Author Identifier

Bassam Al-Hanahi

https://orcid.org/0000-0002-5205-1059

Date of Award

2023

Document Type

Thesis - ECU Access Only

Publisher

Edith Cowan University

Degree Name

Doctor of Philosophy

School

School of Engineering

First Supervisor

Daryoush Habibi

Second Supervisor

Iftekhar Ahmad

Abstract

In recent years, the global adoption of commercial electric vehicles (CEVs) has been on the rise due to stricter emission standards worldwide. New government regulations and incentives are promoting the large-scale adoption of CEVs, particularly in urban settings where cargo, freight, and delivery entities are prevalent. Charging of CEVs is typically performed at depots and public charging stations along their routes. Returnto- base charging, which involves charging the vehicles at dedicated charging stations at depots, is common. However, simultaneous charging of CEVs can increase peak demand that increases costs and affects infrastructure upgrades. As CEV fleets grow, upgrading the power infrastructure at depots to add charging stations can be costly and impractical. Therefore, it is imperative to effectively manage the charging of large CEV fleets at depots with limited charging infrastructure, while taking into account their operational conditions. These challenges of depot charging also influence the public charging schedules of CEVs along their routes, significantly impacting both the operational costs and the sustainability of logistics services.

To address these issues, this thesis presents novel strategies for coordinating CEV fleet charging at depots and public charging stations. For return-to-base charging, a smart charging system is proposed that manages a CEV fleet with the objective of minimizing the peak demand at the depot, considering different operating conditions of the depots and CEVs, such as the vehicle to grid (V2G) technology and demand response programs. Simulation studies demonstrate that the proposed solution can reduce demand charges by up to 54% compared to uncontrolled charging schemes.

For CEVs that require public charging, an optimization algorithm is developed to address optimal charging and routing problems. The algorithm considers various charging variants, including peak demand, time-of-use tariffs, partial recharging, waiting times, and characteristics of public stations. Results indicate the effectiveness of the developed algorithm in achieving optimal routes that maximize logistics company benefits while satisfying all constraints.

Finally, a new charging strategy for managing the charging of large CEV fleets is being put forward. Specifically, the proposed strategy involves the allocation and coordination of CEV fleets at both limited depot charging stations and public charging stations, taking into account operational schedules, demand charges, and the features of public charging stations. The findings demonstrate the effectiveness of this approach in optimizing CEV charging at different stations, ensuring uninterrupted logistics service, and reducing total travel costs by 30% relative to current solutions.

DOI

10.25958/dvp1-pt78

Access Note

Access to this thesis is restricted to ECU staff and students only

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