Internship | Electric Vehicle Charging Scheduling Algorithm for Large-Scale Fleets
2 maanden geleden
About this position
In response to the urgent need for zero-emission transportation solutions, particularly in heavy-duty transport, the adoption of Battery Electric Vehicles (BEVs) has gained significant ground. Conventional fleets are rapidly being replaced with BEVs, introducing a set of unique challenges. Logistics companies used to rely on their fully developed and optimized fleet planning software, which is based on conventional trucks. The adoption of BEVs into the fleet introduces new challenges, such as charging of the fleet. There is a clear need for a robust and reliable charging scheduling algorithm suitable for depot charging that tackles the following problems: 1) grid congestion resulting in limited available grid connection, 2) limited amount of chargers, 3) least impact on logistics planning (waiting times, driver breaks, vehicle range). Additional factors that may be included are variable energy supply by local renewable energy sources, local battery energy storage, variable electricity prices, maximizing the battery lifetime, and charging at multiple locations (multi-depot, public charging). TNO has done research in the past on charge planning of electric fleets, but is interested in exploring alternative/new methods to tackle this problem, such as a Distributed Multi-Agent.
What will be your role?
You will do an extensive literature research on charge planning algorithms, the research TNO has conducted, and other relevant literature related to distributed multi-agent based scheduling. You will formulate the problem definition, requirements, constraints, etc. and translate this into a mathematical problem formulation. Based on your findings, you will develop the charging scheduling algorithm, for example, in Matlab or Python. Logistics planning data of a large-scale fleet will be provided to test, validate, and compare the algorithm to TNO’s current tooling.
Assignment tasks:
You will be working in the Powertrains department of the unit Mobility & Built Environment. The department is doing research on all kinds of topics related to sustainable mobility, in the fields H2ICE, Fuell Cells, Batteries, Energy Management, with applications in Heavy-Duty transport, but also Maritime and Defense. You will be discussing your progress on a weekly basis with supervisor. Besides that you can count on support of other colleagues that have experience with EV Charging and Charge Planning Optimization. We encourage you to work from the office to integrate with the team, but working from home is also possible.
What we expect from you
You have a bachelor’s degree in Engineering (i.e. Mechanical, Electrical, Automotive, Mathematics, etc.). You are coursing a master in Engineering (i.e. Mechanical, Electrical, Automotive, Mathematics, etc.) Knowledge in Matlab and/or Python. Knowledge / interested in optimization, scheduling, logistics. You enjoy developing innovative solutions to technically challenging problems and have the right mix of intellectual curiosity and pragmatism.
What you'll get in return
You want an internship opportunity on the precursor of your career; an internship gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Furthermore, we provide:
A highly professional, innovative internship environment, within a team of top experts. A suitable internship allowance ( euro for wo-, hbo- and mbo-students, for a full-time internship). Possibility of eight hours of free leave per internship month (for a full-time internship). A free membership of , where you can meet other TNO professionals and join , such as sports activities, (work-related) courses or the yearly ski-trip. Use of a laptop. An allowance for travel expenses in case you don’t receive an OV-card.-
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