Summary of "Embedded Systems and Design & Development - Feb 17, 2026 | Afternoon | VisionAstraa EV Academy"

Overview / goals

Course objective: implement basic BMS functionality (monitor → control → communicate) on an embedded controller, focusing on over‑voltage protection for a single lithium cell.
Required measurements: current, voltage, temperature (sensors + ADCs + signal conditioning).
Protection hardware: MOSFET (to isolate the cell from the charger), TVS diode (transient suppression), fuse (final physical isolation).

ADC / MCU considerations

Key ADC parameters to check in datasheets: resolution, conversion time, input voltage range, number of channels.
Typical automotive MCUs (examples: SPC series, Infineon, NXP) commonly provide 12‑bit ADCs; battery‑pack applications may use 16‑bit ADCs for higher precision.
Example calculation:
- With a 12‑bit ADC and 0–5 V range: LSB ≈ 5 / 4096 ≈ 1.22 mV.
- For a 100 mV over‑voltage detection requirement, 12‑bit resolution is adequate.
Example MCU discussed: ATmega328 (provides ADCs, timers, interrupts, serial modules, etc.).

Design flow and algorithm

Typical data flow:

Sensor → ADC → store in memory → CPU processes via firmware → control MOSFET to disconnect when cell ≥ threshold (example threshold: 4.1 V).

Pseudocode (high level):

initialize_peripherals()
while true:
    raw = read_adc(channel)
    voltage = convert_raw_to_voltage(raw)
    if voltage >= threshold:
        drive_gpio(disconnect_switch)
    else:
        drive_gpio(connect_switch)
    delay(loop_interval)

Firmware choices: assembly (rare), embedded C/C++ (common), MicroPython, or graphical block editors (Blockly-style) for onboarding and simple logic.

Using generative agents to speed development

Practical tip: use generative AI (ChatGPT, Gemini, etc.) to parse large datasheets (PDFs) and extract specifics (e.g., ADC resolution) instead of manual page scanning.
Always cross‑verify critical values against the original datasheet.
Recommended workflow: use AI to produce skeleton code (“wipe coding” / agent‑assisted code generation), then refine and test thoroughly in the target environment.

“Wipe coding” / agent‑assisted code generation is useful for producing skeleton code quickly; treat generated code as a starting point and validate for safety‑critical applications.

Hands‑on tutorial — Tinkercad + Arduino demo

Platform: Tinkercad Circuits (free). Use Arduino UNO model and either blockly (blocks), text, or combined editors.
Demo: analog input using a potentiometer to simulate a sensor; built‑in LED indicates threshold crossing.
Voltage divider scaling example:
- Goal: scale a 9 V source to 0–5 V ADC input.
- Instructor example: R1 ≈ 800 Ω and R2 = 1 kΩ to map 9 V to ≈5 V.
- Emphasized: use standard resistor values, account for tolerances, and always include margin (never drive ADC beyond its max).
Simulation tips:
- Use the multimeter in Tinkercad.
- Check ADC input referenced to MCU ground.
- Avoid feeding voltages > ADC maximum on real hardware.
Assignment: implement the over‑voltage protection example in Tinkercad and modify code so a threshold (e.g., 3 V in the demo) toggles the LED. Instructor will demo a solution in the next class.

Signal conditioning and measurement fidelity

Single‑ended ADC inputs share a common reference; noise on one channel can affect others.
For higher fidelity:
- Use differential measurement inputs.
- Use external signal conditioning (filters, buffering, isolation amplifiers).
Always reference analog measurements to the MCU reference/ground and account for channel buffering differences (some channels may be unbuffered).

Current sensing overview (brief)

Reviewed common current‑sensor types and tradeoffs:

Shunt resistor
- Pros: simple, direct (I → V via Ohm’s law).
- Cons: power dissipation (I^2R), resistor drift, floating node/isolation challenges.
Hall‑effect sensors
- Measure magnetic flux; available as open‑loop or closed‑loop designs.
Current transformers (CT)
- Suitable for AC only.
Industrial sensors
- Fluxgate and magnetoresistive sensors; fluxgate used for high‑accuracy industrial measurements.

Safety and isolation:

Consider ASIL/safety levels, galvanic isolation, and floating‑node issues when measuring high or floating currents.
Use isolation or specialized sensors as required.

Next steps / roadmap mentioned

Next session: design of a shunt‑resistor current sensor and practical core current protection.
Later topics: thermal protection, constant‑current/constant‑voltage control, cell balancing, SOC estimation algorithms (software side).
Encouragement: complete the Tinkercad over‑voltage protection circuit before the next class.

Tools, platforms and references mentioned

Hardware / MCUs: ATmega328 (Arduino UNO), SPC series, Infineon, NXP.
Vendors / datasheets: Mouser.
Tools: Tinkercad (simulation + block/text coding), Arduino IDE‑style environments, MATLAB/Simulink (Embedded Coder and HIL potential), multimeter (for simulation checks).
AI/generative agents: ChatGPT, Gemini.
Languages: Embedded C/C++, MicroPython, graphical block editors (Blockly).

Practical tips / best practices

Always consult and verify datasheets; use AI to speed extraction but cross‑check critical numbers.
Keep ADC inputs within safe range; include margin for resistor tolerances.
Use differential measurement or isolation for noisy/high‑fidelity applications.
Use agent‑generated code as a skeleton; thoroughly test and fine‑tune for safety‑critical systems.
Simulate first (Tinkercad), then test on real hardware; account for non‑idealities (component tolerances, power dissipation).

Main speaker / sources

Instructor: VisionAstraa EV Academy (primary speaker and demonstrator).
Participants: class questions and interactions.
Referenced tools and sources: Atmel/ATmega328 (Arduino UNO), SPC/Infineon/NXP MCU datasheets, Mouser, Tinkercad, ChatGPT/Gemini, MATLAB/Simulink.