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Experimental evaluation of model-based control strategies of sodium-nickel chloride battery plus supercapacitor hybrid storage systems for urban electric vehicles

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  • Capasso, Clemente
  • Lauria, Davide
  • Veneri, Ottorino

Abstract

This paper deals with hybrid energy storage system (HESS) management strategies, optimized for urban road electric vehicle applications. These new control strategies aim to extend battery pack durability by reducing charging/discharging current peaks by means of supercapacitors. The optimization is carried out with reference to the case study of a HESS composed of a high power unit, i.e. supercapacitor module plus a high energy unit, i.e. a battery pack, based on nickel-chloride ZEBRA (ZEolite Battery Research Africa) technology. On-board integration of the two storage devices is obtained through a DC/DC bidirectional power converter, as this configuration is particularly convenient for many kinds of urban vehicle operations. The novelty of this work consists in an analytical methodology, based on non-linear programming and calculus of variations theory, to evaluate management strategies characterized by high effectiveness in reducing battery current transients. The identification and optimization of these strategies are initially performed on the basis of a vehicle model, built in the Matlab-Simulink simulation environment. To this purpose, the experimental characterization of the supercapacitor module is obtained with reference to three different models, whose selection depends on the required fitting performance and computational effort indexes, as evaluated in the paper. The energy management strategies identified show promising results in the simulation environment, followed by experimental activities carried out by means of a dedicated 1:1 scale laboratory test bench. The various experimental results presented in this manuscript highlight that the identified λ-control strategy presents effectiveness values up to 57%, close to the ideal results obtained in the simulation environment. In fact, the methodology proposed in this paper, validated by laboratory experiments, definitely reduces the negative consequences of power peaks on the HESS, indicating the real possibility of using these results in the design and control of urban road vehicles.

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  • Capasso, Clemente & Lauria, Davide & Veneri, Ottorino, 2018. "Experimental evaluation of model-based control strategies of sodium-nickel chloride battery plus supercapacitor hybrid storage systems for urban electric vehicles," Applied Energy, Elsevier, vol. 228(C), pages 2478-2489.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:2478-2489
    DOI: 10.1016/j.apenergy.2018.05.049
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    References listed on IDEAS

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    1. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Han, Xuebing & Ouyang, Minggao, 2015. "Optimization for a hybrid energy storage system in electric vehicles using dynamic programing approach," Applied Energy, Elsevier, vol. 139(C), pages 151-162.
    2. Fotouhi, Abbas & Auger, Daniel J. & Propp, Karsten & Longo, Stefano & Wild, Mark, 2016. "A review on electric vehicle battery modelling: From Lithium-ion toward Lithium–Sulphur," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1008-1021.
    3. Castaings, Ali & Lhomme, Walter & Trigui, Rochdi & Bouscayrol, Alain, 2016. "Comparison of energy management strategies of a battery/supercapacitors system for electric vehicle under real-time constraints," Applied Energy, Elsevier, vol. 163(C), pages 190-200.
    4. Veneri, Ottorino & Capasso, Clemente & Patalano, Stanislao, 2017. "Experimental study on the performance of a ZEBRA battery based propulsion system for urban commercial vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 2005-2018.
    5. Fouda, M.E. & Elwakil, A.S. & Radwan, A.G. & Allagui, A., 2016. "Power and energy analysis of fractional-order electrical energy storage devices," Energy, Elsevier, vol. 111(C), pages 785-792.
    6. Zhang, Shuo & Xiong, Rui & Cao, Jiayi, 2016. "Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system," Applied Energy, Elsevier, vol. 179(C), pages 316-328.
    7. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
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    Cited by:

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    2. Beatrice, C. & Capasso, C. & Doulgeris, S. & Samaras, Z. & Veneri, O., 2024. "Hybrid storage system management for hybrid electric vehicles under real operating conditions," Applied Energy, Elsevier, vol. 354(PB).
    3. Ren, Guizhou & Wang, Jinzhong & Chen, Changlei & Wang, Haoran, 2021. "A variable-voltage ultra-capacitor/battery hybrid power source for extended range electric vehicle," Energy, Elsevier, vol. 231(C).
    4. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine," Applied Energy, Elsevier, vol. 254(C).
    5. Zhou, Yanting & Wang, Yanan & Wang, Kai & Kang, Le & Peng, Fei & Wang, Licheng & Pang, Jinbo, 2020. "Hybrid genetic algorithm method for efficient and robust evaluation of remaining useful life of supercapacitors," Applied Energy, Elsevier, vol. 260(C).
    6. Zhuang, Weichao & Ye, Jianwei & Song, Ziyou & Yin, Guodong & Li, Guangmin, 2020. "Comparison of semi-active hybrid battery system configurations for electric taxis application," Applied Energy, Elsevier, vol. 259(C).
    7. Amjad, Muhammad & Farooq-i-Azam, Muhammad & Ni, Qiang & Dong, Mianxiong & Ansari, Ejaz Ahmad, 2022. "Wireless charging systems for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    8. Liu, Yongjie & Huang, Zhiwu & Wu, Yue & Yan, Lisen & Jiang, Fu & Peng, Jun, 2022. "An online hybrid estimation method for core temperature of Lithium-ion battery with model noise compensation," Applied Energy, Elsevier, vol. 327(C).
    9. Pedram Asef & Marzia Milan & Andrew Lapthorn & Sanjeevikumar Padmanaban, 2021. "Future Trends and Aging Analysis of Battery Energy Storage Systems for Electric Vehicles," Sustainability, MDPI, vol. 13(24), pages 1-28, December.
    10. Adrian Chmielewski & Piotr Piórkowski & Krzysztof Bogdziński & Jakub Możaryn, 2023. "Application of a Bidirectional DC/DC Converter to Control the Power Distribution in the Battery–Ultracapacitor System," Energies, MDPI, vol. 16(9), pages 1-40, April.

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