Dr Carlos Fernandez's Outputs (41)

Online parameter identification and state of charge estimation of lithium-ion batteries based on improved artificial fish swarms forgetting factor least squares and differential evolution extended Kalman filter. (2022)
Journal Article
XIAO, W., WANG, S., YU, C., YANG, X., QIU, J. and FERNANDEZ, C. 2022. Online parameter identification and state of charge estimation of lithium-ion batteries based on improved artificial fish swarms forgetting factor least squares and differential evolution extended Kalman filter. Journal of The Electrochemical Society [online], 169(12), 120534. Available from: https://doi.org/10.1149/1945-7111/acaa5b

State of Charge (SOC) estimation is the focus of battery management systems, and it is critical to accurately estimate battery SOC in complex operating environments. To weaken the impact of unreasonable forgetting factor values on parameter estimatio... Read More about Online parameter identification and state of charge estimation of lithium-ion batteries based on improved artificial fish swarms forgetting factor least squares and differential evolution extended Kalman filter..

A novel nonlinear decreasing step-bacterial foraging optimization algorithm and simulated annealing-back propagation model for long-term battery state of health estimation. (2022)
Journal Article
XIONG, R., WANG, S., YU, C., FERNANDEZ, C., XIAO, W. and JIA, J. 2023. A novel nonlinear decreasing step-bacterial foraging optimization algorithm and simulated annealing-back propagation model for long-term battery state of health estimation. Journal of energy storage [online], 59, article 106484. Available from: https://doi.org/10.1016/j.est.2022.106484

With the rapid development of electric energy storage, more and more attention has been paid to the accurate construction of energy storage lithium-ion battery (LIB) model and the efficient monitoring of battery states. Based on this requirement, a s... Read More about A novel nonlinear decreasing step-bacterial foraging optimization algorithm and simulated annealing-back propagation model for long-term battery state of health estimation..

An improved forgetting factor recursive least square and unscented particle filtering algorithm for accurate lithium-ion battery state of charge estimation. (2022)
Journal Article
HAO, X., WANG, S., FAN, Y., XIE, Y. and FERNANDEZ, C. 2023. An improved forgetting factor recursive least square and unscented particle filtering algorithm for accurate lithium-ion battery state of charge estimation. Journal of energy storage [online], 59, article 106478. Available from: https://doi.org/10.1016/j.est.2022.106478

As an indispensable part of the battery management system, accurately predicting the estimation of the state of charge (SOC) has attracted more attention, which can improve the efficiency of battery use and ensure its safety performance. Taking the t... Read More about An improved forgetting factor recursive least square and unscented particle filtering algorithm for accurate lithium-ion battery state of charge estimation..

Joint state of charge and state of health estimation of lithium-ion battery using improved adaptive dual extended Kalman filter based on piecewise forgetting factor recursive least squares. (2022)
Presentation / Conference Contribution
LIANG, Y., WANG, S., FAN, Y., YANG, X., XIE, Y. and FERNANDEZ, C. 2022. Joint state of charge and state of health estimation of lithium-ion battery using improved adaptive dual extended Kalman filter based on piecewise forgetting factor recursive least squares. In Proceedings of the 4th Smart power and internet energy systems international conference 2022 (SPIES 2022): towards a net-zero carbon future, 9-12 December 2022, Beijing, China. Piscataway: IEEE [online], pages 1923-1927. Available from https://doi.org/10.1109/spies55999.2022.10082478

This work aims to improve the accuracy of state of charge estimation for lithium-ion battery, as well as to accurately estimate state of health. This study presents a piecewise forgetting factor recursive least squares method based on integral separa... Read More about Joint state of charge and state of health estimation of lithium-ion battery using improved adaptive dual extended Kalman filter based on piecewise forgetting factor recursive least squares..

An improved weighting coefficient optimization-particle filtering algorithm based on Gaussian degradation model for remaining useful life prediction of lithium-ion batteries. (2022)
Journal Article
GAO, H., WANG, S., QIAO, J., YANG, X. and FERNANDEZ, C. 2022. An improved weighting coefficient optimization-particle filtering algorithm based on Gaussian degradation model for remaining useful life prediction of lithium-ion batteries. Journal of The Electrochemical Society [online], 169(12), article 120502. Available from: https://doi.org/10.1149/1945-7111/aca6a2

Establishing a capacity degradation model accurately and predicting the remaining useful life of lithium-ion batteries scientifically are of great significance for ensuring safety and reliability throughout the batteries' whole life cycle. Aiming at... Read More about An improved weighting coefficient optimization-particle filtering algorithm based on Gaussian degradation model for remaining useful life prediction of lithium-ion batteries..

A bench-scale electrochemical peroxidation reactor performance on removal of organic pollutants from tannery industrial wastewater. (2022)
Journal Article
GOPAL, S., SOMANATHAN, A., JEYAKUMAR, R. and FERNANDEZ, C. 2022. A bench-scale electrochemical peroxidation reactor performance on removal of organic pollutants from tannery industrial wastewater. Desalination and water treatment [online], 277, pages 120-135. Available from: https://doi.org/10.5004/dwt.2022.29039

The aim of this study is to evaluate the performance of a novel laboratory scale electrochemical peroxidation (ECP) reactor using iron (Fe) electrodes (anode and cathode) for treatment of tannery wastewater. In order to minimize operating cost, the e... Read More about A bench-scale electrochemical peroxidation reactor performance on removal of organic pollutants from tannery industrial wastewater..

A chaotic firefly-particle filtering method of dynamic migration modeling for the state-of-charge and state-of-health co-estimation of a lithium-ion battery performance. (2022)
Journal Article
QIAO, J., WANG, S., YU, C., YANG, X. and FERNANDEZ, C. 2022. A chaotic firefly-particle filtering method of dynamic migration modeling for the state-of-charge and state-of-health co-estimation of a lithium-ion battery performance. Energy [online], 263(Part E), article 126164. Available from: https://doi.org/10.1016/j.energy.2022.126164

In this research, a novel dynamic migration model is proposed, which can better describe the dynamic characteristics of the lithium-ion batteries under different aging states by adjusting the battery parameters in real-time. A novel chaotic firefly -... Read More about A chaotic firefly-particle filtering method of dynamic migration modeling for the state-of-charge and state-of-health co-estimation of a lithium-ion battery performance..

Research on the state of charge estimation method of lithium-ion batteries based on novel limited memory multi-innovation least squares method and SDE-2-RC equivalent model. (2022)
Journal Article
CAO, J., WANG, S., XIE, Y. and FERNANDEZ, C. 2023. Research on the state of charge estimation method of lithium-ion batteries based on novel limited memory multi-innovation least squares method and SDE-2-RC equivalent model. International journal of circuit theory and applications [online], 51(4), pages 1902-1917. Available from: https://doi.org/10.1002/cta.3500/

Because of the common data redundancy phenomenon in the current least-squares parameter identification algorithm and the complex offline parameter identification process, this research innovatively proposes a Limited Memory Multi-Innovation Least Squ... Read More about Research on the state of charge estimation method of lithium-ion batteries based on novel limited memory multi-innovation least squares method and SDE-2-RC equivalent model..

Novel improved particle swarm optimization-extreme learning machine algorithm for state of charge estimation of lithium-Ion batteries. (2022)
Journal Article
ZHANG, C., WANG, S., YU, C., XIE, Y. and FERNANDEZ, C. 2022. Novel improved particle swarm optimization-extreme learning algorithm for state of charge estimation of lithium-ion batteries. Industrial and engineering chemistry research [online], 61(46), pages 17209-17217. Available from: https://doi.org/10.1021/acs.iecr.2c02476

Incisively estimating the state of charge (SOC) of lithium-ion batteries is essential to ensure the safe and stable operation of a battery management system. Neural network methods do not depend on a specific lithium-ion battery model and are able to... Read More about Novel improved particle swarm optimization-extreme learning machine algorithm for state of charge estimation of lithium-Ion batteries..

An optimized long short-term memory-weighted fading extended Kalman filtering model with wide temperature adaptation for the state of charge estimation of lithium-ion batteries. (2022)
Journal Article
TAKYI-ANINAKWA, P., WANG, S., ZHANG, H., YANG, X. and FERNANDEZ, C. 2022. An optimized long short-term memory-weighted fading extended Kalman filtering model with wide temperature adaptation for the state of charge estimation of lithium-ion batteries. Applied energy [online], 326, article 120043. Available from: https://doi.org/10.1016/j.apenergy.2022.120043

Accurate state of charge (SOC) estimation at different operating temperatures is essential for the reliable and safe operation of battery management systems (BMS) for lithium-ion batteries in electric vehicles (EVs). In this paper, an optimized long-... Read More about An optimized long short-term memory-weighted fading extended Kalman filtering model with wide temperature adaptation for the state of charge estimation of lithium-ion batteries..

Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries. (2022)
Journal Article
WANG, S., FAN, Y., JIN, S., TAKYI-ANINAKWA, P. and FERNANDEZ, C. 2023. Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries. Reliability engineering and system safety [online], 230, article 108920. Available from: https://doi.org/10.1016/j.ress.2022.108920

Safety assurance is essential for lithium-ion batteries in power supply fields, and the remaining useful life (RUL) prediction serves as one of the fundamental criteria for the performance evaluation of energy and storage systems. Based on an improve... Read More about Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries..

A novel multiple training-scale dynamic adaptive cuckoo search optimized long short-term memory neural network and multi-dimensional health indicators acquisition strategy for whole life cycle health evaluation of lithium-ion batteries. (2022)
Journal Article
REN, P., WANG, S., CHEN, X., ZHOU, H., FERNANDEZ, C. and STROE, D.-I. 2022. A novel multiple training-scale dynamic adaptive cuckoo search optimized long short-term memory neural network and multi-dimensional health indicators acquisition strategy for whole life cycle health evaluation of lithium-ion batteries. Electrochimica Acta [online], 435, article 141404. Available from: https://doi.org/10.1016/j.electacta.2022.141404

State of health evaluation of lithium-ion batteries has become a significant research direction in related fields attributed to the crucial impact on the reliability and safety of electric vehicles. In this research, a dynamic adaptive cuckoo search... Read More about A novel multiple training-scale dynamic adaptive cuckoo search optimized long short-term memory neural network and multi-dimensional health indicators acquisition strategy for whole life cycle health evaluation of lithium-ion batteries..

Current development and future challenges in microplastic detection techniques: a bibliometrics-based analysis and review. (2022)
Journal Article
JIN, M., LIU, J., YU, J., ZHOU, Q., WU, W., FU, L., YIN, C., FERNANDEZ, C. and KARIMI-MALEH, H. 2022. Current development and future challenges in microplastic detection techniques: a bibliometrics-based analysis and review. Science progress [online], 105(4), pages 1-22. Available from: https://doi.org/10.1177/003685042211321

Microplastics have been considered a new type of pollutant in the marine environment and have attracted widespread attention worldwide in recent years. Plastic particles with particle size less than 5 mm are usually defined as microplastics. Because... Read More about Current development and future challenges in microplastic detection techniques: a bibliometrics-based analysis and review..

Application of thermal spray coatings in electrolysers for hydrogen production: advances, challenges, and opportunities. (2022)
Journal Article
FAISAL, N.H., PRATHURU, A., AHMED, R. et al. 2022. Application of thermal spray coatings in electrolysers for hydrogen production: advances, challenges, and opportunities. ChemNanoMat [online], 8(12), article number e202200384. Available from: https://doi.org/10.1002/cnma.202200384

Thermal spray coatings have the advantage of providing thick and functional coatings from a range of engineering materials. The associated coating processes provide good control of coating thickness, morphology, microstructure, pore size and porosity... Read More about Application of thermal spray coatings in electrolysers for hydrogen production: advances, challenges, and opportunities..

Improved compound correction-electrical equivalent circuit modeling and double transform-unscented Kalman filtering for the high-accuracy closed-circuit voltage and state-of-charge co-estimation of whole-life-cycle lithium-ion batteries. (2022)
Journal Article
WANG, S., TAKYI-ANINAKWA, P., YU, C., JIN, S. and FERNANDEZ, C. 2022. Improved compound correction-electrical equivalent circuit modeling and double transform-unscented Kalman filtering for the high-accuracy closed-circuit voltage and state-of-charge co-estimation of whole-life-cycle lithium-ion batteries. Energy technology [online], 10(12), article 2200921. Available from: https://doi.org/10.1002/ente.202200921

For complex energy storage conditions, it is necessary to monitor the state-of-charge (SOC) and closed-circuit voltage (CCV) status accurately for the reliable power supply application of lithium-ion batteries. Herein, an improved compound correction... Read More about Improved compound correction-electrical equivalent circuit modeling and double transform-unscented Kalman filtering for the high-accuracy closed-circuit voltage and state-of-charge co-estimation of whole-life-cycle lithium-ion batteries..

Towards an ultra-long lifespan Li-CO2: electron structure and charge transfer pathway regulation on hierarchical architecture. [Dataset] (2022)
Data
WANG, Y., WANG, J., WANG, J., YANG, M., ZOU, G., LI, L., TSE, J.S., FERNANDEZ, C. and PENG, Q. 2022. Towards an ultra-long lifespan Li-CO2: electron structure and charge transfer pathway regulation on hierarchical architecture. [Dataset]. Chemical engineering journal [online], 451(Part 3), article 138953. Available from: https://www.sciencedirect.com/science/article/pii/S1385894722044321#s0075

Energy shortage and environmental pollution are severe challenges for achieving sustainable development of human society. Li-CO2 batteries offer particularly attractive merits in combination with CO2 fixation and energy storage, in which it shows a... Read More about Towards an ultra-long lifespan Li-CO2: electron structure and charge transfer pathway regulation on hierarchical architecture. [Dataset].

Towards an ultra-long lifespan Li-CO2: electron structure and charge transfer pathway regulation on hierarchical architecture. (2022)
Journal Article
WANG, Y., WANG, J., WANG, J., YANG, M., ZOU, G., LI, L., TSE, J.S., FERNANDEZ, C. and PENG, Q. 2022. Towards an ultra-long lifespan Li-CO2: electron structure and charge transfer pathway regulation on hierarchical architecture. Chemical engineering journal [online], 451(Part 3), article 138953. Available from: https://doi.org/10.1016/j.cej.2022.138953

Lithium-CO2 batteries are recognized as an essential strategy for efficient carbon sequestration and energy storage to achieve carbon neutrality. Their cycle-ability and polarization voltage, however, are hindered by high decomposition voltage (≈4.3–... Read More about Towards an ultra-long lifespan Li-CO2: electron structure and charge transfer pathway regulation on hierarchical architecture..

Improved particle swarm optimization-extreme learning machine modeling strategies for the accurate lithium-ion battery state of health estimation and high-adaptability remaining useful life prediction. (2022)
Journal Article
ZHANG, C.-Y., WANG, S.-L., YU, C.-M., XIE, Y.-X. and FERNANDEZ, C. [2022]. Improved particle swarm optimization-extreme learning machine modeling strategies for the accurate lithium-ion battery state of health estimation and high-adaptability remaining useful life prediction. Journal of the Electrochemical Society [online], 169(8), article 080520. Available from: https://doi.org/10.1149/1945-7111/ac8a1a

To ensure the secure and stable operation of lithium-ion batteries, the state of health (SOH) and the remaining useful life (RUL) are the critical state parameters of lithium-ion batteries, which need to be estimated precisely. A joint SOH and RUL es... Read More about Improved particle swarm optimization-extreme learning machine modeling strategies for the accurate lithium-ion battery state of health estimation and high-adaptability remaining useful life prediction..

A novel adaptive back propagation neural network-unscented Kalman filtering algorithm for accurate lithium-ion battery state of charge estimation. (2022)
Journal Article
WANG, Y., WANG, S., FAN, Y., XIE, Y. and FERNANDEZ, C. 2022. A novel adaptive back propagation neural network-unscented Kalman filtering algorithm for accurate lithium-ion battery state of charge estimation. Metals [online], 12(8), article 1369. Available from: https://doi.org/10.3390/met12081369

Accurate State of Charge (SOC) estimation for lithium-ion batteries has great significance with respect to the correct decision-making and safety control. In this research, an improved second-order-polarization equivalent circuit (SO-PEC) modelling m... Read More about A novel adaptive back propagation neural network-unscented Kalman filtering algorithm for accurate lithium-ion battery state of charge estimation..

An optimized relevant long short-term memory-squared gain extended Kalman filter for the state of charge estimation of lithium-ion batteries. (2022)
Journal Article
TAKYI-ANINAKWA, P., WANG, S., ZHANG, H., LI, H., XU, W. and FERNANDEZ, C. 2022. An optimized relevant long short-term memory-squared gain extended Kalman filter for the state of charge estimation of lithium-ion batteries. Energy [online], 260, article 125093. Available from: https://doi.org/10.1016/j.energy.2022.125093

Accurate state of charge (SOC) estimation of lithium-ion batteries by the battery management system (BMS) plays a prominent role in ensuring their reliability, safe operation, and acceptable durability in smart devices, electric vehicles, etc. In thi... Read More about An optimized relevant long short-term memory-squared gain extended Kalman filter for the state of charge estimation of lithium-ion batteries..