80 hours — Renewable Energy & EV Engineering. Understand, model, design, simulate, monitor and test Battery Management Systems for electric vehicles, solar energy storage and industrial battery applications.
Course objective: Equip learners with the knowledge and practical skills to work on BMS for electric vehicles, solar energy storage and industrial battery packs. The curriculum can be adjusted for the learner’s electrical background and the depth of hands-on hardware training required.
A simulation-focused path teaches modelling and control. Professional BMS hardware design also needs hands-on electronics, embedded programming, safety validation and real battery testing. High-voltage EV battery work is performed only with appropriate equipment, supervision and safety procedures.
Module 1 — Battery Fundamentals
Chemistry, construction and performance.
- Battery types: lead-acid, lithium-ion, LFP and NMC
- Primary and rechargeable batteries
- Cell, module and pack architecture
- Voltage, current, capacity, energy and power
- C-rate, energy density and power density
- Charging and discharging characteristics
- Battery efficiency, degradation and cycle life
Module 2 — BMS Architecture and Design
Hardware, control and protection.
- Purpose and functions of a BMS
- Centralised, distributed and modular BMS architectures
- Battery monitoring and control units
- Cell voltage and pack current measurement
- Temperature sensing and sensor selection
- Contactors, fuses and pre-charge circuits
- Overvoltage, undervoltage, overcurrent and short-circuit protection
- Isolation monitoring and high-voltage interlocks
Module 3 — Battery State Estimation
Battery performance algorithms.
- State of Charge (SoC) estimation
- State of Health (SoH) estimation
- State of Power (SoP)
- Coulomb counting and voltage-based estimation
- Open-circuit voltage methods
- Battery equivalent-circuit models
- Kalman filter fundamentals
- Battery degradation and remaining useful life
Module 4 — Cell Balancing and Thermal Management
Battery reliability and safety.
- Cell imbalance and its effects
- Passive and active cell balancing
- Battery thermal behaviour
- Cooling and heating methods
- Thermal runaway fundamentals
- Temperature monitoring and safety strategies
- Battery operating limits and derating
Module 5 — MATLAB / Simulink Battery Modelling
Software-based design and simulation.
- Introduction to MATLAB and Simulink
- Battery equivalent-circuit modelling
- Series and parallel battery pack modelling
- Charging and discharging simulation
- Load profiles and power demand analysis
- SoC estimation and BMS control logic
- Fault-condition simulation
- Introduction to Simscape Electrical and battery modelling libraries, subject to licence availability
Module 6 — Embedded BMS and Communication
Controller integration.
- Microcontroller fundamentals
- ADC and sensor interfacing
- Temperature and voltage monitoring
- BMS control logic implementation
- CAN bus and UART communication
- Introduction to automotive communication and diagnostics
- Data logging and fault alerts
- Firmware testing and debugging
Module 7 — BMS Applications
EV, solar and energy storage.
- EV battery packs and powertrain integration
- Battery charging systems and charging limits
- Solar PV and battery storage integration
- UPS and industrial energy storage
- Battery Energy Storage Systems (BESS)
- Battery monitoring and remote diagnostics
- Energy management and operating profiles
Module 8 — Battery Testing, Validation and Safety
Engineering verification.
- Capacity and performance testing
- Charge/discharge cycle testing
- Sensor calibration and measurement accuracy
- Fault diagnosis and event logging
- Protection system verification
- Battery handling, storage and emergency response
- Introduction to relevant battery and automotive safety standards
Module 9 — Digital Twin and Advanced Simulation
Virtual validation before prototyping.
- Virtual battery pack modelling
- Battery behaviour under different loads
- Simulated faults and abnormal operating conditions
- Virtual testing of BMS algorithms
- Comparison of simulation with measured data
- Introduction to predictive maintenance
- AI/ML applications for battery health prediction
Practical projects
Project 1 — Smart Battery Monitoring System
Measure voltage, current and temperature, display readings and implement basic warning alerts.
Project 2 — MATLAB/Simulink BMS Digital Twin
Simulate a battery pack, estimate SoC and study performance under changing load conditions.
Project 3 — Cell Balancing and Protection
Model cell imbalance, develop balancing logic and test protection behaviour in simulation.
Project 4 — Solar Battery Energy Storage
Study solar generation, battery charging, load demand and energy storage management.
Recommended course duration
| Training component |
Suggested hours |
| Battery fundamentals and BMS architecture | 12 |
| State estimation, balancing and thermal management | 12 |
| MATLAB/Simulink and battery modelling | 16 |
| Embedded systems and communication | 12 |
| EV, solar and BESS applications | 8 |
| Testing, safety and validation | 8 |
| Capstone project | 12 |
| Total | 80 hours |
Expected learning outcomes
- Explain battery technologies and BMS architecture.
- Understand cell monitoring, balancing and protection.
- Develop basic battery models and BMS algorithms in MATLAB/Simulink.
- Analyse battery behaviour under different load conditions.
- Understand BMS integration with EVs, solar systems and energy storage.
- Build and demonstrate a suitable simulation or low-voltage prototype project.
