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Battery‐lifetime‐conscious energy management strategy based on SP‐SDP for commuter plug‐in hybrid electric vehicles
Author(s) -
Xu Fuguo,
Jiao Xiaohong,
Wang Yuying,
Jing Yuan
Publication year - 2018
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22590
Subject(s) - energy management , automotive engineering , battery (electricity) , dynamic programming , electric vehicle , computer science , driving cycle , plug in , stochastic programming , mathematical optimization , engineering , power (physics) , energy (signal processing) , statistics , physics , mathematics , quantum mechanics , algorithm , programming language
The energy management strategy used to split the energy flow among different energy resources of hybrid electric vehicles plays a critically important role in achieving fuel economy. Additionally, battery degradation and high production cost lead to the necessary consideration of the battery lifetime in the energy management strategy design for a plug‐in hybrid electric vehicle (PHEV). This paper investigates the PHEV energy management problem taking into consideration battery lifetime on how to distribute power between the engine and the electric equipment during the driving cycle to achieve the whole economy for a commuter PHEV. Shortest path stochastic dynamic programming (SP‐SDP) is employed to address this energy management problem, which is formulated as a stochastic optimal control problem with the minimization of a weighted combination of the fuel and electricity consumption and the battery degradation rate for a stochastic process model with the statistic characteristics captured from the historical traffic speed profiles. The solution of this optimization problem, derived from a modified policy iteration algorithm, is a time‐invariant, state‐dependent power split strategy, which can be directly applied on the actual running vehicle. Simulation results carried on a PHEV Prius model in MATLAB/Simulink environment over some driving cycles are presented to demonstrate the effectiveness of the proposed energy management strategy. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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