Structure and Electrochemical Behavior of ZnLaFeO 4 Alloy as a Negative Electrode in Ni-MH Batteries
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- 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.
- 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.
- Smith, William J., 2010. "Can EV (electric vehicles) address Ireland’s CO2 emissions from transport?," Energy, Elsevier, vol. 35(12), pages 4514-4521.
- Johansson, Bengt & Mårtensson, Anders, 2000. "Energy and environmental costs for electric vehicles using CO2-neutral electricity in Sweden," Energy, Elsevier, vol. 25(8), pages 777-792.
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.- 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.
- Liu, Nian & Chen, Zheng & Liu, Jie & Tang, Xiao & Xiao, Xiangning & Zhang, Jianhua, 2014. "Multi-objective optimization for component capacity of the photovoltaic-based battery switch stations: Towards benefits of economy and environment," Energy, Elsevier, vol. 64(C), pages 779-792.
- 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.
- 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.
- Ming Zhang & Dongfang Yang & Jiaxuan Du & Hanlei Sun & Liwei Li & Licheng Wang & Kai Wang, 2023. "A Review of SOH Prediction of Li-Ion Batteries Based on Data-Driven Algorithms," Energies, MDPI, vol. 16(7), pages 1-28, March.
- Varga, Bogdan Ovidiu, 2013. "Electric vehicles, primary energy sources and CO2 emissions: Romanian case study," Energy, Elsevier, vol. 49(C), pages 61-70.
- Guoqing Jin & Lan Li & Yidan Xu & Minghui Hu & Chunyun Fu & Datong Qin, 2020. "Comparison of SOC Estimation between the Integer-Order Model and Fractional-Order Model Under Different Operating Conditions," Energies, MDPI, vol. 13(7), pages 1-17, April.
- 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.
- Li, Yue & Chattopadhyay, Pritthi & Xiong, Sihan & Ray, Asok & Rahn, Christopher D., 2016. "Dynamic data-driven and model-based recursive analysis for estimation of battery state-of-charge," Applied Energy, Elsevier, vol. 184(C), pages 266-275.
- Hu, Lin & Hu, Xiaosong & Che, Yunhong & Feng, Fei & Lin, Xianke & Zhang, Zhiyong, 2020. "Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering," Applied Energy, Elsevier, vol. 262(C).
- Li, Xiaoyu & Xu, Jianhua & Hong, Jianxun & Tian, Jindong & Tian, Yong, 2021. "State of energy estimation for a series-connected lithium-ion battery pack based on an adaptive weighted strategy," Energy, Elsevier, vol. 214(C).
- Li, Hao & Fu, Lijun & Long, Xinlin & Liu, Lang & Zeng, Ziqing, 2024. "A hybrid deep learning model for lithium-ion batteries state of charge estimation based on quantile regression and attention," Energy, Elsevier, vol. 294(C).
- Quan Ouyang & Rui Ma & Zhaoxiang Wu & Guotuan Xu & Zhisheng Wang, 2020. "Adaptive Square-Root Unscented Kalman Filter-Based State-of-Charge Estimation for Lithium-Ion Batteries with Model Parameter Online Identification," Energies, MDPI, vol. 13(18), pages 1-14, September.
- Zheng, Xiujuan & Fang, Huajing, 2015. "An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 74-82.
- Graabak, Ingeborg & Wu, Qiuwei & Warland, Leif & Liu, Zhaoxi, 2016. "Optimal planning of the Nordic transmission system with 100% electric vehicle penetration of passenger cars by 2050," Energy, Elsevier, vol. 107(C), pages 648-660.
- Zhaohua Wang & Xiaoyang Dong, 2016. "Determinants and policy implications of residents’ new energy vehicle purchases: the evidence from China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(1), pages 155-173, May.
- 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.
- 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).
- Dai, Ziyi & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall, 2022. "Electric vehicle market potential and associated energy and emissions reduction benefits," Applied Energy, Elsevier, vol. 322(C).
- 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.
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:gam:jeners:v:18:y:2025:i:13:p:3251-:d:1684247. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.