K
King Jet Tseng
Researcher at Singapore Institute of Technology
Publications - 293
Citations - 7944
King Jet Tseng is an academic researcher from Singapore Institute of Technology. The author has contributed to research in topics: Battery (electricity) & Torque. The author has an hindex of 44, co-authored 292 publications receiving 6531 citations. Previous affiliations of King Jet Tseng include Agency for Science, Technology and Research & University of Cambridge.
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Journal ArticleDOI
Thermal investigation of lithium-ion battery module with different cell arrangement structures and forced air-cooling strategies
TL;DR: In this paper, the thermal performance of battery module under different cell arrangement structures, which includes: 1.5 × 5 arrays rectangular arrangement, 19 cells hexagonal arrangement and 28 cells circular arrangement, was explored.
Proceedings ArticleDOI
Nonlinear control of interior permanent-magnet synchronous motor
TL;DR: In this article, an adaptive backstepping technique for an interior permanent-magnet synchronous motor (IPMSM) drive based on newly developed adaptive back stepping technique is presented.
Journal ArticleDOI
Design of a Robust Grid Interface System for PMSG-Based Wind Turbine Generators
TL;DR: A robust and reliable grid power interface system for wind turbines using a permanent-magnet synchronous generator (PMSG) is proposed in this paper, where an integration of a generator-side three-switch buck-type rectifier and a grid-side Z-source inverter is employed as a bridge between the generator and the grid.
Journal ArticleDOI
A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model
TL;DR: In this article, a multi-timescale method for dual estimation of state of charge (SOC) and capacity with an online identified battery model is presented, where the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them.
Journal ArticleDOI
Online Model Identification and State-of-Charge Estimate for Lithium-Ion Battery With a Recursive Total Least Squares-Based Observer
TL;DR: A novel technique which integrates a recursive total least squares (RTLS) with an SOC observer is proposed to enhance the online model identification and SOC estimate and provides a more reliable estimation of SOC.