Where advanced engineering, applied innovation, and technological sustainability converge.
SEIUM Research Areas
- Vehicles & Systems
- Energy and Networks
- IA & Simulator
- Safety and RAMS
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SEIUM Univesity
Research at SEIUM — International University of Advanced Multimodal Engineering is organised into four core areas of knowledge that integrate applied science, complex-systems simulation, and next-generation engineering. Each area addresses global challenges in mobility, energy, autonomy, digitalisation, and security, generating knowledge that supports both teaching and technology transfer to industry.
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Methodological approach
Objective: to accelerate the transition from concept design to prototype validation, reducing development cycles and maximising reliability and sustainability.
- Coupled 1D–3D multiphysics models (Simulink, AMESim, Adams, Ansys TwinBuilder).
- HIL/SIL integration for real-time validation.
- Data-driven engineering: training predictive models using telemetry.
- Instrumented experimental test rigs (7-post rig, dynamometers, wind tunnel).
Vehicles and Systems
From concept to prototype: multimodal design, validation, and sustainability
The Vehicles and Systems area addresses the end-to-end development of land, air, naval, and space platforms through MBSE (Model-Based Systems Engineering) methodologies, digital twins (Digital Twins), and cyber-physical systems simulation.
Research lines
Vehicle dynamics and control
Non-linear modelling, modal analysis, active suspension control, braking and stability (ESP, yaw control, roll mitigation).
Propulsion and energy systems
Electric, hybrid, and optimised internal-combustion engines; integrated thermal management; power management; and energy harvesting.
Vehicle Architectures
Modular design, lightweight structures (Al-CFRP, hybrid composites), integration of electrical and electronic systems (E/E architecture).
Aerodynamics and aeroelasticity.
Multiphysics CFD, topology optimisation, wind tunnel testing, simulation-to-track correlation.
NVH and acoustic comfort.
Vibroacoustic simulation, active noise control, modal metamodeling.
Advanced manufacturing.
High-precision processes, additive manufacturing, smart assembly, digital dimensional control.
Type Approval & Lifecycle Compliance
Regulatory validation (UNECE, ISO, EN, EASA), end-to-end traceability and compliance-by-design.
Full lifecycle sustainability.
LCA analysis, recycling of structural materials, energy impact, and industrial circularity.
Energy & Grids
Energy transition, smart grids, and sustainable power systems
The Energy & Grids (SEN) area focuses on the architecture, control, and digitalisation of interconnected energy infrastructures. It combines electrical engineering, power electronics, and automation with a sustainability- and resilience-driven approach.
Research lines.
- Smart Grids & Power Systems: hierarchical control of HVDC/FACTS networks, microgrid synchronisation, transient stability modelling.
- Renewable energy: integration of solar PV, wind, and marine energy with energy storage (Li-ion, Na-ion, solid-state, hydrogen).
- Energy conversion and storage: bidirectional converters, DC microgrids, solid-state transformers.
- Renewable energy: integration of solar PV, wind, and marine energy with energy storage (Li-ion, Na-ion, solid-state, hydrogen).
- Transport electrification: charging systems, V2G (Vehicle-to-Grid), electric corridors, and dynamic charging load control.
- Power electronics and drives: vector control, PWM optimisation, wide-bandgap semiconductors (SiC, GaN).
- Supervision and reliability: fault detection in inverters, thermal modelling, condition monitoring of power networks.
- Energy digitalisation: IoT, edge computing, SCADA/EMS, energy blockchain, and predictive maintenance.
Simulation and validation platforms.
- EMT/RTDS simulation and co-simulation between electrical grids and transport systems.
- Hardware-in-the-Loop for converters and hybrid systems.
- SEN laboratories with HV cells, load banks, grid emulators, and test stations.
- Resilience modelling against climate-driven disruptions and cyberattacks.
Objective: to design the energy infrastructure of the future—resilient, digital, and clean—capable of supporting mobility and Industry 4.0.
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DAIS infrastructure.
Objective: to integrate AI, physics, and data into a continuous cycle of design, testing, and improvement, creating smarter, safer, and more efficient systems.
Digital Twins:
- Hybrid GPU/CPU HPC cluster for large-scale training and simulation.
- Frameworks: TensorFlow, PyTorch, ANSYS TwinBuilder, Modelica, Simcenter Amesim.
- Autonomous simulation environments (CARLA, Gazebo, AirSim, Unity Simulation).
- A distributed testbed network for in-field testing of algorithms.
Artificial Intelligence & Simulation.
Digital twins, predictive simulation, and cognitive autonomy
The AI & Simulation (DAIS) area advances the use of artificial intelligence, big data, and coupled physics-based models to optimise design, control, and operations in complex systems. It combines data science, software engineering, and computational physics to build digital ecosystems for advanced validation.
Digital Twins:
Hybrid models (data-driven + physics-based) for vehicles, power plants, and smart grids.
Machine Learning Applied to Engineering.
Convolutional neural networks for fault detection, reinforcement learning for adaptive control.
Multiphysics Simulation & HPC.
Coupling of fluid dynamics, structures, thermal behaviour, and electromagnetism.
Explainable AI (XAI).
Interpretability in safety-critical models, decision traceability, and regulatory validation.
Real-time simulation.
Reduced-order models, real-time co-simulation, integration with ECU controllers.
Advanced manufacturing.
High-precision processes, additive manufacturing, smart assembly, digital dimensional control.
Data governance & MLOps.
Technical data management, versioning, training pipelines, deployment, and continuous monitoring.
Edge AI and distributed autonomy.
Embedded systems with on-device AI, federated learning, and decentralised control.
AR/VR and immersive simulation.
Mixed reality for collaborative design and advanced training.
Safety, Reliability and RAMS.
Safety, security, and compliance in complex, safety-critical systems
Modern engineering cannot be separated from functional safety, cyber protection, and operational reliability. The Safety & RAMS area (Safety, Reliability, Availability, Maintainability, Security) ensures that the systems designed at SEIUM meet the highest international standards of technical, legal, and ethical safety.
Research lines
- Safety by Design: ISO 26262, IEC 61508, EN 50128/29 (rail), DO-178C (aero), and MIL-STD (defence) methodologies.
- RAMS analysis: probabilistic modelling, FMEA/FMECA, fault trees, reliability analysis (MTBF, Weibull, Markov).
- Industrial cybersecurity: defence for OT/ICS systems, network segmentation, and cryptography in embedded devices.
- Safety-critical software validation: formal verification, unit testing, model checking, structural coverage.
- Safe autonomous systems: ethics, fail-operational design, and residual risk management.
- AI safety: validation of non-deterministic models, algorithm certification, and bias auditing.
- International compliance: UNECE WP.29 (connected vehicles), the EU AI Act, ITAR/EAR (export controls).
- Lifecycle management: document traceability, safety requirements, safety cases, configuration management.
Infrastructure and tools.
- Safety labs with SIL/HIL platforms for functional validation.
- Tools: ANSYS Medini Analyze, Safety Architect, IBM DOORS, Capella, Polarion ALM.
- Multi-sector reliability databases and RAMS standards repositories.
- Simulated OT/ICS cybersecurity environments (firewalling, IDS, ethical penetration testing).
Objective: to ensure that every SEIUM system is safe, traceable, verifiable, and compliant with international standards, promoting ethical and responsible engineering.
Cross-cutting approach across all areas.
All SEIUM research areas share a multimodal, interdisciplinary, and ethical approach, supported by advanced methodologies and interconnected digital ecosystems:
Impact & met
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Active projects in energy, automotive, aerospace, and defence.
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Indexed scientific publications (Scopus, SAE, IEEE, Elsevier).
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Spin-offs and technology licences over the last five years.
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Active projects in energy, automotive, aerospace, and defence.
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ISO/EN 17025-accredited laboratories and six HPC clusters distributed globally.