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Pedro Ascencio
Pedro Ascencio
Post-doctoral Researcher at Oxford University, Energy and Power Group
Email verificata su eng.ox.ac.uk - Home page
Titolo
Citata da
Citata da
Anno
Online estimation of battery equivalent circuit model parameters and state of charge using decoupled least squares technique
C Zhang, W Allafi, Q Dinh, P Ascencio, J Marco
Energy 142, 678-688, 2018
3332018
A lumped thermal model of lithium-ion battery cells considering radiative heat transfer
W Allafi, C Zhang, K Uddin, D Worwood, TQ Dinh, PA Ormeno, K Li, ...
Applied Thermal Engineering 143, 472-481, 2018
512018
Adaptive soft-sensors for on-line particle size estimation in wet grinding circuits
D Sbarbaro, P Ascencio, P Espinoza, F Mujica, G Cortes
Control Engineering Practice 16 (2), 171-178, 2008
452008
Backstepping PDE design: A convex optimization approach
P Ascencio, A Astolfi, T Parisini
IEEE Transactions on automatic control 63 (7), 1943-1958, 2017
342017
An adaptive fuzzy hybrid state observer for bioprocesses
P Ascencio, D Sbarbaro, SF de Azevedo
IEEE Transactions on Fuzzy Systems 12 (5), 641-651, 2004
302004
Bayesian parameter estimation applied to the Li-ion battery single particle model with electrolyte dynamics
A Aitio, SG Marquis, P Ascencio, D Howey
IFAC-PapersOnLine 53 (2), 12497-12504, 2020
182020
Adaptive observer for charge-state and crossover estimation in disproportionation redox flow batteries undergoing self-discharge
P Ascencio, K Smith, CW Monroe, D Howey
2019 American Control Conference (ACC), 5452-5457, 2019
92019
T., T. Parisini, T. Backstepping PDE Design: A Convex Optimization Approach
P Ascencio, T Astolfi
IEEE Trans. Automat. Control 63 (7), 1943-1958, 2018
92018
An adaptive observer for a class of parabolic PDEs based on a convex optimization approach for backstepping PDE design
P Ascencio, A Astolfi, T Parisini
2016 American Control Conference (ACC), 3429-3434, 2016
82016
Backstepping PDE design, Volterra and Fredholm operators: A convex optimization approach
P Ascencio, A Astolfi, T Parisini
2015 54th IEEE Conference on Decision and Control (CDC), 7048-7053, 2015
52015
Adaptive observer design for parabolic partial differential equations
P Ascencio
32017
Backstepping PDE-based adaptive observer for a single particle model of lithium-ion batteries
P Ascencio, A Astolfi, T Parisini
2016 IEEE 55th Conference on Decision and Control (CDC), 5623-5628, 2016
32016
Discretisation-free battery fast-charging optimisation using the measure-moment approach
NE Courtier, R Drummond, P Ascencio, LD Couto, DA Howey
2022 European Control Conference (ECC), 628-634, 2022
22022
A Convex Optimization Approach for Backstepping PDE Design: Volterra and Fredholm Operators
P Ascencio, A Astolfi, T Parisini
arXiv preprint arXiv:1710.03723, 2017
12017
Augmented State Observer for Simultaneous Estimation of Charge State and Crossover in Self-Discharging Disproportionation Redox Flow Batteries
P Ascencio, K Smith, D Howey, CW Monroe
2019 IEEE Conference on Control Technology and Applications (CCTA), 481-486, 2019
2019
Online Characterization of Porous Separators for Disproportionation Redox Flow Batteries
KP Smith, P Ascencio, DA Howey, CW Monroe
Electrochemical Society Meeting Abstracts ecee2019, 182-182, 2019
2019
Real-Time Reservoir Balancing and Leak-Free Nonaqueous Cell Design for Flow Batteries
KP Smith, DA Howey, P Ascencio, CW Monroe
Electrochemical Society Meeting Abstracts 235, 455-455, 2019
2019
Property quantification for new flow-battery architectures using adaptive simulations
C Monroe, K Smith, P Ascencio, D Howey
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 257, 2019
2019
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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