Search Results - lebesgue+sampling

4 Results

Sort By:

Lebesgue-Sampling-based Deep Learning for Battery Diagnosis and Prognosis

Reference #: 01603 The University of South Carolina is offering licensing opportunities for Lebesgue-Sampling-based Deep Learning for Battery Diagnosis and Prognosis Background: Accurate and efficient modeling of battery degradation is of great challenge and is becoming more and more complex for batteries in modern applications. Traditional degradation...

Published: 5/16/2023 | Inventor(s): Bin Zhang, Guangxing Niu

Keywords(s): Deep belief network, Diagnosis and prognosis, Fault dynamic model, Lebesgue sampling, Lithium-ion battery, Particle filter, Uncertainty management

Category(s): Engineering and Physical Sciences, Energy

Lithium-ion battery health management based on single particle model

Reference #: 01494 The University of South Carolina is offering licensing opportunities for Lithium-ion battery health management based on single particle model Background: A single particle model is used in simulating the behavior of lithium-ion battery. Particle swarm optimization is used to identify the parameters of the single particle model....

Published: 9/3/2022 | Inventor(s): Guangxing Niu, Bin Zhang

Keywords(s): Bayesian approach, Lebesgue sampling, Particle swarm optimization, Single particle model, State of charge, State of health

Category(s): Energy, Engineering and Physical Sciences

Li-ion-Battery State-of-charge diagnosis-prognosis based on Lebesgue-sampling equivalent-circuit-model

Reference #: 01527 The University of South Carolina is offering licensing opportunities for Li-ion-Battery State-of-charge diagnosis-prognosis based on Lebesgue-sampling equivalent-circuit-model. Background: Traditional SOC estimation and prediction is mainly based on the electrochemical model (EM) or ECM of Li-battery. The EM method has a high computation...

Published: 1/26/2023 | Inventor(s): Bin Zhang, Enhui Liu

Keywords(s): accuracy, computation, efficiency, Equivalent circuit model, Lebesgue sampling, open circuit voltage, SOC diagnostics and prognostics

Category(s): Energy

Lebesgue-sampling-based battery whole-service-life SOC estimation using simplified first principle model

Reference #: 01493 The University of South Carolina is offering licensing opportunities for Lebesgue-sampling-based battery whole-service-life SOC estimation using simplified first principle model Background: Traditional state of health and state of charge estimation is mainly based on the electrochemical model or equivalent circuit model of Li-battery....

Published: 7/17/2023 | Inventor(s): Enhui Liu, Bin Zhang

Keywords(s): accuracy, computation, Lebesgue sampling, Simplified first principle model, SOC estimation

Category(s): Engineering and Physical Sciences, Energy