Work

Study on Power Management Strategy of HEV using Dynamic Programming

Year: 2016

Type: article

Abstract: For hybrid electric vehicle, it is necessary to control power distribution among multiple power sources to improve fuel economy performance of vehicle. In this paper, power management strategy of hybrid electric vehicle using Dynamic programming is studied. Deterministic dynamic programming could present outstanding fuel economy, while its application as real time control of vehicle is limited. Thus, different kinds of power management strategy using dynamic programming are studied. Stochastic dynamic programming, artificial neural networks and rule-based power management strategy using results from dynamic programming are studied. Simulations using parallel type hybrid electric vehicle model are conducted. Simulation results including fuel economy performance on diverse driving cycles are compared and analysed.

Source: World Electric Vehicle Journal

DOI: 10.3390/wevj8010274

Authors: Heeyun Lee, Changbeom Kang, Yeong-il Park, Suk Cha

Institutions: Seoul National University, Seoul National University of Science and Technology

Language: English

Topic: Electric and Hybrid Vehicle Technologies

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: gold

Estimated APC paid: $1,689