Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation

ArXi:2605.29560v1 Announce Type: new Parameterizing high-fidelity "digital twins" of batteries is a critical yet challenging inverse problem that hinders the pace of battery innovation. Prevailing methods formulate this as a black-box optimization (BBO) task, employing algorithms that are sample-inefficient and blind to the underlying physics. In this work, we