Thesis: Predictive Charging & Readiness for EV Fleets

Scania Group

Södertälje kommun

On-site

SEK 201,000 - 312,000

Full time

7 days ago

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Job summary

Scania Group is offering a Master’s thesis position in the area of predictive readiness and smart charging for electric heavy vehicles. The project focuses on estimating readiness probability during vehicle charging and using that to optimize charging and preconditioning strategies.

Work involves building probabilistic models, evaluating readiness, and extending strategies to bidirectional power transfer. Start date January 2027 and duration of 20 weeks, with opportunities to contribute to

Qualifications

Master’s student in a relevant field with strong Python & SQL skills.
Solid knowledge of statistics and machine learning.
Fluent English and ability to work in a multidisciplinary environment.

Responsibilities

Review research on departure and energy prediction and smart charging.
Build probabilistic models for departure time and energy and combine with charging progress.
Define how a “not ready” outcome is identified and evaluate the models.
Design and test a charging/preconditioning strategy with historical sessions.
Extend strategy to bidirectional power transfer and estimate feasible energy/power while maintaining readiness.
Estimate the value of flexibility via simulation on historical sessions for use cases such as depot peak shaving or price optimization.
Deliver a prototype view, final report and presentation.