Master thesis: The Power Behind the Ride: Understanding Micromobility Energy Use
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This Master Thesis Project is not just another academic project — it’s a chance to: Look into real-world embedded systems powering hundreds of thousands of vehicles across Europe. Designing and implementing complex filtering from scratch and to collaborate with experienced embedded developers, gaining practical skills and mentorship.
Sven Åkersten
Embedded Hardware Engineer
The thesis
Shared micromobility vehicles, such as e-scooters and e-bikes, are shaping the future of urban transport. Their success depends not only on user adoption but also on how well they can be adapted into a complex environment. Essential to lower negative effect in cities are user compliance of regulation and ability to support user to follow regulation. Key for this is understanding and improving the vehicles ability to sense placement in time and space.
YOUR MISSION:
This thesis explores how to improve the vehicles sense of placement and orientation by applying sensor fusion into vehicle firmware. Today the vehicles are equipped with multiple sensors. These measurements could be fused with a suitable estimator to improve the quality of the available data. This should be done on edge (the vehicle) due to limitations of network communication, costly and slow in comparison to calculate useful estimates directly on edge.
To implement this requires consideration of real world problems when implementing advanced filtering. Numerical stability, memory usage and making sure the estimator is stable in all possible conditions (initialisation and outliers among other issues must be considered). The implementation should be done in C together with a real time OS in an already existing project. Full freedom to choose filter type, Kalman filter, particle filter or any type of estimator can be evaluated.
STUDENT PROFILE:
We are looking for an electrical engineering, mechatronics/control engineering or computer science student with an interest in:
- Sensor fusion
- Embedded systems/low level programming
- Signal processing
- Hands-on skills and curiosity for signal processing are highly valued, as this project blends advanced signal processing and low level programming.
About Voi Technology
Since 2018, Voi has been on a mission to create safe, sustainable and reliable micromobility for everyone. Today we are the leading shared micromobility operator in Europe, with HQ in Stockholm (Sweden), operating 150,000+ vehicles in 110+ towns and cities across 12 countries, serving 8+ million riders with over 400+ MILLION rides to date, and we have no intention of stopping here! We believe that micromobility will play a central role in changing how people move in our towns and cities in the future and want to ensure that the micromobility transformation happens the right way - through real innovative technology, partnership and transparent dialogue with towns, cities and governments, and by adapting our products to the local needs. In addition to improving quality of life in cities around the world, we are contributing to the solution for climate change by making sustainable transportation options more widely available and promoting renewable energy use and circularity along our supply chain.
Diversity Matters
As a Voiager, we offer you a friendly, collaborative and fast-paced workplace where you can bring your whole self to work, regardless of gender, age, ethnicity, religion, disability or sexual orientation - and welcome applications from whoever you are, including veterans, those actively serving as a Reservist and their partners. What is most important to us is how you treat others and what skills and value you bring to our team. We believe that having a wide diversity of people with different backgrounds and perspectives within Voi is essential to our success in delivering the best user experience to our equally diverse user base. With employees from over 50 nationalities working within Voi, we believe we have made good progress but know we can still do more - therefore we discourage any photos, personal letters, or disclosure of any information that concerns other information than your professional experience.
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