Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Sulzer, Valentin"'
A data-driven model augmentation framework, referred to as Weakly-coupled Integrated Inference and Machine Learning (IIML), is presented to improve the predictive accuracy of physical models. In contrast to parameter calibration, this work seeks corr
Externí odkaz:
http://arxiv.org/abs/2207.10819
Autor:
Planella, Ferran Brosa, Ai, Weilong, Boyce, Adam M., Ghosh, Abir, Korotkin, Ivan, Sahu, Smita, Sulzer, Valentin, Timms, Robert, Tranter, Thomas G., Zyskin, Maxim, Cooper, Samuel J., Edge, Jacqueline S., Foster, Jamie M., Marinescu, Monica, Wu, Billy, Richardson, Giles
Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus model complex
Externí odkaz:
http://arxiv.org/abs/2203.16091
Autor:
Weng, Andrew, Mohtat, Peyman, Attia, Peter M., Sulzer, Valentin, Lee, Suhak, Less, Greg, Stefanopoulou, Anna
Publikováno v:
Joule, Volume 5, Issue 11, 17 November 2021, Pages 2971-2992
Increasing the speed of battery formation can significantly lower lithium-ion battery manufacturing costs. However, adopting faster formation protocols in practical manufacturing settings is challenging due to a lack of inexpensive, rapid diagnostic
Externí odkaz:
http://arxiv.org/abs/2203.14158
Autor:
Attia, Peter M., Bills, Alexander, Planella, Ferran Brosa, Dechent, Philipp, Reis, Gonçalo dos, Dubarry, Matthieu, Gasper, Paul, Gilchrist, Richard, Greenbank, Samuel, Howey, David, Liu, Ouyang, Khoo, Edwin, Preger, Yuliya, Soni, Abhishek, Sripad, Shashank, Stefanopoulou, Anna G., Sulzer, Valentin
Lithium-ion batteries can last many years but sometimes exhibit rapid, nonlinear degradation that severely limits battery lifetime. In this work, we review prior work on "knees" in lithium-ion battery aging trajectories. We first review definitions f
Externí odkaz:
http://arxiv.org/abs/2201.02891
Autor:
O'Kane, Simon E. J., Ai, Weilong, Madabattula, Ganesh, Alvarez, Diego Alonso, Timms, Robert, Sulzer, Valentin, Edge, Jacqueline Sophie, Wu, Billy, Offer, Gregory J., Marinescu, Monica
Predicting lithium-ion battery degradation is worth billions to the global automotive, aviation and energy storage industries, to improve performance and safety and reduce warranty liabilities. However, very few published models of battery degradatio
Externí odkaz:
http://arxiv.org/abs/2112.02037
Autor:
Bonkile, Mayur P., Jiang, Yang, Kirkaldy, Niall, Sulzer, Valentin, Timms, Robert, Wang, Huizhi, Offer, Gregory, Wu, Billy
Publikováno v:
In Journal of Power Sources 30 June 2024 606
Fast charging of lithium-ion batteries is crucial to increase desirability for consumers and hence accelerate the adoption of electric vehicles. A major barrier to shorter charge times is the accelerated aging of the battery at higher charging rates,
Externí odkaz:
http://arxiv.org/abs/2108.07833
Autor:
Zubov, Kirill, McCarthy, Zoe, Ma, Yingbo, Calisto, Francesco, Pagliarino, Valerio, Azeglio, Simone, Bottero, Luca, Luján, Emmanuel, Sulzer, Valentin, Bharambe, Ashutosh, Vinchhi, Nand, Balakrishnan, Kaushik, Upadhyay, Devesh, Rackauckas, Chris
Physics-informed neural networks (PINNs) are an increasingly powerful way to solve partial differential equations, generate digital twins, and create neural surrogates of physical models. In this manuscript we detail the inner workings of NeuralPDE.j
Externí odkaz:
http://arxiv.org/abs/2107.09443
Autor:
Annevelink, Emil, Kurchin, Rachel, Muckley, Eric, Kavalsky, Lance, Hegde, Vinay I., Sulzer, Valentin, Zhu, Shang, Pu, Jiankun, Farina, David, Johnson, Matthew, Gandhi, Dhairya, Dave, Adarsh, Lin, Hongyi, Edelman, Alan, Ramsundar, Bharath, Saal, James, Rackauckas, Christopher, Shah, Viral, Meredig, Bryce, Viswanathan, Venkatasubramanian
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical materials
Externí odkaz:
http://arxiv.org/abs/2011.04426
Recent data-driven approaches have shown great potential in early prediction of battery cycle life by utilizing features from the discharge voltage curve. However, these studies caution that data-driven approaches must be combined with specific desig
Externí odkaz:
http://arxiv.org/abs/2010.07460