Date of Award

1-14-2020

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Industrial and Manufacturing Systems Engineering

Keywords

electric vehicles, lithium-ion batteries, reverse logistics, stochastic processes

Supervisor

Walid Kader

Rights

info:eu-repo/semantics/openAccess

Abstract

Electric Vehicles are becoming trendy and proved to have no harmful exhaust like traditional fuel-powered vehicles which makes them one of the best solution to reduce greenhouse gas emissions. As the world shifts towards electric vehicle adoption, we will need efficient power sources to provide enough capacity for all these vehicles to function. Lithium-Ion batteries are the driving force behind this new trend. The goal of this research is to analyze the lifespan and long-term ratio composition of Lithium-Ion batteries in electric vehicles by developing two models, an Absorbing Markov Chain model, and a Markov Chain Steady-State Census model. A sensitivity analysis is also conducted to alleviate the scarcity of enough input data. The models show that the lifespan of the new batteries can be extended by 4.5 years, which will have a positive environmental impact and reap economic benefits. Further, the long term composition of batteries in New, remanufactured, repurposed and recycled states can be projected. The increasing demand for EVs globally has created a necessity for more batteries to power them, and these batteries require materials to be made. By considering reverse logistics processes, it is possible to recycle batteries and recover the valuable materials. Not only does this support the environment, but given the rising demand and finite raw material supply, there is an opportunity to capture the economic benefit of recycling. From this research, the recovered materials cobalt, lithium, and nickel are calculated, and this is especially important for the optimal planning of sustainable manufacturing.

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