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Pumpkin seeds as an eco-friendly corrosion inhibitor for 7075-T6 alloy in 3.5% NaCl solution: electrochemical, surface and computational studies. (2021)
Journal Article
RADI, M., MELIAN, R., GALAI, M., DKHIRCHE, N., MAKHA, M., VERMA, C., FERNANDEZ, C. and EBN TOUHAMI, M. 2021. Pumpkin seeds as an eco-friendly corrosion inhibitor for 7075-T6 alloy in 3.5% NaCl solution: electrochemical, surface and computational studies. Journal of molecular liquids [online], 337, article 116547. Available from: https://doi.org/10.1016/j.molliq.2021.116547

For the aeronautics industry, constraints of mechanical strength are paramount. Aluminum and its alloys are widely used for various household and industrial applications. Among the various established and identified aluminum alloys, 7075 alloy, which... Read More about Pumpkin seeds as an eco-friendly corrosion inhibitor for 7075-T6 alloy in 3.5% NaCl solution: electrochemical, surface and computational studies..

Improved splice‐electrochemical circuit polarization modeling and optimized dynamic functional multi‐innovation least square parameter identification for lithium‐ion batteries. (2021)
Journal Article
SHI, H., WANG, S., FERNANDEZ, C., YU, C., FAN, Y. and CAO, W. 2021. Improved splice-electrochemical circuit polarization modeling and optimized dynamic functional multi-innovation least square parameter identification for lithium-ion batteries. International journal of energy research [online], 45(10), pages 15323-15337. Available from: https://doi.org/10.1002/er.6807

The internal nonlinearity of the lithium-ion battery makes its mathematical modeling a big challenge. In this paper, a novel lithium-ion battery splice-electrochemical circuit polarization (S-ECP) model is proposed, which integrates the strengths of... Read More about Improved splice‐electrochemical circuit polarization modeling and optimized dynamic functional multi‐innovation least square parameter identification for lithium‐ion batteries..

A novel combined estimation method of online full-parameter identification and adaptive unscented particle filter for Li-ion batteries SOC based on fractional-order modeling. (2021)
Journal Article
CHEN, L., WANG, S., JIANG, H., FERNANDEZ, C. and XIONG, X. 2021. A novel combined estimation method of online full-parameter identification and adaptive unscented particle filter for Li-ion batteries SOC based on fractional-order modeling. International journal of energy research [online], 45(10), pages 15481-15494. Available from: https://doi.org/10.1002/er.6817

Accurate estimation of the state of charge (SOC) of Li-ion battery can ensure the reliability of the storage system. A combined estimator of online full-parameter identification and adaptive unscented particle filter for Li-ion battery SOC based on a... Read More about A novel combined estimation method of online full-parameter identification and adaptive unscented particle filter for Li-ion batteries SOC based on fractional-order modeling..

A novel high-fidelity unscented particle filtering method for the accurate state of charge estimation of lithium-ion batteries. (2021)
Journal Article
XIE, Y., WANG, S., FERNANDEZ, C., YU, C., FAN, Y. and CAO, W. 2021. A novel high-fidelity unscented particle filtering method for the accurate state of charge estimation of lithium-ion batteries. International journal of electrochemical science [online], 16(6), article ID 210623. Available from: https://doi.org/10.20964/2021.06.38

Power Li-ion batteries are one of the core "three powers" systems of new energy vehicles, and its accurate batteries modeling and state prediction have become the core technology of the scientific and technological progress in the industry. This pape... Read More about A novel high-fidelity unscented particle filtering method for the accurate state of charge estimation of lithium-ion batteries..

Novel feedback-Bayesian BP neural network combined with extended Kalman filtering for the battery state-of-charge estimation. (2021)
Journal Article
ZHANG, Y., WANG, S., XU, W., FERNANDEZ, C. and FAN, Y. 2021. Novel feedback-Bayesian BP neural network combined with extended Kalman filtering for the battery state-of-charge estimation. International journal of electrochemical science [online], 16(6), article ID 210624. Available from: https://doi.org/10.20964/2021.06.40

The state of charge estimation of lithium-ion batteries plays an important role in real-time monitoring and safety. To solve the problem that high non-linearity during real-time estimation of lithium-ion batteries who cause that it is dif... Read More about Novel feedback-Bayesian BP neural network combined with extended Kalman filtering for the battery state-of-charge estimation..

A novel autoregressive rainflow-integrated moving average modeling method for the accurate state of health prediction of lithium-ion batteries. (2021)
Journal Article
HUANG, J., WANG, S., XU, W., SHI, W. and FERNANDEZ, C. 2021. A novel autoregressive rainflow-integrated moving average modeling method for the accurate state of health prediction of lithium-ion batteries. Processes [online], 9(5), article 795. Available from: https://doi.org/10.3390/pr9050795

The accurate estimation and prediction of lithium-ion battery state of health are one of the important core technologies of the battery management system, and are also the key to extending battery life. However, it is difficult to track state of heal... Read More about A novel autoregressive rainflow-integrated moving average modeling method for the accurate state of health prediction of lithium-ion batteries..

A novel adaptive function-dual Kalman filtering strategy for online battery model parameters and state of charge co-estimation. (2021)
Journal Article
FAN, Y., SHI, H., WANG, S., FERNANDEZ, C., CAO, W. and HUANG, J. 2021. A novel adaptive function-dual Kalman filtering strategy for online battery model parameters and state of charge co-estimation. Energies [online], 14(8), article 2268. Available from: https://doi.org/10.3390/en14082268

This paper aims to improve the stability and robustness of the state-of-charge estimation algorithm for lithium-ion batteries. A new internal resistance-polarization circuit model is constructed on the basis of the Thevenin equivalent circuit to char... Read More about A novel adaptive function-dual Kalman filtering strategy for online battery model parameters and state of charge co-estimation..

A novel adaptive dual extended Kalman filtering algorithm for the Li‐ion battery state of charge and state of health co‐estimation. (2021)
Journal Article
XU, W., WANG, S., JIANG, C., FERNANDEZ, C., YU, C., FAN, Y. and CAO, W. 2021. A novel adaptive dual extended Kalman filtering algorithm for the Li-ion battery state of charge and state of health co-estimation. International journal of energy research [online], 45(10), pages 14592-14602. Available from: https://doi.org/10.1002/er.6719

Accurate prediction of the state of health (SOH) of Li-ion battery has an important role in the estimation of battery state of charge (SOC), which can not only improve the efficiency of battery usage but also ensure its safety performance. The batter... Read More about A novel adaptive dual extended Kalman filtering algorithm for the Li‐ion battery state of charge and state of health co‐estimation..

Challenges and progresses of lithium-metal batteries. (2021)
Journal Article
WANG, J., GE, B., YANG, M., WANG, J., LIU, D., FERNANDEZ, C., CHEN, X. and PENG, Q. 2021. Challenges and progresses of lithium-metal batteries. Chemical engineering journal [online], 420(1), article 129739. Available from: https://doi.org/10.1016/j.cej.2021.129739

Lithium-metal batteries (LMBs) have received considerable enthusiasm as the candidates for next-generation high energy density storage devices. However, the unexpected electrochemical deposition of metallic Li on the surface of anode has been conside... Read More about Challenges and progresses of lithium-metal batteries..

A novel adaptive particle swarm optimization algorithm based high precision parameter identification and state estimation of lithium-ion battery. (2021)
Journal Article
HE, M., WANG, S., FERNANDEZ, C., YU, C., LI, X. and BOBOBEE, E.D. 2021. A novel adaptive particle swarm optimization algorithm based high precision parameter identification and state estimation of lithium-ion battery. International journal of electrochemical science [online], 16(5), article 21054. Available from: https://doi.org/10.20964/2021.05.55

Lithium-ion batteries are widely used in new energy vehicles, energy storage systems, aerospace and other fields because of their high energy density, long cycle life and high-cost performance. Accurate equivalent modeling, adaptive internal state ch... Read More about A novel adaptive particle swarm optimization algorithm based high precision parameter identification and state estimation of lithium-ion battery..