43 citations · 195 across the 20 of their papers we have counts for
6 papers · 1 filter
Bayesian Analysis of Interpretable Aging across Thousands of Lithium-ion Battery Cycles
Marc D. Berliner, Minsu Kim, Xiao Cui +5
The Doyle-Fuller-Newman (DFN) model is a common mechanistic model for lithium-ion batteries. The reaction rate constant and diffusivity within the DFN model are key parameters that…
Diagnostic-free onboard battery health assessment
Yunhong Che, Vivek N. Lam, Jinwook Rhyu +5
Diverse usage patterns induce complex and variable aging behaviors in lithium-ion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are of…
Safe Learning-Based Optimization of Model Predictive Control: Application to Battery Fast-Charging
Sebastian Hirt, Andreas Höhl, Johannes Pohlodek +4
Model predictive control (MPC) is a powerful tool for controlling complex nonlinear systems under constraints, but often struggles with model uncertainties and the design of suitab…
Accounting for the Effects of Probabilistic Uncertainty During Fast Charging of Lithium-ion Batteries
Minsu Kim, Joachim Schaeffer, Marc D. Berliner +3
Batteries are nonlinear dynamical systems that can be modeled by Porous Electrode Theory models. The aim of optimal fast charging is to reduce the charging time while keeping batte…
Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging
Sebastian Hirt, Andreas Höhl, Joachim Schaeffer +3
Tuning parameters in model predictive control (MPC) presents significant challenges, particularly when there is a notable discrepancy between the controller's predictions and the a…
Cycle Life Prediction for Lithium-ion Batteries: Machine Learning and More
Joachim Schaeffer, Giacomo Galuppini, Jinwook Rhyu +4
Batteries are dynamic systems with complicated nonlinear aging, highly dependent on cell design, chemistry, manufacturing, and operational conditions. Prediction of battery cycle l…