All Outputs (333)

Improved back-propagation neural network-multi-information gain optimization Kalman filter method for high-precision estimation of state-of-energy in lithium-ion batteries. (2025)
Journal Article
SHI, H., WU, Q., WANG, S., CAO, W., LI, Y., FERNANDEZ, C. and HUANG, Q. 2025. Improved back-propagation neural network-multi-information gain optimization Kalman filter method for high-precision estimation of state-of-energy in lithium-ion batteries. Energy [online], In Press. Available from: https://doi.org/10.1016/j.energy.2025.138214

The accurate estimation of the state-of-energy (SOE) is crucial for extending battery life and improving the performance of electric vehicles. To address the issue of low estimation accuracy of SOE in lithium-ion batteries, a back-propagation neural... Read More about Improved back-propagation neural network-multi-information gain optimization Kalman filter method for high-precision estimation of state-of-energy in lithium-ion batteries..

Synthesis of substituted triazines and evaluation of their corrosion inhibition performance on Fe(100) in 1 M HCl: a combined experimental and DFT study. (2025)
Journal Article
TSHIKHUDO, F., MUGWENA, D.S., MNYAKENI-MOLEELE, S.S., KABANDA, M.M., FERNANDEZ, C. and MURULANA, L.C. 2025. Synthesis of substituted triazines and evaluation of their corrosion inhibition performance on Fe(100) in 1 M HCl: a combined experimental and DFT study. International journal of electrochemical science [online], 20(10), article number 101153. Available from: https://doi.org/10.1016/j.ijoes.2025.101153

This study aimed to evaluate the effectiveness of synthesized substituted triazine, namely 4,6-dichloro-2-morpholine-1,3,5-triazine (DMT), 4,6-dichloro-2-anilino-1,3,5-triazine (DPT), and 4,6-dichloro-N-methylanilino-1,3,5-triazine (DNT), in inhibiti... Read More about Synthesis of substituted triazines and evaluation of their corrosion inhibition performance on Fe(100) in 1 M HCl: a combined experimental and DFT study..

A novel extended Kalman filter-guided long short-term memory algorithm for power lithium-ion battery state of charge estimation at multiple temperatures. (2025)
Journal Article
LIU, D., WANG, S., LI, X., FAN, Y., FERNANDEZ, C. and BLAABJERG, F. 2025. A novel extended Kalman filter-guided long short-term memory algorithm for power lithium-ion battery state of charge estimation at multiple temperatures. Energy [online], 335, article 137973. Available from: https://doi.org/10.1016/j.energy.2025.137973

The power lithium-ion battery's state of charge (SOC) is critical for electric vehicles. However, current neural network-based SOC estimation algorithms fail to consider the effects of feature enhancement in reducing the network training time and imp... Read More about A novel extended Kalman filter-guided long short-term memory algorithm for power lithium-ion battery state of charge estimation at multiple temperatures..

A multi-layer kernel extreme learning machine model based on the fusion algorithm for the remaining useful life prediction of lithium-ion batteries. (2025)
Journal Article
CHEN, L., BAI, L., WEI, X., LI, Y. and FERNANDEZ, C. [2025]. A multi-layer kernel extreme learning machine model based on the fusion algorithm for the remaining useful life prediction of lithium-ion batteries. Ionics [online], Latest Articles. Available from: https://doi.org/10.1007/s11581-025-06597-3

The remaining useful life (RUL) of lithium-ion batteries is a key parameter of battery management systems, and accurate prediction is an important guarantee for the stable and efficient operation of new energy vehicles. A fusion algorithm based on a... Read More about A multi-layer kernel extreme learning machine model based on the fusion algorithm for the remaining useful life prediction of lithium-ion batteries..

Improved dynamic discount function identification strategy for adaptive current transients and capturing complex carrier behavior inside lithium-ion batteries. (2025)
Journal Article
LIN, R., SHI, H., WANG, S., YU, C., NIE, S., FERNANDEZ, C. and KAZMI, M.M. 2025. Improved dynamic discount function identification strategy for adaptive current transients and capturing complex carrier behavior inside lithium-ion batteries. Journal of The Electrochemical Society [online], 172(7), article number 070527. Available from: https://doi.org/10.1149/1945-7111/adeece

In the application of lithium-ion batteries, instantaneous changes in the magnitude and direction of the current cause distortion during online parameter identification, resulting in increased instability and errors. To address this problem, this pap... Read More about Improved dynamic discount function identification strategy for adaptive current transients and capturing complex carrier behavior inside lithium-ion batteries..

Improved hybrid neural network based on CNN-BiLSTM-attention for co-estimation of SOC and SOE in lithium-ion batteries. (2025)
Journal Article
LUO, T., SHI, H., LI, K., LI, H., WANG, S., YU, C. and FERNANDEZ, C. 2025. Improved hybrid neural network based on CNN-BiLSTM-attention for co-estimation of SOC and SOE in lithium-ion batteries. Journal of energy storage [online], 131(Part B), article number 117651. Available from: https://doi.org/10.1016/j.est.2025.117651

As the core of modern energy storage technology, lithium-ion batteries are widely used in fields such as electric vehicles, renewable energy storage, and portable electronic devices. Accurately estimating the state-of-charge (SOC) and state-of-energy... Read More about Improved hybrid neural network based on CNN-BiLSTM-attention for co-estimation of SOC and SOE in lithium-ion batteries..

A hybrid squeeze excitation gate recurrent unit-autoregressive integrated moving average model for long-term state of health estimation of lithium-ion batteries with adaptive enhancement ability. (2025)
Journal Article
WU, W., WANG, S., FAN, Y., LIU, D., LONG, G. and FERNANDEZ, C. 2025. A hybrid squeeze excitation gate recurrent unit-autoregressive integrated moving average model for long-term state of health estimation of lithium-ion batteries with adaptive enhancement ability. Journal of energy storage [online], 131(part B), article number 117600. Available from: https://doi.org/10.1016/j.est.2025.117600

The accurate estimation of the state of health (SOH) of lithium-ion batteries is crucial for ensuring their safe operation and effective management. Since the data acquired from the lithium-ion battery aging experiment is abundant in electrochemical... Read More about A hybrid squeeze excitation gate recurrent unit-autoregressive integrated moving average model for long-term state of health estimation of lithium-ion batteries with adaptive enhancement ability..

Boron-doped hexagonal boridene-derived sulfides unlock high reversible capacity for rechargeable magnesium batteries. (2025)
Journal Article
WU, F., YANG, W., WANG, Y., GAO, W., LIU, D., WANG, P., SUN, Y., LIU, S., ZOU, G., WANG, J., FERNANDEZ, C. and PENG, Q. [2025]. Boron-doped hexagonal boridene-derived sulfides unlock high reversible capacity for rechargeable magnesium batteries. Advanced functional materials [online], Early View, article number e10635. Available from: https://doi.org/10.1002/adfm.202510635

Rechargeable magnesium batteries (RMBs) are emerging as compelling alternatives for next-generation high-energy-density storage systems, owing to magnesium's abundance, safety, and high volumetric capacity. However, the divalent nature of magnesium i... Read More about Boron-doped hexagonal boridene-derived sulfides unlock high reversible capacity for rechargeable magnesium batteries..

Adversarial multi-source domain generalization approach for power prediction in unknown photovoltaic systems. (2025)
Journal Article
LIU, S., QI, Y., LI, D., LIU, L., WANG, S., FERNANDEZ, C. and GAO, X. 2025. Adversarial multi-source domain generalization approach for power prediction in unknown photovoltaic systems. Applied soft computing [online], 181, article number 113495. Available from: https://doi.org/10.1016/j.asoc.2025.113495

Accurate forecasting of power output for previously unseen photovoltaic installations is of critical importance to the reliability and efficiency of renewable-energy management systems. Existing data-driven PV prediction techniques rely primarily on... Read More about Adversarial multi-source domain generalization approach for power prediction in unknown photovoltaic systems..

Enhanced quantile regression long short-term memory hybrid neural network for the state of charge point and interval estimation of lithium-ion batteries. (2025)
Journal Article
ZOU, Y., WANG, S., HAI, N., BLAABJERG, F., FERNANDEZ, C. and CAO, W. 2025. Enhanced quantile regression long short-term memory hybrid neural network for the state of charge point and interval estimation of lithium-ion batteries. Energy [online], 332, article number137201. Available from: https://doi.org/10.1016/j.energy.2025.137201

The state of charge (SOC) estimation accuracy of lithium-ion batteries directly affects the reliability and management efficiency of clean energy storage systems. However, due to the nonlinear characteristics of batteries and complex working conditio... Read More about Enhanced quantile regression long short-term memory hybrid neural network for the state of charge point and interval estimation of lithium-ion batteries..

Improved adaptive fusion parameter identification and chaotic gravitational search-Kalman particle filtering method for state-of-energy accurate estimation of lithium-ion batteries. (2025)
Journal Article
WANG, C., WANG, S., ZHANG, G., CHEN, L., SHI, H., LIN, R. and FERNANDEZ, C. 2025. Improved adaptive fusion parameter identification and chaotic gravitational search-Kalman particle filtering method for state-of-energy accurate estimation of lithium-ion batteries. Journal of power sources [online], 650, article number 237495. Available from: https://doi.org/10.1016/j.jpowsour.2025.237495

State-of-energy (SOE) is an important parameter in the battery management system, which determines the current maximum possible range of electric vehicles. In this study, an improved chaotic gravitational search-Kalman particle filtering method for S... Read More about Improved adaptive fusion parameter identification and chaotic gravitational search-Kalman particle filtering method for state-of-energy accurate estimation of lithium-ion batteries..

Improved hyperparameter Bayesian optimization-bidirectional long short-term memory optimization for high-precision battery state of charge estimation. (2025)
Journal Article
WANG, S., MA, C., GAO, H., DENG, D., FERNANDEZ, C. and BLAABJERG, F. 2025. Improved hyperparameter Bayesian optimization-bidirectional long short-term memory optimization for high-precision battery state of charge estimation. Energy [online], 328, article number 136598. Available from: https://doi.org/10.1016/j.energy.2025.136598

At a time when new energy sources are constantly developing, mitigating the safety hazards of lithium batteries and prolonging their lifespan. In this paper, we take a ternary lithium-ion battery as an experimental object and carry out research based... Read More about Improved hyperparameter Bayesian optimization-bidirectional long short-term memory optimization for high-precision battery state of charge estimation..

An improved transformer-GRU neural model optimized by polar light optimizer for SOC estimation of lithium-ion batteries under complex operating conditions. (2025)
Journal Article
SHU, X., SHI, H., ZOU, Y., CAO, W. and FERNANDEZ, C. [2025]. An improved transformer-GRU neural model optimized by polar light optimizer for SOC estimation of lithium-ion batteries under complex operating conditions. Ionics [online], Online First. Available from: https://doi.org/10.1007/s11581-025-06353-7

Estimating the battery's state-of-charge (SOC) is essential for determining how safe electric cars are and their remaining range. An SOC estimation technique for lithium-ion batteries based on the Transformer architecture is presented in this paper.... Read More about An improved transformer-GRU neural model optimized by polar light optimizer for SOC estimation of lithium-ion batteries under complex operating conditions..

Deep learning framework designed for high-performance lithium-ion batteries state monitoring. (2025)
Journal Article
TAKYI-ANINAKWA, P., WANG, S., LIU, G., FERNANDEZ, C., KANG, W. and SONG, Y. 2025. Deep learning framework designed for high-performance lithium-ion batteries state monitoring. Renewable and sustainable energy reviews [online], 218, article number 115803. Available from: https://doi.org/10.1016/j.rser.2025.115803

Accurate state of charge (SOC) estimation is crucial for ensuring the safety of batteries, especially in real-time battery management system (BMS) applications. Deep learning methods have become increasingly popular, driving significant advancements... Read More about Deep learning framework designed for high-performance lithium-ion batteries state monitoring..

An improved bidirectional long short-term memory hybrid neural network with Gaussian filtering for multi-temperature state of charge estimation of lithium-ion batteries. (2025)
Journal Article
LIU, Q., SHI, H., ZOU, Y., CAO, W. and FERNANDEZ, C. 2025. An improved bidirectional long short-term memory hybrid neural network with Gaussian filtering for multi-temperature state of charge estimation of lithium-ion batteries. Ionics [online], Latest Articles. Available from: https://doi.org/10.1007/s11581-025-06343-9

The new energy revolution is fundamentally reshaping the global energy structure. Power lithium batteries face issues such as charge-discharge imbalance and limited endurance. To enhance the performance and economic efficiency of power lithium batter... Read More about An improved bidirectional long short-term memory hybrid neural network with Gaussian filtering for multi-temperature state of charge estimation of lithium-ion batteries..

A novel multi–input–multi–output–fuzzy uncoupling model parameter identification strategy for the online state of charge estimation of high-power lithium-ion batteries. (2025)
Journal Article
LIU, D., LI, X., WANG, S., FAN, Y. and FERNANDEZ, C. [2025]. A novel multi–input–multi–output–fuzzy uncoupling model parameter identification strategy for the online state of charge estimation of high-power lithium-ion batteries. Ionics [online], Online First. Available from: https://doi.org/10.1007/s11581-025-06330-0

Due to the strong nonlinear characteristics of multi-state coupling of physical fields such as different charge states and discharge rates in lithium-ion batteries, it poses a great challenge for the parameter identification of the model and the esti... Read More about A novel multi–input–multi–output–fuzzy uncoupling model parameter identification strategy for the online state of charge estimation of high-power lithium-ion batteries..

An improved pelican optimization-kernel extreme learning machine for highly accurate state of charge estimation of lithium-ion batteries in energy storage systems. (2025)
Journal Article
LI, S., WANG, S., CAO, W., ZHANG, L. and FERNANDEZ, C. [2025]. An improved pelican optimization-kernel extreme learning machine for highly accurate state of charge estimation of lithium-ion batteries in energy storage systems. Ionics [online], Online First. Available from: https://doi.org/10.1007/s11581-025-06327-9

The accurate estimation of the state of charge (SOC) of lithium-ion batteries is crucial for real-time monitoring and safety control. This paper proposes a novel method for estimating SOC by optimizing the kernel extreme learning machine (KELM) with... Read More about An improved pelican optimization-kernel extreme learning machine for highly accurate state of charge estimation of lithium-ion batteries in energy storage systems..

Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. (2025)
Journal Article
ZHOU, L., SUN, Y., ZOU, G., HU, H., ZHANG, Y., SU, H., ZHENG, S., ZHU, Y., CHEN, P., FERNANDEZ, C. and PENG, Q. 2025. Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. Journal of materials science and technology [online], 237, pages 298-311. Available from: https://doi.org/10.1016/j.jmst.2025.01.082

Conventional manufacturing approaches, including casting, thermal deformation and annealing, have faced great challenges in achieving both exceptional strength and ductility for Mg alloys. Herein, we report an effective strategy for simultaneously en... Read More about Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys..

Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. [Video] (2025)
Data
ZHOU, L., SUN, Y., ZOU, G., HU, H., ZHANG, Y., SU, H., ZHENG, S., ZHU, Y., CHEN, P., FERNANDEZ, C. and PENG, Q. 2025. Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. [Video]. Journal of materials science and technology [online], 237, pages 298-311. Available from: https://doi.org/10.1016/j.jmst.2025.01.082

Conventional manufacturing approaches, including casting, thermal deformation and annealing, have faced great challenges in achieving both exceptional strength and ductility for Mg alloys. Herein, we report an effective strategy for simultaneously en... Read More about Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. [Video].

Online state of charge estimation for lithium-ion batteries using improved fuzzy C-means sparrow backpropagation algorithm. (2025)
Journal Article
HAI, N., WANG, S., CAO, W., BLAABJERG, F. and FERNANDEZ, C. 2025. Online state of charge estimation for lithium-ion batteries using improved fuzzy C-means sparrow backpropagation algorithm. Journal of energy storage [online], 119, article 116351. Available from: https://doi.org/10.1016/j.est.2025.116351

With the rapid development of new energy vehicles (EVs), cloud-based management of the lithium-ion batteries (LIBs) state of charge (SOC) has become the technological mainstream under increasing intelligence. However, SOC is highly sensitive to the m... Read More about Online state of charge estimation for lithium-ion batteries using improved fuzzy C-means sparrow backpropagation algorithm..