Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Leonidas Kiliaris"'
Publikováno v:
Journal of Power Sources. 196:835-846
This paper presents an optimal online power management strategy applied to a vehicular power system that contains multiple power sources and deals with largely fluctuated load requests. The optimal online power management strategy is developed using
Autor:
Zhihang Chen, Anthony Mark Phillips, Leonidas Kiliaris, M.A. Masrur, Yi Lu Murphey, Jungme Park, M.L. Kuang
Publikováno v:
IEEE Transactions on Vehicular Technology. 58:4741-4756
Previous research has shown that current driving conditions and driving style have a strong influence over a vehicle's fuel consumption and emissions. This paper presents a methodology for inferring road type and traffic congestion (RT&TC) levels fro
Publikováno v:
2009 IEEE Vehicle Power and Propulsion Conference.
This paper presents a machine learning approach to train an intelligent power controller for a series hybrid electric vehicle. The proposed machine learning approach exploits the best efficiency of the components associated with the roadway type and
Publikováno v:
CIVVS
This paper presents an innovative approach to classifying the driver's driving style by analyzing the jerk profile of the driver. Driving style is a dynamic behavior of a driver on the road. At times a driver can be calm but aggressive at others. The
Autor:
Jungme Park, Zhihang Chen, Yi Lu Murphey, M.A. Masrur, Leonidas Kiliaris, Ming Kuang, Anthony Mark Phillips
Publikováno v:
VTC Fall
This paper presents a machine learning approach to the efficient vehicle power management and an intelligent power controller (IPC) that applies the learnt knowledge about the optimal power control parameters specific to specific road types and traff
Autor:
Jungme Park, Yi Li Murphey, Ming Kuang, Abul Masrur, Anthony Mark Phillips, Zhihang Chen, Leonidas Kiliaris
Publikováno v:
IJCNN
Vehicle power management has been an active research area in the past decade, and has intensified recently by the emergence of hybrid electric vehicle technologies. Research has shown that driving style and environment have strong influence over fuel