A Simulation-Heuristic Approach to Optimally Design Drone Delivery Systems in Rural Areas

In recent years, drone delivery has become one of the most widely adopted emerging technologies. Under the current Covid-19 pandemic, drones greatly improve logistics, especially in rural areas, where inefficient road networks and long distances between customers reduce the delivery capacity of conventional ground vehicles. Considering the limited flight range of drones, charging stations play essential roles in the rural delivery system. In this study, we utilize simulation to optimize the drone delivery system design, in order to minimize the cost of serving the maximum capacity of customers. As facility siting is usually difficult to optimize, we propose a novel simulation-heuristic framework that continuously improves the objective to find near-optimal solutions. In addition, we conduct a case study using real-world data collected from Knox County, Tennessee. The results suggest that the proposed approach saves over 15% on total costs compared with the benchmark. © 2022 IEEE.

Electric Vehicle Charging Behavior Prediction using Machine Learning Models

The global spread of the COVID-19 pandemic has significantly impacted the electric vehicle (EV) industry. The lockdown restriction has resulted in a significant shift in the use of public charging infrastructures. This paper investigates the effects of COVID-19 on electric vehicle users' charging behavior before, after, and during COVID-19 lockdown restrictions, using the data from a public charging facility from the City of California. In this study, we performed data visualization using K-means and hierarchical clustering analysis. This work uses the vehicle's connection and disconnection time to identify common charging pattern identification and charging behavior where K-means clustering outperforms the hierarchical clustering for all three different scenarios modelled. In addition, prediction of collective charging session duration is achieved using Machine Learning Models, Random Forest and XgBoost. We achieved a mean absolute percentage error (MAPE) of 0.146 and 0.151 percent for XgBoost and Random Forest respectively. © 2022 IEEE.

Location Selection of Charging Stations for Electric Taxis: A Bangkok Case

The transition from ICE to BEV taxis is one of the most important methods for reducing fossil fuel consumption and air pollution in cities such as Bangkok. To support this transition, an adequate number of charging stations to cover each area of charging demand must be established. This paper presents a data-driven process for determining suitable charging locations for BEV taxis based on their characteristic driving patterns. The location selection process employs GPS trajectory data collected from taxis and the locations of candidate sites. Suitable locations are determined based on estimated travel times and charging demands. A queueing model is used to simulate charging activities and identify an appropriate number of chargers at each station. The location selection results are validated using data from existing charging services. The validation results show that the proposed process can recommend better locations for charging stations than current practices. By using the traveling time data that take the current traffic condition into account, e.g., via Google Maps API, we can minimize the overall travel time to charging stations of the taxi fleet better than using the distance data. This process can also be applied to other cities.

Technical Coordination of Aggregated Electric Vehicle Charging and Residential Loads at the Medium Voltage Level

Despite the coronavirus pandemic, the market share of electric vehicles (EV) has increased in recent years. For this reason, planning of new charging stations and active operation of charging stations have become more important. Studies about the integration of electric vehicles are very common, but the parameters and models adopted in these studies are simplified and analyses are made by making contradictory general assumptions. Therefore, there is a need for electric vehicle studies to be carried out with more detailed and realistic parameters. This study includes a wide range of normal and fast charging sessions and the housing demand of several customers. An aggregated charging management solution is developed, to keep the overall demand below the maximum limit at the medium voltage transformer level. This study provides a way to determine the suitability of the infrastructure or the integration challenges in the areas where the installation of parking and charging stations is aimed and proposes solutions. Initial simulation results show peaks at specific time intervals, especially in evening hours and these peaks cause overloads. To solve this problem two different methods were used. The first method is the random selection method, the second method is the sorted selection method. After the solutions are applied, high load values decrease, both worked successfully but the sorted selection method was more flexible and obtained more usable results. On the other hand, random method generally gave mix of good and bad results. © 2022 IEEE.

A Sustainability Improvement Strategy of Interconnected Data Centers Based on Dispatching Potential of Electric Vehicle Charging Stations

With the rapid development of information technology, the electricity consumption of Internet Data Centers (IDCs) increases drastically, resulting in considerable carbon emissions that need to be reduced urgently. In addition to the introduction of Renewable Energy Sources (RES), the joint use of the spatial migration capacity of IDC workload and the temporal flexibility of the demand of Electric Vehicle Charging Stations (EVCSs) provides an important means to change the carbon footprint of the IDC. In this paper, a sustainability improvement strategy for the IDC carbon emission reduction was developed by coordinating the spatial-temporal dispatch flexibilities of the IDC workload and the EVCS demand. Based on the Minkowski sum algorithm, a generalized flexible load model of the EVCSs, considering traffic flow and Road Impedance (RI) was formulated. The case studies show that the proposed method can effectively increase the renewable energy consumption, reduce the overall carbon emissions of multi-IDCs, reduce the energy cost of the DCO, and utilize the EV dispatching potential. Discussions are also provided on the relationship between workload processing time delay and the renewable energy consumption rate.

Comprehensive Assessment of Electric Vehicle Development, Deployment, and Policy Initiatives to Reduce GHG Emissions: Opportunities and Challenges

Embracing innovative vehicle technology in the transportation sector provides constructive solutions to the rising pollution levels and global warming. Developing Electric Vehicles (EV) with market competency, deploying standardized charging infrastructure in sufficient numbers, and government promotional policies all impact EV adoption and help reduce tail pipe emissions. To determine the key hurdles to EV adoption that still exist in today's market, the comparison between the most preferred EV and the Conventionally Propelled Vehicle (CPV) is deliberated under various parameters like vehicle class, type, specification, performance, pricing etc. The research assessed the countries with the most CPV (China, the USA, Japan, Germany, and India), as well as the expertise and experience of the country (Norway) that pioneered the EV industry, to discover the key policies that will help accelerate EV adoption in their respective regions. Significant findings within the local market and across markets belonging to the countries of concern and research recommendations addressing the issues have been discussed as a result of the study conducted with data obtained from the vehicle manufacturer's website, government statistical institutes, and other affiliated survey organizations, as well as technical reports published online. These qualitative and quantitative findings and recommendations will aid in the creation of EV and charging station designs, as well as the formulation of strategies aimed at generating more cost-effective EV designs that take into account local usage patterns, car kinds, and performance. It also assists legislators in their efforts to streamline EV policy. Consideration of these issues aids in the reduction of greenhouse gas (GHG) emissions.

Aerodock (a smart, autonomous charging and docking station for unmanned aerial vehicles)

The COVID-19 pandemic has laid bare the need for contactless operations. While unmanned aerial vehicles (UAVs) are being developed to aid humans in countless domains, the need for effective battery management and performance optimization remains a huge task. The proposed solution, the “AeroDock”, aims to tackle these challenges by using wireless power transfer (WPT) technology coupled with smart monitoring of the drone's health. The performance and hardware checks are assessed at the user end via cloud computing and IoT technology. This system is contact-less, safe, reliable and its usage is not affected by external factors. Thus, the AeroDock is a smart docking station for UAVs which eliminates the need for human intervention in effective charging and maintenance. © 2022 Institute of Physics Publishing. All rights reserved.

Design and Implementation of Solar PV Charging Stations for City of Huntsville Aquatic Center

In addition to ABET-defined course objectives, goals and outcomes, senior design projects also serve as unique bridges between the academia and the communities. Residents at City of Huntsville-Texas Aquatic Center, a city owned recreation center, have had lacked satisfactory shaded areas particularly when they waited for their children or friends while swimming classes were in session. The residents also needed an easy access to AC outlets for charging their smartphones, laptops and other electronic devices. This paper presents design, construction, and operation of two separate solar Photovoltaic (PV) charging stations at the City of Huntsville Aquatic Center as part of a senior design course requirements in a B.S. in Engineering Technology program. 3D-sketches, electrical circuits, Gantt charts, bill of materials and student experience are provided. This senior project initially began with four undergraduate students with multidisciplinary engineering technology majors in Fall 2019, then extended to Spring 2020 due to the scope of the project, and finally completed in August 2020 by two different senior students due to the graduations and Covid-19 pandemic related challenges. The funding for the project was provided by the City of Huntsville. The students and faculty members involved in the senior design project have served for the community outreach purposes. There are two objectives of this senior design project;(1) to provide more shading for guests and staff members in the aquatic center since the area is missing satisfactory shading, (2) to help the city for improving its sustainability efforts by providing renewable energy-based charging stations. Since the project was completed in Summer 2020, the PV charging stations have been used by aquatic center staff and guests extensively both during the day and evening programs since the charging stations also provide lighting through deep-cycle battery storage. This senior project provided students to use their knowledge and increase hands on and project management skills in a real-life environment. Students worked in the project were majored in interdisciplinary majors in the Department of Engineering technology including Engineering Design, construction management, safety management, and electronics and computer engineering technology. Students were also involved in professional meetings with city officials to discuss and present their project progress efforts. The Mayor's office and the aquatic center staff officials expressed their strong interest to work with B.S. in engineering technology senior students and faculty to design and implement more renewable energy projects in future. © American Society for Engineering Education, 2021