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**Harvard**

Pourabdollah, M. (2015) *Optimization of Plug-in Hybrid Electric Vehicles*. Göteborg : Chalmers University of Technology (Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, nr: ).

** BibTeX **

@book{

Pourabdollah2015,

author={Pourabdollah, Mitra},

title={Optimization of Plug-in Hybrid Electric Vehicles},

isbn={978-91-7597-149-0},

abstract={The rising concerns about the global warming and emissions on one hand,
and the limited resources of fossil fuels on the other hand, have made electrification
of vehicles a necessary topic among researchers and companies.
Hybrid electric vehicles (HEV), which in addition to a primary power source,
such as internal combustion engine or fuel cell, have an electric motor and
an electric energy storage, such as a battery, have proved to decrease the
fuel consumption. This is mainly due to regeneration of the braking energy,
possibility to turn the engine off at low power demands, and higher efficiency
gained from the extra freedom in choosing the engine operating points and
downsized engine. Plug-in hybrid electric vehicles (PHEV) have the additional
ability to run on electrical energy charged from the electrical grid due
to their large capacity batteries. However, having extra electrical components
in these vehicles, which results in higher cost, opens new questions
concerning both the energy management and sizing of the components.
This thesis further develops the application of convex optimization to
simultaneously minimize operational and components costs. This means
that besides the optimal component sizes, the optimization gives the optimal
energy management strategy. Two different configurations, namely
parallel and series PHEVs, are investigated. For a parallel PHEV, the effect
of different performance requirement levels and battery prices on the
optimal costs and sizes are investigated. For a series PHEV, the effect
of driver’s driving and charging behaviors, performance requirements, and
pricing scenarios on the optimal component sizes in different configurations
are studied. To generate driving cycles that reflect driving patterns of different
drivers, a systematic method based on Markov chain is used.
Moreover, the impact of reduction in modeling detail is investigated on
both computational time and accuracy of the results in the optimal sizing
of a fuel cell PHEV. To cope with the integer variables in the problem, an
iterative method using dynamic programming and convex optimization is
introduced.},

publisher={Institutionen för signaler och system, Reglerteknik, Chalmers tekniska högskola,},

place={Göteborg},

year={2015},

series={Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, no: },

}

** RefWorks **

RT Dissertation/Thesis

SR Print

ID 212374

A1 Pourabdollah, Mitra

T1 Optimization of Plug-in Hybrid Electric Vehicles

YR 2015

SN 978-91-7597-149-0

AB The rising concerns about the global warming and emissions on one hand,
and the limited resources of fossil fuels on the other hand, have made electrification
of vehicles a necessary topic among researchers and companies.
Hybrid electric vehicles (HEV), which in addition to a primary power source,
such as internal combustion engine or fuel cell, have an electric motor and
an electric energy storage, such as a battery, have proved to decrease the
fuel consumption. This is mainly due to regeneration of the braking energy,
possibility to turn the engine off at low power demands, and higher efficiency
gained from the extra freedom in choosing the engine operating points and
downsized engine. Plug-in hybrid electric vehicles (PHEV) have the additional
ability to run on electrical energy charged from the electrical grid due
to their large capacity batteries. However, having extra electrical components
in these vehicles, which results in higher cost, opens new questions
concerning both the energy management and sizing of the components.
This thesis further develops the application of convex optimization to
simultaneously minimize operational and components costs. This means
that besides the optimal component sizes, the optimization gives the optimal
energy management strategy. Two different configurations, namely
parallel and series PHEVs, are investigated. For a parallel PHEV, the effect
of different performance requirement levels and battery prices on the
optimal costs and sizes are investigated. For a series PHEV, the effect
of driver’s driving and charging behaviors, performance requirements, and
pricing scenarios on the optimal component sizes in different configurations
are studied. To generate driving cycles that reflect driving patterns of different
drivers, a systematic method based on Markov chain is used.
Moreover, the impact of reduction in modeling detail is investigated on
both computational time and accuracy of the results in the optimal sizing
of a fuel cell PHEV. To cope with the integer variables in the problem, an
iterative method using dynamic programming and convex optimization is
introduced.

PB Institutionen för signaler och system, Reglerteknik, Chalmers tekniska högskola,

T3 Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, no:

LA eng

OL 30