376 citations · 437 across the 11 of their papers we have counts for
11 papers
Phantom LAM and LLI: Resistance and Hysteresis Bias in Voltage-Curve Degradation Mode Analysis
Mohammed Asheruddin N, Matheus Leal De Souza, Thomas Holland +3
Degradation mode analysis (DMA) is widely used to decompose capacity fade into loss of lithium inventory (LLI) and loss of active material (LAM) from low-rate voltage-capacity data…
Lithium-ion battery degradation: Introducing the concept of reservoirs to design for lifetime
Mohammed Asheruddin Nazeeruddin, Ruihe Li, Simon E. J. OKane +2
Designing lithium-ion batteries for long service life remains a challenge, as most cells are optimized for beginning-of-life metrics such as energy density, often overlooking how d…
Merging Physics-Based Synthetic Data and Machine Learning for Thermal Monitoring of Lithium-ion Batteries: The Role of Data Fidelity
Yusheng Zheng, Wenxue Liu, Yunhong Che +6
Since the internal temperature is less accessible than surface temperature, there is an urgent need to develop accurate and real-time estimation algorithms for better thermal manag…
Mapping safety transitions as batteries degrade: A model-based analysis towards full-lifespan battery safety management
Xinlei Gao, Ruihe Li, Gregory J. Offer +1
Battery safety is important, yet safety limits are normally static and do not evolve as batteries degrade. Consequently, many battery systems are overengineered to meet increasingl…
Lithium-ion battery performance model including solvent segregation effects
Ruihe Li, Simon O'Kane, Andrew Wang +5
A model of a lithium-ion battery containing a cosolvent electrolyte is developed and implemented within the open-source PyBaMM platform. Lithium-ion electrolytes are essential to b…
Lithium-ion battery degradation: using degradation mode analysis to validate lifetime prediction modelling
Ruihe Li, Niall D. Kirkaldy, Fabian Oehler +3
Predicting lithium-ion battery lifetime is one of the greatest unsolved problems in battery research right now. Recent years have witnessed a surge in lifetime prediction papers us…
A million cycles in a day: enabling high-throughput computing of lithium-ion battery degradation with physics-based models
Ruihe Li, Simon O'Kane, Jianbo Huang +2
High-throughput computing (HTC) is a pivotal asset in many scientific fields, such as biology, material science and machine learning. Applying HTC to the complex physics-based degr…
A Computational Framework Integrating Physics-based Model and Equivalent Circuit Network Model to Simulate Li-ion Batteries
Han Yuan, Shen Li, Tao Zhu +4
Battery models generally fall into two categories: physics-based models and ECM models. Physics-based Doyle-Fuller-Newman (DFN) models can accurately simulate the battery internal…
Diffusion-aware voltage source: An equivalent circuit network to resolve lithium concentration gradients in active particles
Mingzhao Zhuo, Niall Kirkaldy, Tom Maull +3
Traditional equivalent circuit models (ECMs) have difficulties in estimating battery internal states due to the lack of relevant physics, such as the lithium diffusion in active pa…
Degradation model of high-nickel positive electrodes: Effects of loss of active material and cyclable lithium on capacity fade
Mingzhao Zhuo, Gregory Offer, Monica Marinescu
Nickel-rich layered oxides have been widely used as positive electrode materials for high-energy-density lithium-ion batteries, but their degradation has severely affected cell per…
Lithium-ion battery degradation: how to model it
Simon E. J. O'Kane, Weilong Ai, Ganesh Madabattula +7
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…