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Battery Management System for Future Electric Vehicles
| Battery Management System for Future Electric Vehicles |
| Autore | Söffker Dirk |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (154 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
state of charge (SOC)
joint estimation lithium-ion battery variational Bayesian approximation dual extended Kalman filter (DEKF) measurement statistic uncertainty electric vehicles renewable energy sources microgrid economic dispatching capacity allocation cooperative optimization SOC second-order RC model model parameter optimization AUKF small-signal modeling battery energy storage system battery management system control stability dynamic response wireless power state-of-charge electric vehicle LiFePO4 batteries state of charge (SoC) Butler-Volmer equation Arrhenius Peukert coulomb efficiency back propagation neural network (BPNN) torque and battery distribution particle swarm optimization air-cooled BTMS compact lithium ion battery module ANN battery electric vehicles battery management hybrid energy storage |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557625603321 |
Söffker Dirk
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Wind Power Integration into Power Systems: Stability and Control Aspects
| Wind Power Integration into Power Systems: Stability and Control Aspects |
| Autore | Meegahapola Lasantha |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (264 p.) |
| Soggetto topico |
Technology: general issues
Energy industries & utilities |
| Soggetto non controllato |
DFIG
ES virtual inertia control capacity allocation fuzzy logic controller wind power generation multi-model predictive control fuzzy clustering virtual synchronous generator doubly fed induction generator sub-synchronous resonance impedance modeling renewable energy sources (RESs) regional RoCoF model-based operational planning linear sensitivity-based method (LSM) cumulant-based method (CBM) collaborative capacity planning distributed wind power (DWP) energy storage system (ESS) optimization variable-structure copula Reynolds-averaged Navier-Stokes method wind turbine wake model 3D aerodynamic model turbulence model correction modules hybrid prediction model wavelet decomposition long short-term memory scenario analysis weak grids full-converter wind active power output control parameters subsynchronous oscillation eigenvalue analysis doubly fed induction generator (DFIG) wind generation frequency control artificial neural network (ANN) error following forget gate-based long short-term memory ultra-short-term prediction wind power load frequency control (LFC) wind farm particle swarm optimization kinetic energy inertial response low inertia the center of inertia frequency response metrics wind integration PSS/E FORTRAN electromechanical dynamics FCWG dynamics strong interaction electromechanical loop correlation ratio (ELCR) FCWG dynamic correlation ratio (FDCR) quasi- electromechanical loop correlation ratio (QELCR) permanent magnet synchronous generator (PMSG) supercapacitor energy storage (SCES) rotor overspeed control low voltage ride through (LVRT) capacity configuration of SCES |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Wind Power Integration into Power Systems |
| Record Nr. | UNINA-9910557761903321 |
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Meegahapola Lasantha
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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