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An improved variable forgetting factor recursive least square-double extend Kalman filtering based on global mean particle swarm optimization algorithm for collaborative state of energy and state of health estimation of lithium-ion batteries. (2023)
Journal Article
LONG, T., WANG, S., CAO, W., ZHOU, H. and FERNANDEZ, C. 2023. An improved variable forgetting factor recursive least square-double extend Kalman filtering based on global mean particle swarm optimization algorithm for collaborative state of energy and state of health estimation of lithium-ion batteries. Electrochimica acta [online], 450, article 142270. Available from: https://doi.org/10.1016/j.electacta.2023.142270

Accurate assessment of SOE and SOH is a critical issue in the battery management system. This paper proposes an improved variable forgetting factor recursive least square-double extend Kalman filtering algorithm based on global mean particle swarm op... Read More about An improved variable forgetting factor recursive least square-double extend Kalman filtering based on global mean particle swarm optimization algorithm for collaborative state of energy and state of health estimation of lithium-ion batteries..

A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures. (2023)
Journal Article
TAKYI-ANINAKWA, P., WANG, S., ZHANG, H., XIAO, Y. and FERNANDEZ, C. 2023. A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures. Energy [online], In press, article 127231. Available from: https://doi.org/10.1016/j.energy.2023.127231

Accurately estimating the state of charge (SOC) of lithium-ion batteries by the battery management system (BMS) is crucial for safe electric vehicle (EV) operations. This paper proposes a SOC estimation method for lithium-ion batteries based on a dee... Read More about A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures..

Corrosion monitoring at the interface using sensors and advanced sensing materials: methods, challenges and opportunities. (2023)
Journal Article
RAJENDRAN, V., PRATHURU, A., FERNANDEZ, C. and FAISAL, N.H. 2023. Corrosion monitoring at the interface using sensors and advanced sensing materials: methods, challenges and opportunities. Corrosion engineering, science and technology [online], Latest Articles. Available from: https://doi.org/10.1080/1478422X.2023.2180195

Detecting and monitoring of corrosion is one of the major challenges in insulated metallic structures, or structures with one or more than one interface. This review paper aims to consolidate scattered literature on laboratory system-based corrosion... Read More about Corrosion monitoring at the interface using sensors and advanced sensing materials: methods, challenges and opportunities..

A novel combined estimation method for state of energy and predicted maximum available energy based on fractional-order modeling. (2023)
Journal Article
CHEN, L., WANG, S., JIANG, H. and FERNANDEZ, C. 2023. A novel combined estimation method for state of energy and predicted maximum available energy based on fractional-order modeling. Journal of energy storage [online], 62, article 106930. Available from: https://doi.org/10.1016/j.est.2023.106930

Although accurate SOE estimation can enhance the reliability of residual energy prediction, the environmental temperature, parameter coupling, and multiple state constraints increase the difficulty of obtaining SOE accurately. A combined estimation m... Read More about A novel combined estimation method for state of energy and predicted maximum available energy based on fractional-order modeling..

Multi-time scale identification of key kinetic processes for lithium-ion batteries considering variable characteristic frequency. (2023)
Journal Article

The electrification of vehicles puts forward higher requirements for the power management efficiency of integrated battery management systems as the primary or sole energy supply. In this paper, an efficient adaptive multi-time scale identification s... Read More about Multi-time scale identification of key kinetic processes for lithium-ion batteries considering variable characteristic frequency..

Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries. (2023)
Journal Article
XIE, Y., WANG, S., ZHANG, G., FAN, Y., FERNANDEZ, C. and BLAABJERG, F. 2023. Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries. Applied energy [online], 336, article 120866. Available from: https://doi.org/10.1016/j.apenergy.2023.120866

With the demand for high-endurance lithium-ion batteries in new energy vehicles, communication and portable devices, high energy density lithium-ion batteries have become the main research direction of the battery industry. State of Charge (SoC), as... Read More about Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries..

On the bramble way to Mg metal anodes in secondary Mg ion batteries. (2023)
Journal Article
ZOU, G., FENG, J., ZHAO, X., WANG, J., WANG, Y., YANG, W., WEI, M., WANG, Y., LI, L., REN, L., FERNANDEZ, C. and PENG, Q. 2023. On the bramble way to Mg metal anodes in secondary Mg ion batteries. Journal of materials science and technology [online], 150, pages 175-189. Available from: https://doi.org/10.1016/j.jmst.2022.11.038

As a prospective alternative to lithium-ion batteries, rechargeable magnesium metal batteries (RMBs) have many unparalleled advantages, including direct use of Mg metal as the electrode; large nature abundance; intrinsically safe merits; high theoret... Read More about On the bramble way to Mg metal anodes in secondary Mg ion batteries..

Wave-layered dendrite-free lithium deposition with unprecedented long-term cyclability. [Dataset] (2023)
Dataset
FENG, J., GE, B., WANG, J., ZHANG, L., LIU, D., ZOU, G., TSE, J.S., FERNANDEZ, C., YAN, X. and PENG, Q. 2023. Wave-layered dendrite-free lithium deposition with unprecedented long-term cyclability. [Dataset]. Journal of power sources [online], 560, article 232697. Available from: https://www.sciencedirect.com/science/article/pii/S0378775323000721#appsec1

As the most promising candidate for next-generation batteries, Li metal batteries (such as Li-air and Li–S) have received considerable attention for their ultrahigh theoretical capacity (3860 mAh g−1), the lowest electrochemical potential (−3.040 V v... Read More about Wave-layered dendrite-free lithium deposition with unprecedented long-term cyclability. [Dataset].

Wave-layered dendrite-free lithium deposition with unprecedented long-term cyclability. (2023)
Journal Article
FENG, J., GE, B., WANG, J., ZHANG, L., LIU, D., ZOU, G., TSE, J.S., FERNANDEZ, C., YAN, X. and PENG, Q. 2023. Wave-layered dendrite-free lithium deposition with unprecedented long-term cyclability. Journal of power sources [online], 560, article 232697. Available from: https://doi.org/10.1016/j.jpowsour.2023.232697

Lithium dendrite growth on the anode during cycling leads to poor stability and severe safety issue, hampering long-term cycle for high-energy batteries. Herein, we firstly found that dendrite-free Li can be deposited layer-by-layer on the surface of... Read More about Wave-layered dendrite-free lithium deposition with unprecedented long-term cyclability..

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..

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 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..

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. 2022. 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, Early Access. 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..