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Matthias Preindl
Matthias Preindl
Columbia University, Electrical Engineering Department
Zweryfikowany adres z columbia.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
State-of-charge estimation of Li-ion batteries using deep neural networks: A machine learning approach
E Chemali, PJ Kollmeyer, M Preindl, A Emadi
Journal of Power Sources 400, 242-255, 2018
7452018
Long short-term memory networks for accurate state-of-charge estimation of Li-ion batteries
E Chemali, PJ Kollmeyer, M Preindl, R Ahmed, A Emadi
IEEE Transactions on Industrial Electronics 65 (8), 6730-6739, 2017
7452017
Model predictive direct speed control with finite control set of PMSM drive systems
M Preindl, S Bolognani
IEEE Transactions on Power Electronics 28 (2), 1007-1015, 2012
6102012
Making the case for electrified transportation
B Bilgin, P Magne, P Malysz, Y Yang, V Pantelic, M Preindl, A Korobkine, ...
IEEE Transactions on Transportation electrification 1 (1), 4-17, 2015
5072015
Model predictive direct torque control with finite control set for PMSM drive systems, Part 1: Maximum torque per ampere operation
M Preindl, S Bolognani
IEEE Transactions on Industrial Informatics 9 (4), 1912-1921, 2013
4552013
Electrochemical and electrostatic energy storage and management systems for electric drive vehicles: State-of-the-art review and future trends
E Chemali, M Preindl, P Malysz, A Emadi
IEEE Journal of Emerging and Selected Topics in Power Electronics 4 (3 …, 2016
3542016
Model predictive direct torque control with finite control set for PMSM drive systems, part 2: Field weakening operation
M Preindl, S Bolognani
IEEE Transactions on Industrial Informatics 9 (2), 648-657, 2012
2792012
Switching frequency reduction using model predictive direct current control for high-power voltage source inverters
M Preindl, E Schaltz, P Thogersen
IEEE Transactions on Industrial Electronics 58 (7), 2826-2835, 2010
2572010
Sensorless model predictive direct current control using novel second-order PLL observer for PMSM drive systems
M Preindl, E Schaltz
IEEE Transactions on Industrial Electronics 58 (9), 4087-4095, 2010
1942010
Thermal management of electric machines
Y Yang, B Bilgin, M Kasprzak, S Nalakath, H Sadek, M Preindl, J Cotton, ...
IET Electrical Systems in Transportation 7 (2), 104-116, 2017
1832017
Optimal state reference computation with constrained MTPA criterion for PM motor drives
M Preindl, S Bolognani
IEEE Transactions on Power Electronics 30 (8), 4524-4535, 2014
1602014
Fast model predictive control for redistributive lithium-ion battery balancing
L McCurlie, M Preindl, A Emadi
IEEE Transactions on Industrial Electronics 64 (2), 1350-1357, 2016
1512016
Bus bar design for high-power inverters
AD Callegaro, J Guo, M Eull, B Danen, J Gibson, M Preindl, B Bilgin, ...
IEEE Transactions on Power Electronics 33 (3), 2354-2367, 2017
1402017
Robust control invariant sets and Lyapunov-based MPC for IPM synchronous motor drives
M Preindl
IEEE Transactions on Industrial Electronics 63 (6), 3925-3933, 2016
1142016
Comparison of direct and PWM model predictive control for power electronic and drive systems
M Preindl, S Bolognani
2013 Twenty-Eighth Annual IEEE Applied Power Electronics Conference and …, 2013
892013
Unified wide-speed sensorless scheme using nonlinear optimization for IPMSM drives
Y Sun, M Preindl, S Sirouspour, A Emadi
IEEE Transactions on Power Electronics 32 (8), 6308-6322, 2016
832016
MTPA fitting and torque estimation technique based on a new flux-linkage model for interior-permanent-magnet synchronous machines
Y Miao, H Ge, M Preindl, J Ye, B Cheng, A Emadi
IEEE Transactions on Industry Applications 53 (6), 5451-5460, 2017
752017
Review and trends of thermoelectric generator heat recovery in automotive applications
R Rodriguez, M Preindl, JS Cotton, A Emadi
IEEE Transactions on Vehicular Technology 68 (6), 5366-5378, 2019
742019
Optimization-based position sensorless finite control set model predictive control for IPMSMs
S Nalakath, Y Sun, M Preindl, A Emadi
IEEE Transactions on Power Electronics 33 (10), 8672-8682, 2017
742017
Towards unified machine learning characterization of lithium-ion battery degradation across multiple levels: A critical review
AG Li, AC West, M Preindl
Applied Energy 316, 119030, 2022
712022
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