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Welcome to OpenAIR@RGU

OpenAIR@RGU is the open access institutional repository of Robert Gordon University. It contains examples of research outputs produced by staff and research students, as well as related information about the university's funded projects and staff research interests. Further information is available in the repository policy. Any questions about submissions to the repository or problems with access to any of its content should be sent to the Publications Team at publications@rgu.ac.uk



Latest Additions

An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles. [Dataset] (2024)
Dataset
ZHU, C., WANG, S., YU, C., ZHOU, H., FERNANDEZ, C. and GUERRERO, J.M. 2024. An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles. [Dataset]. Journal of energy storage [online], 88, article number 111552. Available from: https://www.sciencedirect.com/science/article/pii/S2352152X2401137X?via%3Dihub#s0100

The accurate estimation of battery State of Charge (SOC) is a key technology in the research of electric vehicle battery management systems. In order to solve the problem of inaccurate noise estimation in nonlinear systems, an improved Cauchy robust... Read More about An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles. [Dataset].

An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles. (2024)
Journal Article
ZHU, C., WANG, S., YU, C., ZHOU, H., FERNANDEZ, C. and GUERRERO, J.M. 2024. An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles. Journal of energy storage [online], 88, article number 111552. Available from: https://doi.org/10.1016/j.est.2024.111552

The accurate estimation of battery State of Charge (SOC) is a key technology in the research of electric vehicle battery management systems. In order to solve the problem of inaccurate noise estimation in nonlinear systems, an improved Cauchy robust... Read More about An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles..

Large scoping reviews: managing volume and potential chaos in a pool of evidence sources. (2024)
Journal Article
ALEXANDER, L., COOPER, K., PETERS, M.D.J., TRICCO, A.C., KHALIL, H., EVANS, C., MUNN, Z., PIEPER, D., GODFREY, C.M., MCINERNEY, P. and POLLOCK, D. [2024]. Large scoping reviews: managing volume and potential chaos in a pool of evidence sources. Journal of clinical epidemiology [online], Articles in Press. Available from: https://doi.org/10.1016/j.jclinepi.2024.111343

Scoping reviews can identify a large number of evidence sources. This commentary describes and provides guidance on planning, conducting, and reporting large scoping reviews. This guidance is informed by experts in scoping review methodology, includi... Read More about Large scoping reviews: managing volume and potential chaos in a pool of evidence sources..

State of health prediction of lithium-ion batteries based on SSA optimized hybrid neural network model. (2024)
Journal Article
ZHOU, J., WANG, S., CAO, W., XIE, Y. and FERNANDEZ, C. 2024. State of health prediction of lithium-ion batteries based on SSA optimized hybrid neural network model. Electrochimica acta [online], 487, article number 144146. Available from: https://doi.org/10.1016/j.electacta.2024.144146

The accurate state of health (SOH) estimation of lithium-ion batteries (LIBs) is crucial for the operation and maintenance of new energy electric vehicles. To address this current problem, an improved hybrid neural network model for SOH prediction ba... Read More about State of health prediction of lithium-ion batteries based on SSA optimized hybrid neural network model..

Identifying the supportive care needs of people affected by non-muscle invasive bladder cancer: an integrative systematic review. (2024)
Journal Article
SCHUBACH, K., NIYONSENGA, T., TURNER, M. and PATERSON, C. 2024. Identifying the supportive care needs of people affected by non-muscle invasive bladder cancer: n integrative systematic review. Journal of cancer survivorship [online], Online First. Available from: https://doi.org/10.1007/s11764-024-01558-7

To understand supportive care needs among people with non-muscle invasive bladder cancer (NMIBC). An integrative systematic review was reported using the Preformed Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. Seven ele... Read More about Identifying the supportive care needs of people affected by non-muscle invasive bladder cancer: an integrative systematic review..