IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v70y2014icp618-625.html
   My bibliography  Save this article

Comparison of comprehensive properties of Ni-MH (nickel-metal hydride) and Li-ion (lithium-ion) batteries in terms of energy efficiency

Author

Listed:
  • Kang, Jianqiang
  • Yan, Fuwu
  • Zhang, Pei
  • Du, Changqing

Abstract

In this work, we successfully proposed a method to compare the comprehensive properties of different battery systems in terms of a parameter, energy efficiency. The quantitative relationship of OCV (open circuit voltage) and SOC (state of charge) for Ni-MH batteries is firstly established to calculate the energy efficiency. Then a comprehensive comparison of the energy efficiency for Ni-MH and Li-ion batteries is systemically analyzed under different operating conditions. The results suggest that the energy efficiency is larger for Li-ion batteries than for Ni-MH batteries under charge and charge–discharge cycles, but lesser under a large current rate discharge. The outcome indicates that Ni-MH batteries are more favorable in the case of large current rates discharge than Li-ion batteries. Under plus current rates, two factors, SOC and current rates are analyzed with respect to energy efficiency. For both the batteries, the energy efficiency is varied slightly with SOC, but declines greatly with increased current rates.

Suggested Citation

  • Kang, Jianqiang & Yan, Fuwu & Zhang, Pei & Du, Changqing, 2014. "Comparison of comprehensive properties of Ni-MH (nickel-metal hydride) and Li-ion (lithium-ion) batteries in terms of energy efficiency," Energy, Elsevier, vol. 70(C), pages 618-625.
  • Handle: RePEc:eee:energy:v:70:y:2014:i:c:p:618-625
    DOI: 10.1016/j.energy.2014.04.038
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214004514
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2014.04.038?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rao, Zhonghao & Wang, Shuangfeng, 2011. "A review of power battery thermal energy management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4554-4571.
    2. Eddahech, Akram & Briat, Olivier & Vinassa, Jean-Michel, 2013. "Thermal characterization of a high-power lithium-ion battery: Potentiometric and calorimetric measurement of entropy changes," Energy, Elsevier, vol. 61(C), pages 432-439.
    3. Sun, Fengchun & Hu, Xiaosong & Zou, Yuan & Li, Siguang, 2011. "Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles," Energy, Elsevier, vol. 36(5), pages 3531-3540.
    4. Hu, Xiaosong & Li, Shengbo Eben & Jia, Zhenzhong & Egardt, Bo, 2014. "Enhanced sample entropy-based health management of Li-ion battery for electrified vehicles," Energy, Elsevier, vol. 64(C), pages 953-960.
    5. Fernández, I.J. & Calvillo, C.F. & Sánchez-Miralles, A. & Boal, J., 2013. "Capacity fade and aging models for electric batteries and optimal charging strategy for electric vehicles," Energy, Elsevier, vol. 60(C), pages 35-43.
    6. Xiong, Rui & Sun, Fengchun & He, Hongwen & Nguyen, Trong Duy, 2013. "A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles," Energy, Elsevier, vol. 63(C), pages 295-308.
    7. Zhang, Xiongwen & Kong, Xin & Li, Guojun & Li, Jun, 2014. "Thermodynamic assessment of active cooling/heating methods for lithium-ion batteries of electric vehicles in extreme conditions," Energy, Elsevier, vol. 64(C), pages 1092-1101.
    8. Pei, Lei & Zhu, Chunbo & Wang, Tiansi & Lu, Rengui & Chan, C.C., 2014. "Online peak power prediction based on a parameter and state estimator for lithium-ion batteries in electric vehicles," Energy, Elsevier, vol. 66(C), pages 766-778.
    9. He, Hongwen & Zhang, Xiaowei & Xiong, Rui & Xu, Yongli & Guo, Hongqiang, 2012. "Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles," Energy, Elsevier, vol. 39(1), pages 310-318.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Shaofeng & Zhu, Yanping & Xu, Xiaomin & Sunarso, Jaka & Shao, Zongping, 2017. "Adsorption-based synthesis of Co3O4/C composite anode for high performance lithium-ion batteries," Energy, Elsevier, vol. 125(C), pages 569-575.
    2. Bazinski, S.J. & Wang, X. & Sangeorzan, B.P. & Guessous, L., 2016. "Measuring and assessing the effective in-plane thermal conductivity of lithium iron phosphate pouch cells," Energy, Elsevier, vol. 114(C), pages 1085-1092.
    3. Yang, Chen & Li, Peng & Yu, Jia & Zhao, Li-Da & Kong, Long, 2020. "Approaching energy-dense and cost-effective lithium–sulfur batteries: From materials chemistry and price considerations," Energy, Elsevier, vol. 201(C).
    4. Fan, Guodong & Li, Xiaoyu & Zhang, Ruigang, 2021. "Global Sensitivity Analysis on Temperature-Dependent Parameters of A Reduced-Order Electrochemical Model And Robust State-of-Charge Estimation at Different Temperatures," Energy, Elsevier, vol. 223(C).
    5. Gu, Li & Gui, John Yupeng & Wang, Jing V. & Zhu, Guorong & Kang, Jianqiang, 2019. "Parameterized evaluation of thermal characteristics for a lithium-ion battery," Energy, Elsevier, vol. 178(C), pages 21-32.
    6. Hongling Liu & Chuanyu Bie & Fan Luo & Jianqiang Kang & Yuping Zhang, 2022. "Rapid Prediction of Retired Ni-MH Batteries Capacity Based on Reliable Multi-Parameter Driven Analysis," Energies, MDPI, vol. 15(23), pages 1-11, December.
    7. Eddahech, Akram & Briat, Olivier & Vinassa, Jean-Michel, 2015. "Performance comparison of four lithium–ion battery technologies under calendar aging," Energy, Elsevier, vol. 84(C), pages 542-550.
    8. Yang, Jufeng & Huang, Wenxin & Xia, Bing & Mi, Chris, 2019. "The improved open-circuit voltage characterization test using active polarization voltage reduction method," Applied Energy, Elsevier, vol. 237(C), pages 682-694.
    9. Bumin Meng & Yaonan Wang & Jianxu Mao & Jianwen Liu & Guochang Xu & Jian Dai, 2018. "Using SoC Online Correction Method Based on Parameter Identification to Optimize the Operation Range of NI-MH Battery for Electric Boat," Energies, MDPI, vol. 11(3), pages 1-20, March.
    10. Dai, Haifeng & Guo, Pingjing & Wei, Xuezhe & Sun, Zechang & Wang, Jiayuan, 2015. "ANFIS (adaptive neuro-fuzzy inference system) based online SOC (State of Charge) correction considering cell divergence for the EV (electric vehicle) traction batteries," Energy, Elsevier, vol. 80(C), pages 350-360.
    11. Lv, Peng & Huot, Jacques, 2017. "Hydrogenation improvement of TiFe by adding ZrMn2," Energy, Elsevier, vol. 138(C), pages 375-382.
    12. Yuechen Liu & Linjing Zhang & Jiuchun Jiang & Shaoyuan Wei & Sijia Liu & Weige Zhang, 2017. "A Data-Driven Learning-Based Continuous-Time Estimation and Simulation Method for Energy Efficiency and Coulombic Efficiency of Lithium Ion Batteries," Energies, MDPI, vol. 10(5), pages 1-15, April.
    13. Hassan, I.A. & Ramadan, Haitham S. & Saleh, Mohamed A. & Hissel, Daniel, 2021. "Hydrogen storage technologies for stationary and mobile applications: Review, analysis and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    14. Xu, Meng & Zhang, Zhuqian & Wang, Xia & Jia, Li & Yang, Lixin, 2015. "A pseudo three-dimensional electrochemical–thermal model of a prismatic LiFePO4 battery during discharge process," Energy, Elsevier, vol. 80(C), pages 303-317.
    15. Dong, Guangzhong & Zhang, Xu & Zhang, Chenbin & Chen, Zonghai, 2015. "A method for state of energy estimation of lithium-ion batteries based on neural network model," Energy, Elsevier, vol. 90(P1), pages 879-888.
    16. Julian Marius Müller & Raphael Kunderer, 2019. "Ex-Ante Prediction of Disruptive Innovation: The Case of Battery Technologies," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    17. Sergi Obrador Rey & Juan Alberto Romero & Lluis Trilla Romero & Àlber Filbà Martínez & Xavier Sanchez Roger & Muhammad Attique Qamar & José Luis Domínguez-García & Levon Gevorkov, 2023. "Powering the Future: A Comprehensive Review of Battery Energy Storage Systems," Energies, MDPI, vol. 16(17), pages 1-21, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cheng, Yujie & Lu, Chen & Li, Tieying & Tao, Laifa, 2015. "Residual lifetime prediction for lithium-ion battery based on functional principal component analysis and Bayesian approach," Energy, Elsevier, vol. 90(P2), pages 1983-1993.
    2. Singh, Karanjot & Tjahjowidodo, Tegoeh & Boulon, Loïc & Feroskhan, Mir, 2022. "Framework for measurement of battery state-of-health (resistance) integrating overpotential effects and entropy changes using energy equilibrium," Energy, Elsevier, vol. 239(PA).
    3. Deng, Zhongwei & Yang, Lin & Cai, Yishan & Deng, Hao & Sun, Liu, 2016. "Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery," Energy, Elsevier, vol. 112(C), pages 469-480.
    4. Pang, Haidong & Yang, Zunxian & Lv, Jun & Yan, Wenhuan & Guo, Tailiang, 2014. "Novel MnOx@Carbon hybrid nanowires with core/shell architecture as highly reversible anode materials for lithium ion batteries," Energy, Elsevier, vol. 69(C), pages 392-398.
    5. Fei Feng & Rengui Lu & Guo Wei & Chunbo Zhu, 2015. "Online Estimation of Model Parameters and State of Charge of LiFePO 4 Batteries Using a Novel Open-Circuit Voltage at Various Ambient Temperatures," Energies, MDPI, vol. 8(4), pages 1-27, April.
    6. Bai, Hongwei & Liu, Zhaoyang & Sun, Darren Delai & Chan, Siew Hwa, 2014. "Hierarchical 3D micro-/nano-V2O5 (vanadium pentoxide) spheres as cathode materials for high-energy and high-power lithium ion-batteries," Energy, Elsevier, vol. 76(C), pages 607-613.
    7. Yanhui, Zhang & Wenji, Song & Guoqing, Xu, 2014. "Relaxation effect analysis on the initial state of charge for LiNi0.5Co0.2Mn0.3O2/graphite battery," Energy, Elsevier, vol. 74(C), pages 368-373.
    8. Zhao, Xiaowei & Cai, Yishan & Yang, Lin & Deng, Zhongwei & Qiang, Jiaxi, 2017. "State of charge estimation based on a new dual-polarization-resistance model for electric vehicles," Energy, Elsevier, vol. 135(C), pages 40-52.
    9. Li, Yanwen & Wang, Chao & Gong, Jinfeng, 2017. "A multi-model probability SOC fusion estimation approach using an improved adaptive unscented Kalman filter technique," Energy, Elsevier, vol. 141(C), pages 1402-1415.
    10. Zhang, Sijie & Zhao, Rui & Liu, Jie & Gu, Junjie, 2014. "Investigation on a hydrogel based passive thermal management system for lithium ion batteries," Energy, Elsevier, vol. 68(C), pages 854-861.
    11. Hu, Xiaosong & Li, Shengbo Eben & Jia, Zhenzhong & Egardt, Bo, 2014. "Enhanced sample entropy-based health management of Li-ion battery for electrified vehicles," Energy, Elsevier, vol. 64(C), pages 953-960.
    12. Li, Yanwen & Wang, Chao & Gong, Jinfeng, 2016. "A combination Kalman filter approach for State of Charge estimation of lithium-ion battery considering model uncertainty," Energy, Elsevier, vol. 109(C), pages 933-946.
    13. Zhao, Rui & Gu, Junjie & Liu, Jie, 2017. "Optimization of a phase change material based internal cooling system for cylindrical Li-ion battery pack and a hybrid cooling design," Energy, Elsevier, vol. 135(C), pages 811-822.
    14. Shun Xiang & Guangdi Hu & Ruisen Huang & Feng Guo & Pengkai Zhou, 2018. "Lithium-Ion Battery Online Rapid State-of-Power Estimation under Multiple Constraints," Energies, MDPI, vol. 11(2), pages 1-20, January.
    15. Cuma, Mehmet Ugras & Koroglu, Tahsin, 2015. "A comprehensive review on estimation strategies used in hybrid and battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 517-531.
    16. Dai, Haifeng & Jiang, Bo & Hu, Xiaosong & Lin, Xianke & Wei, Xuezhe & Pecht, Michael, 2021. "Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    17. Shen, Yanqing, 2014. "Hybrid unscented particle filter based state-of-charge determination for lead-acid batteries," Energy, Elsevier, vol. 74(C), pages 795-803.
    18. Dai, Haifeng & Guo, Pingjing & Wei, Xuezhe & Sun, Zechang & Wang, Jiayuan, 2015. "ANFIS (adaptive neuro-fuzzy inference system) based online SOC (State of Charge) correction considering cell divergence for the EV (electric vehicle) traction batteries," Energy, Elsevier, vol. 80(C), pages 350-360.
    19. Dai, Haifeng & Yu, Chenchen & Wei, Xuezhe & Sun, Zechang, 2017. "State of charge estimation for lithium-ion pouch batteries based on stress measurement," Energy, Elsevier, vol. 129(C), pages 16-27.
    20. Zhou, Zhizuan & Wang, Dong & Peng, Yang & Li, Maoyu & Wang, Boxuan & Cao, Bei & Yang, Lizhong, 2022. "Experimental study on the thermal management performance of phase change material module for the large format prismatic lithium-ion battery," Energy, Elsevier, vol. 238(PC).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:70:y:2014:i:c:p:618-625. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.