All Outputs (237)

An ASTSEKF optimizer with nonlinear condition adaptability for accurate SOC estimation of lithium-ion batteries. (2023)
Journal Article
TAKYI-ANINAKWA, P., WANG, S., ZHANG, H., LI, H., YANG, X. and FERNANDEZ, C. 2023. An ASTSEKF optimizer with nonlinear condition adaptability for accurate SOC estimation of lithium-ion batteries. Journal of energy storage [online], 70, article 108098. Available from: https://doi.org/10.1016/j.est.2023.108098

Safe and reliable operations of lithium-ion batteries in electric vehicles (EVs), etc., highly depend on the accurate state of charge (SOC) estimated by the battery management system (BMS). However, due to the battery's nonlinear operating conditions... Read More about An ASTSEKF optimizer with nonlinear condition adaptability for accurate SOC estimation of lithium-ion batteries..

State of energy estimation for lithium-ion batteries using adaptive fuzzy control and forgetting factor recursive least squares combined with AEKF considering temperature. (2023)
Journal Article
LIU, D., WANG, S., FAN, Y., LIANG, Y., FERNANDEZ, C., STROE, D.I. 2023. State of energy estimation for lithium-ion batteries using adaptive fuzzy control and forgetting factor recursive least squares combined with AEKF considering temperature. Journal of energy storage [online], 70, article 108040. Available from: https://doi.org/10.1016/j.est.2023.108040

As the main energy storage component of electric vehicles (EV), lithium-ion battery state estimation is an essential part of the battery management system (BMS). State of Energy (SOE) is one of the important state parameters, and its accurate estimat... Read More about State of energy estimation for lithium-ion batteries using adaptive fuzzy control and forgetting factor recursive least squares combined with AEKF considering temperature..

High-precision state of charge estimation of lithium-ion batteries based on joint compression factor particle swarm optimization-forgetting factor recursive least square-adaptive extended Kalman filtering. (2023)
Journal Article
YANG, J., WANG, S., CHEN, L., QIAO, J., FERNANDEZ, C. and GUERRERO, J.M. 2023. High-precision state of charge estimation of lithium-ion batteries based on joint compression factor particle swarm optimization-forgetting factor recursive least square-adaptive extended Kalman filtering. Journal of The Electrochemical Society [online], 170(6), article 060527. Available from: https://doi.org/10.1149/1945-7111/acd815

Accurate state of charge (SOC) estimation is an important basis for battery energy management and the applications of lithium-ion batteries. In this paper, an improved compression factor particle swarm optimization-forgetting factor recursive least s... Read More about High-precision state of charge estimation of lithium-ion batteries based on joint compression factor particle swarm optimization-forgetting factor recursive least square-adaptive extended Kalman filtering..

An improved sliding window: long short-term memory modeling method for real-world capacity estimation of lithium-ion batteries considering strong random charging characteristics. (2023)
Journal Article
WANG, S., TAKYI-ANINAKWA, P., JIN, S., LIU, K. and FERNANDEZ, C. 2023. An improved sliding window: long short-term memory modeling method for real-world capacity estimation of lithium-ion batteries considering strong random charging characteristics. Journal of energy storage [online], 70, article 108038. Available from: https://doi.org/10.1016/j.est.2023.108038

Capacity estimation plays a significant role in ensuring safe and acceptable energy delivery, especially under real-time complex working conditions for whole-life-cycle lithium-ion batteries. For high-precision and robust capacity estimation, an impr... Read More about An improved sliding window: long short-term memory modeling method for real-world capacity estimation of lithium-ion batteries considering strong random charging characteristics..

Hybrid gray wolf optimization method in support vector regression framework for highly precise prediction of remaining useful life of lithium-ion batteries. (2023)
Journal Article
ZHANG, M., WANG, S., XIE, Y., YANG, X., HAO, X. and FERNANDEZ, C. 2023. Hybrid gray wolf optimization method in support vector regression framework for highly precise prediction of remaining useful life of lithium-ion batteries. Ionics [online], 29(9), pages 3597-3607. Available from: https://doi.org/10.1007/s11581-023-05072-1

The prediction of remaining useful life (RUL) of lithium-ion batteries takes a critical effect in the battery management system, and precise prediction of RUL guarantees the secure and reliable functioning of batteries. For the difficult problem of s... Read More about Hybrid gray wolf optimization method in support vector regression framework for highly precise prediction of remaining useful life of lithium-ion batteries..

Investigation of wave propagation pattern in a multilayer planar structure. (2023)
Journal Article
RAJENDRAN, V., PRATHURU, A., FERNANDEZ, C. and FAISAL, N.H. 2023. Investigation of wave propagation pattern in a multilayer planar structure. e-Journal of nondestructive testing [online], Special Issue NDE-Nuclear-2023: proceedings of the 2nd Non-destructive examination in nuclear international conference (NDE in Nuclear 2023), 27-29 June 2023, Sheffield, UK, article number 28270. Available from: https://www.ndt.net/search/docs.php3?id=28270

Acoustic emission (AE) is used to monitor conditions of various structures across many industrial sectors, including containment vessels or storage tanks of nuclear materials. Periodic monitoring, inspection and analysis of structure conditions can h... Read More about Investigation of wave propagation pattern in a multilayer planar structure..

A NARX network optimized with an adaptive weighted square-root cubature Kalman filter for the dynamic state of charge estimation of lithium-ion batteries. (2023)
Journal Article
TAKYI-ANINAKWA, P., WANG, S., ZHANG, H., XIAO, Y. and FERNANDEZ, C. 2023. A NARX network optimized with an adaptive weighted square-root cubature Kalman filter for the dynamic state of charge estimation of lithium-ion batteries. Journal of energy storage [online], 68, article 107728. Available from: https://doi.org/10.1016/j.est.2023.107728

Due to the high nonlinearities and unstable working conditions, accurately estimating the state of charge (SOC) by the battery management system (BMS) is a major challenge in ensuring the safety and reliability of lithium-ion batteries in electric ve... Read More about A NARX network optimized with an adaptive weighted square-root cubature Kalman filter for the dynamic state of charge estimation of lithium-ion batteries..

High-precision state of charge estimation of urban-road-condition lithium-ion batteries based on optimized high-order term compensation-adaptive extended Kalman filtering. (2023)
Journal Article
FENG, R., WANG, S., YU, C., ZHOU, H. and FERNANDEZ, C. 2023. High-precision state of charge estimation of urban-road-condition lithium-ion batteries based on optimized high-order term compensation-adaptive extended Kalman filtering. Journal of The Electrochemical Society [online], 170(5), article 050539. Available from: https://doi.org/10.1149/1945-7111/acd303

It is significant to improve the accuracy of estimating the state of charge (SOC) of lithium-ion batteries under different working conditions on urban roads. In this study, an improved second-order polarized equivalent circuit (SO-PEC) modeling metho... Read More about High-precision state of charge estimation of urban-road-condition lithium-ion batteries based on optimized high-order term compensation-adaptive extended Kalman filtering..

An error covariance correction-adaptive extended Kalman filter based on piecewise forgetting factor recursive least squares method for the state-of-charge estimation of lithium-ion batteries. (2023)
Journal Article
LIANG, Y., WANG, S., FAN, Y., TAKYI-ANINAKWA, P., XIE, Y. and FERNANDEZ, C. 2023. An error covariance correction-adaptive extended Kalman filter based on piecewise forgetting factor recursive least squares method for the state-of-charge estimation of lithium-ion batteries. Journal of energy storage [online], 68, article 107629. Available from: https://doi.org/10.1016/j.est.2023.107629

Accurate state-of-charge (SOC) estimation is essential for fully utilizing the battery performance of electric vehicles. Considering the demand for algorithms with the advantages of simplicity, fewer calculations, good stability, and high accuracy in... Read More about An error covariance correction-adaptive extended Kalman filter based on piecewise forgetting factor recursive least squares method for the state-of-charge estimation of lithium-ion batteries..

Review: optimized particle filtering strategies for high-accuracy state of charge estimation of LIBs. (2023)
Journal Article
WANG, S., JIA, X., TAKYI-ANINAKWA, P., STROE, D.-I. and FERNANDEZ, C. 2023. Review: optimized particle filtering strategies for high-accuracy state of charge estimation of LIBs. Journal of The Electrochemical Society [online], 170(5), article 050514. Available from: https://doi.org/10.1149/1945-7111/acd148

Lithium-ion batteries (LIBs) are used as energy storage systems due to their high efficiency. State of charge (SOC) estimation is one of the key functions of the battery management system (BMS). Accurate SOC estimation helps to determine the driving... Read More about Review: optimized particle filtering strategies for high-accuracy state of charge estimation of LIBs..

Improved lumped electrical characteristic modeling and adaptive forgetting factor recursive least squares-linearized particle swarm optimization full-parameter identification strategy for lithium-ion batteries considering the hysteresis component effect. (2023)
Journal Article
XIE, Y., WANG, S., ZHANG, C., FAN, Y., FERNANDEZ, C. and GUERRERO, J.M. 2023. Improved lumped electrical characteristic modeling and adaptive forgetting factor recursive least squares-linearized particle swarm optimization full-parameter identification strategy for lithium-ion batteries considering the hysteresis component effect. Journal of energy storage [online], 67, article 107597. Available from: https://doi.org/10.1016/j.est.2023.107597

Electric vehicles, as a new green mode of transportation, have put forward higher demand indicators for accurate modeling and efficient parameter identification strategies for lithium-ion batteries. In this paper, a lumped electrical characteristic m... Read More about Improved lumped electrical characteristic modeling and adaptive forgetting factor recursive least squares-linearized particle swarm optimization full-parameter identification strategy for lithium-ion batteries considering the hysteresis component effect..

A novel M-1 structured bidirectional long short term memory-rauch Tung Striebel smoothing algorithm for the joint estimation state of charge and multi-constrained sustained peak power of lithium-ion batteries. (2023)
Journal Article
LONG, T., WANG, S., CAO, W., ZHOU, H., FERNANDEZ, C. and WANG, Y. 2023. A novel M-1 structured bidirectional long short term memory-rauch Tung Striebel smoothing algorithm for the joint estimation state of charge and multi-constrained sustained peak power of lithium-ion batteries. Journal of energy storage [online], 67, article number 107576. Available from: https://doi.org/10.1016/j.est.2023.107576

The estimation of State of Charge (SoC) and State of Power (SoP) of lithium-ion batteries is an important part of battery management system. For the purpose of obtaining high-precision SoC and SoP estimation results, this paper proposes a novel M-1 s... Read More about A novel M-1 structured bidirectional long short term memory-rauch Tung Striebel smoothing algorithm for the joint estimation state of charge and multi-constrained sustained peak power of lithium-ion batteries..

An improved proportional control forgetting factor recursive least square-Monte Carlo adaptive extended Kalman filtering algorithm for high-precision state-of-charge estimation of lithium-ion batteries. (2023)
Journal Article
ZHU, C., WANG, S., YU, C., ZHOU, H. and FERNANDEZ, C. 2023. An improved proportional control forgetting factor recursive least square-Monte Carlo adaptive extended Kalman filtering algorithm for high-precision state-of-charge estimation of lithium-ion batteries. Journal of solid state electrochemistry [online], 27(9), pages 2277-2287. Available from: https://doi.org/10.1007/s10008-023-05514-w

For lithium-ion batteries, the state of charge (SOC) of batteries plays an important role in the battery management system, and the accuracy of the battery model and parameter identification is the basis of SOC estimation. Considering that the system... Read More about An improved proportional control forgetting factor recursive least square-Monte Carlo adaptive extended Kalman filtering algorithm for high-precision state-of-charge estimation of lithium-ion batteries..

Enhanced multi-state estimation methods for lithium-ion batteries considering temperature uncertainties. (2023)
Journal Article
TAKYI-ANINAKWA, P., WANG, S., ZHANG, H., XIAO, Y. and FERNANDEZ, C. 2023. Enhanced multi-state estimation methods for lithium-ion batteries considering temperature uncertainties. Journal of energy storage [online], 66, article number 107495. Available from: https://doi.org/10.1016/j.est.2023.107495

Due to their high energy density and minimal emissions, lithium-ion batteries are frequently employed in electric vehicles (EVs). Accurate estimation of the micro-parameters, state of charge (SOC), and state of health (SOH) are a few primary monitori... Read More about Enhanced multi-state estimation methods for lithium-ion batteries considering temperature uncertainties..

An improved long short-term memory based on global optimization square root extended Kalman smoothing algorithm for collaborative state of charge and state of energy estimation of lithium-ion batteries. (2023)
Journal Article
WU, F., WANG, S., CAO, W., LONG, T., LIANG, Y. and FERNANDEZ, C. 2023. An improved long short-term memory based on global optimization square root extended Kalman smoothing algorithm for collaborative state of charge and state of energy estimation of lithium-ion batteries. International journal of circuit theory and applications [online], 51(8), pages 3880-3896. Available from: https://doi.org/10.1002/cta.3624

State of charge and state of energy are essential performance indicators of the battery management system and the key to reflecting the remaining capacity of batteries. Aiming at the problems of low precision, long time, and strongly nonlinear system... Read More about An improved long short-term memory based on global optimization square root extended Kalman smoothing algorithm for collaborative state of charge and state of energy estimation of lithium-ion batteries..

Crystal-defect engineering of electrode materials for energy storage and conversion. (2023)
Journal Article
WANG, J., ZHAO, X., ZOU, G., ZHANG, L., HAN, S., LI, Y., LIU, D., FERNANDEZ, C., LI, L., REN, L. and PENG, Q. 2023. Crystal-defect engineering of electrode materials for energy storage and conversion. Materials today nano [online], 22, article number 100336. Available from: https://doi.org/10.1016/j.mtnano.2023.100336

Crystal-defect engineering (CDE) in electrode materials is an emerging research area for tailoring properties, which opens up unprecedented possibilities not only in battery and catalysis, but also in controlling physical, chemical, and electronic pr... Read More about Crystal-defect engineering of electrode materials for energy storage and conversion..

An improved particle swarm optimization-least squares support vector machine-unscented Kalman filtering algorithm on SOC estimation of lithium-ion battery. (2023)
Journal Article
ZHOU, Y., WANG, S., XIE, Y., ZHU, T. and FERNANDEZ, C. 2023. An improved particle swarm optimization-least squares support vector machine-unscented Kalman filtering algorithm on SOC estimation of lithium-ion battery. International journal of green energy [online], Latest Articles. Available from: https://doi.org/10.1080/15435075.2023.2196328

For real-time monitoring and safe control of electrical vehicles, it is important to accurately estimate the state of charge of lithium-ion batteries. A combined data-driven modeling approach based on Least squares support vector machine based on par... Read More about An improved particle swarm optimization-least squares support vector machine-unscented Kalman filtering algorithm on SOC estimation of lithium-ion battery..

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., YANG, X. 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], 273, 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], 58(3), pages 281-321. 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..