[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Wang et al., 2018 - Google Patents

A novel safety anticipation estimation method for the aerial lithium-ion battery pack based on the real-time detection and filtering

Wang et al., 2018

View PDF
Document ID
11665990383902919065
Author
Wang S
Fernandez C
Chen M
Wang L
Su J
Publication year
Publication venue
Journal of cleaner production

External Links

Snippet

Lithium-ion battery packs have become increasingly important for power supply applications, in which the state of charge estimation and output voltage tracking should be very critical for the safety protection. A novel real-time estimation method is proposed by …
Continue reading at rgu-repository.worktribe.com (PDF) (other versions)

Classifications

    • H—ELECTRICITY
    • H01—BASIC ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/44—Methods for charging or discharging
    • H01M10/446—Initial charging measures
    • H—ELECTRICITY
    • H01—BASIC ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H01M2010/4271—Battery management systems including electronic circuits, e.g. control of current or voltage to keep battery in healthy state, cell balancing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Apparatus for testing electrical condition of accumulators or electric batteries, e.g. capacity or charge condition
    • G01R31/3644—Various constructional arrangements
    • G01R31/3648—Various constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
    • G01R31/3651—Software aspects, e.g. battery modeling, using look-up tables, neural networks
    • H—ELECTRICITY
    • H01—BASIC ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/05—Accumulators with non-aqueous electrolyte
    • H01M10/052—Li-accumulators
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Apparatus for testing electrical condition of accumulators or electric batteries, e.g. capacity or charge condition
    • G01R31/3606—Monitoring, i.e. measuring or determining some variables continuously or repeatedly over time, e.g. current, voltage, temperature, state-of-charge [SoC] or state-of-health [SoH]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging several batteries simultaneously or sequentially
    • H02J7/0021—Monitoring or indicating circuits
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage

Similar Documents

Publication Publication Date Title
Wang et al. A novel safety anticipation estimation method for the aerial lithium-ion battery pack based on the real-time detection and filtering
Wang et al. An adaptive working state iterative calculation method of the power battery by using the improved Kalman filtering algorithm and considering the relaxation effect
Tang et al. Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method
Xu et al. Co-estimating the state of charge and health of lithium batteries through combining a minimalist electrochemical model and an equivalent circuit model
Wei et al. Adaptive estimation of state of charge and capacity with online identified battery model for vanadium redox flow battery
Shi et al. Battery health management using physics-informed machine learning: Online degradation modeling and remaining useful life prediction
Yang et al. A novel method on estimating the degradation and state of charge of lithium-ion batteries used for electrical vehicles
Li et al. A practical lithium-ion battery model for state of energy and voltage responses prediction incorporating temperature and ageing effects
Shuzhi et al. A novel one-way transmitted co-estimation framework for capacity and state-of-charge of lithium-ion battery based on double adaptive extended Kalman filters
Wang et al. Modeling and state-of-charge prediction of lithium-ion battery and ultracapacitor hybrids with a co-estimator
Zhang et al. A multi time-scale framework for state-of-charge and capacity estimation of lithium-ion battery under optimal operating temperature range
Zhang et al. An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model
He et al. A novel Gaussian model based battery state estimation approach: State-of-Energy
Dong et al. A method for state of energy estimation of lithium-ion batteries based on neural network model
Lin et al. Evaluation of electrochemical models based battery state-of-charge estimation approaches for electric vehicles
CN103020445B (en) A kind of SOC and SOH Forecasting Methodology of electric-vehicle-mounted ferric phosphate lithium cell
Wang et al. Open circuit voltage and state of charge relationship functional optimization for the working state monitoring of the aerial lithium-ion battery pack
Wang et al. Online state of charge estimation for the aerial lithium-ion battery packs based on the improved extended Kalman filter method
Huang et al. Soc estimation of li-ion battery based on improved ekf algorithm
Locorotondo et al. Online identification of thevenin equivalent circuit model parameters and estimation state of charge of lithium-ion batteries
Xu et al. Dual fuzzy-based adaptive extended Kalman filter for state of charge estimation of liquid metal battery
Tang et al. A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models
He et al. An improved coulomb counting approach based on numerical iteration for SOC estimation with real-time error correction ability
Rezaei et al. A fast sliding-mode-based estimation of state-of-charge for Lithium-ion batteries for electric vehicle applications
Wang et al. A comprehensive working state monitoring method for power battery packs considering state of balance and aging correction