Project

# Title Team Members TA Documents Sponsor
35 UAV Battery Management System with Integrated SOC and SOH Estimation
 Edward Chow
Jay Goenka
Samar Kumar
# Title
UAV Battery Management System with Integrated SOC and SOH Estimation

# Team Members:
- Edward Chow (ec34)
- Jay Sunil Goenka (jgoenka2)
- Samar Kumar (sk127)

# Problem
UAV batteries are safety-critical and performance-critical as a weak or degraded pack can cause sudden voltage drop, shutdown, reduced flight time, or unsafe thermal behavior. The usual BMS implementations primarily rely on fixed thresholds for voltage, temperature or current to prevent immediate failures. However, threshold-only systems do not provide predictive insight into battery degradation. Battery health issues are often discovered only after runtime loss or unsafe behavior. Additionally high discharge currents and fluctuating temperatures are common in UAV operations, which fastens degradation. A lightweight BMS that not only protects the pack in real time but also estimates battery health and degradation risk would improve reliability, reduce unexpected failures, and enable better operational decisions such as deciding if the battery is safe to use or needs to be retired.

# Solution
To address the delicate nature of UAV batteries we decided to undertake a project with the aim to design and construct a compact and efficient battery management system that seamlessly integrates reliable real-time protection with intelligent prediction. Our primary algorithm for estimating the battery’s State of Charge (SOC) will be coulomb counting, which relies on continuous current measurement. We are researching the Kalman filter method as a second algorithm for more accurate calculation. The BMS will also monitor cell voltages and temperatures to ensure safe operation and provide valuable data for battery condition assessment. By analyzing SOC history, voltage behavior, current profiles, and temperature data, the system should be able to estimate the State of Health (SOH) of the battery. SOH over time will help us understand the capacity fade and degradation trends over time. We also plan to log all measurements and stream it to an external dashboard for visualization and analysis. As an extension, the project could also incorporate a lightweight AI-driven model to assist in SOH estimation and degradation assessment.

# Solution Components
## Slave Board
The slave board will be responsible for monitoring individual cell voltages and temperatures and supporting passive cell balancing. It will report accurate measurement data to the master board, ensuring safe operation of the battery pack at the cell level. The HW components and sensors include: Cell monitoring IC: Analog Devices LTC6811 or LTC6813s (multi-cell voltage sensing with built-in diagnostics and balance control) isoSPI communication interface: Analog Devices LTC6820 Temperature sensors: 10 kΩ NTC thermistors (e.g., Murata NCP18XH103F03RB) Passive balancing: bleed resistors (33–100 Ω) and N-MOSFETs per cell Cell sense connectors and basic RC filtering/ESD protection Power regulation: buck converter (e.g., TPS62130) and 3.3 V LDO

## Master Board
The master board is responsible for actually performing pack-level protection, SOC and SOH estimation, data logging, and external communication. It makes sure safety limits are enforced by aggregating data from the slave board. The HW components and sensors include: Microcontroller: STM32H7 series Current sensing: shunt resistor with TI INA240 current-sense amplifier Protection switching: back-to-back N-channel MOSFETs with gate driver (e.g., BQ76200) Power regulation: buck converter (e.g., TPS62130) and 3.3 V LDO Communication: isoSPI (LTC6820), CAN Data logging: microSD card or onboard flash memory

## BMS Viewer
The BMS Viewer will be a software dashboard used to visualize real-time and logged battery data and assess battery health.

Potential features: Live display of SOC, SOH, pack voltage, pack current, and temperature Time-series plots of voltage, current, temperature, and SOC Data ingestion via USB, CAN, or wireless telemetry Backend implemented in Python or Node.js with a web-based dashboard

# Criterion For Success
- BMS detects and mitigates fault conditions within a bounded response time (≤100 ms).
- Cell voltage within ±50 mV per cell, pack current within ±10%, temperature within ±5°C after calibration.
- SOC remains within ±10% of a reference SOC over a full UAV-like discharge cycle.
- SOH estimate is within ±15% of a capacity-based reference and shows consistent degradation trends.
- BMS Viewer displays and logs SOC, SOH, pack voltage/current, and temperature in real time.

Mushroom Growing Tent

Elizabeth Boyer, Cameron Fuller, Dylan Greenhagen

Mushroom Growing Tent

Featured Project

# Mushroom Growing Tent Project

Team Members:

- Elizabeth Boyer (eboyer2)

- Cameron Fuller (chf5)

- Dylan Greenhagen (dylancg2)

# Problem

Many people want to grow mushrooms in their own homes to experiment with safe cooking recipes, rather than relying on risky seasonal foraging, expensive trips to the store, or time and labor-intensive DIY growing methods. However, living in remote areas, specific environments, or not having the experience makes growing your own mushrooms difficult, as well as dangerous. Without proper conditions and set-up, there are fire, electrical, and health risks.

# Solution

We would like to build a mushroom tent with humidity and temperature sensors that could monitor the internal temperature and humidity, and heating, and humidity systems to match user settings continuously. There would be a visual interface to display the current temperature and humidity within the environment. It would be medium-sized (around 6 sq ft) and able to grow several batches at a time, with more success and less risk than relying on a DIY mushroom tent.

Some solutions to home-grown mushroom automation already exist. However, there is not yet a solution that encompasses all problems we have outlined. Some solutions are too small of a scale, so they don’t have the heating/cooling power for a larger scale solution. Therefore, it’s not enough to yield consistent batches. Additionally, there are solutions that give you a heater, a light set, and a humidifier, but it’s up to the user to juggle all of these modules. These can be difficult to balance and keep an eye on, but also dangerous if the user does not have experience. Spores can get released, heaters can overheat, and bacteria and mold can grow. Our solution offers an all-in-one, simple, user-friendly environment to bulk growing.

# Solution Components

## Control Unit and User Interface

The control unit and user interface are grouped together because the microcontroller is central to the design of both, and they are closely linked in function.

The user interface will involve a display that shows measured or set values for different conditions (temperature, humidity, etc) on a display, such as an LCD display, and the user will have buttons and/or knobs that allow the user to change values.

The control unit will be centered around a microcontroller on our PCB with circuitry to connect to the other subsystems.

Parts List:

1x Microcontroller

1x PCB, including small buttons and/or knobs, power circuitry

1x Display module

1x Power supply

## Temperature Sensing and Control

The temperature sensing and control components will ensure that the grow box stays at the desired temperature that promotes optimal growth. The system will include one temperature sensor that will record the current temperature of the box and feed a data output back into our PCB. From here, the microcontroller in our control unit will read the data received and send the necessary adjustments to a Peltier module. The Peltier module will be able to increase the temperature of the box according to the current temperature of the box and set temperature. Cooling will not be required, as maintaining a minimum temperature is more important than a maximum temperature for growth.

Parts List:

1x Temperature Sensor

1x Peltier module

## Humidity Sensing and Control

The humidity sensing and control system will work in a similar way to the temperature system, only with different ways to adjust the value. We will have one humidity sensor that will be continually sending data to our PCB. From here, the PCB will determine whether the current value is where it should be, or whether adjustments need to be made. If an increase in humidity is needed, the PCB will send a signal to our misting system which will activate. If a decrease is needed, a signal will be sent to our air cycling system to increase the rate of cycling, thereby decreasing the humidity within the box.

Parts List:

1x Humidity Sensor

4x Misting heads

Water tubing as needed

## Air Quality Control

The air filtration system is run constantly, as healthy mushroom growth (free of bacteria) needs clean, fresh air, and mycelium requires and uses up oxygen as it grows. Additionally, this unit is connected to the hydration sensing unit- external humidity is in most cases going to be lower than internal humidity, and cycling in new air can be used to decrease humidity. When high humidity is detected, the air filtration system will decrease the internal humidity by cycling in less humid air.

Parts List:

Flexible Air duct length as needed

1x Fan for promoting air cycling

# Criteria For Success

Our demo will show that each of our subsystems functions as expected and described below:

For the control unit and user interface, we will demonstrate that the user can change the set temperature and humidity values through buttons or knobs.

The humidity sensing and control system’s functionality will demonstrate that introducing dry air into the device activates the misting system, which requires functional sensors and a water pump.

The temperature sensing and control system demo will involve showing that the heater turns on when the measured temperature is below the set temperature.

The air quality control system’s success will be demonstrated as air movement coming from the fan enters the tent.

Project Videos