پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 623 |
| تعداد مقالات | 9,160 |
| تعداد مشاهده مقاله | 67,493,060 |
| تعداد دریافت فایل اصل مقاله | 8,022,060 |
طراحی و آنالیز سیستم مدیریت باتری (BMS) اتوبوس برقی بر پایه تخمین وضعیت شارژ | ||
| مدل سازی در مهندسی | ||
| دوره 23، شماره ویژه 81، تیر 1404، صفحه 49-63 اصل مقاله (1.44 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22075/jme.2024.33115.2611 | ||
| نویسندگان | ||
| سید مهدی موسوی بادجانی* ؛ محمد هادی ریسمانی؛ مصطفی اسلامی؛ مهدی صالحی اسکندری | ||
| مجتمع الکترومغناطیس، دانشگاه صنعتی مالک اشتر، تهران، ایران | ||
| تاریخ دریافت: 08 بهمن 1402، تاریخ بازنگری: 13 تیر 1403، تاریخ پذیرش: 27 مرداد 1403 | ||
| چکیده | ||
| امروزه به‌دلیل آلودگی محیط‌زیست و پیشرفت تکنولوژی، تولید خودروهای برقی رشد تصاعدی پیدا کرده است. حیاتی‌ترین بخش در اکثر خودروها و اتوبوس‌های برقی، سیستم ذخیره‌ساز انرژی الکتریکی و مهم‌ترین عنصر ذخیره‌ساز انرژی الکتریکی، باتری‌های لیتیوم یونی است. به منظور کنترل عملکرد باتری، حفظ شرایط پایدار و ایمنی، افزایش بهره‌وری و طول عمر آن، استفاده از سیستم مدیریت باتری (BMS) الزامی می‌باشد. در این مقاله، برای طراحی بسته باتری اتوبوس برقی با وزن 19 تن، با تخمین توان و انرژی مورد نیاز (مصرف 2kWh به ازای هر کیلومتر)، به طوریکه بسته باتری امکان شارژ با توان 330kW را داشته باشد، به انتخاب سلول مناسب پرداخته شده است. BMS ضمن پایش مداوم بسته باتری، با استفاده از فیلتر کالمن بدون اثر (UKF) وضعیت شارژ باتری (SoC) را تخمین می‌زند. برای تخمین وضعیت سلامت باتری (SoH)، روش تخمین مشترک به کار رفته است. جهت متعادل‌سازی انرژی سلول‌های بسته باتری، روش مقاومت موازی سوئیچ‌شونده استفاده گردیده و در نهایت به منظور پایداری دمایی بسته باتری تحت شرایط کاری مختلف، از یک سیستم مدیریت گرمایی (BTMS) استفاده شد. نتایج حاصل از شبیه‌سازی نشان می‌دهد که بخش‌های مختلف BMS طراحی‌شده به‌درستی حالات کاری باتری را تخمین زده و باعث ایجاد پایداری و شرایط ایمن می‌گردد. | ||
| کلیدواژه‌ها | ||
| اتوبوس برقی؛ سیستم مدیریت باتری؛ بسته باتری؛ سلول لیتیوم یونی | ||
| عنوان مقاله [English] | ||
| Design and Analysis of Electric Bus Battery Management System (BMS) Based on Charge State Estimation | ||
| نویسندگان [English] | ||
| Seyyed Mahdi Mousavi Badjani؛ Mohammad Hadi Rismani؛ Mustafa Islami؛ Mahdi Salehi Eskandari | ||
| Electromagnetism Complex, Malek Ashtar University of Technology, Tehran, Iran | ||
| چکیده [English] | ||
| Due to the environmental pollution and technological progress, the production of electric vehicles has grown exponentially. The most vital part in electric cars and buses is the electric energy storage system and a energy storage source with excellent performance is lithium-ion batteries. In order to control performance, maintain stable conditions and safety, increase productivity and its lifespan, it is necessary to use a Battery Management System (BMS). In this article, to design a battery pack for an electric bus with a weight of 19 tons, by estimating the required power and energy (2kWh consumption per kilometer), so that you have a chargeable battery pack with a power of 330kW, choosing the appropriate cell. We pay While continuously monitoring the battery, the BMS estimates the State of Charge of the battery (SoC) using a Unscented Kalman Filter (UKF). To estimate the battery State of Health (SoH), joint estimation method is used. In order to replace the energy of the closed cells, the switched parallel resistance method is used, and finally, a battery thermal management system (BTMS) is used for the environmental stability of the closed cell depending on the working conditions. The results of the simulation show that the different parts of the designed BMS correctly estimate the working states of the battery and create stability and safe conditions. | ||
| کلیدواژه‌ها [English] | ||
| Electric bus, Battery pack, Battery management system, Lithium-Ion cell | ||
| مراجع | ||
|
[1] A. Hatami, P. Bayat, P. Bayat and S.M. Toosi, "Presentation of a new strategy magazine for motor vehicle energy management based on two-way converter and fuzzy controller", Tabriz University Electrical Engineering 46, no. 3 (2015): 122. [2] Seeking Alpha. "The EV Boom Just Keeps Getting Bigger." https://seekingalpha.com/article/4235630-ev-boom-just-keeps-getting-bigger-update-for-end-of-2018, Last modified: Jan 25 2019. [3] Slideshare, Bus Karo: Future of Electric Buses, C.K. Goel, DIIMTS, Delhi, https://www.slideshare.net/sachiaggarwal/bus-karo-future-of-electric-buses?from_action=save, Last modified: Nov 2016. [4] D. Göhlich, T.A. Fay, and S. Park. "Conceptual design of urban e-bus systems with special focus on battery technology." In Proceedings of the design society: international conference on engineering design, vol. 1, no. 1, pp. 2823-2832. Cambridge University Press, 2019. [5] B. Scrosati, J. Garche and W. Tillmets, eds. Advances in battery technologies for electric vehicles. Woodhead Publishing, 2015. [6] A. Nikolian, J. Jaguemont, J. De Hoog, S. Goutam, N. Omar, P. Van Den Bossche, and J. Van Mierlo. "Complete cell-level lithium-ion electrical ECM model for different chemistries (NMC, LFP, LTO) and temperatures (− 5 C to 45 C)–Optimized modelling techniques." International Journal of Electrical Power & Energy Systems 98 (2018): 133-146. [7] A. Fotouhi, D. J. Auger, K. Propp, S. Longo, and M. Wild. "A Review on Electric Vehicle Battery Modelling: From Lithium-Ion toward Lithium–Sulphur." Renewable and Sustainable Energy Reviews 56 (2016): 1008-1021. [8] M. Daowd, N. Omar, P. Van Den Bossche and J. Van Mierlo." Passive and active battery balancing comparison based on MATLAB simulation." In 2011 IEEE Vehicle Power and Propulsion Conference, pp. 1-7. IEEE, 2011. [9] L. Zhou, X. Lai, B. Li, Y. Yao, M. Yuan, J. Weng, and Y. Zheng. "State estimation models of lithium-ion batteries for battery management system: status, challenges, and future trends." Batteries 9, no. 2 (2023): 131. [10] M.A. Hannan, M.S.H. Lipu, A. Hussain, and A. Mohamed. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations." Renewable and Sustainable Energy Reviews 78 (2017): 834-854. [11] Alibaba, 3.2v 200Ah LiFePO4 battery lithium SE200 CALB Battery for boat car energy storage 200ah prismatic cell, https://evlithium.en.alibaba.com/product/60684809939- 817515004/200Ah LiFePO4 lithium SE200 CALB Battery for boat car energy storage.html , Last modified: 2021. [12] J. Sarda, H. Patel, Y. Popat, K. L. Hui, and M. Sain. "Review of Management System and State-of-Charge Estimation Methods for Electric Vehicles." World Electric Vehicle Journal 14, no. 12 (2023): 325. [13] Z. Chen, H. Zhao, Y. Zhang, S. Shen, J. Shen, and Y. Liu. "State of health estimation for lithium-ion batteries based on temperature prediction and gated recurrent unit neural network." Journal of Power Sources 521 (2022): 230892. [14] R. Xiong and W. Shen. Advanced Battery Management Technologies for Electric Vehicles. John Wiley & Sons, 2019. [15] W. Wang and J. Mu. "State of charge estimation for lithium-ion battery in electric vehicle based on Kalman filter considering model error." Ieee Access 7 (2019): 29223-29235. [16] A.I. Ilieş, G. Chindriş, and D. Pitică. "A comparison between state of charge estimation methods: extended Kalman filter and unscented Kalman filter." In 2020 IEEE 26th International Symposium for Design and Technology in Electronic Packaging (SIITME), pp. 376-381. IEEE, 2020. [17] R. Xiong and W. Shen. Advanced battery management technologies for electric vehicles. John Wiley & Sons, 2019. [18] M.F. Ge, Y. Liu, X. Jiang, and J. Liu. "A review on state of health estimations and remaining useful life prognostics of lithium-ion batteries." Measurement 174 (2021): 109057. [19] M.M. Hoque, M.A. Hannan, A. Mohamed, and A. Ayob. "Battery charge equalization controller in electric vehicle applications: A review." Renewable and Sustainable Energy Reviews 75 (2017): 1363-1385 [20] J. Gallardo-Lozano, E. Romero-Cadaval, M. I. Milanes-Montero, and M. A. Guerrero-Martinez. "Battery equalization active methods." Journal of Power Sources 246 (2014): 934-949. [21] A. Kumar N, U. Ramanan, R. Joseph, and T. Tharunsushreeth. "Simulation study of a battery management system for electric vehicles using MATLAB/Simulink." In AIP Conference Proceedings, vol. 2452, no. 1. AIP Publishing, 2022. [22] M.Z. Afzal, M. Aurangzeb, S. Iqbal, M. Pushkarna, A.U. Rehman, H. Kotb, K.M. AboRas, N.F. Alshammari, M. Bajaj, and V. Bereznychenko. "A Novel Electric Vehicle Battery Management System Using an Artificial Neural Network‐Based Adaptive Droop Control Theory." International Journal of Energy Research 2023, no. 1 (2023): 2581729. [23] R. Bhovi, K. Ranjith, B. Sachin, and S. Kariyappa. "Modeling and Simulation of Battery Management System (BMS) for Electric Vehicles." Journal of University of Shanghai for Science and Technology 23, no. 06 (2021): 805-815. [24] R. Xiong and W. Shen. Advanced Battery Management Technologies for Electric Vehicles - chapter1: Introduction, 1th ed, JohnWiley & Sons, New Jersey, pp. 12-19, 2019. [25] D. Simon. Optimal State Estimation, 1th edition, JohnWiley & Sons, New Jersey, ch. 14, pp. 433-459, 2006. [26] M. Vale, R. Martins, and A. Maitelli. "Method hybrid for fault detection and identification based on state observers and decision trees." Journal Européen Des Systèmes Automatisés (2014). [27] MathsWorks. Help Center. Nonlinear State Estimation of a Degrading Battery System, https://www.mathworks.com/help/predmaint/ug/nonlinear-state-estimation-of-a-degrading-battery-system.html, Last modified: 2021. [28] Management Technologies for Electric Vehicles- chapter7: Battery Balancing, 1th ed, JohnWiley & Sons, New Jersey, pp. 183- R. Xiong and W. Shen, Advanced Battery 227, 2019. [29] M. Yao, Y. Gan, J. Liang, D. Dong, L. Ma, J. Liu, Q. Luo, and Y. Li. "Performance simulation of a heat pipe and refrigerant-based lithium-ion battery thermal management system coupled with electric vehicle air-conditioning." Applied Thermal Engineering 191 (2021): 116878 [30] Electronics Weekly, EW. Staff, Will supercapacitors supersede batteries, https://www.electronicsweekly.com/news/design/will-supercapacitors-supersede-batteries-2018-11, Last modified: 6th November 2018. [31] Z. Ma, J. Jiang, W. Shi, W. Zhang, and C.C. Mi. "Investigation of path dependence in commercial lithium-ion cells for pure electric bus applications: Aging mechanism identification." Journal of Power Sources 274 (2015): 29-40. [32] D. Gohlich, T.A. Fay, D. Jefferies, E. Lauth, A. Kunith and X. Zhang. "Design of urban electric bus systems." Design Science 4 (2018): e15. [33] H.M. Fischer. "Voltage Classes for Electric Mobility." ZVEI. German Electrical and Electronic Manufacturers, AsSoCiation, Centre of Excellence Electric Mobility, 2014. [34] T. Huria, M. Ceraolo, J. Gazzarri and R. Jackey. "High fidelity electrical model with thermal dependence for characterization and simulation of high power lithium battery cells." In 2012 IEEE international electric vehicle conference, pp. 1-8. IEEE, 2012. [35] MathWorks, Y.Altman, Design and Test Lithium Ion Battery Management Algorithms, https://www.mathworks.com/matlabcentral/fileexchange/72865-design-and-test-lithium-ion-battery management-algorithms , Last modified: January 15, 2022. | ||
|
آمار تعداد مشاهده مقاله: 120 تعداد دریافت فایل اصل مقاله: 97 |
||