Research Article
BibTex RIS Cite

THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS

Year 2017, Volume: 18 Issue: 4, 804 - 818, 31.10.2017
https://doi.org/10.18038/aubtda.340367

Abstract

Road vehicles using electric power sources have become
increasingly popular in the last decade.
Meanwhile,
battery technology is still not mature enough to meet expected vehicle range; thus
the transition from ICE vehicle to fully electric vehicle is not imminent.
Therefore the concept of hybrid drivetrain technology was introduced. The
hybrid powertrain configuration includes at least two different energy
converters together with an energy storage medium. In this article, different
gear shifting algorithms were introduced to increase ICE efficiency in
conventional vehicle. Besides, a parallel hybrid configuration was also
introduced to enhance drivetrain efficiency. The Equivalent Energy Minimization
Method (ECMS) and Dynamic Programming (DP) algorithms were selected as online
and offline implementable optimal control methods for hybrid power sharing
management. Totally six different case studies were planned to compare the
efficiency of each configuration. Finally, the effect of the gear ratio
selection and power split algorithms were compared on conventional and parallel
hybrid drivetrains regarding overall efficiency.

References

  • Davis S. C, Diegel S. W, Boundy R. G. Transportation Energy Data Book. 34th ed. Oak Ridge, Tennessee, USA: U.S. Department of Energy, 2015.
  • Amini A, Önder E. T, Başlamışlı S. Ç, Köprübaşı K, S. Solmaz, Paralel hibrit bir araç için eşdeğer enerji minimizasyonu yöntemi ile yakıt tüketimi optimizasyonu. In: 8. Otomotiv Teknolojileri Kongresi; 23-24 May 2016, Bursa, Turkey. “(article in Turkish with an abstract in English)”.
  • Karaoğlan M, Kuralay N. S, Şehiriçi toplu taşımacılıkta hibrit tahrik uygulamaları, TMMOB Mühendis ve Makina 2014; 55: 650: 1-16. “(article in Turkish with an abstract in English)”.
  • Boyalı A. Hibrid elektrikli yol taşıtlarının modellenmesi ve kontrolü. PhD, İstanbul Technical University, İstanbul, Turkey, 2008.
  • Köprübaşı K. Modeling and Control of a Power-Split Hybrid Vehicle for Drivability and Fuel Economy Improvements. PhD, The Ohio State University, Ohio, U.S, 2008.
  • Ulsoy A, Peng H, Çakmakci M. Automotive Control Systems. 1st ed. New York, NY, USA: Cambridge University Press, 2012.
  • Liu J, Peng H, Modeling and Control of a Power-Split Hybrid Vehicle, IEEE Transactions on Control Systems Technology 2008; 16: 6: 1242-1251.
  • Boyalı A, Acarman T, Güvenç L. Component Sizing in Hybrid Electric Vehicle Design using Optimization and Design of Experiments Techniques. In: 3rd AUTOCOM Workshop on Hybrid Electric Vehicle Modeling and Control; January 2007; İTÜ, Istanbul, Turkey.
  • Fleuren M, Romijn T, Donkers M. An Equivalent Consumption Minimisation Strategy based on 1-Step Look-Ahead Stochastic Dynamic Programming. In: 19th International Federation of Automatic Control; 24-29 August 2014; Cape Town, South Africa. pp. 72-77.
  • Musardo C, Rizzoni G, Fellow, IEEE, B Staccia. A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management. In: 44th IEEE Conference on Decision and Control and the European Control Conference; 12-15 December 2005; Seville, Spain. pp. 1816-1823.
  • Fu L, Özgüner Ü, Tulpule P, Marano V. Real-time Energy Management and Sensitivity Study for Hybrid Electric Vehicle. In: American Control Conference; June 29 - July 01, 2011; San Francisco, CA, USA. pp. 2113-2118.
  • Sciarretta A, Back M, Guzzella M. L, Optimal Control of Parallel Hybrid Electric Vehicles, IEEE Transactions on Control Systems Technology 2004; 12: 3: 352-363.
  • Başlamışlı S. Ç, İnce B, Koçak M, Saygılı H. Hibrit-elektrikli şehir içi otobüslerde yakıt ekonomisinin iyileştirilmesine yönelik enerji yönetim sistemi algoritmalarının tasarımı. In: 8. Otomotiv Teknolojileri Kongresi; 23-24 May 2016, Bursa, Turkey. “(article in Turkish with an abstract in English)”
  • Boyalı A, Güvenç L, Hibrit elektrikli araçların modellenmesi ve kural tabanlı kontrolü, İTÜ Dergisi, Mühendislik 2010; 9: 2: 83-94.
  • Elbert P, Ebbesen S, Guzzella L, Implementation of Dynamic Programming for n-Dimensional Optimal Control Problems With Final State Constraints, IEEE Transactıons on Control Systems Technology 2013; 21: 3: 924-931.
  • Sundstrom O, Guzzella L. A Generic Dynamic Programming Matlab Function. In: International Conference on Control Applications; July 8-10 2009; Saint Petersburg, Russia. p.p. 1625-1630
  • Sundström O, Ambühl D, Guzzella L, On Implementation of Dynamic Programming for Optimal Control Problems with Final State Constraints, Oil & Gas Science and Technology 2010; 65: 1: 91-102.
  • Julian H. S. An Introduction to Modern Vehicle Design. 1st ed. Jordan Hill, Oxford, Great Britain: Butterworth-Heinemann, 2001.
  • Sundstrom O, Guzzella L, Soltic P. Optimal Hybridization in Two Parallel Hybrid Electric Vehicles using Dynamic Programming. In: 17th World Congress the International Federation of Automatic Control; July 6-11 2008; Seoul, Korea. p.p. 4642-4647.
Year 2017, Volume: 18 Issue: 4, 804 - 818, 31.10.2017
https://doi.org/10.18038/aubtda.340367

Abstract

References

  • Davis S. C, Diegel S. W, Boundy R. G. Transportation Energy Data Book. 34th ed. Oak Ridge, Tennessee, USA: U.S. Department of Energy, 2015.
  • Amini A, Önder E. T, Başlamışlı S. Ç, Köprübaşı K, S. Solmaz, Paralel hibrit bir araç için eşdeğer enerji minimizasyonu yöntemi ile yakıt tüketimi optimizasyonu. In: 8. Otomotiv Teknolojileri Kongresi; 23-24 May 2016, Bursa, Turkey. “(article in Turkish with an abstract in English)”.
  • Karaoğlan M, Kuralay N. S, Şehiriçi toplu taşımacılıkta hibrit tahrik uygulamaları, TMMOB Mühendis ve Makina 2014; 55: 650: 1-16. “(article in Turkish with an abstract in English)”.
  • Boyalı A. Hibrid elektrikli yol taşıtlarının modellenmesi ve kontrolü. PhD, İstanbul Technical University, İstanbul, Turkey, 2008.
  • Köprübaşı K. Modeling and Control of a Power-Split Hybrid Vehicle for Drivability and Fuel Economy Improvements. PhD, The Ohio State University, Ohio, U.S, 2008.
  • Ulsoy A, Peng H, Çakmakci M. Automotive Control Systems. 1st ed. New York, NY, USA: Cambridge University Press, 2012.
  • Liu J, Peng H, Modeling and Control of a Power-Split Hybrid Vehicle, IEEE Transactions on Control Systems Technology 2008; 16: 6: 1242-1251.
  • Boyalı A, Acarman T, Güvenç L. Component Sizing in Hybrid Electric Vehicle Design using Optimization and Design of Experiments Techniques. In: 3rd AUTOCOM Workshop on Hybrid Electric Vehicle Modeling and Control; January 2007; İTÜ, Istanbul, Turkey.
  • Fleuren M, Romijn T, Donkers M. An Equivalent Consumption Minimisation Strategy based on 1-Step Look-Ahead Stochastic Dynamic Programming. In: 19th International Federation of Automatic Control; 24-29 August 2014; Cape Town, South Africa. pp. 72-77.
  • Musardo C, Rizzoni G, Fellow, IEEE, B Staccia. A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management. In: 44th IEEE Conference on Decision and Control and the European Control Conference; 12-15 December 2005; Seville, Spain. pp. 1816-1823.
  • Fu L, Özgüner Ü, Tulpule P, Marano V. Real-time Energy Management and Sensitivity Study for Hybrid Electric Vehicle. In: American Control Conference; June 29 - July 01, 2011; San Francisco, CA, USA. pp. 2113-2118.
  • Sciarretta A, Back M, Guzzella M. L, Optimal Control of Parallel Hybrid Electric Vehicles, IEEE Transactions on Control Systems Technology 2004; 12: 3: 352-363.
  • Başlamışlı S. Ç, İnce B, Koçak M, Saygılı H. Hibrit-elektrikli şehir içi otobüslerde yakıt ekonomisinin iyileştirilmesine yönelik enerji yönetim sistemi algoritmalarının tasarımı. In: 8. Otomotiv Teknolojileri Kongresi; 23-24 May 2016, Bursa, Turkey. “(article in Turkish with an abstract in English)”
  • Boyalı A, Güvenç L, Hibrit elektrikli araçların modellenmesi ve kural tabanlı kontrolü, İTÜ Dergisi, Mühendislik 2010; 9: 2: 83-94.
  • Elbert P, Ebbesen S, Guzzella L, Implementation of Dynamic Programming for n-Dimensional Optimal Control Problems With Final State Constraints, IEEE Transactıons on Control Systems Technology 2013; 21: 3: 924-931.
  • Sundstrom O, Guzzella L. A Generic Dynamic Programming Matlab Function. In: International Conference on Control Applications; July 8-10 2009; Saint Petersburg, Russia. p.p. 1625-1630
  • Sundström O, Ambühl D, Guzzella L, On Implementation of Dynamic Programming for Optimal Control Problems with Final State Constraints, Oil & Gas Science and Technology 2010; 65: 1: 91-102.
  • Julian H. S. An Introduction to Modern Vehicle Design. 1st ed. Jordan Hill, Oxford, Great Britain: Butterworth-Heinemann, 2001.
  • Sundstrom O, Guzzella L, Soltic P. Optimal Hybridization in Two Parallel Hybrid Electric Vehicles using Dynamic Programming. In: 17th World Congress the International Federation of Automatic Control; July 6-11 2008; Seoul, Korea. p.p. 4642-4647.
There are 19 citations in total.

Details

Subjects Engineering
Journal Section Articles
Authors

Ali Amini

S. Çağlar Başlamışlı

Bayramcan İnce

Mertcan Koçak This is me

Publication Date October 31, 2017
Published in Issue Year 2017 Volume: 18 Issue: 4

Cite

APA Amini, A., Başlamışlı, S. Ç., İnce, B., Koçak, M. (2017). THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering, 18(4), 804-818. https://doi.org/10.18038/aubtda.340367
AMA Amini A, Başlamışlı SÇ, İnce B, Koçak M. THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS. AUJST-A. October 2017;18(4):804-818. doi:10.18038/aubtda.340367
Chicago Amini, Ali, S. Çağlar Başlamışlı, Bayramcan İnce, and Mertcan Koçak. “THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 18, no. 4 (October 2017): 804-18. https://doi.org/10.18038/aubtda.340367.
EndNote Amini A, Başlamışlı SÇ, İnce B, Koçak M (October 1, 2017) THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 18 4 804–818.
IEEE A. Amini, S. Ç. Başlamışlı, B. İnce, and M. Koçak, “THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS”, AUJST-A, vol. 18, no. 4, pp. 804–818, 2017, doi: 10.18038/aubtda.340367.
ISNAD Amini, Ali et al. “THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 18/4 (October 2017), 804-818. https://doi.org/10.18038/aubtda.340367.
JAMA Amini A, Başlamışlı SÇ, İnce B, Koçak M. THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS. AUJST-A. 2017;18:804–818.
MLA Amini, Ali et al. “THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering, vol. 18, no. 4, 2017, pp. 804-18, doi:10.18038/aubtda.340367.
Vancouver Amini A, Başlamışlı SÇ, İnce B, Koçak M. THE EFFECT OF DIFFERENT GEAR RATIO SELECTION ALGORITHMS ON THE EFFICIENCY OF CONVENTIONAL AND PARALLEL HYBRID DRIVETRAINS. AUJST-A. 2017;18(4):804-18.