Listar por autor "64bfd9ba43b483c7c2345af46a09bc6e"
Mostrando ítems 1-13 de 13
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Bridging the Gap between ECMs and PBMs: Electrode-level Extended ECM
Fernandez Gonzalez, Sergio; Lopetegi Tapia, Iker; IRAOLA, UNAI (2025)Accurate and efficient Li-ion battery models are essential for control, diagnostics, and system-level integration. While physics-based models (PBMs) offer detailed electrochemical insight, they are often too complex for ... -
A critical look at efficient parameter estimation methodologies of electrochemical models for Lithium-Ion cells
Rojas Garcia, Clara; Oca, Laura; Lopetegi Tapia, Iker; IRAOLA, UNAI; Carrasco, Javier (Elsevier, 2024)Physics-Based Models (PBMs) offer a promising approach to develop advanced battery management systems that rely on information about the internal states of battery cells. The reliability of model predictions heavily depends ... -
Electrochemical Model and Sigma Point Kalman Filter Based Online Oriented Battery Model
Miguel, Eduardo; Lopetegi Tapia, Iker; Oca, Laura; IRAOLA, UNAI (IEEE, 2021)This paper presents a reduced-order electrochemical battery model designed for online implementation of battery control systems. This model is based on porous-electrode and concentratedsolution theory frameworks and is ... -
Electrode State of Charge and State of Health Estimation with Electrode-Level Equivalent-Circuit Models
Lopetegi Tapia, Iker; Fernandez Gonzalez, Sergio; Plett, Gregory L.; Trimboli, M. Scott; IRAOLA, UNAI (IOP Publishing, 2025)To prolong battery lifetime and maximize performance, battery management systems (BMSs) need to estimate internal variables that are related to battery aging. For that, accurate battery models that can represent internal ... -
Elucidating the role of particle radius and active material diffusivity in metal-ion batteries
Oca, Laura; Arcelus, O.; Fernandez Gonzalez, Sergio; Lopetegi Tapia, Iker; Gucciardi, E.; Herran, A. (2025)The impact of particle size distribution and shape in metal-ion batteries has been widely reported1. For the same active material properties (active material diffusivity, open circuit potential etc.) the use of smaller ... -
Intuitive Degradation Mode Estimation Tool: ModEst
Fernandez Gonzalez, Sergio; Lopetegi Tapia, Iker; Oca, Laura; Yeregui, Josu; GARAYALDE, ERIK; IRAOLA, UNAI (IEEE, 2024)Battery ageing is one of the main concerns in most battery applications. To reduce this degradation rate, it is key to understand how batteries age. However, the diagnosis of battery ageing is very challenging due to the ... -
Lithium-ion Battery Aging Prediction with Electrochemical Models: P2D vs SPMe
Lopetegi Tapia, Iker; Yeregui, Josu; Oca, Laura; Rojas Garcia, Clara; IRAOLA, UNAI (IEEE, 2023)Battery aging models are essential tools when predicting how much a battery will age under certain working conditions, which is key when sizing a battery pack and controlling its operation. Nowadays, mostly empirical battery ... -
ModEst: battery degradation mode estimation tool
Lopetegi Tapia, Iker; Oca, Laura; Fernandez Gonzalez, Sergio (2024)The software itself is a tool capable of estimating Li-ion battery degradation modes. Battery degradation modes group different battery degradation mechanism into three main degradation modes: Loss of Active Material (LAM) ... -
Modular Battery Energy Storage Systems for Available Energy Increase
Dorronsoro, Xabier; Lopetegi Tapia, Iker; GARAYALDE, ERIK; IRAOLA, UNAI; Yeregui, Josu (IEEE, 2022)The aim of this work is to dive into the available energy of different configurations of battery packs, a vital factor when it comes to improving the driving range of electric vehicles. To that end, two different storage ... -
Modular BESS architecture for enhanced performance and extended lifetime
Aizpurua, Manex; GARAYALDE, ERIK; Lopetegi Tapia, Iker; Yeregui, Josu; Dorronsoro, Xabier; IRAOLA, UNAI (IEEE, 2024)This paper evaluates and compares the performances of non-modular and modular battery systems. The modular architecture consists of several battery modules that are individually controlled by means of their corresponding ... -
A New Battery SOC/SOH/eSOH Estimation Method Using a PBM and Interconnected SPKFs: Part I. SOC and Internal Variable Estimation
Lopetegi Tapia, Iker; Oca, Laura; IRAOLA, UNAI (IOP Publishing, 2024)Battery management systems (BMSs) are required to estimate many non-measurable values that describe the actual operating condition of batteries; such as the state of charge (SOC) or the state of health (SOH). In order to ... -
A New Battery SOC/SOH/eSOH Estimation Method Using a PBM and Interconnected SPKFs: Part II. SOH and eSOH Estimation
Lopetegi Tapia, Iker; Oca, Laura; IRAOLA, UNAI (IOP Publishing, 2024)Battery management systems (BMSs) are required to estimate many non-measurable values that describe the actual operating condition of batteries; such as state of charge (SOC) or state of health (SOH). In order to improve ... -
State of charge estimation combining physics-based and artificial intelligence models for Lithium-ion batteries
Yeregui, Josu; Oca, Laura; Lopetegi Tapia, Iker; GARAYALDE, ERIK; Aizpurua, Manex; IRAOLA, UNAI (Elsevier, 2023)This paper presents a sequential model based on Physic Based Models (PBM) and Artificial Intelligence Models (AI) focused on the estimation of the State of Charge (SoC). The PBM can provide interesting information about ...
