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ANALYSIS AND MODELLING OF ENERGY SOURCE COMBINATIONS FOR ELECTRIC VEHICLES

Jarushi, Ali Milad

[Thesis]. Manchester, UK: The University of Manchester; 2011.

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Abstract

The objective of this research is to develop suitable models to simulate and analyse Electrical Vehicle (EV) power-trains to identify and improve some of the deficiencies of EVs and investigate new system architectures.Although some electro-chemical batteries improvements have lately been achieved in specific-energy, the power density is still low. Therefore, an efficient, cost-effective and high power density support unit could facilitate EV competitiveness compared to conventional internal combustion engine powered vehicles in the near future.The Na-Ni-Cl2, or ZEBRA battery as it is most commonly known, has good energy and power densities; it is very promising electro-chemical battery candidate for EV’s. The thesis presents a detail simulation model for the ZEBRA technology and investigates its application in an EV power-train with regard to state-of-charge and voltage transients. Unlike other battery systems, the ZEBRA technology can sustain about 5-10% of failed cells. While this is advantageous in single series string or single battery operation it is problematic when higher numbers of batteries are connected in parallel. The simulation model is used to investigate faulted operation of parallel battery configurations.A non-linear capacitance versus voltage function is implemented for the supercapacitor model which yields good energy and terminal voltage predictions when the supercapacitor is cycled over dynamic regimes common to EV applications. A thermal model is also included. Multiple energy source systems are modelled and studied in the form of an energy dense ZEBRA battery connected in parallel with a power dense supercapacitor system. The combination is shown to increase available power, reduce the maximum power demanded from the battery and decrease battery internal power loss. Consequently, battery life would be increased and more energy would be recovered from regenerative braking, enhancing the energy conversion efficiency of the power-train.A combination of ICE and ZEBRA battery is implemented as a range extender for London taxi driving from Manchester to London. The hybridisation ratio of the system is discussed and applied to fulfil the requirement with minimum emissions. This study offers a suitable model for different energy sources, and then optimises the vehicle energy storage combination to realize its full potential. The developed model is used to assess different energy source combinations in order to achieve an energy efficient combination that provides an improved vehicle performance, and, importantly, to understand the energy source interconnection issues in terms of energy flow and circuit transients.

Additional content not available electronically

Matlab/Simulink tool box has been used for modelling the Electric vehicle power-train components

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Electrical and Electronic Engineering
Publication date:
Location:
Manchester, UK
Total pages:
171
Abstract:
The objective of this research is to develop suitable models to simulate and analyse Electrical Vehicle (EV) power-trains to identify and improve some of the deficiencies of EVs and investigate new system architectures.Although some electro-chemical batteries improvements have lately been achieved in specific-energy, the power density is still low. Therefore, an efficient, cost-effective and high power density support unit could facilitate EV competitiveness compared to conventional internal combustion engine powered vehicles in the near future.The Na-Ni-Cl2, or ZEBRA battery as it is most commonly known, has good energy and power densities; it is very promising electro-chemical battery candidate for EV’s. The thesis presents a detail simulation model for the ZEBRA technology and investigates its application in an EV power-train with regard to state-of-charge and voltage transients. Unlike other battery systems, the ZEBRA technology can sustain about 5-10% of failed cells. While this is advantageous in single series string or single battery operation it is problematic when higher numbers of batteries are connected in parallel. The simulation model is used to investigate faulted operation of parallel battery configurations.A non-linear capacitance versus voltage function is implemented for the supercapacitor model which yields good energy and terminal voltage predictions when the supercapacitor is cycled over dynamic regimes common to EV applications. A thermal model is also included. Multiple energy source systems are modelled and studied in the form of an energy dense ZEBRA battery connected in parallel with a power dense supercapacitor system. The combination is shown to increase available power, reduce the maximum power demanded from the battery and decrease battery internal power loss. Consequently, battery life would be increased and more energy would be recovered from regenerative braking, enhancing the energy conversion efficiency of the power-train.A combination of ICE and ZEBRA battery is implemented as a range extender for London taxi driving from Manchester to London. The hybridisation ratio of the system is discussed and applied to fulfil the requirement with minimum emissions. This study offers a suitable model for different energy sources, and then optimises the vehicle energy storage combination to realize its full potential. The developed model is used to assess different energy source combinations in order to achieve an energy efficient combination that provides an improved vehicle performance, and, importantly, to understand the energy source interconnection issues in terms of energy flow and circuit transients.
Additional digital content not deposited electronically:
Matlab/Simulink tool box has been used for modelling the Electric vehicle power-train components
Thesis main supervisor(s):
Funder(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:123309
Created by:
Jarushi, Ali Milad
Created:
20th May, 2011, 13:17:29
Last modified by:
Jarushi, Ali Milad
Last modified:
21st June, 2011, 12:29:10

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