Probabilistic analysis course in electromobility
Online course of 300 hours in probabilistic analysis in e-mobility, structured in 6 modules covering probability and reliability, system risk analysis, uncertainty propagation, e-mobility applications, and risk decision-making and communication, with an assigned technical tutor.
Probabilistic analysis course in electromobility — studying from the United Kingdom
The United Kingdom is building capability in electric vehicles, battery manufacturing and hydrogen technologies, driven by the national net zero strategy. Battery gigafactory projects, electric vehicle plants and research centres such as the Faraday Institution support growing demand for cell design, battery management and recycling expertise. Hydrogen projects in Teesside, Scotland and the North West explore production, storage and fuel cell applications. Engineers in these areas work with automotive manufacturers, energy companies and research bodies.
Fees for the United Kingdom: £537 (Pound sterling), with instalments and employer sponsorship available.
Relevant bodies in the United Kingdom
Typical roles
Questions from the United Kingdom
Which UK bodies are relevant to electromobility, battery and hydrogen engineering qualifications?
Relevant UK bodies include the Institution of Engineering and Technology (IET), the Institute of Materials, Minerals and Mining (IOM3), and the Institution of Mechanical Engineers (IMechE). Chartered registration is managed through the Engineering Council. SEIUM's qualifications are private and not accredited by these bodies, so confirm with the relevant institution how your study would be considered.
Are electromobility and battery skills in demand with UK employers, and do private qualifications count?
UK employers in electric vehicles, battery manufacturing, energy storage and hydrogen projects look for practical technical skills and relevant experience. A private qualification can demonstrate specialist knowledge, but employers decide how much to rely on it. Project evidence and hands-on competence are generally what carry the most weight.
Can I study this from the UK while working, and what should I check about time and funding?
Yes, programmes are fully online, so you can study from anywhere in the UK without a student visa. Teaching is in English, so good technical English is needed. An assigned technical tutor supports you throughout. Fees can be paid in instalments, and employer sponsorship may be possible depending on your employer. Check the hours involved against your working week.
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
Apply statistical distributions to component reliability analysis.
Build fault trees, FMEA and Markov models of electrical systems.
Propagate uncertainties using Monte Carlo and global sensitivity analysis.
Assess thermal runaway, availability and warranty risks in e-mobility.
Calculate hardware metrics in accordance with ISO 26262.
Communicate probabilistic results for decision-making.
Develop a complete probabilistic analysis of an e-mobility system.
Who it's for
- Reliability engineers working on EV components and charging systems.
- Functional safety engineers who need quantitative hardware metrics.
- Risk analysts.
- Warranty engineers estimating failure costs.
- Quality engineers.
- Risk management consultants for the automotive and energy sectors.
- Engineering or science graduates looking to enter the automotive industry.
What you'll work with
- ISO 26262 (functional safety of road vehicles)
- IEC 61025 (fault tree analysis)
- IEC 60812 (failure modes and effects analysis, FMEA)
- IEC 61078 (reliability block diagrams)
- IEC 61165 (application of Markov techniques)
- ISO 31000 (risk management guidelines)
- IEC 31010 (risk assessment techniques)
- JCGM 100:2008 (GUM) (guide to the expression of uncertainty in measurement)
- ReliaSoft Weibull++
- Isograph Reliability Workbench
- OpenTURNS
- Python (SciPy)
- MATLAB
6 modules
1.1Random variables and probability distributions1.2Weibull, lognormal and exponential distributions1.3Failure rate and the bathtub curve1.4Bayesian inference applied to reliability1.5Parameter estimation with censored data1.6Confidence intervals and sample size1.7Reliability of series and parallel systems1.8Availability and maintainability1.9Sources of component reliability data1.10Workshop: Weibull fit to charger failures
2.1Failure mode analysis according to IEC 608122.2Fault trees according to IEC 610252.3Reliability block diagrams2.4Markov models for repairable systems2.5Event trees and accident sequences2.6Common cause failures2.7FMEDA and ISO 26262 hardware metrics2.8Probability of random hardware failure and ASIL targets2.9Bayesian networks in risk analysis2.10Practical: fault tree of a BMS
3.1Monte Carlo method3.2Latin hypercube sampling3.3Global sensitivity analysis with Sobol indices3.4Metamodels and kriging3.5Measurement uncertainty according to the GUM3.6Uncertainty in battery models3.7Structural reliability with FORM and SORM3.8Optimisation under uncertainty3.9Probabilistic model validation3.10Lab: Monte Carlo of a vehicle's range
4.1Probability of thermal runaway in packs4.2Availability of charging networks4.3Probabilistic charging demand on the grid4.4Battery service life with uncertainty4.5Fire risk in underground car parks4.6Reliability of traction inverters4.7Planning of critical spare parts4.8Expected warranty costs4.9Risk in charging investment projects4.10Case study: availability of a charging station
5.1Risk management according to ISO 310005.2Assessment techniques according to IEC 310105.3ALARP criterion and tolerable risk5.4Risk matrices and their limitations5.5Cost-benefit analysis of measures5.6Decision theory under uncertainty5.7Communicating risk to management5.8Reliability software tools5.9Critical review of probabilistic studies5.10Case study: redundancy in a charging system
6.1Definition of the system and the problem6.2Collection of failure data6.3System reliability model6.4Uncertainty propagation6.5Sensitivity analysis6.6Assessment of the resulting risk6.7Proposal of improvement measures6.8Communication of results6.9Report and presentation6.10Final project: final 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. There are no fixed timetables: you progress at your own pace within the intake, making it compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ReliaSoft Weibull++, Isograph Reliability Workbench, OpenTURNS, Python (SciPy) and MATLAB, in free, academic or evaluation versions. Practical work is based on real procedures for Weibull analysis of field data, fault trees of battery systems and Monte Carlo simulation of availability. Assessment is continuous by module, plus the final integrating project.
Standards covered: ISO 26262, IEC 61025, IEC 60812, IEC 61078, IEC 61165, ISO 31000, IEC 31010, JCGM 100:2008 (GUM).
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- No prior qualification is required.
- An internet connection and a computer capable of running the programme software.
- English sufficient to read 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 300 hours over 3 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with ReliaSoft Weibull++, Isograph Reliability Workbench, OpenTURNS, Python (SciPy) and MATLAB, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute certificate, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
No prior qualification is required; you need an internet connection, a computer able to run the programme software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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