Postgraduate Diploma in Simulation-Guided Set-up Optimisation
Online 800-hour Postgraduate Diploma in Simulation-Guided Set-up Optimisation. 8 modules covering ISO 8855:2011 vehicle dynamics vocabulary, FIA Formula 1 Technical Regulations and Adams Car. Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Relate each set-up parameter to its effect on performance.
Select the appropriate vehicle model for each decision.
Design efficient virtual set-up experiments.
Apply multi-objective optimisation with regulatory constraints.
Integrate tyre management into set-up definition.
Make set-up decisions during a race weekend.
Evaluate the quality of predictions after each event.
Who it's for
- Performance engineer looking to specialise in Simulation-Guided Set-up Optimisation.
- Track engineer looking to specialise in Simulation-Guided Set-up Optimisation.
- Vehicle simulation engineer looking to specialise in Simulation-Guided Set-up Optimisation.
- Vehicle dynamics engineer looking to specialise in Simulation-Guided Set-up Optimisation.
- Race data analyst looking to specialise in Simulation-Guided Set-up Optimisation.
- Tyre engineer looking to specialise in Simulation-Guided Set-up Optimisation.
- Engineering or science graduates seeking to enter single-seater racing.
What you'll work with
- ISO 8855:2011 vehicle dynamics, vocabulary
- FIA Formula 1 Technical Regulations
- FIA Formula 1 Sporting Regulations
- ISO 4138 steady-state circular driving test
- ISO 7401 lateral transient response
- SAE J670 Vehicle Dynamics Terminology
8 modules · 800 h
1.1Set-up parameters and their overall effect1.2Mechanical and aerodynamic balance1.3Spring and anti-roll bar stiffness1.4Ride heights and rake1.5Camber and toe angles1.6Damping and platform control1.7Brake balance and differential1.8Tyre pressures and temperatures1.9Trade-offs between slow and fast corners1.10Workshop: annotated set-up sheet
2.1Quasi-static models with suspension2.2Seven-degree-of-freedom models2.3Aerodynamic maps as a function of ride height2.4Tyre models with temperature2.5Multibody models with Adams Car2.6Fidelity versus computational cost2.7Metamodels and surrogate models2.8Subsystem-level model validation2.9Parameter database management2.10Practice: seven-degree-of-freedom model
3.1Choice of set-up factors and ranges3.2Factorial and fractional designs3.3Latin Hypercube and space-filling designs3.4Polynomial response surfaces3.5Kriging and Gaussian processes3.6Analysis of variance of sensitivities3.7Parameter interactions3.8Adaptive sampling in areas of interest3.9Multivariable results visualisation3.10Laboratory: set-up DoE in a simulator
4.1Definition of objectives and constraints4.2Lap time versus degradation4.3NSGA-II genetic algorithms4.4Gradient-based optimisation and adjoints4.5Pareto fronts and selection4.6Robust optimisation under uncertainty4.7Regulatory and safety constraints4.8Circuit-specific and condition-specific optimisation4.9Computational cost and parallelisation4.10Case study: aerodynamic set-up Pareto front
5.1Rubber temperature window5.2Minimum pressures imposed by the supplier5.3Wear and thermal degradation5.4Graining and blistering5.5Effect of camber on temperature5.6Tyre thermomechanical models5.7Tyre management over a long run5.8Stint-oriented set-up5.9Correlation with tyre blankets and sensors5.10Practice: set-up study for a long run
6.1Pre-event baseline set-up preparation 6.2 Practice program and run plan 6.3 data interpretation and quick decisions 6.4 model adjustment with practice data 6.5 track evolution and conditions 6.6 Set-Up for Qualifying and the Race 6.7 Parc Fermé and Change Restrictions 6.8 Communicating Changes to the Mechanic 6.9 Feedback with the Driver 6.10 Case Study: Adjustment between practice and qualifying
7.1Checking predictions against results7.2Set-up accuracy indicators7.3Circuit-specific knowledge bases7.4Machine learning on historical data7.5Detecting model bias7.6Structured post-event review7.7Updating metamodels7.8Managing the risk of large changes7.9Lessons learned and documentation7.10Workshop: post-event set-up report
8.1Definition of circuit and conditions8.2Selection of parameters and constraints8.3Building the simulation model8.4Designing the virtual experiment8.5Fitting the response metamodel8.6Multi-objective set-up optimisation8.7Validation against reference data8.8Final set-up recommendation8.9Report and presentation8.10Final review with the tutor
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Adams Car, modeFRONTIER, MATLAB/Simulink, ChassisSim, Python with scikit-learn, in free, academic or evaluation versions. Tests are studied through real procedures: pre-event set-up optimisation, set-up adjustment during practice, and post-event analysis of predictions. Assessment is continuous per module, plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Relate each set-up parameter to its effect on performance.
Select the appropriate vehicle model for each decision.
Design efficient virtual set-up experiments.
Apply multi-objective optimisation with regulatory constraints.
Integrate tyre management into set-up definition.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow technical standards documentation.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme comprises 800 hours in total, spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
You will work with Adams Car, modeFRONTIER, MATLAB/Simulink, ChassisSim and Python with scikit-learn. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An own diploma from SEIUM upon passing the continuous assessment and the integrating project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the advanced programme. Please check the recognition policy when you enrol.
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