Skip to main content
Top
Published in:

09-03-2023 | Original Paper

Data-driven-based fuzzy control system design for a hybrid electric vehicle

Authors: Ahmet Beşkardeş, Yakup Hameş

Published in: Electrical Engineering | Issue 4/2023

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

A well-designed energy management system plays a crucial role in increasing fuel efficiency and reducing polluting emissions in dual-power hybrid electric vehicles (HEVs), which are an intermediate stage in the transition from combustion engine vehicles to fully electric vehicles. Despite many studies to optimize energy management, innovative ideas are needed to ensure the most appropriate energy use according to changing road, vehicle, and driver types. For this purpose, we developed a data-driven method to construct a stochastic energy management system, considering realistic uncertainties. We have demonstrated that an HEV can be used more efficiently with an appropriate energy management strategy depending on the road type and driving style. We collected and analyzed 38 thousand km of real driving data with nine different drivers. We transformed these data into meaningful information with a comprehensive data processing methodology and then classified driving styles according to these data using data mining methods. The classification algorithm we designed predicted driving style for three different roads with an average success rate of 95%. We achieved better fuel and emission values with a fuzzy logic-based energy management system that we designed according to the driving style determined by our classification algorithm. The fuzzy controller we developed achieved fuel improvements of up to 7% on the motorway, 9% on the urban road, and 16% on the residential district, based on real driving data results. Although there is a trade-off between fuel and pollutant emissions, our proposed system has also produced significant improvements in harmful emissions. Our results can be used as an inspiration and guide in the studies of improving fuel and emissions in HEVs.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
12.
go back to reference Rolim C, Farias T (2017) Real-time feedback ımpacts on eco-driving behavior and ınfluential variables in fuel consumption in a lisbon urban bus operator. IEEE Trans Intell Transp Syst 18:1–11 CrossRef Rolim C, Farias T (2017) Real-time feedback ımpacts on eco-driving behavior and ınfluential variables in fuel consumption in a lisbon urban bus operator. IEEE Trans Intell Transp Syst 18:1–11 CrossRef
18.
go back to reference Wu B, Chen Y, Yeh C, Li Y (2013) Reasoning-based framework for driving safety monitoring using driving event recognition. IEEE Trans Intell Transp Syst 14:1–11CrossRef Wu B, Chen Y, Yeh C, Li Y (2013) Reasoning-based framework for driving safety monitoring using driving event recognition. IEEE Trans Intell Transp Syst 14:1–11CrossRef
22.
37.
go back to reference Iguyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182MATH Iguyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182MATH
43.
go back to reference Panday A, Bansal HO (2014) A review of optimal energy management strategies for hybrid electric vehicle. Int J Veh Technol 2014:19 Panday A, Bansal HO (2014) A review of optimal energy management strategies for hybrid electric vehicle. Int J Veh Technol 2014:19
44.
go back to reference Gurkaynak Y, Khaligh A, Emadi A (2009) State of the art power management algorithms for hybrid electric vehicles. In: 2009 IEEE vehicle power and propulsion conference, pp 388–394 Gurkaynak Y, Khaligh A, Emadi A (2009) State of the art power management algorithms for hybrid electric vehicles. In: 2009 IEEE vehicle power and propulsion conference, pp 388–394
45.
go back to reference Hajimiri MH, Salmasi FR (2006) A fuzzy energy management strategy for series hybrid electric vehicle with predictive control and durability extension of the battery. In: 2006 IEEE conference on electric and hybrid vehicles, pp 1–5 Hajimiri MH, Salmasi FR (2006) A fuzzy energy management strategy for series hybrid electric vehicle with predictive control and durability extension of the battery. In: 2006 IEEE conference on electric and hybrid vehicles, pp 1–5
48.
go back to reference Lu D, Li W, Xu G, Zhou M (2012). Fuzzy logic control approach to the energy management of parallel hybrid electric vehicles. In: 2012 IEEE ınternational conference on ınformation and automation, pp 592–596 Lu D, Li W, Xu G, Zhou M (2012). Fuzzy logic control approach to the energy management of parallel hybrid electric vehicles. In: 2012 IEEE ınternational conference on ınformation and automation, pp 592–596
51.
go back to reference Zhou M, Zhang H, Wang X (2011) Research on fuzzy energy management strategy of parallel hybrid electric vehicle. In: Proceedings of 2011 ınternational conference on electronic & mechanical engineering and ınformation technology, pp 967–971 Zhou M, Zhang H, Wang X (2011) Research on fuzzy energy management strategy of parallel hybrid electric vehicle. In: Proceedings of 2011 ınternational conference on electronic & mechanical engineering and ınformation technology, pp 967–971
52.
go back to reference van Jaarsveld MJ, Gouws R (2020) An active hybrid energy storage system utilising a fuzzy logic rule-based control strategy. World Electr Veh J 11:34 CrossRef van Jaarsveld MJ, Gouws R (2020) An active hybrid energy storage system utilising a fuzzy logic rule-based control strategy. World Electr Veh J 11:34 CrossRef
54.
go back to reference Fazeli AM, Nabi A, Rajaei Salmasi F, Amiri M (2006) Development of energy management system for a parallel hybrid electric vehicle using fuzzy logic. In: ASME 8th Biennial conference on engineering systems design and analysis, pp 151–156. https://doi.org/10.1115/ESDA2006-95359 Fazeli AM, Nabi A, Rajaei Salmasi F, Amiri M (2006) Development of energy management system for a parallel hybrid electric vehicle using fuzzy logic. In: ASME 8th Biennial conference on engineering systems design and analysis, pp 151–156. https://​doi.​org/​10.​1115/​ESDA2006-95359
Metadata
Title
Data-driven-based fuzzy control system design for a hybrid electric vehicle
Authors
Ahmet Beşkardeş
Yakup Hameş
Publication date
09-03-2023
Publisher
Springer Berlin Heidelberg
Published in
Electrical Engineering / Issue 4/2023
Print ISSN: 0948-7921
Electronic ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-023-01776-9

Other articles of this Issue 4/2023

Electrical Engineering 4/2023 Go to the issue