Lithium-ion battery State of Health(SOH)estimation is an essential issue in battery management systems.In order to better estimate battery SOH,Extreme Learning Machine(ELM)is used to establish a model to estimate lith...Lithium-ion battery State of Health(SOH)estimation is an essential issue in battery management systems.In order to better estimate battery SOH,Extreme Learning Machine(ELM)is used to establish a model to estimate lithium-ion battery SOH.The Swarm Optimization algorithm(PSO)is used to automatically adjust and optimize the parameters of ELM to improve estimation accuracy.Firstly,collect cyclic aging data of the battery and extract five characteristic quantities related to battery capacity from the battery charging curve and increment capacity curve.Use Grey Relation Analysis(GRA)method to analyze the correlation between battery capacity and five characteristic quantities.Then,an ELM is used to build the capacity estimation model of the lithium-ion battery based on five characteristics,and a PSO is introduced to optimize the parameters of the capacity estimation model.The proposed method is validated by the degradation experiment of the lithium-ion battery under different conditions.The results show that the battery capacity estimation model based on ELM and PSO has better accuracy and stability in capacity estimation,and the average absolute percentage error is less than 1%.展开更多
Recent studies have shown that the concentration of greenhouse gases such as carbon dioxide in the atmosphere is growing rapidly over recent years and this can lead to major dangers for the planet.This growth is mainl...Recent studies have shown that the concentration of greenhouse gases such as carbon dioxide in the atmosphere is growing rapidly over recent years and this can lead to major dangers for the planet.This growth is mainly due to the emissions from fossil power source such as diesel plants and gas turbines.The purpose of the present paper is to study the feasibility of integrating a technique based on power to gas concept in fossil power plants such as gas turbine.This work is based on the reduction of pollutant gas emissions produced from a gas turbine plant,especially the carbon dioxide.This captured gas(CO_(2))can be converted once again into energy via the technique of power to gas concept.This concept starts by extracting CO_(2)from exhaust gases which is carried out by multiple chemical process.On the other side,H2 is produced from water electrolysis using the excess electricity which is produced but not consumed by the existing loads.finally the production of Methane(CH4)can be achieved by combination of the captured CO_(2)and the extracted H2 via a reactor known as a reactor of Sabatier,this operation is called methanation or hydrogenation of carbon dioxide.Simulation results are presented for the validation of the proposed technique based on real data obtained on site from a gas turbine plant.展开更多
基金This work was supported by the State Grid Corporation Headquarters Management Technology Project(SGTYHT/19-JS-215)Southwest Jiaotong University new interdisciplinary cultivation project by(YH1500112432273).
文摘Lithium-ion battery State of Health(SOH)estimation is an essential issue in battery management systems.In order to better estimate battery SOH,Extreme Learning Machine(ELM)is used to establish a model to estimate lithium-ion battery SOH.The Swarm Optimization algorithm(PSO)is used to automatically adjust and optimize the parameters of ELM to improve estimation accuracy.Firstly,collect cyclic aging data of the battery and extract five characteristic quantities related to battery capacity from the battery charging curve and increment capacity curve.Use Grey Relation Analysis(GRA)method to analyze the correlation between battery capacity and five characteristic quantities.Then,an ELM is used to build the capacity estimation model of the lithium-ion battery based on five characteristics,and a PSO is introduced to optimize the parameters of the capacity estimation model.The proposed method is validated by the degradation experiment of the lithium-ion battery under different conditions.The results show that the battery capacity estimation model based on ELM and PSO has better accuracy and stability in capacity estimation,and the average absolute percentage error is less than 1%.
基金This work was supported by the Applied Automation and Industrial Diagnostic Laboratory,University of Djelfa,Algeria and Modelling,Simulation and Optimization of Alternative and Sustainable Systems Team,University of Boumerdes,Algeria and the Fuel Cell Laboratory of the Technology University of Belfort Montbelillard,France.
文摘Recent studies have shown that the concentration of greenhouse gases such as carbon dioxide in the atmosphere is growing rapidly over recent years and this can lead to major dangers for the planet.This growth is mainly due to the emissions from fossil power source such as diesel plants and gas turbines.The purpose of the present paper is to study the feasibility of integrating a technique based on power to gas concept in fossil power plants such as gas turbine.This work is based on the reduction of pollutant gas emissions produced from a gas turbine plant,especially the carbon dioxide.This captured gas(CO_(2))can be converted once again into energy via the technique of power to gas concept.This concept starts by extracting CO_(2)from exhaust gases which is carried out by multiple chemical process.On the other side,H2 is produced from water electrolysis using the excess electricity which is produced but not consumed by the existing loads.finally the production of Methane(CH4)can be achieved by combination of the captured CO_(2)and the extracted H2 via a reactor known as a reactor of Sabatier,this operation is called methanation or hydrogenation of carbon dioxide.Simulation results are presented for the validation of the proposed technique based on real data obtained on site from a gas turbine plant.
