Literatura académica sobre el tema "Battery state-of-health"
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Artículos de revistas sobre el tema "Battery state-of-health"
Yang, Qingxia, Ke Ma, Liyou Xu, Lintao Song, Xiuqing Li y Yefei Li. "A Joint Estimation Method Based on Kalman Filter of Battery State of Charge and State of Health". Coatings 12, n.º 8 (24 de julio de 2022): 1047. http://dx.doi.org/10.3390/coatings12081047.
Texto completoWei, Yupeng. "Prediction of State of Health of Lithium-Ion Battery Using Health Index Informed Attention Model". Sensors 23, n.º 5 (26 de febrero de 2023): 2587. http://dx.doi.org/10.3390/s23052587.
Texto completoHuang, Kai, Yong-Fang Guo, Ming-Lang Tseng, Kuo-Jui Wu y Zhi-Gang Li. "A Novel Health Factor to Predict the Battery’s State-of-Health Using a Support Vector Machine Approach". Applied Sciences 8, n.º 10 (2 de octubre de 2018): 1803. http://dx.doi.org/10.3390/app8101803.
Texto completoO. Hadi, Pradita y Goro Fujita. "Battery Charge Control by State of Health Estimation". Indonesian Journal of Electrical Engineering and Computer Science 5, n.º 3 (1 de marzo de 2017): 508. http://dx.doi.org/10.11591/ijeecs.v5.i3.pp508-514.
Texto completoPatel, Nisarg. "A Review of State of Health and State of Charge Estimation Methods". International Journal for Research in Applied Science and Engineering Technology 9, n.º 11 (30 de noviembre de 2021): 259–64. http://dx.doi.org/10.22214/ijraset.2021.38693.
Texto completoBrunelli Lazzarin, Telles y Ivo Barbi. "A system for state-of-health diagnosis of lead-acid batteries integrated with a battery charger". Eletrônica de Potência 17, n.º 1 (1 de febrero de 2012): 401–8. http://dx.doi.org/10.18618/rep.2012.1.401408.
Texto completoZhang, Tao, Ningyuan Guo, Xiaoxia Sun, Jie Fan, Naifeng Yang, Junjie Song y Yuan Zou. "A Systematic Framework for State of Charge, State of Health and State of Power Co-Estimation of Lithium-Ion Battery in Electric Vehicles". Sustainability 13, n.º 9 (5 de mayo de 2021): 5166. http://dx.doi.org/10.3390/su13095166.
Texto completoNuroldayeva, Gulzat, Yerkin Serik, Desmond Adair, Berik Uzakbaiuly y Zhumabay Bakenov. "State of Health Estimation Methods for Lithium-Ion Batteries". International Journal of Energy Research 2023 (3 de marzo de 2023): 1–21. http://dx.doi.org/10.1155/2023/4297545.
Texto completoYu, Zhilong, Na Liu, Yekai Zhang, Lihua Qi y Ran Li. "Battery SOH Prediction Based on Multi-Dimensional Health Indicators". Batteries 9, n.º 2 (24 de enero de 2023): 80. http://dx.doi.org/10.3390/batteries9020080.
Texto completoMei, Peng, Hamid Reza Karimi, Fei Chen, Shichun Yang, Cong Huang y Song Qiu. "A Learning-Based Vehicle-Cloud Collaboration Approach for Joint Estimation of State-of-Energy and State-of-Health". Sensors 22, n.º 23 (4 de diciembre de 2022): 9474. http://dx.doi.org/10.3390/s22239474.
Texto completoTesis sobre el tema "Battery state-of-health"
Grube, Ryan J. "Automotive Battery State-of-Health Monitoring Methods". Wright State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=wright1229787557.
Texto completoSöderhielm, Camilla. "Investigation of Battery Parameters for Li-ion Battery State of Health Estimation". Thesis, KTH, Kemiteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299432.
Texto completoEnvironmental concerns associated with greenhouse gas emissions from conventional combustion engines have contributed to a transition towards electric mobility. In this transition, lithium-ion (Li-ion) batteries play an important part as an energy storage system. However, Li-ion batteries can pose a safety risk due to their reactive chemistry. The Swedish Armed Forces are approaching a transition towards electric mobility, therefore, understanding Li-ion battery behavior with regard to non-normal use and ageing is critical for safe military applications. This project aimed to identify and evaluate battery parameters (impedance, resistance, capacity and surface temperature) suitable for State of Health (SOH) estimation of Li-ion batteries in military applications. Furthermore, this project aimed to investigate the ambient temperature’s effect on battery parameters, and identify the battery’s end of life (EOL) based on battery parameter tracking. Commercial NMC/graphite Li-ion batteries were exposed to ageing through repeated charge and discharge cycles. A critical application was mimicked, where the batteries operated at 1C charge rate (4 A) and 2.5C discharge rate (10 A) between 100 % and 0 % state of charge, for up to 250 charge/discharge cycles. The ageing process was tracked through regular measurements of impedance, resistance, capacity and surface temperature. In order to investigate the ambient temperature’s effect on the investigated battery parameters, the batteries were aged at either 52 ± 3 °C, 21 ± 3 °C or −15 ± 3 °C. Impedance measured at 980 Hz was the most stable battery parameter with respect to variations in state of charge and temperature, and was therefore regarded as the most suitable parameter for SOH estimation with respect to flexibility. Measurements of resistance and capacity at given temperatures were likely reflecting electrochemical ageing phenomena more accurately, hence the most suitable battery parameters for SOH estimation with respect to accuracy. Tracking of surface temperature provided insufficient information for accurate estimation of the batteries SOH. Decreasing the ambient temperature from 21 °C to −15 °C had a major effect on capacity and resistance; the resistance increased and the capacity decreased, corresponding to a decrease in battery performance. With respect to capacity fade, neither of the batteries aged at 21 °C reached their EOL within 250 cycles, while batteries aged at 52 °C or −15 °C reached their EOL after 150–200 cycles. With respect to resistance, one battery kept at 21 °C reached their EOL after 200 cycles, all batteries kept at 52 °C reached their EOL after 150–200 cycles, and batteries kept at −15 °C reached their EOL between 200–250 cycles. Finally, with respect to impedance measured at 980 Hz, one battery kept at 21 °C reached their EOL after 200 cycles, one battery kept at 52 °C reached their EOL after 150 cycles, and batteries kept at −15 °C reached their EOL between 200–250 cycles.
Kerley, Ross Andrew. "Automotive Lead-Acid Battery State-of-Health Monitoring System". Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/64870.
Texto completoMaster of Science
Suozzo, Christopher. "Lead-Acid Battery Aging and State of Health Diagnosis". The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1212002134.
Texto completoSamolyk, Mateusz y Jakub Sobczak. "Development of an algorithm for estimating Lead-Acid Battery State of Charge and State of Health". Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2937.
Texto completoI detta papper, är ett laddningstillstånd (SOC) och hälsotillstånd (SOH) skattningsmetod för blybatterier presenteras. I algoritmen mätningarna av batteriets polspänning, ström och temperatur används i processen för SOC beräkning. Avhandlingen är skriven i samarbete med Micropower AB. Algoritmen har utformats för att uppfylla de särskilda kraven för elektriska fordon: ett fel under 5% av SOC, computational enkelhet och möjligheten att genomföras i ett grundläggande programmeringsspråk. Den nuvarande metoden vid Micropower, Coulomb räkning, jämförs med en metod som presenteras av Chiasson och Vairamohan 2005 baserad på modifierad Thevein kretsen under laddning och urladdning av batteriet.
Salyer, Zachary M. "Identification of Optimal Fast Charging Control based on Battery State of Health". The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587037951166857.
Texto completoCordoba, Arenas Andrea Carolina. "Aging Propagation Modeling and State-of-Health Assessment in Advanced Battery Systems". The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385967836.
Texto completoKlass, Verena. "Battery Health Estimation in Electric Vehicles". Doctoral thesis, KTH, Tillämpad elektrokemi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-173544.
Texto completoQC 20150914
Schmidt, Alexander Patrick [Verfasser]. "A Novel Electrochemical Battery Model For State Of Charge And State Of Health Estimation / Alexander Patrick Schmidt". Aachen : Shaker, 2010. http://d-nb.info/1084536315/34.
Texto completoHyun, Ji Hoon. "State of Health Estimation System for Lead-Acid Car Batteries Through Cranking Voltage Monitoring". Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71796.
Texto completoMaster of Science
Capítulos de libros sobre el tema "Battery state-of-health"
Fernandez, Carlos, Ji Wu, Lei Chen, Mingfang He, Peng Yu, Pu Ren, Shunli Wang, Xiao Yang, Siyu Jin y Yangtao Wang. "Battery State of Health Estimation". En Multidimensional Lithium-Ion Battery Status Monitoring, 211–46. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003333791-4.
Texto completoFotouhi, Abbas, Karsten Propp, Daniel J. Auger y Stefano Longo. "State of Charge and State of Health Estimation Over the Battery Lifespan". En Behaviour of Lithium-Ion Batteries in Electric Vehicles, 267–88. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69950-9_11.
Texto completoSingh, Rupam, V. S. Bharath Kurukuru y Mohammed Ali Khan. "Data-Driven Model for State of Health Estimation of Lithium-Ion Battery". En Computational Methods and Data Engineering, 279–93. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7907-3_21.
Texto completoSaqli, K., H. Bouchareb, M. Oudghiri y N. K. M’Sirdi. "Critical Review of Ageing Mechanisms and State of Health Estimation Methods for Battery Performance". En Sustainability in Energy and Buildings, 507–18. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9868-2_43.
Texto completoSun, Bingxiang, Yuzhe Chen, Shichang Ma, Zhengtao Cui y Zhanguo Wang. "Estimating Contrast of State of Health for Lithium-Ion Battery Based on Accumulated Residual Energy". En The Proceedings of the 9th Frontier Academic Forum of Electrical Engineering, 83–96. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6609-1_8.
Texto completoSudhakar Reddy, Mandeddu y M. Monisha. "A Survey on Battery State of Charge and State of Health Estimation Using Machine Learning and Deep Learning Techniques". En Lecture Notes in Networks and Systems, 355–67. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6088-8_31.
Texto completoLi, Fan, Yusheng Wang y Duzhi Wu. "Prognostics for State of Health Estimation of Battery System Under Uncertainty Based on Adaptive Learning Technique". En Advances in Intelligent Systems and Computing, 313–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47241-5_27.
Texto completoSánchez, Luciano, José Otero, Manuela González, David Anseán y Inés Couso. "Online Estimation of the State of Health of a Rechargeable Battery Through Distal Learning of a Fuzzy Model". En Advances in Intelligent Systems and Computing, 68–77. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20055-8_7.
Texto completoWang, Shunli, Yongcun Fan, Daniel-Ioan Stroe, Carlos Fernandez, Chunmei Yu, Wen Cao y Zonghai Chen. "Battery state-of-health estimation methods". En Battery System Modeling, 255–311. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-323-90472-8.00007-x.
Texto completo"Battery State of Health Estimation". En Advanced Battery Management Technologies for Electric Vehicles, 95–130. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119481652.ch4.
Texto completoActas de conferencias sobre el tema "Battery state-of-health"
Bandong, Steven, Muhammad Ihsan y Endra Joelianto. "Chaotic Behavior of Battery State of Health". En 2019 6th International Conference on Electric Vehicular Technology (ICEVT). IEEE, 2019. http://dx.doi.org/10.1109/icevt48285.2019.8993986.
Texto completoZhu, Xuetao, Qiongbin Lin, Shi You, Sixiong Chen y Yiming Hong. "A Review of Battery State of Health Estimation". En 2019 4th International Conference on Intelligent Green Building and Smart Grid (IGBSG). IEEE, 2019. http://dx.doi.org/10.1109/igbsg.2019.8886281.
Texto completoSarikurt, Turev, Murat Ceylan y Abdulkadir Balikci. "An analytical battery state of health estimation method". En 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE). IEEE, 2014. http://dx.doi.org/10.1109/isie.2014.6864855.
Texto completoRamadan, M. Nisvo, Bhisma A. Pramana, Adha Cahyadi y Oyas Wahyunggoro. "State of health estimation in lithium polymer battery". En PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON SYNCHROTRON RADIATION INSTRUMENTATION – SRI2015. Author(s), 2016. http://dx.doi.org/10.1063/1.4958523.
Texto completoTairov, Stanislav y Luiz Carlos Stevanatto. "Impedance measurements for battery state of health monitoring". En 2011 2nd International Conference on Control, Instrumentation, and Automation (ICCIA). IEEE, 2011. http://dx.doi.org/10.1109/icciautom.2011.6356634.
Texto completoHe, Liang, Eugene Kim, Kang G. Shin, Guozhu Meng y Tian He. "Battery state-of-health estimation for mobile devices". En ICCPS '17: ACM/IEEE 8th International Conference on Cyber-Physical Systems. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3055004.3055018.
Texto completoArif, Ameera, Muhammad Hassaan, Mujahid Abdullah, Ahmad Nadeem y Naveed Arshad. "Estimating Battery State of Health using Machine Learning". En 2022 10th International Conference on Smart Grid and Clean Energy Technologies (ICSGCE). IEEE, 2022. http://dx.doi.org/10.1109/icsgce55997.2022.9953596.
Texto completoNatella, D. y F. Vasca. "Battery State of Health Estimation via Reinforcement Learning". En 2021 European Control Conference (ECC). IEEE, 2021. http://dx.doi.org/10.23919/ecc54610.2021.9655199.
Texto completoGuo, Qi, Wei Qu, Haoran Deng, Xueyuan Zhang, Yi Li, Xiaowei Wang y Xiangwu Yan. "Estimation of electric vehicle battery state of health based on relative state of health evaluation". En 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2017. http://dx.doi.org/10.1109/iaeac.2017.8054365.
Texto completoBashash, Saeid y Hosam K. Fathy. "Battery State of Health and Charge Estimation Using Polynomial Chaos Theory". En ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-4088.
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