M
Ming L. Kuang
Researcher at Ford Motor Company
Publications - 18
Citations - 2931
Ming L. Kuang is an academic researcher from Ford Motor Company. The author has contributed to research in topics: Electric vehicle & Powertrain. The author has an hindex of 10, co-authored 17 publications receiving 2785 citations.
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Proceedings ArticleDOI
Predictive energy management of a power-split hybrid electric vehicle
TL;DR: Simulation results over multiple driving cycles indicate better fuel economy over conventional strategies can be achieved and the proposed algorithm is causal and has the potential for real-time implementation.
Journal ArticleDOI
MPC-Based Energy Management of a Power-Split Hybrid Electric Vehicle
Hoseinali Borhan,Ardalan Vahidi,Anthony Mark Phillips,Ming L. Kuang,Ilya Kolmanovsky,S. Di Cairano +5 more
TL;DR: The results of a nonlinear MPC strategy show a noticeable improvement in fuel economy with respect to those of an available controller in the commercial Powertrain System Analysis Toolkit (PSAT) software and the other proposed methodology by the authors based on a linear time-varying MPC.
Journal ArticleDOI
Power Smoothing Energy Management and Its Application to a Series Hybrid Powertrain
TL;DR: Simulations of the urban dynamometer driving schedule (UDDS) and US06 cycles using a complete vehicle system model and experimental tests of the UDDS cycle show improved fuel economy with respect to baseline strategies.
Proceedings ArticleDOI
Optimally controlling Hybrid Electric Vehicles using path forecasting
Georgia-Evangelia Katsargyri,Ilya Kolmanovsky,John Ottavio Michelini,Ming L. Kuang,Anthony Mark Phillips,Michael Rinehart,Munther A. Dahleh +6 more
TL;DR: In this approach, the dynamic programming is used as a tool to quantify the benefits offered by route information availability to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted vehicle route.