All Outputs (259)

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..

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..

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)
Dataset
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..

Improved multi-time scale lumped thermoelectric coupling modeling and parameter dispersion evaluation of lithium-ion batteries. (2022)
Journal Article
SHI, H., WANG, S., FERNANDEZ, C., YU, C., XU, W., DABLU, B.E. and WANG, L. 2022. Improved multi-time scale lumped thermoelectric coupling modeling and parameter dispersion evaluation of lithium-ion batteries. Applied energy [online], 324, article 119789. Available from: https://doi.org/10.1016/j.apenergy.2022.119789

The rapid development of new energy fields such as electric vehicles and smart grids has put forward higher requirements for the power management of battery integrated systems. Considering that internal temperature and parameter consistency are impor... Read More about Improved multi-time scale lumped thermoelectric coupling modeling and parameter dispersion evaluation of lithium-ion batteries..

Incremental capacity curve health-indicator extraction based on gaussian filter and improved relevance vector machine for lithium–ion battery remaining useful life estimation. (2022)
Journal Article
FAN, Y., QIU, J., WANG, S., YANG, X., LIU, D. and FERNANDEZ, C. 2022. Incremental capacity curve health-indicator extraction based on gaussian filter and improved relevance vector machine for lithium–ion battery remaining useful life estimation. Metals [online], 12(8), article 1331. Available from: https://doi.org/10.3390/met12081331

Accurate prediction of the remaining useful life (RUL) of lithium–ion batteries is the focus of lithium–ion battery health management. To achieve high–precision RUL estimation of lithium–ion batteries, a novel RUL prediction model is proposed by comb... Read More about Incremental capacity curve health-indicator extraction based on gaussian filter and improved relevance vector machine for lithium–ion battery remaining useful life estimation..

A novel equivalent modeling method combined with the splice-electrochemical polarization model and prior generalized inverse least-square parameter identification for UAV lithium-ion batteries. (2022)
Journal Article
PENG, J., SHI, H., WANG, S., WANG, L., FERNANDEZ, C., XIONG, X. and DABLU, B.E. 2022. A novel equivalent modeling method combined with the splice-electrochemical polarization model and prior generalized inverse least-square parameter identification for UAV lithium-ion batteries. Energy science and engineering [online], 10(10), pages 3727-3740. Available from: https://doi.org/10.1002/ese3.1268

The accuracy of lithium-ion battery state estimation is critical to the safety of unmanned aerial vehicles (UAVs). In this paper, aiming at the high-fidelity modeling of the UAV lithium-ion battery, a splice-electrochemical polarization model (S-EPM)... Read More about A novel equivalent modeling method combined with the splice-electrochemical polarization model and prior generalized inverse least-square parameter identification for UAV lithium-ion batteries..

A novel square root adaptive unscented Kalman filter combined with variable forgetting factor recursive least square method for accurate state-of-charge estimation of lithium-ion batteries. (2022)
Journal Article
ZHANG, M., WANG, S., YANG, X., XU, W., YANG, X. and FERNANDEZ, C. 2022. A novel square root adaptive unscented Kalman filter combined with variable forgetting factor recursive least square method for accurate state-of-charge estimation of lithium-ion batteries. International journal of electrochemical science [online], 17(9), article 220915. Available from: https://doi.org/10.20964/2022.09.27

Lithium-ion battery state-of-charge (SOC) serves as an important battery state parameter monitored by the battery management system (BMS), real-time and accurate estimation of the SOC is vital for safe, reasonable, and efficient use of the battery as... Read More about A novel square root adaptive unscented Kalman filter combined with variable forgetting factor recursive least square method for accurate state-of-charge estimation of lithium-ion batteries..

A systematic review and bibliometric analysis of flame-retardant rigid polyurethane foam from 1963 to 2021. (2022)
Journal Article
PAN, Y., YIN, C., FERNANDEZ, C., FU, L. and LIN, C.-T. 2022. A systematic review and bibliometric analysis of flame-retardant rigid polyurethane foam from 1963 to 2021. Polymers [online], 14(15), article 3011. Available from: https://doi.org/10.3390/polym14153011

Flame-retardant science and technology are sciences developed to prevent the occurrence of fire, meet the needs of social safety production, and protect people's lives and property. Rigid polyurethane (PU) is a polymer formed by the additional polyme... Read More about A systematic review and bibliometric analysis of flame-retardant rigid polyurethane foam from 1963 to 2021..

Battery hysteresis compensation modeling and state-of-charge estimation adaptive to time-varying ambient temperature conditions. (2022)
Journal Article
SHI, H., WANG, S., FERNANDEZ, C., HUANG, J., XU, W. and WANG, L. 2022. Battery hysteresis compensation modeling and state-of-charge estimation adaptive to time-varying ambient temperature conditions. International journal of energy research [online], 46(12), pages 17096-17112. Available from: https://doi.org/10.1002/er.8373

Temperature and cell hysteretic effects are two major factors that influence the reliability and safety in long-term management of battery-integrated systems. In this paper, a hysteresis-compensated electrical characteristic model is established to t... Read More about Battery hysteresis compensation modeling and state-of-charge estimation adaptive to time-varying ambient temperature conditions..

A critical review of improved deep convolutional neural network for multi-timescale state prediction of lithium-ion batteries. (2022)
Journal Article
WANG, S., REN, P., TAKYI-ANINAKWA, P., JIN, S. and FERNANDEZ, C. 2022. A critical review of improved deep convolutional neural network for multi-timescale state prediction of lithium-ion batteries. Energies [online], 15(14), article 5053. Available from: https://doi.org/10.3390/en15145053

Lithium-ion batteries are widely used as effective energy storage and have become the main component of power supply systems. Accurate battery state prediction is key to ensuring reliability and has significant guidance for optimizing the performance... Read More about A critical review of improved deep convolutional neural network for multi-timescale state prediction of lithium-ion batteries..