Publicaciones en las que colabora con DAVID ANSEAN GONZALEZ (15)

2024

  1. ICFormer: A Deep Learning model for informed lithium-ion battery diagnosis and early knee detection

    Journal of Power Sources, Vol. 592

2023

  1. Characterization of a commercial Nickel-Rich/Silicon-Graphite battery, under long term static and dynamic cycling

    Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023

  2. Learning remaining useful life with incomplete health information: A case study on battery deterioration assessment

    Array, Vol. 20

2022

  1. Distal learning of the incremental capacity curve of a LiFePO4battery

    Logic Journal of the IGPL, Vol. 30, Núm. 2, pp. 301-313

  2. Informed Weak Supervision for Battery Deterioration Level Labeling

    Communications in Computer and Information Science

  3. Li-ion battery degradation modes diagnosis via Convolutional Neural Networks

    Journal of Energy Storage, Vol. 55

2020

  1. Fast charging protocols based on pulse-modulation with varying relaxation for electric vehicle li-ion cells

    2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings

  2. Health Monitoring of Automotive Batteries in Fast-Charging Conditions Through a Fuzzy Model of the Incremental Capacity

    Studies in Computational Intelligence (Springer), pp. 155-164

  3. Health assessment of LFP automotive batteries using a fractional-order neural network

    Neurocomputing, Vol. 391, pp. 345-354

  4. Online Estimation of the State of Health of a Rechargeable Battery Through Distal Learning of a Fuzzy Model

    Advances in Intelligent Systems and Computing

2019

  1. Lithium-Ion Battery Degradation Indicators Via Incremental Capacity Analysis

    IEEE Transactions on Industry Applications, Vol. 55, Núm. 3, pp. 2992-3002

  2. Using Fuzzy Preference Orderings in θ-Dominance with Application to Health Monitoring of Li-Ion Batteries

    Journal of Multiple-Valued Logic and Soft Computing, Vol. 32, Núm. 3-4, pp. 343-367

2018

  1. Assessing the health of LiFePo4 traction batteries through monotonic echo state networks

    Sensors (Switzerland), Vol. 18, Núm. 1

  2. Health assessment of automotive batteries through computational intelligence-based soft sensors: An empirical study

    Advances in Intelligent Systems and Computing

2017

  1. A Model-Based Virtual Sensor for Condition Monitoring of Li-Ion Batteries in Cyber-Physical Vehicle Systems

    Journal of Sensors, Vol. 2017