Master’s in Advanced BMS and Diagnostics/Prognostics (SoX)
Online master's programme of 1,900 hours in advanced BMS and diagnostics/prognostics (SoX) — SoC/SoH/SoF estimation, algorithms and data. 12 modules covering BMS architecture, cell modelling, SoC, SoH, SoP and SoE estimation, cell balancing, fault diagnosis, prognostics and remaining useful life, BMS hardware and software, functional safety and cybersecurity, and validation and cloud analytics, with an assigned technical tutor.
Master’s in Advanced BMS and Diagnostics/Prognostics (SoX) — studying from India
India is actively building its electric mobility and clean energy ecosystem, supported by national schemes such as FAME and the PLI programme for advanced chemistry cell batteries. Manufacturers including Tata Motors, Mahindra & Mahindra, Ola Electric and Ather Energy are expanding electric vehicle production, while companies like Amara Raja and Exide are building battery capacity. Hydrogen initiatives such as the National Green Hydrogen Mission are driving research and pilot projects. Engineers work on battery systems, electric drivetrains, charging infrastructure and hydrogen technologies, with regulation shared among the Ministry of Heavy Industries and the Ministry of New and Renewable Energy.
Fees for India: ₹628,000 (Indian Rupee), with instalments and employer sponsorship available.
Relevant bodies in India
Typical roles
Questions from India
How are battery and e-mobility engineers recognised in India?
India recognises these engineers mainly through the Automotive Research Association of India (ARAI), the Bureau of Indian Standards for product standards, and the Institution of Engineers (India). Government schemes such as FAME and PLI for batteries shape the sector but are not licences. SEIUM's qualifications are private and not accredited by a national body, so recognition depends on employers or the relevant body.
Which employers in India hire electromobility, battery and hydrogen engineers?
Employers include EV makers such as Tata Motors and Ola Electric, battery cell and pack manufacturers, charging network operators, and energy companies working on green hydrogen projects, including public sector firms like NTPC and IOCL. A private online qualification can support a move into these roles, but employers focus on hands-on experience and technical projects.
Can I study this alongside work in India, and how much time is involved?
Yes. The programme is 100% online and taught in English, so you can study from home without a student visa. Time commitment is about 300 hours for specialist courses, 800 for postgraduate diplomas and 1,900 for master's programmes. Each student has an assigned technical tutor, schedules follow IST, and fees can be paid in instalments. Check with your employer about funding.
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
Design BMS architectures and their measurement hardware.
Model cells for state estimation.
Estimate SoC, SoH, SoP and SoE with robust methods.
Design cell balancing strategies.
Diagnose faults and forecast service life.
Apply functional safety and cybersecurity to the BMS.
Validate algorithms using HiL and fleet data.
Who it's for
- BMS algorithm engineers.
- Battery software engineers.
- Battery diagnostics engineers.
- Battery data scientists.
- Functional safety engineers.
- BMS validation engineers.
- Engineering or science graduates looking to move into electric automotive.
What you'll work with
- ISO 26262 (road vehicle functional safety)
- ISO/SAE 21434 (road vehicle cybersecurity engineering)
- IEC 62660-1 (performance testing of lithium-ion traction cells)
- Regulation (EU) 2023/1542 (EU Batteries Regulation)
- ISO 6469-1 (on-board rechargeable energy storage safety)
- IEC 62619 (safety of industrial lithium batteries)
- SAE J2464 (EV battery abuse testing)
- MATLAB Simulink
- PyBaMM
- dSPACE SCALEXIO
- Vector CANoe
- Python
12 modules
1.1Functions of a battery management system1.2Centralised, modular and distributed architectures1.3Voltage, current and temperature monitoring1.4AFE measurement circuits1.5Contactors and pre-charge1.6Internal and vehicle communication1.7Measurement accuracy requirements1.8Stationary versus automotive BMS1.9The BMS market1.10Case study: specification of an 800 V BMS
2.1Equivalent circuit models2.2First- and second-order Thevenin models2.3OCV-SoC curve2.4Hysteresis2.5Temperature dependence2.6Reduced-order electrochemical models2.7Parameter identification2.8HPPC tests2.9Model validation2.10Lab: identification of a 2RC model
3.1Coulomb counting3.2OCV correction3.3Extended Kalman filter3.4Unscented Kalman filter3.5Particle filters3.6Non-linear observers3.7Data-driven estimators3.8Robustness to sensor errors3.9Accuracy metrics3.10Practical: SoC with an EKF in MATLAB
4.1SoH definitions4.2Capacity estimation4.3Internal resistance estimation4.4Online incremental capacity analysis4.5Joint state and parameter estimation4.6Calendar and cycle ageing4.7Degradation models4.8Fleet data4.9Battery health certificates4.10Lab: capacity estimation with field data
5.1State of power (SoP)5.2Current limits5.3Prediction of available power5.4State of energy (SoE)5.5Remaining range5.6State of safety (SoS)5.7Temperatures and derating5.8Communication with vehicle control5.9Bench validation5.10Practical: model-based SoP algorithm
6.1Cell-to-cell imbalance6.2Passive balancing6.3Active balancing6.4Active balancing topologies6.5Balancing strategies6.6Balancing during charging and at rest6.7Losses and thermal management6.8Impact on service life6.9Strategy selection6.10Lab: active balancing simulation
7.1Sensor faults7.2Cell faults7.3Incipient internal short circuits7.4Lithium plating detection7.5Insulation faults7.6Model-based diagnosis7.7Data-driven diagnosis7.8Fault management and degraded modes7.9Diagnostic trouble codes7.10Case study: internal short-circuit detection
8.1Health indicators8.2RUL prognostics8.3Machine learning models8.4Prognostics with uncertainty8.5Battery digital twins8.6Cloud-based prognostics8.7Warranties and residual value8.8Second life8.9Prognostic metrics8.10Practical: RUL with ageing data
9.1Safety microcontrollers9.2Analog Devices and Texas Instruments AFEs9.3Wireless BMS9.4AUTOSAR software9.5Model-based development9.6Automatic code generation9.7Calibration9.8OTA updates9.9Unit and integration testing9.10Lab: SoC code on a microcontroller
10.1ISO 26262 applied to the BMS10.2HARA and safety goals10.3ASIL of BMS functions10.4Safety architectures10.5Diagnostic mechanisms10.6ISO/SAE 2143410.7Communication security10.8Safety validation10.9Documentation10.10Workshop: HARA analysis of a BMS
11.1BMS hardware-in-the-loop11.2Cell emulators11.3In-vehicle testing11.4Fleet data in the cloud11.5Large-scale battery analytics11.6Battery passport11.7Batteries Regulation requirements11.8Remote diagnostic services11.9Lessons from the field11.10Practical: fleet analytics pipeline
12.1BMS specification12.2Cell model12.3SoC and SoH estimators12.4SoP estimation12.5Balancing strategy12.6Diagnostics and prognostics12.7HiL validation12.8Safety analysis12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online learning 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, so you can combine it with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB Simulink, PyBaMM, dSPACE SCALEXIO, Vector CANoe and Python, in free, academic or evaluation versions. Testing is studied through real procedures: HPPC cell tests, hardware-in-the-loop validation and fleet data analysis. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: ISO 26262, ISO/SAE 21434, IEC 62660-1, Regulation (EU) 2023/1542 (batteries), ISO 6469-1, IEC 62619, SAE J2464.
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
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer able to run 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 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with MATLAB Simulink, PyBaMM, dSPACE SCALEXIO, Vector CANoe and Python, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. 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 in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the 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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