Hướng dẫn python for ece students

This article presents 5 Python project suggestions for engineering students looking to showcase some software development skills while focusing on engineering.

Introduction

Python is a tremendously popular programming language with many applications in science and engineering.

As undergraduate engineers in Ireland, we only completed one programming module on MATLAB. As a result, there was not much emphasis on improving your software development skills, a skill I found to be vital when I entered the industry.

As an aerospace engineer who has worked as a developer and tester and is now embarking on a career in AI and data science, everything I learned about software development is self-taught. For the most part, this is still true today.

One thing I wish I did in college was spend more time tinkering and building small programs based on what I was learning in class. But instead, what I did was learn content with the sole purpose of passing an exam.

Let’s talk about some Python projects you should explore as an engineer if you have free time or want to reinforce some theory you’ve learned.

Below you’ll find the proposals with a brief reason why it’s valuable and the best resources you can follow to get to work.

1) Function Approximation with Taylor Polynomials

Benefit

Taylor series lets you numerically estimate a function like sin(t) or cos(t). Coding this is a terrific little task for engineers as it requires knowledge of symbolic differentiation and numerical methods.

Most students obtain sufficient knowledge in these areas during the first year of university. Taylor series uses these foundational skills, which form the basis of many more advanced topics in science and engineering.

Resources

• What engineering, maths or computer science enthusiast doesn’t know about Grant Sanderson. To understand the underlying nature of the Taylor Series, watch 3Blue1Brown’s video before anything else.
  If the animation on the bottom left looks familiar, I created it using3Blue1Brown’s math animation software, Manim.
• Another beneficial resource is any college calculus textbook. For example, I use Calculus — A Complete Course by Robert A Adams. I don’t own many texts as nowadays you can easily find lecture notes or free online PDF versions of books online.

2) Runge-Kutta Numerical Integration

Benefit

Runge-Kutta is a numerical integration technique. Modelling physical phenomena, such as the change in temperature of a body described by Newton’s law of cooling, incorporates ordinary differential equations (ODEs). Solving ODEs is vital throughout many branches of engineering and science.

Completing this script lays the foundation for the remaining three proposals, so this is probably the most essential to general engineering proficiency.

Resources:

• Good Vibrations with Freeball is a superb YouTube channel for engineers. He implements an RK4 integrator in Python to solve a mass-spring-damper system in Python.
• Secondly, following this lecture by Richard Brunton is ideal for completing this project. At the end of the lesson, he provides the code in MATLAB for an RK4 from scratch. So if you’re struggling to do it in Python, adapt the Matlab code for your purpose.

3) Modelling Dynamic Systems

Benefit

Reinforce the fundamentals of vibrations by modelling the dynamic response of translational mechanical systems. This undertaking is quintessential if you’re interested in vehicle dynamics or spacecraft dynamics.

For example, you can derive a basic model of the suspension of a Formula Onecar, which is pretty cool. Generally, these problems are solved using MATLAB and Simulink, but nothing stops you from doing the same thing in Python.

Resources

• Modelling and Analysis of Dynamic Systems by Charles M. Close. Who doesn’t love finding a free online PDF version of a decent textbook? Very valuable for learning how to derive the system equations of motion and finding sample problems to solve.
• Modelling Dynamic Systems — Rick Hill. Where to start with Dr Rick Hill. For MDS and control systems, the YouTube lectures from Dr Hill are outstanding. I’m sure this set of courses has saved many students, including me, in the past. Thank you for your work, sir.
• Again, Good Vibrations with Freeball is a terrific channel for engineers interested in MDS. Check this link out if you plan to work on this project. There are clear, concise explanations, and the problems are rooted in practical applications.

4) 3D Kinematics Visualisation

Benefit

Simulating a sample trajectory given a particle’s position as a function of time and calculating various other kinematical properties provides a good foundation for more complex dynamics problems.

No numerical integration is required; it is direct plugging and chugging. Although, trajectory visualisation is relatively challenging. However, you don’t need to produce animations for these assignments.

Animations are a nice cherry on the cake for showcasing your work for each project, but understanding how to implement the theory and generate numerical results is the most beneficial aspect.

Resources

• This project stems from an example problem in Orbital Mechanics for Engineering Students. This book contains the mathematical background you need to code this chef-d’oeuvre (artistic masterpiece) in Python using only Numpy and Matplotlib.

5) The Two-Body Problem

Benefit

The final project on the list is not the most difficult, but it is my favourite. Who doesn’t love orbital mechanics? The Two-Body Problem is a classical mechanics problem where you aim to visualise the motion of two bodies due solely to their mutual gravitational attraction.

You can learn to derive the equations of motion, where the process is likely not as complex as you may think. Furthermore, solving them does require numerical integration.

There are tons of fantastic resources to get you started on this project. It is an enjoyable chore if that isn’t an oxymoron, and if you can produce the animations, they are rather satisfying to stare at endlessly for hours (no, just me?).

Resources

• Throughout this article, I heavily reference Orbital Mechanics for Engineering Students. The final two projects originate from the theory presented solely in chapter 1. There are countless more possibilities for projects and simulations in later chapters that you can explore in Python.

Project List

If these project ideas interest you, check out this list with the projects structured in order from beginner to more advanced. I focus on engineering students. However, these projects are for anyone with an interest in maths and science. Also, I constantly refer to Python because that is my programming language preference. If you have skills in a different language, take these ideas and run with them.

Engineering Projects in Python

If you’re interested in Python, engineering, and data science, feel free to follow and check out my other articles.

I hope you found something useful. Thank you for reading.