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Design of a parallel-series hybrid electric vehicle using multi-objective optimization techniques


Design of a parallel-series hybrid electric vehicle using multi-objective optimization techniques

Frantzeskakis, Petros (1994) Design of a parallel-series hybrid electric vehicle using multi-objective optimization techniques. Masters thesis, Concordia University.

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The objective of this thesis is to experimentally and analytically study and design a parallel-series Hybrid Electric Vehicle. The time response, power to cost ratio and overall electric drive efficiency were the criteria used in the selection of the electric drive unit. The results of constant current battery tests on several lead-acid batteries, namely Eastern-Penn RV31, Delco Voyageur 27FMF, Chloride 6EF7, Optima 800, and Eastern-Penn RV27 are presented. Furthermore, constant power tests results for two nickel-cadmium batteries (Saft Nife STM1.130 and Marathon 44SP100) along with the Eastern-Penn RV31 are presented. The Universal Battery Model was slightly modified and used to evaluate analytically the energy and power density of the RV31, STM1.130, and 44SP100 battery systems. Thereafter the analytical results of these batteries were compared with the experimental constant power battery test results. A mathematical model using governing vehicle dynamics equations was developed in the time domain for this investigation. The good agreement between the calculated and experimental results provided confidence to use the mathematical model for carrying out a multi-objective optimization on the electric drive system of the vehicle. The objectives investigated were specific energy, cost and cycle life of the battery system, range and acceleration. The mass of the battery pack, operating voltage of the electric drive system, specific energy density and final drive gear ratio were selected as design parameters. An experimental investigation was performed on the series mode of operation of the hybrid electric vehicle. The results of this investigation were used in the formulation of a multi-objective optimization procedure, which enabled the optimal tuning of the series mode of operation.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Frantzeskakis, Petros
Pagination:xxiv, 185 leaves : ill ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical and Industrial Engineering
Thesis Supervisor(s):Sanker, S
ID Code:69
Deposited By: Concordia University Library
Deposited On:27 Aug 2009 17:09
Last Modified:18 Jan 2018 17:12
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