ناشر تخصصی کنفرانس های ایران

لطفا کمی صبر نمایید

Publisher of Iranian Journals and Conference Proceedings

Please waite ..
Publisher of Iranian Journals and Conference Proceedings
Login |Register |Help |عضویت کتابخانه ها
Paper
Title

Online state-of-charge estimation of lithium-ion and lead-acid batteries in electric vehicles

Year: 1395
Publish place:
COI: ICELE01_201
Language: EnglishView: 713
This Paper With 10 Page And PDF Format Ready To Download
محتوای کامل این Paper با فرمت WORD هم قابل دریافت می باشد.

Buy and Download

با استفاده از پرداخت اینترنتی بسیار سریع و ساده می توانید اصل این Paper را که دارای 10 صفحه است به صورت فایل PDF و یا WORD در اختیار داشته باشید.
آدرس ایمیل خود را در کادر زیر وارد نمایید:

Authors

Mohammad Hossein Ranjbar Jafari - Shahid Bahonar University
Seyed Mohammad Ali Mohammadi - Shahid Bahonar University
Jalal Vahedian - Shahid Bahonar University

Abstract:

In vehicle applications, due to energy, power and voltage commitment the battery systems are usually composed of hundreds of cells that are connected in series and/or parallel configuration. To improve performance conditions and increase the battery lifespan, the battery management system (BMS) should makes decision for battery healthy based on the state of charge (SOC) estimation. In this paper, two strategies for SOC estimation of lithium - ion and lead-acid batteries are presented. In the first strategy, according to the suitability fuzzy logic to uncertainty modelling, the attempting to implement a decision-making system to estimate the battery's SOC is done. This strategy is designed based on the current, voltage and SOC data of the battery. The advantage of the fuzzy identification designing is its independency on battery modeling. In the second strategy, the SOC of the battery is estimated based on an online identification algorithm designed for its open circuit voltage (OCV). Recursive Least Squares (RLS) methode is utilized for identification algorithm According to the inherent relationship between the SOC and OCV, the SOC can be computed by the estimated OCV. The SOC-OCV relationship is modeled by a Neural Network which is trained by the actual data. According to the trained Neural Network, the SOC values are obtained corresponding to the estimated OCV values. In the RLS based strategy, battery dynamical models presented in section 2 are used. In validation section, it is observed that the second strategy shows the better results compared with the first strategy.

Keywords:

Paper COI Code

This Paper COI Code is ICELE01_201. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/504044/

How to Cite to This Paper:

If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Ranjbar Jafari, Mohammad Hossein and Mohammadi, Seyed Mohammad Ali and Vahedian, Jalal,1395,Online state-of-charge estimation of lithium-ion and lead-acid batteries in electric vehicles,کنفرانس بین المللی مهندسی برق,Tehran,https://civilica.com/doc/504044

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :

  • Haifeng, D., Xuezhe, W. (2012). Online cell SOC estimation of ...
  • Long , X., Junping , W. (2012). Kalman filtering state ...
  • IISong, K. (2008). Nonlinear state of charge estimator for hybrid ...
  • Seongjun, L., Kim, Jonghoon, L., BH, C. (2008). State-of-charge and ...
  • Gregory, P. (2004). Extended Kalman filtering for battery management systems ...
  • Piller, S., Perrin, M. (2001). Method for state-of-charge determination and ...
  • Jonghoon, _ Seongjun, L., B.H, Cho. (2011). Discrimination of Li-ion ...
  • Hongwen, H., Rui, X., Jinxin, F. (2011). Evaluation of lithium-ion ...
  • Jinlong, Zh., Chaoying, Xia. (2011). State-of-charge estimation of valve regulated ...
  • Dipti, S. Liew AC. (1955). Applications of fuzzy systems in ...
  • Xidong, T., Xiaofeng, M., Jian, L, Brian K. (2011) .Li-ion ...
  • Research Info Management

    Certificate | Report | من نویسنده این مقاله هستم
    این Paper در بخشهای موضوعی زیر دسته بندی شده است:

    اطلاعات استنادی این Paper را به نرم افزارهای مدیریت اطلاعات علمی و استنادی ارسال نمایید و در تحقیقات خود از آن استفاده نمایید.

    Scientometrics

    The specifications of the publisher center of this Paper are as follows:
    Type of center: دانشگاه دولتی
    Paper count: 16,894
    In the scientometrics section of CIVILICA, you can see the scientific ranking of the Iranian academic and research centers based on the statistics of indexed articles.

    مقالات پیشنهادی مرتبط

    New Papers

    Share this page

    More information about COI

    COI stands for "CIVILICA Object Identifier". COI is the unique code assigned to articles of Iranian conferences and journals when indexing on the CIVILICA citation database.

    The COI is the national code of documents indexed in CIVILICA and is a unique and permanent code. it can always be cited and tracked and assumed as registration confirmation ID.

    Support