Year 2019, Volume 22 , Issue , Pages 64 - 69 2019-11-29

ELEKTRİKLİ BİR ARACIN BATARYA SİSTEMİNİN MODELLENMESİ
MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE

Ümit ÖZBALCI [1] , Erdal KILIÇ [2]


Giderek artan yakıt maliyetleri ve fosil yakıtlı araçların emisyon problemi nedeniyle otomotiv sektörü büyük bir değişim döneminden geçiyor. Bu nedenle hibrit ve elektrikli otomobiller üretilmeye başlandı. Elektrikli araçların maliyet, maksimum hız düşüklüğü, yüksek şarj süresi gibi dezavantajları ise henüz tam olarak çözüme kavuşturulmuş değildir. Lityum tabanlı bataryaların geliştirilmesi, elektrikli ve hibrit araçlarda depolama bataryaları olarak kullanılmaya başlanmıştır. Bu bataryalar performans, dayanıklılık, güvenlik ve maliyet avantajları açısından günümüzde elektriksel sistemlerin enerji ihtiyacını karşılamak için tercih edilmektedir. Bu çalışmada, elektrikli bir araçta kullanılan batarya ve şarj sisteminin benzetim modeli kullanılarak batarya paketinin akım, gerilim ve şarj durumu grafiği elde edilmiştir.

The automotive sector is undergoing a major change due to the increasing fuel costs and the emission problems of fossil fuel vehicles. Therefore, hybrid and electric cars began to be produced. The disadvantages of electric vehicles such as cost, low maximum-speed, high charging time are not yet completely resolved. With the development of lithium-based batteries, it has begun to be used as storage batteries in electric and hybrid vehicles. These batteries are preferred to meet the energy requirements of electrical systems in terms of performance, durability, safety and cost advantages. In this paper, the current, voltage and state of charge (SoC) graphs of a battery pack is obtained by using the simulation model of the battery and charging system used in an electric vehicle.

  • Ahmed, R., (2014). Modeling and state of charge estimation of electric vehicle batteries, (Doctoral dissertation, McMaster University).
  • Ahmed, R., Gazzarri, J., Onori, S., Habibi, S., Jackey, R., Rmezien, K., Tjong, J., LeSage, J. (2015). Model-Based Parameter Identification of Healthy and Aged Li-ion Batteries for Electric Vehicle Applications, SAE Int. J. Alt. Power, 4, 2.
  • Chen, J., Ouyang, Q., Xu, C., Su, H. (2017). Neural network-based state of charge observer design for lithium-ion batteries, IEEE Transactions on Control Systems Technology, 26, 1.
  • Ehsani, M., Gao, Y., Emadi, A. (2010). Modern Electric, Hybrid Electric, and Fuel Cell Vehicles – Fundamentals, Theory, and Design, 2nd edition, CRC Press.
  • Gadoue, S., Chen, K.W., Mitcheson, P., Yufit, V., Brandon, N. (2018). Electrochemical Impedance Spectroscopy State of Charge Measurement for Batteries using Power Converter Modulation, The 9th International Renewable Energy Congress (IREC 2018).
  • Gandolfo, D., Brandao, A., Patino, D., Molina, M. (2015). Dynamic model of lithium polymer battery e Load resistor method for electric parameters identification, Journal of the Energy Institute, 88.
  • Guo, D., He, L., (2018). A Novel Algorithm for SOC using Simple Iteration and Coulomb Counting Method, IEEE Student Conference on Electric Machines and Systems.
  • Hannan, M.A., Lipu, M.S.H., Hussain A., Saad, M.H., Ayob, A. (2018). Neural Network Approach for Estimating State of Charge of Lithium-Ion Battery Using Backtracking Search Algorithm, IEEE Access, 6.
  • Web1 https://ww2.mathworks.cn/matlabcentral/fileexchange/36019-lithium-battery-model-simscape-language-and-simulink-design-optimization
  • Huria, T., Ceraolo, M., Gazzarri, J., Jackey, R. (2012). High Fidelity Electrical Model with Thermal Dependence for Characterization and Simulation of High-Power Lithium Battery Cells, IEEE International Electric Vehicle Conference.
  • Jiang, J., Zhang, C. (2015). Fundamentals and Applications of Lithium-Ion Batteries in Electric Drive Vehicles.
  • Qian, L., Si, Y., Qiu, L. (2015). SOC estimation of LiFePO4 Li-ion battery using BP Neural Network, EVS28 International Electric Vehicle Symposium and Exhibition.
  • Sepasi, S., Roose, L.R., Matsuura, M.M. (2015). Extended Kalman Filter a Fuzzy Method for Accurate Battery Pack State of Charge Estimation, Energies, 8, 6.
  • Tong, S., Klein, M.P., Park, J.W. (2013). A Comprehensive Battery Equivalent Circuit Based Model For Battery Management Application, ASME 2013 Dynamic Syst. and Cont. Conf.
  • Xia, B., Wang, H., Wang, M., Sun, W., Xu, Z., Lai, Y. (2015). A new method for state of charge estimation of lithium-ion battery based on strong tracking cubature kalman filter. Energies, 8, 12.
  • Zeng, Z., Tian, J., Li, D., Tian, Y. (2018). An Online State of Charge Estimation Algorithm for Lithium-Ion Batteries Using an Improved Adaptive Cubature Kalman Filter, Energies, 11, 1.
  • Zhang, C., Allafi, W., Dinh, Q., Ascencio, P., Marco, J. (2018). Online estimation of battery equivalent circuit model parameters and state of charge using decoupled least squares technique, Energy, 142.
  • Zhang, L., Peng, H., Ning, Z., Mu, Z., Sun, C. (2017). Comparative research on RC equivalent circuit models for lithium-ion batteries of electric vehicles, Applied Sciences, 10, 7.
  • Zhou, Y., Bai, C., Sun, J. (2011). Application of Genetic Neural Network in Power Battery Charging State-of-Charge Estimation, I.J. Intelligent Systems and Applications.
Primary Language en
Subjects Engineering, Electrical and Electronic
Journal Section Research Articles
Authors

Orcid: 0000-0003-2685-156X
Author: Ümit ÖZBALCI (Primary Author)
Institution: Kahramanmaras Sütçü İmam University, Electrical-Electronical Engineering Department
Country: Turkey


Orcid: 0000-0002-1572-6109
Author: Erdal KILIÇ
Institution: Kahramanmaras Sütçü İmam University, Electrical-Electronical Engineering Department
Country: Turkey


Dates

Application Date : August 2, 2019
Acceptance Date : November 4, 2019
Publication Date : November 29, 2019

Bibtex @research article { ksujes600809, journal = {Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi}, issn = {}, eissn = {1309-1751}, address = {}, publisher = {Kahramanmaras Sutcu Imam University}, year = {2019}, volume = {22}, pages = {64 - 69}, doi = {10.17780/ksujes.600809}, title = {MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE}, key = {cite}, author = {ÖZBALCI, Ümit and KILIÇ, Erdal} }
APA ÖZBALCI, Ü , KILIÇ, E . (2019). MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi , 22 () , 64-69 . DOI: 10.17780/ksujes.600809
MLA ÖZBALCI, Ü , KILIÇ, E . "MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 (2019 ): 64-69 <http://jes.ksu.edu.tr/en/issue/50210/600809>
Chicago ÖZBALCI, Ü , KILIÇ, E . "MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 (2019 ): 64-69
RIS TY - JOUR T1 - MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE AU - Ümit ÖZBALCI , Erdal KILIÇ Y1 - 2019 PY - 2019 N1 - doi: 10.17780/ksujes.600809 DO - 10.17780/ksujes.600809 T2 - Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi JF - Journal JO - JOR SP - 64 EP - 69 VL - 22 IS - SN - -1309-1751 M3 - doi: 10.17780/ksujes.600809 UR - https://doi.org/10.17780/ksujes.600809 Y2 - 2019 ER -
EndNote %0 Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE %A Ümit ÖZBALCI , Erdal KILIÇ %T MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE %D 2019 %J Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi %P -1309-1751 %V 22 %N %R doi: 10.17780/ksujes.600809 %U 10.17780/ksujes.600809
ISNAD ÖZBALCI, Ümit , KILIÇ, Erdal . "MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 / (November 2019): 64-69 . https://doi.org/10.17780/ksujes.600809
AMA ÖZBALCI Ü , KILIÇ E . MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE. KSU J. Eng. Sci.. 2019; 22: 64-69.
Vancouver ÖZBALCI Ü , KILIÇ E . MODELING THE BATTERY SYSTEM OF AN ELECTRIC VEHICLE. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi. 2019; 22: 69-64.