Postgraduate Diploma in SoC/SoH/SoF Estimation and Fusion Algorithms
Online 800-hour Postgraduate Diploma in SoC/SoH/SoF Estimation and Fusion Algorithms. 8 modules covering ISO 26262, IEC 62660-1 and MATLAB/Simulink. Assigned tutor and enrolment open.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Characterise cells through OCV and HPPC tests.
Parameterise equivalent-circuit and electrochemical models.
Implement SoC estimators based on Kalman filters.
Estimate state of health using ICA and DVA techniques.
Calculate available power over different time horizons.
Combine estimators using fusion algorithms.
Verify algorithms in MIL, SIL and HIL environments.
Who it's for
- BMS algorithm engineer who wants to specialise in SoC/SoH/SoF Estimation and Fusion Algorithms.
- Battery modelling engineer who wants to specialise in SoC/SoH/SoF Estimation and Fusion Algorithms.
- Battery data scientist who wants to specialise in SoC/SoH/SoF Estimation and Fusion Algorithms.
- Embedded software engineer who wants to specialise in SoC/SoH/SoF Estimation and Fusion Algorithms.
- Control engineer who wants to specialise in SoC/SoH/SoF Estimation and Fusion Algorithms.
- HIL validation engineer who wants to specialise in SoC/SoH/SoF Estimation and Fusion Algorithms.
- Engineering or science graduates seeking to enter the electric vehicle sector.
What you'll work with
- ISO 26262
- IEC 62660-1
- ISO 12405-4
- IEC 61982
- Reglamento (UE) 2023/1542
- SAE J1798
- UNECE GTR n.º 22
8 modules · 800 h
1.1OCV–SoC curve and its hysteresis1.2Nominal, usable and available capacity1.3Internal resistance and its thermal dependence1.4Polarisation and time constants1.5LFP versus NMC in estimation1.6Cyclic and calendar ageing1.7Formal definitions of SoC, SoH and SoF1.8Uncertainty of current and voltage sensors1.9HPPC characterisation tests1.10Laboratory: obtaining an OCV curve with pulses
2.1Thevenin and 2RC equivalent circuits2.2Parameter identification by least squares2.3Simplified electrochemical model SPM2.4Doyle-Fuller-Newman P2D models2.5Coupled thermal models2.6Plett hysteresis models2.7Data-based models2.8Validation with WLTP cycles2.9Model selection according to BMS resources2.10Practical: fitting a 2RC model in MATLAB
3.1Coulomb counting and integration drift3.2OCV correction at rest3.3Extended Kalman filter3.4Unscented Kalman filter3.5Particle filters3.6Luenberger and sliding-mode observers3.7SoC estimation in LFP with flat plateau3.8Pack SoC from cells3.9Robustness against sensor error3.10Practical: implementing an EKF for SoC
4.1Capacity and resistance indicators4.2Incremental capacity analysis ICA4.3Differential voltage analysis DVA4.4Joint estimation with dual filters4.5Capacity estimation by recursive least squares4.6Lithium plating detection4.7In-vehicle impedance spectroscopy4.8End-of-life criteria4.9Management of cell-to-cell dispersion4.10Case study: SoH from charging data
5.1Current limits by voltage and temperature5.2Multi-step power prediction5.32, 10 and 30 second windows5.4SoF as the capacity to meet a demand5.5Low-temperature derating5.6Interaction with vehicle control5.7Safety of power estimates5.8Validation with driving profiles5.9Communication of limits over CAN5.10Workshop: calculating SoP with a 2RC model
6.1Fusion of multiple estimators6.2Covariance-based fusion and adaptive weights6.3Federated Kalman filters6.4LSTM neural networks for estimation6.5Hybrid physics-data models6.6Estimation in the cloud and on the BMS6.7Uncertainty quantification6.8Sensor fault detection by residuals6.9Computational cost on microcontrollers6.10Practical: EKF and neural network fusion for SoC
7.1Code generation with Embedded Coder7.2Fixed-point arithmetic7.3MIL, SIL and HIL testing7.4Error metrics: RMSE and maximum7.5Cell and pack testing7.6Parameter calibration by temperature7.7ISO 26262 requirements for estimators7.8Traceability between requirements and test cases7.9Algorithm maintenance via OTA7.10Case study: HIL verification of the estimator
8.1Characterisation of the target cell8.2Model and parameterisation8.3SoC estimator design8.4SoH estimator design8.5Available power calculation8.6Chosen fusion strategy8.7Validation results8.8Embedded implementation proposal8.9Report and presentation8.10Final review with the tutor
How you'll learn
Fully 100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the enrolment period, which makes it compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB/Simulink, Simscape Battery, PyBaMM, Python with scikit-learn, dSPACE SCALEXIO, in free, academic or evaluation versions. Tests are studied using real SoC estimation procedures for vehicles with LFP chemistry, SoH diagnosis in fleets in service, and available power calculation for traction control. Assessment is continuous per module plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Characterise cells through OCV and HPPC tests.
Parameterise equivalent-circuit and electrochemical models.
Implement SoC estimators based on Kalman filters.
Estimate state of health using ICA and DVA techniques.
Calculate available power over different time horizons.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. A university degree is not required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow the reading of technical standards.
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 totals 800 hours spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
Work is carried out with MATLAB/Simulink, Simscape Battery, PyBaMM, Python with scikit-learn, dSPACE SCALEXIO. 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 integrative project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Check the recognition policy when enrolling.
Related programmes
Postgraduate Diploma in Design of Swappable Packs and Mechanical/Electrical Standards
Online 800-hour Postgraduate Diploma in Design of Swappable Packs and Mechanical/Electrical Standards. 8 modules covering IEC 62840-1, IEC 62840-2 and CATIA V5. Assigned tutor and open…
Postgraduate Diploma in Urban Integration and Hub Permits
Online 800-hour Postgraduate Diploma in Urban Integration and Hub Permits. 8 modules covering Regulation (EU) 2023/1804, Royal Decree 1053/2014 (ITC-BT-52) and AutoCAD. Assigned tutor and enrolment…
Postgraduate Diploma in Liquid Hydrogen (LH₂) and Thermal Management
Online Postgraduate Diploma of 800 h in Liquid Hydrogen (LH₂) and Thermal Management. 8 modules covering ISO 13985, EN 13530-1 and Aspen HYSYS. Assigned tutor and…
More in Electromobility, Batteries & Hydrogen
All Electromobility, Batteries & Hydrogen programmes → · How to apply · Fees & financing · Scholarships