Projects
Throughout my academic and professional journey, I have engaged in a variety of engineering projects that highlight my expertise in modeling, simulation, control systems, and sustainable technologies. From fuel cell optimization to electric vehicle control and hybrid vehicle energy analysis, these projects demonstrate my ability to apply advanced engineering principles to solve real-world challenges. Below are some key projects that reflect my technical skills and dedication to innovation.
Project One: Model based Error Analysis of PEM Fuel Cells under real time conditions
Overview:
The focus of this research was to develop a comprehensive model for Proton Exchange Membrane (PEM) fuel cells that captures electrical, thermal, and fluidic dynamics. Using a lumped-parameter approach, the model simplifies the complexity of PEM fuel cell systems while maintaining high accuracy. The goal was to create a model adaptable for real-time conditions and suitable for monitoring the health and performance of the fuel cell.
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Key Contributions:
I developed a lumped-parameter model based on electrochemistry and thermodynamics, integrating core components such as the membrane, catalyst layers, and gas diffusion layers. Model-in-Loop (MIL) simulations were conducted to validate the model against experimental datasets, including the IEEE 2014
A Particle Filter algorithm was implemented for real-time state estimation, achieving less than 7% Root Mean Square (RMS) error compared to experimental data. This work not only demonstrates the model's effectiveness in estimating the internal states of the PEM fuel cell but also lays the groundwork for future research in fuel cell health monitoring and optimization.
Overall, this thesis was graded 1.0, reflecting its high quality and the significant contributions it makes to the field of fuel cell technology.
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Project Two: Field-Oriented Control of PMSM (Permanent Magnet Synchronous Motors)
Overview:
This project focused on analyzing Field-Oriented Control (FOC) algorithms in Simulink to enhance motor control precision and efficiency for electric vehicles (EVs). The goal was to assess the effectiveness of these control strategies in improving the overall performance of electric propulsion systems.
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Key Contributions:
I participated in the analysis of FOC algorithms, evaluating their impact on motor torque and speed control. By applying advanced analytical techniques, I contributed to identifying key performance metrics such as torque production and energy consumption, demonstrating the effectiveness of FOC in optimizing electric vehicle performance. This experience reinforced my understanding of motor control systems and highlighted the potential of FOC to advance electric vehicle technology.
Project Three: Energy Consumption Analysis of Hybrid Powertrains
Objective:
This project aimed to evaluate the energy efficiency of a hybrid vehicle’s powertrain under various driving conditions. My role was to analyze energy flow and power distribution between the combustion engine and electric propulsion systems using MATLAB/Simulink.
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Results:
The analysis led to recommendations on optimizing driving modes and powertrain control strategies. By adjusting the energy flow between the two systems, the overall fuel efficiency improved by 10%. The project provided insights into the best conditions for hybrid operation, helping to align the vehicle's performance with sustainable energy goals.
Project Four: Simulation of derating in an electric powertrain
Objective:
The objective of this demonstration project was to optimize the thermal management system of a hybrid electric vehicle (HEV) to showcase how energy efficiency and battery performance could be improved through advanced thermal control strategies. My role involved using MATLAB/Simulink to model and simulate the vehicle's cooling and heating systems and propose theoretical enhancements to extend battery life and reduce energy consumption.
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Results:
The system analysis and simulations highlighted several key areas where improvements in the thermal management system could theoretically result in significant gains in energy efficiency. Optimized cooling strategies demonstrated the potential to reduce energy consumption by up to 15%. Although the project was a demonstration, these findings emphasized the importance of effective thermal management in enhancing battery longevity and overall vehicle performance.
Project Five: Design and simulation of a hybrid suspension system for heavy-duty vehicles
Overview:
This thesis, conducted in collaboration with a colleague, aimed to design and simulate a novel hybrid suspension system for heavy-duty vehicles, focusing on enhancing ride comfort and vehicle handling. The project integrated coil-over and leaf spring designs to optimize performance under varying load conditions.
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Key Contributions:
Together, we utilized Computer-Aided Design (CAD) tools to develop detailed 3D models of the suspension system, translating engineering requirements into practical design solutions. The project included the development of a control algorithm using MATLAB to optimize suspension response based on different road conditions. We also conducted Finite Element Analysis (FEA) simulations to validate the design, assessing structural integrity and identifying stress concentrations. During the simulation, we evaluated the system's response by varying the base excitation force from 0m to 0.15m and down to -0.15m, reflecting different road profiles. The results indicated that the PID design enable the system to settle within less than 7 seconds when encountering disturbances, showcasing its effectiveness in maintaining ride comfort and stability.This collaborative effort was graded 1.0, reflecting its high quality and significant contribution to the field of automotive engineering.
Project Six : Horizontal Parking Assist System for Trucks
Overview:
This project, conducted in collaboration with a colleague, aimed to develop a Horizontal Parking Assist System specifically designed to assist drivers in parallel parking trucks, enhancing safety and ease of maneuvering in tight spaces through real-time feedback.
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Key Contributions:
We designed a system that integrates advanced sensors and microcontrollers to provide accurate, real-time feedback on the truck's orientation and proximity to surrounding obstacles, facilitating precise parallel parking.
I played a key role in creating a user-friendly interface, inspired by a pilot’s compass, which simplifies the parking process and improves usability for truck drivers.
Conducted extensive testing to evaluate system performance under various conditions and gather user feedback, demonstrating the technology's effectiveness in enhancing parking precision and minimizing accidents.
Our collaborative effort culminated in a comprehensive technical documentation package that details the system architecture, component specifications, and algorithm performance.
This project underscores our commitment to improving vehicle safety and operational efficiency, making the parallel parking process for trucks more accessible and intuitive for drivers.
Project Seven : Real Sense D415 Camera Data Processing
Overview:
In this project, I developed algorithms to process data from the Real Sense D415 Camera for color and depth vision applications. The goal was to enable the camera to accurately detect objects in 3D space, providing both color and depth information for various applications.
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Key Findings:
The algorithms I developed integrated Python scripts within MATLAB for processing the camera data. The system was able to successfully capture and process real-time depth data, with applications in object detection and robotic vision. This project demonstrated the potential of the Real Sense D415 Camera in advanced vision systems, with significant improvements in depth accuracy.
