1. State of the Art in Electric Batteries’ State-of-Health (SoH) Estimation with Machine Learning: A Review. (2025). Ando, Oswaldo Hideo ; Lopes, Srgio F ; Afonso, Jos A ; Carmo, Joao Paulo ; Munhoz, Marcio Lus ; MacIel, Joylan Nunes ; Sylvestrin, Giovane Ronei.
   In: Energies.
   RePEc:gam:jeners:v:18:y:2025:i:3:p:746-:d:1584934.

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2. Lithium-ion batteries lifetime early prediction using domain adversarial learning. (2025). Wang, Yanyu ; Zhang, Zhen ; Ruan, Xingxin.
   In: Renewable and Sustainable Energy Reviews.
   RePEc:eee:rensus:v:208:y:2025:i:c:s1364032124007615.

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3. A comprehensive framework for estimating the remaining useful life of Li-ion batteries under limited data conditions with no temporal identifier. (2025). Alemayehu, Fisseha ; Dabetwar, Shweta ; Ekwaro-Osire, Stephen ; Lopez-Salazar, Camilo.
   In: Reliability Engineering and System Safety.
   RePEc:eee:reensy:v:253:y:2025:i:c:s0951832024005891.

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4. Early prediction of battery lifetime for lithium-ion batteries based on a hybrid clustered CNN model. (2025). Su, Taian ; Hou, Jing ; Xue, Wei ; Yang, Yan ; Gao, Tian.
   In: Energy.
   RePEc:eee:energy:v:319:y:2025:i:c:s0360544225006346.

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5. Coupling a capacity fade model with machine learning for early prediction of the battery capacity trajectory. (2025). Li, Tingkai ; Thelen, Adam ; Liu, Jinqiang ; Yang, Xiao-Guang ; Mishra, Ankush Kumar ; Hu, Chao ; Wang, Zhaoyu.
   In: Applied Energy.
   RePEc:eee:appene:v:389:y:2025:i:c:s0306261925004337.

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6. Inconsistency identification for Lithium-ion battery energy storage systems using deep embedded clustering. (2025). Pan, Ershun ; Xia, Tangbin ; Zhou, DI ; Liu, Weijie ; Chen, Zhen.
   In: Applied Energy.
   RePEc:eee:appene:v:388:y:2025:i:c:s0306261925004076.

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7. Machine learning for full lifecycle management of lithium-ion batteries. (2024). Kang, Qiaoling ; Zhai, Qiangxiang ; Long, Nengbing ; Zhou, Mingjiong ; Yan, Lijing ; Jiang, Hongmin ; Meng, Xianhe ; Ma, Tingli.
   In: Renewable and Sustainable Energy Reviews.
   RePEc:eee:rensus:v:202:y:2024:i:c:s1364032124003733.

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8. Lightweight state-of-health estimation of lithium-ion batteries based on statistical feature optimization. (2024). Lai, Yuan ; Huang, Yiyang ; Zhu, Liqi ; Wang, Jiaxin ; Dai, Houde.
   In: Renewable Energy.
   RePEc:eee:renene:v:222:y:2024:i:c:s0960148123018220.

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9. A robust adapted Flexible Parallel Neural Network architecture for early prediction of lithium battery lifespan. (2024). He, GE ; Huang, Qingsong ; Chen, Junxiong ; Li, Zhuoxiang ; Jiang, Lidang.
   In: Energy.
   RePEc:eee:energy:v:308:y:2024:i:c:s0360544224026148.

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10. An improved dung beetle optimizer- hybrid kernel least square support vector regression algorithm for state of health estimation of lithium-ion batteries based on variational model decomposition. (2024). Fan, Yongcun ; Zhu, Tao ; Wang, Shunli ; Huang, QI ; Hai, Nan ; Fernandez, Carlos.
    In: Energy.
    RePEc:eee:energy:v:306:y:2024:i:c:s0360544224022382.

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11. Enhancing lithium-ion battery lifespan early prediction using a multi-branch vision transformer model. (2024). Zhang, Zhen ; Ding, Wei ; Zhao, Wanjie.
    In: Energy.
    RePEc:eee:energy:v:302:y:2024:i:c:s0360544224015895.

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12. Two-stage prediction method for capacity aging trajectories of lithium-ion batteries based on Siamese-convolutional neural network. (2024). Zhang, Weige ; Li, Shuowei ; Du, Jingcai.
    In: Energy.
    RePEc:eee:energy:v:295:y:2024:i:c:s0360544224007199.

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13. Predict the lifetime of lithium-ion batteries using early cycles: A review. (2024). Mei, Xuesong ; Zhao, Fei ; Wang, Lingzhi ; Liu, Rui ; Sun, Xiaofei ; Yang, Minxing.
    In: Applied Energy.
    RePEc:eee:appene:v:376:y:2024:i:pa:s030626192401554x.

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14. Cross-conditions capacity estimation of lithium-ion battery with constrained adversarial domain adaptation. (2023). Wu, Lifeng ; He, Jiabei.
    In: Energy.
    RePEc:eee:energy:v:277:y:2023:i:c:s0360544223009532.

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15. Attention-based encoder-decoder networks for state of charge estimation of lithium-ion battery. (2023). Zhang, YU ; Wu, Lifeng.
    In: Energy.
    RePEc:eee:energy:v:268:y:2023:i:c:s0360544223000592.

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16. Life prediction model for lithium-ion battery considering fast-charging protocol. (2023). Wu, Lifeng ; Wang, Hongmin ; Zhang, Chen.
    In: Energy.
    RePEc:eee:energy:v:263:y:2023:i:pe:s0360544222029954.

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17. Long Short-Term Memory Network with Transfer Learning for Lithium-ion Battery Capacity Fade and Cycle Life Prediction. (2023). Wang, Yixiu ; Cao, Yankai ; Zhu, Jiangong ; Gopaluni, Bhushan.
    In: Applied Energy.
    RePEc:eee:appene:v:350:y:2023:i:c:s0306261923010243.

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18. An adaptive remaining useful life prediction approach for single battery with unlabeled small sample data and parameter uncertainty. (2022). Jiang, Yuchen ; Li, Xiang ; Yin, Shen ; Huo, Mingyi ; Zhang, Jiusi ; Luo, Hao.
    In: Reliability Engineering and System Safety.
    RePEc:eee:reensy:v:222:y:2022:i:c:s0951832022000369.

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19. A novel method for state of health estimation of lithium-ion batteries based on improved LSTM and health indicators extraction. (2022). Ma, Yan ; Gao, Jinwu ; Chen, Hong ; Shan, CE.
    In: Energy.
    RePEc:eee:energy:v:251:y:2022:i:c:s0360544222008763.

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20. Remaining useful life prediction of lithium-ion batteries using a hybrid model. (2022). Wu, Youxi ; He, Wenxuan ; Ding, Fei ; Yao, Fang ; Meng, Defang.
    In: Energy.
    RePEc:eee:energy:v:248:y:2022:i:c:s0360544222005254.

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21. A hybrid method with cascaded structure for early-stage remaining useful life prediction of lithium-ion battery. (2022). Liu, Yongjie ; Yan, Lisen ; Peng, Jun ; Gao, Dianzhu ; Huang, Zhiwu ; Wu, Yue.
    In: Energy.
    RePEc:eee:energy:v:243:y:2022:i:c:s0360544221032874.

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22. Battery pack consistency modeling based on generative adversarial networks. (2022). He, Xitian ; Fan, Xinyuan ; Zhang, Weige ; Sun, Bingxiang.
    In: Energy.
    RePEc:eee:energy:v:239:y:2022:i:pe:s0360544221026682.

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23. A method for capacity prediction of lithium-ion batteries under small sample conditions. (2022). Guan, Yong ; Zhang, Meng ; Wu, Lifeng ; Kang, Guoqing.
    In: Energy.
    RePEc:eee:energy:v:238:y:2022:i:pc:s0360544221023422.

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24. A novel deep learning-based life prediction method for lithium-ion batteries with strong generalization capability under multiple cycle profiles. (2022). Zhang, Weige ; Wei, Shaoyuan ; Jiang, Jiuchun ; Chen, Dinghong ; Sun, Bingxiang ; Cong, Xinwei.
    In: Applied Energy.
    RePEc:eee:appene:v:327:y:2022:i:c:s030626192201371x.

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25. Complementary cooperative SOC/capacity estimator based on the discrete variational derivative combined with the DEKF for electric power applications. (2021). Park, Seongyun ; Kim, Kun Woo ; Baek, Jongbok.
    In: Energy.
    RePEc:eee:energy:v:232:y:2021:i:c:s0360544221012718.

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26. Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network. (2021). He, Yurong ; Wang, Xinzhi ; Cheng, Gong.
    In: Energy.
    RePEc:eee:energy:v:232:y:2021:i:c:s0360544221012706.

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27. A method for capacity estimation of lithium-ion batteries based on adaptive time-shifting broad learning system. (2021). Guan, Yong ; Hu, Tao ; Zhang, Meng ; Wu, Lifeng ; Kang, Guoqing.
    In: Energy.
    RePEc:eee:energy:v:231:y:2021:i:c:s036054422101207x.

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28. Innovative lumped-battery model for state of charge estimation of lithium-ion batteries under various ambient temperatures. (2021). Song, Youngbin ; Paek, Sung Wook ; Kim, Sangwoo ; Seo, Minhwan.
    In: Energy.
    RePEc:eee:energy:v:226:y:2021:i:c:s0360544221005508.

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29. Early prediction of battery lifetime via a machine learning based framework. (2021). Zhang, Zijun ; Fei, Zicheng ; Li, Lishuai ; Tsui, Kwok-Leung ; Yang, Fangfang.
    In: Energy.
    RePEc:eee:energy:v:225:y:2021:i:c:s0360544221004540.

    Full description at Econpapers || Download paper

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2. Dual Effects of N-Butanol and Magnetite Nanoparticle to Biodiesel-Diesel Fuel Blends as Additives on Emission Pattern and Performance of a Diesel Engine with ANN Validation. (2023). Latiff, Zulkarnain Abdul ; Epin, Vorathin ; Abas, Mohd Azman ; Elahi, Manzoore ; Harny, Irianto ; Veza, Ibham ; Sule, Ahmed.
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3. Optimization of CI Engine Performance and Emissions Using Alcohol–Biodiesel Blends: A Regression Analysis Approach. (2023). Dey, Suman ; Gajghate, Sameer Sheshrao ; Pal, Sagnik ; Das, Pankaj Kumar ; Deb, Madhujit ; Saha, Bidyut Baran ; Singh, Akhilendra Pratap.
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4. Optimizing a Green and Sustainable Off-Grid Energy-System Design: A Real Case. (2023). Nowzari, Raheleh ; Ghadirinejad, Nickyar ; Alsaadi, Naif ; Ottermo, Fredric.
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5. Dynamic carbon emission factor based interactive control of distribution network by a generalized regression neural network assisted optimization. (2023). Guo, Zhengxun ; Yang, Yuyao ; Zhang, Xiaoshun ; Pan, Feng ; Li, Chuansheng.
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6. Multi-objective optimization of the Atkinson cycle gasoline engine using NSGA Ⅲ coupled with support vector machine and back-propagation algorithm. (2023). Zhou, Shi ; Ouyang, Minggao ; Tong, JI ; Liu, Jingping ; Dang, Jian.
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7. Exploring dilution potential for full load operation of medium duty hydrogen engine for the transport sector. (2023). Novella, Ricardo ; Gomez-Soriano, Josep ; Garcia, Antonio ; Fogue-Robles, Alvaro.
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8. Optimizing the effect of a mixture of light naphtha, diesel and gasoline fuels on engine performance and emission values on an HCCI engine. (2023). Demir, Usame ; Kocakulak, Tolga ; Elebi, Samet ; Ergen, Gokhan ; Yilmaz, Emre.
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9. In Search of Non-Obvious Relationships between Greenhouse Gas or Particulate Matter Emissions, Renewable Energy and Corruption. (2022). Dec, Pawe ; Wysocki, Jacek.
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10. Influence of Intake Port Structure on the Performance of a Spark-Ignited Natural Gas Engine. (2022). Li, Wei ; Zhu, Tao ; Ma, Junfang ; Wei, Jing ; Xu, Jingjing ; Pan, Jie ; Liu, Hongzhe ; Zhang, Hairui.
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11. Multi objective optimization of HCCI combustion fuelled with fusel oil and n-heptane blends. (2022). Kocakulak, Tolga ; Safieddin, Seyed Mohammad ; Babagiray, Mustafa ; Solmaz, Hamit ; Calam, Alper ; Nacak, Aatay.
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12. A Generic Pipeline for Machine Learning Users in Energy and Buildings Domain. (2021). Hamdy, Mohamed ; Bashery, Mahmoud Abdelkader.
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13. Application of machine learning tools for constrained multi-objective optimization of an HCCI engine. (2021). Alizadeh, Pouria ; Abbasi, Hamid Reza ; Gharehghani, Ayat.
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14. Prognostics of battery cycle life in the early-cycle stage based on hybrid model. (2021). Peng, Zhen ; Zhang, YU ; Guan, Yong ; Wu, Lifeng.
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15. A data-driven evolutionary algorithm for wind farm layout optimization. (2020). Gu, Wei ; Li, Peikun ; Long, Huan.
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16. Thermodynamic-CFD analysis of waste heat recovery from homogeneous charge compression ignition (HCCI) engine by Recuperative organic Rankine Cycle (RORC): Effect of operational parameters. (2020). Mousavi, Seyed Soheil ; Ezoji, Hosein.
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17. Multi-objective optimization of a syngas powered reciprocating engine equipping a combined heat and power unit. (2020). Costa, M ; Costagliola, M A ; Martoriello, G ; di Blasio, G ; Cirillo, D ; Caputo, C ; Prati, M V ; la Villetta, M.
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18. Daily reference evapotranspiration prediction of Tieguanyin tea plants based on mathematical morphology clustering and improved generalized regression neural network. (2020). Shijie, Song ; Ruiming, Fang.
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19. The Contribution of Energy Taxes to Climate Change Policy in the European Union (EU). (2019). Butkus, Mindaugas ; Matuzeviit, Kristina ; Liobikien, Genovait.
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20. Chaotic Multi-Objective Particle Swarm Optimization Algorithm Incorporating Clone Immunity. (2019). Gao, Yuelin ; Sun, Ying ; Shi, Xudong.
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21. Microgrid-Level Energy Management Approach Based on Short-Term Forecasting of Wind Speed and Solar Irradiance. (2019). Haider, Syed Irtaza ; Alhussein, Musaed ; Aurangzeb, Khursheed.
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22. A literature review of fuel effects on performance and emission characteristics of low-temperature combustion strategies. (2019). He, Zhixia ; Leng, Xianying ; Zhong, Wenjun ; Pachiannan, Tamilselvan ; Rajkumar, Sundararajan ; Wang, Qian.
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23. Engine characteristics analysis of chaulmoogra oil blends and corrosion analysis of injector nozzle using scanning electron microscopy/energy dispersive spectroscopy. (2018). Malayalamurthi, R ; Krishnamoorthi, M.
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25. Economic evaluation of a PV combined energy storage charging station based on cost estimation of second-use batteries. (2018). Liang, Yubo ; Ai, Yaoyao ; Han, Xiaojuan.
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26. Prediction of short-term PV power output and uncertainty analysis. (2018). Wennersten, Ronald ; Sun, Qie ; Liu, Luyao ; Xie, Jiyang ; Yin, Hongyi ; Chang, Dongliang ; Ma, Zhanyu ; Zhao, YI.
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27. Crank angle-resolved exergy analysis of exhaust flows in a diesel engine from the perspective of exhaust waste energy recovery. (2018). Subramanian, Swaminathan ; Krishnan, Sundar Rajan ; Srinivasan, Kalyan Kumar ; Mahabadipour, Hamidreza.
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28. The European Union possibilities to achieve targets of Europe 2020 and Paris agreement climate policy. (2017). Butkus, Mindaugas ; Liobikien, Genovait.
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29. CO2 emissions in Chinas building sector through 2050: A scenario analysis based on a bottom-up model. (2017). Pan, Yiqun ; Yang, Yikun ; Xu, Peng ; Lin, Meishun ; Qin, Bingyue ; Huang, Zhizhong.
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30. Effect of bioethanol on combustion and emissions in advanced CI engines: HCCI, PPC and GCI mode – A review. (2017). No, Soo-Young ; Noh, Hyun Kwon.
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32. Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study. (2016). Cesarotti, Vittorio ; Introna, Vito ; Benedetti, Miriam ; Serranti, Jacopo .
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