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Journals / Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi / 2014 / Cilt: 17 - Sayı: 1

Lithium-Ion Battery Discharge Status Of Genetic Expression Behavior And Prediction Of Programming

Lityum İon Bataryaların Deşarj Durumu Davranışlarının Genetik İfade Programlama İle Kestirimi

Mehmet AVGIN
Ahmet YILMAZ
Mehmet ÜNSAL
Pages
10–15
Publication Date
2014-10-25
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Hence, it is intended to reach an accurate and precise state-of-charge estimation due to battery types.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Due to continuous increase of energy consumption in personal and business life, the battery industry, the emergence of more advanced technologies are needed.
📊
Key Findings & Data:However accurate and precise knowledge of the state-ofcharge is one of the most important components of a battery management system.
💡
Conclusion & Impact:Hence, it is intended to reach an accurate and precise state-of-charge estimation due to battery types.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Şarj Doluluk Durumu · SOC · Genetik Programlama

Abstract

Due to continuous increase of energy consumption in personal and business life, the battery industry, the emergence of more advanced technologies are needed. In this respect, for a battery user, expected to be a priority, the energy needed, the duration of time needed to provide. However accurate and precise knowledge of the state-ofcharge is one of the most important components of a battery management system. In this study, estimation of battery state of charge parameter using genetic expression programming is investigated. To estimate the state-of-charge, which is the most important component of battery management system, estimation methods and battery models in the literature are summarized. In the simulation, the variables of battery current, battery terminal voltage and the time are assigned as inputs. With this process, new specific state-of-charge data and are mathematical discharge equations are obtained for each Lithium-Ion, battery types. Hence, it is intended to reach an accurate and precise state-of-charge estimation due to battery types.

Özet

Artış gösteren kişisel ve iş yaşamındaki enerji tüketimine bağlı olarak, batarya sektöründe daha gelişmiş teknolojilerin ortaya çıkmasına ihtiyaç duyulmaktadır. Bu noktada öncelikli olarak bir bataryadan beklenen, ihtiyaç duyulan enerjiyi, ihtiyaç duyulan zaman süresince sağlamasıdır. Bunun yanında şarj doluluk durumu bilgisinin doğru ve kesin olarak bilinmesi de batarya yönetim sisteminin en önemli unsurlarından biridir. Bu çalışmada, lityum-ion (Li-Ion) akü yönetim sisteminin en önemli unsurlarından birisi olan batarya doluluk durumunu için genetik ifade programlama algoritması ile kestirimi incelenmiştir. Kestirim çalışmasında giriş değerleri olarak atanan batarya akımı, batarya çıkış voltajı ve zaman değişkenleri ile çıkış değeri olarak batarya türlerine özel şarj doluluk durumu verileri elde edilmiştir. Lityum-İon aküler için matematiksel deşarj denklemleri oluşturulmuş ve böylece pil türüne özel deşarj bilgileriyle daha doğru ve kesin SOC tahmini yapılabilmesi amaçlanmıştır.

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Cite This Article

AVGIN, M., YILMAZ, A., ÜNSAL, M. (2014). Lithium-Ion Battery Discharge Status Of Genetic Expression Behavior And Prediction Of Programming. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, Cilt: 17 - Sayı: 1, 10–15. https://ajindex.com/articles/876701

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