Teaching-learning process

Official Degree

Master Degree in Smart Energy Systems. Pending design and verification-authorization by UNIBASQ (*)

Duration

90 ECTS

1,5 years

Campus

Orona-Ideo

Class size

25 places

Languages

Spanish, English

Modality

On-site

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PDF Catalogue

Teaching-learning model

An innovative methodology is proposed that seeks to have the student body concentrate its efforts on a maximum of three subjects at the same time. Therefore:

  • The course is divided into four modules.
  • Two modules per semester.
  • Each module provides practical work at the end, involving all the subjects of that block.

CHALLENGE 1: Battery pack design

The challenge in this module will consist of designing a battery pack. The storage systems are at the energy transition centre and are constantly evolving. You will work on the modelling and management of the latest storage technologies, applying what you learn to the construction of a battery system.

 

CHALLENGE 2: Monitoring of a renewable energy plant

In this module your challenge will be to put a remote monitoring system into operation. Nowadays, the massive collection of data and its analysis opens up infinite possibilities for the improvement and maintenance of any energy system. You will apply advanced technology for the acquisition and processing of data, allowing for the optimsation and creation of digital twins.

 

CHALLENGE 3: Real-time control of an electric vehicle

In this challenge you will put into operation a real-time control on hardware of your own development that you will design and construct using rapid prototyping tools such as Altium and cards from Texas Instruments.

 

CHALLENGE 4: Hardware-in-the-Loop platform

In this challenge you will learn how to use the most advanced simulators that are capable of virtualising energy systems. You will be able to master the use of platforms for reducing costs and resources used by companies for launching their products. You will also work on the development of intelligent monitoring strategies. In this way, you will be able to propose pioneering solutions to reduce maintenance costs and predict faults.