Battery-Sim-Agent reframes inverse battery parameter estimation as an LLM reasoning task in closed loop with a simulator and outperforms Bayesian optimization baselines on diverse benchmarks.
Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models
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A homogenized model derived from Poisson-Nernst-Planck equations with 3D state reconstruction enables PID-based fast charging of Li-ion batteries while keeping anode potentials above the lithium plating threshold.
A P2D electrochemical-thermal-degradation model with consistent parameterization predicts capacity fade trajectories and internal modes for NMC cells across calendar and combined ageing conditions, showing sub-linear to accelerated fade depending on usage.
A computational framework integrates the Doyle-Fuller-Newman electrochemical model with a 3D distributed equivalent circuit network model to simulate Li-ion battery discharge more accurately than lumped models at low temperatures or high rates.
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Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation
Battery-Sim-Agent reframes inverse battery parameter estimation as an LLM reasoning task in closed loop with a simulator and outperforms Bayesian optimization baselines on diverse benchmarks.