Efficiency Analysis of Various Batteries with Real-time Data on a Hybrid Electric Vehicle
Year 2021,
Volume: 5 Issue: 3, 214 - 223, 30.09.2021
Yunus Emre Ekici
,
İsmail Can Dikmen
,
Mustafa Nurmuhammed
,
Teoman Karadağ
Abstract
Battery selection remains an up-to-date engineering problem for hybrid and electric vehicle manufacturers. Type of battery and its capacity will depend on the trip and vehicle parameters. An electric vehicle produced with the ideal bat-tery type will undoubtedly be preferred by customers. Data collected from black boxes of trolleybuses operated by Malatya Metropolitan Municipality were used in this study. The real road and driver characteristics were included in the study with the experimentally obtained data. These data are the accelerator pedal data obtained from vehicles driven by different drivers in regular and congested traf-fic hours. In this study, four different battery chemistries were run separately on a hybrid vehicle model and analyzed. Chosen battery chemistries are the most commonly used by manufacturers. These are Lead Acid, Nickel Cadmium, Nickel Metal Hydride and Lithium Iron Phosphate batteries. The results of the study are presented in detail comparatively. Among the battery chemistries, Lithium iron phosphate is observed to be the most ideal battery type for hybrid electric vehi-cles.
Supporting Institution
Inonu University
Project Number
FOA-2018-1358
Thanks
This study was supported by Research Fund of the Inonu University. Project Number: FOA-2018-1358
References
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Year 2021,
Volume: 5 Issue: 3, 214 - 223, 30.09.2021
Yunus Emre Ekici
,
İsmail Can Dikmen
,
Mustafa Nurmuhammed
,
Teoman Karadağ
Project Number
FOA-2018-1358
References
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- [2] A. Khaligh and Z. Li, “Battery, ultracapacitor, fuel cell, and hybrid energy storage systems for electric, hybrid electric, fuel cell, and plug-in hybrid electric vehicles: State of the art,” IEEE Trans. Veh. Technol., vol. 59, no. 6, pp. 2806–2814, 2010, doi: 10.1109/TVT.2010.2047877.
- [3] J. Oncken and B. Chen, “Real-Time Model Predictive Powertrain Control for a Connected Plug-In Hybrid Electric Vehicle,” IEEE Trans. Veh. Technol., vol. 69, no. 8, pp. 8420–8432, 2020, doi: 10.1109/TVT.2020.3000471.
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