About
As an automobile engineer with professional skill in CAD design and 3D modeling, I have extensive experience in designing and developing innovative and efficient vehicle components and systems.
My strengths include a deep understanding of vehicle dynamics and performance, as well as expertise in using CAD design and 3D modeling software to create accurate and detailed designs.
I have a strong skillset in various CAD design and 3D modeling tools, including AutoCAD, SolidWorks, Fusion 360, and NXCAD. I have also worked on projects involving Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) simulations to optimize vehicle designs.
One of my notable accomplishments is designing and developing a new suspension system for an electric unicycle car, which resulted in a significant increase in performance and handling. I have also worked on projects involving the design and development of conventional vehicle battery systems, as well as chassis and body design.
In terms of education, I have a Bachelor's degree in Automobile Engineering and have completed various training courses in CAD design and 3D modeling.
Overall, I am committed to delivering high-quality design solutions that meet or exceed client expectations. With my expertise in automobile engineering and CAD design and 3D modeling, I am confident in my ability to contribute to the success of any project.
Experience
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Conventional Vehicle battery life prediction
GSG Motors · Part-time
Sep 2021 –
Present
3 yrs 3 mos
Accra, Greater Accra Region, Ghana
Conventional battery life prediction is a critical area of research in the field of battery technology. The aim of this project is to develop an accurate and reliable battery life prediction model that can help improve the performance and longevity of conventional batteries.
To accomplish this project, we will first collect data on various parameters that affect battery life, including temperature, humidity, discharge rate, and charging rate. We will then use this data to train machine learning models to predict battery life under different conditions.
We will use a combination of supervised and unsupervised learning techniques to develop the prediction model. This will involve feature engineering, data cleaning, and exploratory data analysis to identify the most important factors that affect battery life.
Once the model is trained, we will test it on a variety of different battery types and conditions to evaluate its accuracy and reliability. We will also compare our model's predictions to those of existing battery life prediction models to determine its performance.
The results of this project will be useful for a wide range of applications, including the development of more efficient and reliable battery-powered devices, the optimization of battery charging and discharging processes, and the development of new battery technologies. Ultimately, this project aims to contribute to the advancement of battery technology and the creation of more sustainable and efficient energy systems.
Education
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Kwame Nkrumah University of Science and Technology
BSC, Automobile Engineering, 60.38
2018 – 2022
Activities and Societies:
AAES KNUST
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Apostle Safo School of Arts and sciences
High school diploma, Automobile Mechanics, 11
2016 – 2018