li-ion batteries using particle swarm optimization, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 727-732, (2012).
  • Zheng, Y., Song, Y., Hill, D. J. ve Meng, K., Online distributed mpc-based optimal scheduling for ev charging stations in distribution systems, IEEE Transactions on Industrial Informatics, 15, 2, 638-649, (2019).
  • Mehta, R., Srinivasan, D. ve Trivedi, A., Optimal charging scheduling of plug-in electric vehicles for maximizing penetration within a workplace car park, 2016 IEEE Congress on Evolutionary Computation (CEC), 3646-3653, (2016).
  • Horiba, T., Lithium-ion battery systems, Proceedings of the IEEE, 102, 6, 939-950, (2014).
  • Hussein, A. A. H. ve Batarseh, I., A Review of charging algorithms for nickel and lithium battery chargers, IEEE Transactions on Vehicular Technology, 60, 3, 830-838, (2011).
  • Huang, J. W., Liu, Y. H., Wang, S. C. ve Yang, Z. Z., Fuzzy-control-based five-step li-ion battery charger, International Conference on Power Electronics and Drive Systems, 1547–1551, (2009).
  • Lee, Y. S. ve Cheng, M. W., Intelligent control battery equalization for series connected lithium-ion battery strings, IEEE Transactions on Industrial Electronics, 52, 1297–1307, (2005).
  • Ho, Y. H., Huang, S. S., Liu, Y. H., Chiu, Y. S. ve Liu, C. L., Optimization of a fuzzy-logic-control-based five-stage battery charger using a fuzzy-based taguchi method, Energies 2013, 6, 3528–3547, (2013).
  • Lyn, C. E., Rahim, N. A. ve Mekhilef, S., Dsp-based fuzzy logic controller for a battery charger, 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering TENCOM '02. Proceedings, Beijing, China, 28–31, 1512–1515, (2002).
  • Hsieh, G. C., Chen, L. R. ve Huang, K. S., Fuzzy-controlled li-ion battery charge system with active state-of-charge controller, IEEE Transactions on Industrial Electronics, 48, 585–593, (2001).
  • Lee, Y. S., Cheng, M. W. ve Yang, S. C., Fuzzy controlled individual cell equalizers for lithium-ion batteries, IEICE TRANSACTIONS on Communications, 91, 2380–2392, (2008).
  • Choi, Y., Ryu, S., Park, K. ve Kim, H., Machine learning-based lithium-ion battery capacity estimation exploiting multi-channel charging profiles, IEEE Access, 7, 75143-75152, (2009).
  • Liu, C. L., Chiu, Y. S., Liu, Y. H., Ho, Y. H. ve Huang, S. S., Optimization of a fuzzy-logic-control-based five-stage battery charger using a fuzzy-based taguchi method, Energies, 6, 1-20, (2013).
  • Jiang, J., Zhang, C., Wen, J., Zhang, W. ve Sharkh, S. M., An optimal charging method for li-ion batteries using a fuzzy-control approach based on polarization properties, IEEE Transactions on Vehicular Technology, 62, 7, 3000-3009, (2013).
  • Peng, B. R., Wang, S. C., Liu, Y. H. ve Yan S. H., A Li-ion battery charger based on remaining capacity with fuzzy temperature control, 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS), (2016).
  • Huang, Z., Gao, Z., Liu, Y., Guan, K., Liao, H., Wu, Y., Le, Y., Jiang, F. ve Peng, J., A fast energy-efficient pulse preheating strategy for li-ion battery at subzero temperatures., 2020 IEEE Energy Conversion Congress and Exposition (ECCE), 4446-4451, (2020).
  • Min, H., Wang, B., Sun, W., Zhang, Z., Yu, Y. ve Zhang, Y., Research on the combined control strategy of low temperature charging and heating of lithium-ion power battery based on adaptive fuzzy control, Energies, 13, 1584, (2020).
  • Chen, J., Peng, B., Liu, Y. ve Yang, Z., Obtaining optimal membership functions using fuzzy-based taguchi method, 2014 International Conference on Fuzzy Theory and Its Applications (iFUZZY2014), 82-86, (2014).
  • Samadi, M. F. ve Saif, Mehrdad., Takagi-sugeno fuzzy model identification of li-ion battery systems, World Automation Congress, 421-426, (2014).
  • Chau, K.T., Wu, K.C. ve Chan, C. C., A new battery capacity indicator for lithium-ion battery powered electric vehicles using adaptive neuro-fuzzy inference system, Energy Conversion and Management, 45, 1681-1692, (2004).
  • Villuri, R.T., Singh, M., Beck, Y., Experimental analysis of electric vehicle's Li-ion battery with constant pulse and constant voltage charging method, International Journal of Energy Research, 1- 21, (2022).
  • Frankenberger, M., Singh, M., Dinter, A., Jankowksy, S., Schmidt, A. ve Pettinger, K.H., Laminated Lithium Ion Batteries with improved fast charging capability, Journal of Electroanalytical Chemistry, 837, 151-158, (2019).
  • Ma, S., Jiang, M., Tao, P., Song, C., Wu, J., Wang, J., Deng, T. ve Shang, W., Temperature effect and thermal impact in lithium-ion batteries: A review, Progress in Natural Science: Materials International, 28, 6, 653-666, (2018).
  • Nagasubramanian, G., Electrical characteristics of 18650 li-ion cells at low temperatures, Journal of Applied Electrochemistry, 31, 99-104, (2001).
  • https://batteryuniversity.com/article/bu-410-charging-at-high-and-low-temperatures, (20.12.2021).
  • Güler, O. ve Yücedağ, İ., Fuzzy logic based approach to site selection problem of vocational secondary school students, Hacettepe Universitesi Egitim Fakultesi Dergisi-Hacettepe University Journal Of Education, 32 (1), 111-122, (2017).
  • Bayrakdar, M. E., Bayrakdar, S., Yücedağ, İ. ve Çalhan, A., Bilişsel radyo kullanıcıları için bulanık mantık yardımıyla kanal kullanım olasılığı hesabında farklı bir yaklaşım, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 3, 88-99, (2015).
  • Biçen, M., Ş., Çalhan, A. ve Yücedağ, İ., Kablosuz heterojen algilayici ağlarda bulanik mantik tabanli ağ geçidi seçimi, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 4, 655-660, (2016).
  • Sabah, L., Yücedağ, İ. ve Yalcin, C., Earthquake hazard analysis for districts of düzce via ahp and fuzzy logic methods, The Journal of Cognitive Systems, 2 (1), 1-5, (2017).
  • Atagün, E., Korkmaz, M., Tı̇muçı̇n, T. ve Yücedağ, İ., Fuzzy logic based decision support system for broadcaster on twitch, Proceedings of the International Technological Sciences And Design Symposium, 27-29, (2018).
  • Rezvanizaniani, S. M., Liu, Z., Chen, Y. ve Lee, J., Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (ev) safety and mobility, Journal of Power Sources, 256, 110-124, (2014).
  • https://www.apple.com/tr/batteries/why-lithium-ion/ (20.12.2021).

Optimum charging strategy based on fuzzy rules for lithium-ion batteries

Yıl 2023, , 150 - 163, 16.01.2023

Fatih Kara , İbrahim Yücedağ , Muhsin Uğur Doğan

https://doi.org/10.25092/baunfbed.1056634

Öz

Batteries are structures that can store electrical energy by converting it to electrochemical energy. Adjusting the charging current is an important consideration in batteries. High current charging allows the batteries to be charged in a short time. Battery charge capacity varies depending on temperature and current. Among the many studies that adjust the battery charge current value, there are also studies using fuzzy logic. In this study, a method using fuzzy logic in Lithium Ion battery charging is proposed. A fuzzy controller is designed that takes the battery surface temperature and ambient temperature as input and determines the output current. Trials were made on Panasonic NCR-18650B Lithium Ion battery and the results were transferred to the computer with an adjustable current voltage device. Tested at ambient temperatures of 5°C, 23°C and 36°C, the battery's charging capacity gained % 0,2; 2,5; 1,2 respectively.

Anahtar Kelimeler

Fuzzy rule lithium-ion battery charging temperature

Kaynakça

  • Sun, J., Qian, M., Tang, C., Wang, T., Jiang, T. ve Tang, Y., Research on optimization of charging strategy control for aged batteries, IEEE Transactions on Vehicular Technology, 69, 12, 14141-14149, (2020).
  • Han, H., Xu, H. ve Yuan, Z., Research of interactive charging strategy for electrical vehicles in smart grids, 2011 International Conference on Electrical Machines and Systems, Beijing, 1-6, (2011).
  • Wang, S. C., Chen, G. J. ve Liu, Y. H., Adaptive charging strategy with temperature rise mitigation and cycle life extension for li-ion batteries, CPSS Transactions on Power Electronics and Applications, 3, 3, 202-212, (2018).
  • Lin, F. J., Huang, M., Yeh, P. Y., Tsai, H. C. ve Kuan, C. H., DSP-Based probabilistic fuzzy neural network control for li-ion battery charger, IEEE Transactions on Power Electronics, 27, 8, 3782-3794, (2012).
  • Liu, C. L., Wang, S. C., Chiang, S. S., Liu, Y. H. ve Ho, C. H., PSO-based fuzzy logic optimization of dual performance characteristic indices for fast charging of lithium-ion batteries, 2013 IEEE 10th International Conference on Power Electronics and Drive Systems (PEDS), 474-479, (2013).
  • Preethi, A. A., Nesamalar, J. J. D., Suganya, S. ve Raja, C., Economic scheduling of plug-in hybrid electric vehicle considering various travel patterns, 2018 National Power Engineering Conference (NPEC), 1-7, (2018).
  • Geng B., Mills J. K. ve Sun D., Two-stage charging strategy for plug-in electric vehicles at the residential transformer level, IEEE Transactions on Smart Grid, 4, 3, 1442-1452, (2013).
  • Ghorai, S., Majumdar, D., Jash, T. ve Ray, S., PV assisted fuzzy based ev charge scheduling for demand side energy management: a case study, 2020 IEEE Calcutta Conference (CALCON), 486-492, (2020).
  • Liu, C. L., Wang, S. C., Liu, Y. H. ve Tsai, M. C., An optimum fast charging pattern search for li-ion batteries using particle swarm optimization, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 727-732, (2012).
  • Zheng, Y., Song, Y., Hill, D. J. ve Meng, K., Online distributed mpc-based optimal scheduling for ev charging stations in distribution systems, IEEE Transactions on Industrial Informatics, 15, 2, 638-649, (2019).
  • Mehta, R., Srinivasan, D. ve Trivedi, A., Optimal charging scheduling of plug-in electric vehicles for maximizing penetration within a workplace car park, 2016 IEEE Congress on Evolutionary Computation (CEC), 3646-3653, (2016).
  • Horiba, T., Lithium-ion battery systems, Proceedings of the IEEE, 102, 6, 939-950, (2014).
  • Hussein, A. A. H. ve Batarseh, I., A Review of charging algorithms for nickel and lithium battery chargers, IEEE Transactions on Vehicular Technology, 60, 3, 830-838, (2011).
  • Huang, J. W., Liu, Y. H., Wang, S. C. ve Yang, Z. Z., Fuzzy-control-based five-step li-ion battery charger, International Conference on Power Electronics and Drive Systems, 1547–1551, (2009).
  • Lee, Y. S. ve Cheng, M. W., Intelligent control battery equalization for series connected lithium-ion battery strings, IEEE Transactions on Industrial Electronics, 52, 1297–1307, (2005).
  • Ho, Y. H., Huang, S. S., Liu, Y. H., Chiu, Y. S. ve Liu, C. L., Optimization of a fuzzy-logic-control-based five-stage battery charger using a fuzzy-based taguchi method, Energies 2013, 6, 3528–3547, (2013).
  • Lyn, C. E., Rahim, N. A. ve Mekhilef, S., Dsp-based fuzzy logic controller for a battery charger, 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering TENCOM '02. Proceedings, Beijing, China, 28–31, 1512–1515, (2002).
  • Hsieh, G. C., Chen, L. R. ve Huang, K. S., Fuzzy-controlled li-ion battery charge system with active state-of-charge controller, IEEE Transactions on Industrial Electronics, 48, 585–593, (2001).
  • Lee, Y. S., Cheng, M. W. ve Yang, S. C., Fuzzy controlled individual cell equalizers for lithium-ion batteries, IEICE TRANSACTIONS on Communications, 91, 2380–2392, (2008).
  • Choi, Y., Ryu, S., Park, K. ve Kim, H., Machine learning-based lithium-ion battery capacity estimation exploiting multi-channel charging profiles, IEEE Access, 7, 75143-75152, (2009).
  • Liu, C. L., Chiu, Y. S., Liu, Y. H., Ho, Y. H. ve Huang, S. S., Optimization of a fuzzy-logic-control-based five-stage battery charger using a fuzzy-based taguchi method, Energies, 6, 1-20, (2013).
  • Jiang, J., Zhang, C., Wen, J., Zhang, W. ve Sharkh, S. M., An optimal charging method for li-ion batteries using a fuzzy-control approach based on polarization properties, IEEE Transactions on Vehicular Technology, 62, 7, 3000-3009, (2013).
  • Peng, B. R., Wang, S. C., Liu, Y. H. ve Yan S. H., A Li-ion battery charger based on remaining capacity with fuzzy temperature control, 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS), (2016).
  • Huang, Z., Gao, Z., Liu, Y., Guan, K., Liao, H., Wu, Y., Le, Y., Jiang, F. ve Peng, J., A fast energy-efficient pulse preheating strategy for li-ion battery at subzero temperatures., 2020 IEEE Energy Conversion Congress and Exposition (ECCE), 4446-4451, (2020).
  • Min, H., Wang, B., Sun, W., Zhang, Z., Yu, Y. ve Zhang, Y., Research on the combined control strategy of low temperature charging and heating of lithium-ion power battery based on adaptive fuzzy control, Energies, 13, 1584, (2020).
  • Chen, J., Peng, B., Liu, Y. ve Yang, Z., Obtaining optimal membership functions using fuzzy-based taguchi method, 2014 International Conference on Fuzzy Theory and Its Applications (iFUZZY2014), 82-86, (2014).
  • Samadi, M. F. ve Saif, Mehrdad., Takagi-sugeno fuzzy model identification of li-ion battery systems, World Automation Congress, 421-426, (2014).
  • Chau, K.T., Wu, K.C. ve Chan, C. C., A new battery capacity indicator for lithium-ion battery powered electric vehicles using adaptive neuro-fuzzy inference system, Energy Conversion and Management, 45, 1681-1692, (2004).
  • Villuri, R.T., Singh, M., Beck, Y., Experimental analysis of electric vehicle's Li-ion battery with constant pulse and constant voltage charging method, International Journal of Energy Research, 1- 21, (2022).
  • Frankenberger, M., Singh, M., Dinter, A., Jankowksy, S., Schmidt, A. ve Pettinger, K.H., Laminated Lithium Ion Batteries with improved fast charging capability, Journal of Electroanalytical Chemistry, 837, 151-158, (2019).
  • Ma, S., Jiang, M., Tao, P., Song, C., Wu, J., Wang, J., Deng, T. ve Shang, W., Temperature effect and thermal impact in lithium-ion batteries: A review, Progress in Natural Science: Materials International, 28, 6, 653-666, (2018).
  • Nagasubramanian, G., Electrical characteristics of 18650 li-ion cells at low temperatures, Journal of Applied Electrochemistry, 31, 99-104, (2001).
  • https://batteryuniversity.com/article/bu-410-charging-at-high-and-low-temperatures, (20.12.2021).
  • Güler, O. ve Yücedağ, İ., Fuzzy logic based approach to site selection problem of vocational secondary school students, Hacettepe Universitesi Egitim Fakultesi Dergisi-Hacettepe University Journal Of Education, 32 (1), 111-122, (2017).
  • Bayrakdar, M. E., Bayrakdar, S., Yücedağ, İ. ve Çalhan, A., Bilişsel radyo kullanıcıları için bulanık mantık yardımıyla kanal kullanım olasılığı hesabında farklı bir yaklaşım, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 3, 88-99, (2015).
  • Biçen, M., Ş., Çalhan, A. ve Yücedağ, İ., Kablosuz heterojen algilayici ağlarda bulanik mantik tabanli ağ geçidi seçimi, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 4, 655-660, (2016).
  • Sabah, L., Yücedağ, İ. ve Yalcin, C., Earthquake hazard analysis for districts of düzce via ahp and fuzzy logic methods, The Journal of Cognitive Systems, 2 (1), 1-5, (2017).
  • Atagün, E., Korkmaz, M., Tı̇muçı̇n, T. ve Yücedağ, İ., Fuzzy logic based decision support system for broadcaster on twitch, Proceedings of the International Technological Sciences And Design Symposium, 27-29, (2018).
  • Rezvanizaniani, S. M., Liu, Z., Chen, Y. ve Lee, J., Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (ev) safety and mobility, Journal of Power Sources, 256, 110-124, (2014).
  • https://www.apple.com/tr/batteries/why-lithium-ion/ (20.12.2021).
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Fatih Kara 0000-0002-7467-4169

İbrahim Yücedağ 0000-0003-2975-7392

Muhsin Uğur Doğan 0000-0001-7341-1714

Yayımlanma Tarihi 16 Ocak 2023
Gönderilme Tarihi 13 Ocak 2022
Yayımlandığı Sayı Yıl 2023

Kaynak Göster

APA Kara, F., Yücedağ, İ., & Doğan, M. U. (2023). Lityum iyon pillerde bulanık kurallara dayalı optimum şarj stratejisi. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 25(1), 150-163. https://doi.org/10.25092/baunfbed.1056634
AMA Kara F, Yücedağ İ, Doğan MU. Lityum iyon pillerde bulanık kurallara dayalı optimum şarj stratejisi. BAUN Fen. Bil. Enst. Dergisi. Ocak 2023;25(1):150-163. doi:10.25092/baunfbed.1056634
Chicago Kara, Fatih, İbrahim Yücedağ, ve Muhsin Uğur Doğan. “Lityum Iyon Pillerde bulanık Kurallara Dayalı Optimum şarj Stratejisi”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 25, sy. 1 (Ocak 2023): 150-63. https://doi.org/10.25092/baunfbed.1056634.
EndNote Kara F, Yücedağ İ, Doğan MU (01 Ocak 2023) Lityum iyon pillerde bulanık kurallara dayalı optimum şarj stratejisi. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 25 1 150–163.
IEEE F. Kara, İ. Yücedağ, ve M. U. Doğan, “Lityum iyon pillerde bulanık kurallara dayalı optimum şarj stratejisi”, BAUN Fen. Bil. Enst. Dergisi, c. 25, sy. 1, ss. 150–163, 2023, doi: 10.25092/baunfbed.1056634.
ISNAD Kara, Fatih vd. “Lityum Iyon Pillerde bulanık Kurallara Dayalı Optimum şarj Stratejisi”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 25/1 (Ocak 2023), 150-163. https://doi.org/10.25092/baunfbed.1056634.
JAMA Kara F, Yücedağ İ, Doğan MU. Lityum iyon pillerde bulanık kurallara dayalı optimum şarj stratejisi. BAUN Fen. Bil. Enst. Dergisi. 2023;25:150–163.
MLA Kara, Fatih vd. “Lityum Iyon Pillerde bulanık Kurallara Dayalı Optimum şarj Stratejisi”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 25, sy. 1, 2023, ss. 150-63, doi:10.25092/baunfbed.1056634.
Vancouver Kara F, Yücedağ İ, Doğan MU. Lityum iyon pillerde bulanık kurallara dayalı optimum şarj stratejisi. BAUN Fen. Bil. Enst. Dergisi. 2023;25(1):150-63.