Engineering Commons^™

Analog & Digital Remote Synthesizer, Adam Brunner, Andrew Cihon-Scott, Scott Grisso, Linus Wright

Williams Honors College, Honors Research Projects

The purpose of this project is to develop and design an analog synthesizer musical instrument that integrates embedded digital hardware into the design to enable control from a remote source. The use of digital hardware enables the potential for a wide range of convenient features such as sound profile saving and loading, output recording functionality, and the ability to accept digital input from another musical instrument utilizing the Musical Instrument Digital Interface (MIDI). In addition to the synthesizer itself, this project also includes the design of a companion application that can be hosted on a wide variety of consumer computing …

On The (Im)Practicality Of Adversarial Perturbation For Image Privacy, Arezoo Rajabi, Rakesh B. Bobba, Mike Rosulek, Charles Wright, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Image hosting platforms are a popular way to store and share images with family members and friends. However, such platforms typically have full access to images raising privacy concerns. These concerns are further exacerbated with the advent of Convolutional Neural Networks (CNNs) that can be trained on available images to automatically detect and recognize faces with high accuracy.

Recently, adversarial perturbations have been proposed as a potential defense against automated recognition and classification of images by CNNs. In this paper, we explore the practicality of adversarial perturbation based approaches as a privacy defense against automated face recognition. Specifically, we first …

On The Usage And Vulnerabilities Of Api Systems, Conner D. Yu

Cybersecurity Undergraduate Research Showcase

To some, Application Programming Interface (API) is one of many buzzwords that seem to be blanketed in obscurity because not many people are overly familiar with this term. This obscurity is unfortunate, as APIs play a crucial role in today’s modern infrastructure by serving as one of the most fundamental communication methods for web services. Many businesses use APIs in some capacity, but one often overlooked aspect is cybersecurity. This aspect is most evident in the 2018 misuse case by Facebook, which led to the leakage of 50 million users’ records.1 During the 2018 Facebook data breach incident, threat actors …

The Digitization Of Court Processes In African Regional And Subregional Judicial Institutions, Frederic Drabo

Walden Dissertations and Doctoral Studies

Despite information technology (IT) officers’ multiple efforts to develop reliable and efficient electronic justice (e-justice) systems, digitizing court processes still presents several quality challenges associated with IT infrastructure and literacy issues. Grounded in the principles of total quality management, the purpose of this qualitative multiple case study was to identify strategies and best practices IT officers in African regional economic communities (REC) use for digitizing regional and subregional court processes to improve African e-justice systems. The participants included four IT officers working as assistant computer system analysts (ACSA), computer system analysts (CSA), and heads of IT (HIT) in regional and …

Strategies For Catalyzing Clinicians’ Support Of Telemedicine Programs In Rural Communities, Jonathan Liwag

Walden Dissertations and Doctoral Studies

Clinicians’ failure to accept contemporary technology has been a critical barrier to telemedicine program adoption. Staff technical challenges and resistance to change can affect technology return on investment, which concerns telemedicine program leaders. Grounded in Davis’s technology acceptance model, the purpose of this qualitative, descriptive single case study was to explore strategies used by program leaders in the Marianas Islands who successfully gained clinicians’ acceptance of contemporary technology. The participants were 5 program leaders recommended by their institution because of their leadership role and telemedicine technologies experience. Data were collected from 4 face-to-face and 1 audio teleconference interview with the …

Optimizing Peer Selection Among Internet Service Providers (Isps), Shahzeb Mustafa

Electronic Theses and Dissertations, 2020-2023

Connections among Internet Service Providers (ISPs) form the backbone of the Internet. This enables communications across the globe. ISPs are represented as Autonomous Systems (ASes) in the global Internet and inter-ISP traffic exchange takes place via inter-AS links, which are formed based on inter-ISP connections and agreements. In addition to customer-provider agreements, a crucial type of inter-ISP agreement is peering. ISP administrators use various platforms like AP-NIC and NANOG networking events for establishing new peering connections in accordance with their business and technical needs. Such methods are often inefficient and slow, potentially resulting in missed opportunities or sub-optimal routes. The …

Distributed Cross-Community Collaboration For The Cloud-Based Energy Management Service, Yu-Wen Chen, J. Morris Chang

Publications and Research

Customers’ participation is a critical factor for inte-grating the distributed energy resources via demand response and demand-side management programs, especially when customers become prosumers. Incentives need to be delivered by the energy management service to attract prosumers to operate their distributed energy resources and electricity loads grid-friendly actively. The cloud-based energy management service enables virtual trading for customers within the same community to minimize cost and smooth the fluctuation. With the potential fast-growing number of service providers and customers, the needs exist for efficiently collaborating across multiple service providers and customers. This paper proposes the distributed cross-community collaboration (XCC) for …

Appointment Scheduling System, Guzaloi Noori

Undergraduate Honors Theses

Appointment Scheduling System designed for universities so that students can schedule appointments with their university’s faculty and staff regarding academic, employment, immigration, or personal issues. The scheduling system has the ability of being embedded to the Computer Science Capstone project iAcademic, which I took part in as a front-end developer.

Improving Performance And Flexibility Of Fabric-Attached Memory Systems, Vamsee Reddy Kommareddy

Electronic Theses and Dissertations, 2020-2023

As demands for memory-intensive applications continue to grow, the memory capacity of each computing node is expected to grow at a similar pace. In high-performance computing (HPC) systems, the memory capacity per compute node is decided upon the most demanding application that would likely run on such a system, and hence the average capacity per node in future HPC systems is expected to grow significantly. However, diverse applications run on HPC systems with different memory requirements and memory utilization can fluctuate widely from one application to another. Since memory modules are private for a corresponding computing node, a large percentage …

Are We In The Digital Dark Times? How The Philosophy Of Hannah Arendt Can Illuminate Some Of The Ethical Dilemmas Posed By Modern Digital Technologies, Damian Gordon, Anna Becevel

Conference Papers

Philosophers are not generally credited with being clairvoyant, and yet because they recognise, record and reflect on trends in their society, their observations can often appear prescient. In the field of the ethics of technology, there is, perhaps, no philosopher whose perspective on these issues is worth examining in detail more than that of Hannah Arendt, who can offer real perspective on the challenges we are facing with technologies in the twenty-first century. Arendt, a thinker of Jewish-German origin, student of Martin Heidegger and Karl Jaspers, encountered her life turning point when she was forced into becoming a refugee as …

Utilizing Resonant Scattering Signal Characteristics Via Deep Learning For Improvedclassification Of Complex Targets, Tuğçe Toprak, Mustafa Alper Selver, Mustafa Seçmen, Emi̇ne Yeşi̇m Zoral

Turkish Journal of Electrical Engineering and Computer Sciences

Object classification using late-time resonant scattering electromagnetic signals is a significant problem found in different areas of application. Due to their unique properties, spherical objects play an essential role in this field both as a challenging target and a resource of analytical late-time resonant scattering electromagnetic signals. Although many studies focus on their detailed analysis, the challenges associated with target classification by resonant late-time resonant scattering electromagnetic signals from multilayer spheres have not been investigated in detail. Moreover, existing studies made the simplifying assumption that the objects having (one or more) layers constitute equal permeability values at the core and …

An Improved Version Of Multi-View K-Nearest Neighbors (Mvknn) For Multipleview Learning, Eli̇fe Öztürk Kiyak, Derya Bi̇rant, Kökten Ulaş Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

Multi-view learning (MVL) is a special type of machine learning that utilizes more than one views, where views include various descriptions of a given sample. Traditionally, classification algorithms such as k-nearest neighbors (KNN) are designed for learning from single-view data. However, many real-world applications involve datasets with multiple views and each view may contain different and partly independent information, which makes the traditional single-view classification approaches ineffective. Therefore, this article proposes an improved MVL algorithm, called multi-view k-nearest neighbors (MVKNN), based on the existing KNN algorithm. The experimental results conducted in this research show that a significant improvement is achieved …

Arkhe - Unmanned Detection Robot, Hannah Klooster

Senior Honors Theses and Projects

Our project is an Unmanned Thermal Detection Robot. Our robot contains a visual camera, a sonar sensor, and a thermal sensor. This project involves hardware building and coding of the sensors and robot itself. The purpose of this project is to create an accessible and affordable unmanned robot with sensors capable of being able to detect human life forms in disaster areas, or areas inaccessible to humans, and to protect the lives of rescuers, find people in disaster areas quicker, and to help save lives. Our project has successfully created an affordable robot that uses sensors to detect and avoid …

Scalable Approaches For Auditing The Completeness Of Biomedical Ontologies, Fengbo Zheng

Theses and Dissertations--Computer Science

An ontology provides a formalized representation of knowledge within a domain. In biomedicine, ontologies have been widely used in modern biomedical applications to enable semantic interoperability and facilitate data exchange. Given the important roles that biomedical ontologies play, quality issues such as incompleteness, if not addressed, can affect the quality of downstream ontology-driven applications. However, biomedical ontologies often have large sizes and complex structures. Thus, it is infeasible to uncover potential quality issues through manual effort. In this dissertation, we introduce automated and scalable approaches for auditing the completeness of biomedical ontologies. We mainly focus on two incompleteness issues -- …

A Monte-Carlo Analysis Of Monetary Impact Of Mega Data Breaches, Mustafa Canan, Omer Ilker Poyraz, Anthony Akil

Engineering Management & Systems Engineering Faculty Publications

The monetary impact of mega data breaches has been a significant concern for enterprises. The study of data breach risk assessment is a necessity for organizations to have effective cybersecurity risk management. Due to the lack of available data, it is not easy to obtain a comprehensive understanding of the interactions among factors that affect the cost of mega data breaches. The Monte Carlo analysis results were used to explicate the interactions among independent variables and emerging patterns in the variation of the total data breach cost. The findings of this study are as follows: The total data breach cost …

Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura

Browse all Theses and Dissertations

Classification is an important branch of machine learning that impacts many areas of modern life. Many classification algorithms (classifiers for short) have been developed. They have highly different levels of sophistication and classification accuracy. Classification problems often have highly different levels of hardness and complexity. Practitioners of classification modeling need better understanding of those algorithms in order to select the optimal algorithm for given classification problems. Researchers of classification need new insight on how given classifiers are weak and how they can be improved by correcting their classification errors. This dissertation introduces new tools and concepts to analyze classifier weakness …

Orientation And Social Influences Matter: Revisiting Neutralization Tendencies In Information Systems Security Violation, Frank Curtis King

CCAC Theses and Dissertations

It is estimated that over half of all information systems security breaches are due directly or indirectly to the poor security practices of an organization’s employees. Previous research has shown neutralization techniques as having influence on the intent to violate information security policy. In this study, we proposed an expansion of the neutralization model by including the effects of business and ethical orientation of individuals on their tendencies to neutralize and compromise with information security policy. Additionally, constructs from social influences and pressures have been integrated into this model to measure the impact on the intent to violate information security …

Long Short-Term Memory With Spin-Based Binary And Non-Binary Neurons, Meghana Reddy Vangala

Electronic Theses and Dissertations, 2020-2023

Research in the field of neural networks has shown advancement in the device technology and machine learning application platforms of use. Some of the major applications of neural network prominent in recent scenarios include image recognition, machine translation, text classification and object categorization. With these advancements, there is a need for more energy-efficient and low area overhead circuits in the hardware implementations. Previous works have concentrated primarily on CMOS technology-based implementations which can face challenges of high energy consumption, memory wall, and volatility complications for standby modes. We herein developed a low-power and area-efficient hardware implementation for Long Short-Term Memory …

Spectral And Latent Representation Distortion For Tts Evaluation, Thananchai Kongthaworn

Chulalongkorn University Theses and Dissertations (Chula ETD)

One of the main problems in the development of text-to-speech (TTS) systems is its reliance on subjective measures, typically the Mean Opinion Score (MOS). MOS requires a large number of people to reliably rate each utterance, making the development process slow and expensive. Recent research on speech quality assessment tends to focus on training models to estimate MOS, which requires a large number of training data, something that might not be available in low-resource languages. We propose an objective assessment metric based on the DTW distance using the spectrogram and the high-level features from an Automatic Speech Recognition (ASR) model …

Improved Secure And Low Computation Authentication Protocol For Wireless Body Area Network With Ecc And 2d Hash Chain, Soohyeon Choi

Electronic Theses and Dissertations

Since technologies have been developing rapidly, Wireless Body Area Network (WBAN) has emerged as a promising technique for healthcare systems. People can monitor patients’ body condition and collect data remotely and continuously by using WBAN with small and compact wearable sensors. These sensors can be located in, on, and around the patient’s body and measure the patient’s health condition. Afterwards sensor nodes send the data via short-range wireless communication techniques to an intermediate node. The WBANs deal with critical health data, therefore, secure communication within the WBAN is important. There are important criteria in designing a security protocol for a …

Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.

Energy-Aware Real-Time Scheduling On Heterogeneous And Homogeneous Platforms In The Era Of Parallel Computing, Ashik Ahmed Bhuiyan

Electronic Theses and Dissertations, 2020-2023

Multi-core processors increasingly appear as an enabling platform for embedded systems, e.g., mobile phones, tablets, computerized numerical controls, etc. The parallel task model, where a task can execute on multiple cores simultaneously, can efficiently exploit the multi-core platform's computational ability. Many computation-intensive systems (e.g., self-driving cars) that demand stringent timing requirements often evolve in the form of parallel tasks. Several real-time embedded system applications demand predictable timing behavior and satisfy other system constraints, such as energy consumption. Motivated by the facts mentioned above, this thesis studies the approach to integrating the dynamic voltage and frequency scaling (DVFS) policy with real-time …

A Comparison Of Artificial Neural Networks And The Statistical Methods In Predicting Mba Student’S Academic Performance, Ojoung Kwon, Harry Hui Xia, Serin Zhang

Journal of International Technology and Information Management

MBA has become one of the most popular and vital professional degrees internationally. The MBA program admission process’s essential task is to choose the best analysis tools to accurately predict applicants’ academic performance potential based on the evaluation criteria in making admission decisions. Prior research finds that the Graduate Management Admission Test (GMAT) and undergraduate grade point average (UGPA) are common predictors of MBA academic performance indicated by graduate grade point average (GGPA). Using a sample of 250 MBA students enrolled in a state university with AACSB accreditation from Fall 2010 to Fall 2017, we test and compare the effectiveness …

An Integrated View Of Knowledge Management Enablers, Components, And Benefits: Comprehensive Literature Review, Shuaibu Hassan Usman, Jigish Zaveri, Aminu Hamza

Journal of International Technology and Information Management

The key to success in the 21^st century, knowledge-based economy, will be the effective and efficient management of knowledge. Knowledge Management (KM) has a direct impact on organizational success. KM in a knowledge-based economy entails growth, value, and improving living standards through knowledge creation, storage, and dissemination. This study aims to integrate KM enablers, components, and benefits into a single view through a comprehensive literature search. The integrative view of these three factors would facilitate the understanding of KM initiatives within organizations. This paper performs a comprehensive literature review to explain the KM enablers, components, and benefits. From the …

การสร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันของซอฟต์แวร์จากการจำแนกบทวิจารณ์ของผู้ใช้งานโมไบล์แอปพลิเคชัน, ธนัชชา พันธ์ธรรม

Chulalongkorn University Theses and Dissertations (Chula ETD)

บทวิจารณ์ของผู้ใช้งานเป็นแหล่งข้อมูลที่สำคัญสำหรับนักพัฒนาโมไบล์แอปพลิเคชัน เพื่อใช้ในการปรับปรุงและวิวัฒนาการแอปพลิเคชันหลังจากที่ได้ปล่อยให้ใช้งานไปแล้ว เนื่องจากข้อมูลบทวิจารณ์ของผู้ใช้งานมีจำนวนมากจึงเป็นเรื่องยุ่งยากสำหรับทีมนักพัฒนาโมไบล์แอปพลิเคชันที่จะระบุว่าบทวิจารณ์ของผู้ใช้งานใดประกอบไปด้วยข้อมูลที่เป็นประโยชน์ต่อการปรับปรุงและวิวัฒนาการโมไบล์แอปพลิเคชันเพิ่มเติม วิทยานิพนธ์นี้นำเสนอความพยายามที่จะอำนวยความสะดวกให้แก่ทีมนักพัฒนาในขั้นต้นด้วยการสร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันโดยอัตโนมัติจากข้อมูลบทวิจารณ์ของผู้ใช้งานโมไบล์แอปพลิเคชันบนแอปสโตร์และเพลย์สโตร์ แนวทางที่นำเสนอประกอบด้วยสามขั้นตอน เริ่มจากการใช้อัลกอริทึมการจำแนกข้อความเพื่อจำแนกบทวิจารณ์ของผู้ใช้งานออกเป็นบทวิจารณ์ของผู้ใช้งานเชิงฟังก์ชันหรือที่ไม่ใช่เชิงฟังก์ชัน ขั้นตอนที่สองบทวิจารณ์ของผู้ใช้งานที่ไม่ซ้ำกันจะถูกระบุโดยใช้เทคนิคการจัดกลุ่มและการวิเคราะห์ความคล้ายคลึงกันของข้อความ ในขั้นตอนสุดท้ายข้อมูลที่มีความสำคัญจะถูกสกัดจากบทวิจารณ์ของผู้ใช้งานเพื่อใช้สร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันโดยใช้แบบรูปข้อมูลบทวิจารณ์ของผู้ใช้งานและแม่แบบความต้องการ ในส่วนของการประเมินผล ความต้องการที่ถูกสร้างขึ้นจากแนวทางที่นำเสนอได้รับคะแนนต่ำถึงสูงแตกต่างกันไปในแง่ของความสามารถในการอ่านได้ง่าย ความไม่กำกวม ความสมบูรณ์ และความสมเหตุสมผล ซึ่งแนวทางที่วิทยานิพนธ์นำเสนอนี้สามารถช่วยทีมนักพัฒนาระบุถึงความต้องการการเปลี่ยนแปลงทั้งในเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันจากเสียงสะท้อนโดยตรงของผู้ใช้งานซึ่งควรได้รับการพิจารณาเพื่อใช้ในการปรับปรุงและวิวัฒนาการโมไบล์แอปพลิเคชันต่อไป

Transforming Timing Diagram Into Timed Automata For Preemptive Scheduling, อมรัตน์ พิมโคตร

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานที่เกิดขึ้นพร้อมกันในระบบเรียลไทม์อาจต้องการทรัพยากรที่ใช้ร่วมกันอย่างจำกัด เช่นการใช้งานร่วมกันของ CPU เพียงตัวเดียวที่มีงานเป็นจำนวนมาก เมื่อใช้การจัดกระบวนการเชิงพรีเอ็มทีฟ ซึ่งงานที่กำลังทำงานอยู่ที่มีค่าลำดับความสำคัญต่ำกว่ามักจะถูกจัดลำดับให้อยู่ในสถานะพักการทำงานหรือสถานะโดเมน โดยงานใหม่ที่มีค่าลำดับความสำคัญสูงกว่าจะเข้ามาแทนที่ สุดท้ายจึงกลายเป็นว่างานใหม่เข้ามาทำงานแทนลำดับงานที่โดนแทรกหรือถูกพรีเอ็มทีฟไว้ก่อนหน้านี้ที่มีค่าลำดับความสำคัญต่ำกว่า งานที่มีค่าลำดับความสำคัญต่ำกว่าดังกล่าวจะเริ่มต้นทำงานอีกครั้งเพื่อดำเนินการต่อในสถานะที่ทำงานทันทีหลังจากงานที่มีค่าลำดับความสำคัญสูงกว่าได้ทำงานเสร็จสิ้น แผนภาพเวลาเป็นแผนภาพที่มีลักษณะงานเป็นอิสระต่อกัน และงานจะถูกเริ่มต้นพร้อมกัน ผลกระทบของการจัดกระบวนการเชิงพรีเอ็มทีฟเอาไว้จะมีความสัมพันธ์กันและทำให้การดำเนินของเส้นเวลาหรือไทม์ไลน์ของงานที่เกิดขึ้นพร้อมกันเหล่านี้ถูกเปลี่ยนแปลงไป กฎการจับคู่สำหรับการแปลงแผนภาพเวลาที่เป็นอิสระต่อกันเป็นไทมด์ออโตมาตาที่ได้รับการออกแบบในวิทยานิพนธ์นี้ และยังมีเครื่องมือซอฟต์แวร์ที่ได้รับการพัฒนาเพื่อแปลงไฟล์ต้นทางนำเข้าสกุลไฟล์ XML ของแผนภาพเวลาเป็นไฟล์ไทมด์ออโตมาตา สามารถจำลองแผนภาพไทมด์ออโตมาตาด้วยเครื่องมือ UPPAAL ซึ่งผลลัพธ์ของไทมด์ออโตมาตาจะแสดงกรอบเวลาโดยรวมของงานที่เกิดขึ้นพร้อมกันอันเป็นผลกระทบของการจัดกำหนดการเชิงฟรีเอ็มทีฟ การจำลองไทมด์ออโตมาตาจะจัดเตรียมตัวแปรนาฬิกาและสถานะโดเมนพิเศษเพิ่มเติม จากนั้นจึงนำไทมด์ออโตมาตาที่แปลงมาทวนสอบคุณสมบัติ TCTL ว่าการทำงานนั้นถูกต้อง เครื่องมือซอฟต์แวร์ของเราจะดำเนินการแปลงไดอะแกรมสำหรับการจัดกระบวนการเชิงพรีเอ็มทีฟ และใช้กรณีศึกษาสามกรณีเพื่อแสดงกระบวนการแปลงและการจำลองขั้นตอนกระบวนการทำงาน

Human-Robot Collaboration Enabled By Real-Time Vision Tracking, Travis Deegan

Electronic Theses and Dissertations

The number of robotic systems in the world is growing rapidly. However, most industrial robots are isolated in caged environments for the safety of users. There is an urgent need for human-in-the-loop collaborative robotic systems since robots are very good at performing precise and repetitive tasks but lack the cognitive ability and soft skills of humans. To fill this need, a key challenge is how to enable a robot to interpret its human co-worker’s motion and intention. This research addresses this challenge by developing a collaborative human-robot interface via innovations in computer vision, robotics, and system integration techniques. Specifically, this …

Human Activity Recognition Based On Wearable Flex Sensor And Pulse Sensor, Xiaozhu Jin

Electronic Theses and Dissertations

In order to fulfill the needs of everyday monitoring for healthcare and emergency advice, many HAR systems have been designed [1]. Based on the healthcare purpose, these systems can be implanted into an astronaut’s spacesuit to provide necessary life movement monitoring and healthcare suggestions. Most of these systems use acceleration data-based data record as human activity representation [2,3]. But this data attribute approach has a limitation that makes it impossible to be used as an activity monitoring system for astronavigation. Because an accelerometer senses acceleration by distinguishing acceleration data based on the earth’s gravity offset [4], the accelerometer cannot read …

Research Framework Of Human Factors Interactions With Technical And Security Factors In Cloud Computing, Hongjiang Xu, Sakthi Mahenthiran

Scholarship and Professional Work - Business

There are many advantages to adopt cloud computing, however, some important issues need to be addressed, such as cybersecurity, cost-saving, trust, implementation complexity, and cloud provider’s reliability. This study developed a research framework to study the human factors that interact with technical and cybersecurity factors to affect the cloud-computing provider’s performance from the user’s perspective. Research hypotheses were developed and a survey was conducted to test the hypotheses and validate the research framework.

Speed-Sensorless Predictive Torque Controlled Induction Motor Drive Withfeed-Forward Control Of Load Torque For Electric Vehicle Applications, Emrah Zerdali̇, Ridvan Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, the global trend is towards reducing CO2 emissions and one solution is to replace internal combustion vehicles with electric vehicles. To this end, electric drive system, the most crucial part of an electric vehicle, has gained importance and has become a major research field. The induction motor (IM) is one of the best candidates for electric vehicle applications due to its advantages such as having simple and robust design, its low cost maintenance requirements and the ability to operate in harsh environments. However, it has a highly nonlinear model with timevarying electrical and mechanical parameters making them difficult to …