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Erschienen in: Structural and Multidisciplinary Optimization 3/2015

01.09.2015 | INDUSTRIAL APPLICATION

Torque control strategy and optimization for fuel consumption and emission reduction in parallel hybrid electric vehicles

verfasst von: Satoshi Kitayama, Marina Saikyo, Yui Nishio, Kojiro Tsutsumi

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 3/2015

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Abstract

To reduce fuel consumption and exhaust emissions in hybrid electric vehicles (HEVs), it is important to develop a well-organized energy management system (EMS). This paper proposes a torque control strategy coupled with optimization for a parallel HEV. A torque control strategy is developed first. In particular, a function to control the driving condition, called the internal combustion engine (ICE) torque control function, is introduced. This function controls the driving conditions (electric motor (EM) driving, ICE driving, and ICE driving assisted by EM) for reducing fuel consumption and exhaust emissions. This function depends on several design variables that should be optimized. Numerical simulation of HEV using Matlab/Simulink is so computationally intensive that a sequential approximate optimization (SAO) using a radial basis function network (RBF) is adopted to determine the optimal values of these design variables. As the result, the optimal ICE torque control function is determined with a small number of simulation runs. In this paper, CO2 and NOx emissions are minimized simultaneously for reducing the fuel consumption and exhaust emission. Through numerical simulations using typical driving cycles, the trade-off between CO2 and NOx emissions is clarified and the validity of the proposed torque control strategy coupled with the proposed optimization is examined.

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Metadaten
Titel
Torque control strategy and optimization for fuel consumption and emission reduction in parallel hybrid electric vehicles
verfasst von
Satoshi Kitayama
Marina Saikyo
Yui Nishio
Kojiro Tsutsumi
Publikationsdatum
01.09.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 3/2015
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-015-1254-8

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