Premium
Model Predictive Control of Hybrid Electric Vehicles for Improved Fuel Economy
Author(s) -
Yu K.,
Tan X.,
Yang H.,
Liu W.,
Cui L.,
Liang Q.
Publication year - 2016
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1304
Subject(s) - cruise control , fuel efficiency , model predictive control , position (finance) , state of charge , trajectory , cruise , electric vehicle , battery (electricity) , automotive engineering , control theory (sociology) , optimal control , control (management) , computer science , engineering , mathematical optimization , mathematics , artificial intelligence , economics , power (physics) , physics , finance , quantum mechanics , astronomy , aerospace engineering
This brief proposes a model predictive control method using preceding vehicle information within hybrid electric vehicles' (HEVs') predictive cruise control system to improve car following performance and reduce fuel consumption. This paper adds two original contributions to the related literature. First, a real‐time optimization approach using Pontryagin's minimum principle with analytical methods rather than numerical iteration methods is proposed. Second, to compute the desired battery state of charge trajectory as a function of vehicle position, only the topographic profile of the future road segments must be known. Both the fuel economy and the driving profile are optimized using the proposed approach. Simulation results show that fuel economy using the proposed method is improved significantly.