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**Harvard**

Pourabdollah, M., Silvas, E., Murgovski, N., Steinbuch, M. och Egardt, B. (2015) *Optimal Sizing of a Series PHEV: Comparison between Convex Optimization and Particle Swarm Optimization*.

** BibTeX **

@conference{

Pourabdollah2015,

author={Pourabdollah, Mitra and Silvas, Emilia and Murgovski, Nikolce and Steinbuch, Maarten and Egardt, Bo},

title={Optimal Sizing of a Series PHEV: Comparison between Convex Optimization and Particle Swarm Optimization},

booktitle={4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2015, Columbus, United States, 23-26 August 2015},

pages={16-22},

abstract={Building a plug-in hybrid electric vehicle that has a low fuel consumption at low hybridization cost requires detailed design optimization studies. This paper investigates optimization of a PHEV with a series powertrain configuration, where plant and control parameters are found concurrently. In this work two often used methods are implemented to find optimal energy management with component sizes. In the first method, the optimal energy management is found simultaneously with the optimal design of the vehicle by using convex optimization to minimize the sum of operational and component costs over a given driving cycle. To find the integer variable, i.e., engine on-o, dynamic programming and heuristics are used. In the second method, particle swarm optimization is used to find the optimal component sizing, together with dynamic programming to find the optimal energy management. The results show that both methods converge to the same optimal design, achieving a 10.4% fuel reduction from the initial powertrain design. Additionally, it is highlighted that the usage of each of the method
poses challenges, such as computational time (where convex optimization outperform particle swarm optimization by a factor of 20) and the tuning effort for the particle swarm optimization and the ability to handle integer variables of convex optimization.},

year={2015},

}

** RefWorks **

RT Conference Proceedings

SR Electronic

ID 221284

A1 Pourabdollah, Mitra

A1 Silvas, Emilia

A1 Murgovski, Nikolce

A1 Steinbuch, Maarten

A1 Egardt, Bo

T1 Optimal Sizing of a Series PHEV: Comparison between Convex Optimization and Particle Swarm Optimization

YR 2015

T2 4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2015, Columbus, United States, 23-26 August 2015

SP 16

OP 22

AB Building a plug-in hybrid electric vehicle that has a low fuel consumption at low hybridization cost requires detailed design optimization studies. This paper investigates optimization of a PHEV with a series powertrain configuration, where plant and control parameters are found concurrently. In this work two often used methods are implemented to find optimal energy management with component sizes. In the first method, the optimal energy management is found simultaneously with the optimal design of the vehicle by using convex optimization to minimize the sum of operational and component costs over a given driving cycle. To find the integer variable, i.e., engine on-o, dynamic programming and heuristics are used. In the second method, particle swarm optimization is used to find the optimal component sizing, together with dynamic programming to find the optimal energy management. The results show that both methods converge to the same optimal design, achieving a 10.4% fuel reduction from the initial powertrain design. Additionally, it is highlighted that the usage of each of the method
poses challenges, such as computational time (where convex optimization outperform particle swarm optimization by a factor of 20) and the tuning effort for the particle swarm optimization and the ability to handle integer variables of convex optimization.

LA eng

DO 10.1016/j.ifacol.2015.10.003

LK http://dx.doi.org/10.1016/j.ifacol.2015.10.003

LK http://publications.lib.chalmers.se/records/fulltext/221284/local_221284.pdf

OL 30