BMS Training and Research System

The BMS Training and Research System (BMSTS) by Ecosense is a modular and scalable educational platform designed for advanced experimentation and real-time simulation of Battery Management Systems (BMS). Tailored for EV applications, this system provides a hands-on learning experience in SoC estimation, cell balancing, thermal management, and safety logic using actual EV components. With an integrated environmental chamber and open-source control software, BMSTS enables students and researchers to design, test, and validate custom BMS algorithms in a safe and controlled environment.

Key Features

Hands-On EV BMS Platform
Includes a modifiable BMS, actual EV-compatible components, and a BYOB (Bring Your Own Battery) interface for realistic and personalized testing scenarios.
Integrated Learning and Experimental Environment
The setup includes a battery pack, customizable BMS, battery cycler, and environmental chamber—providing a turnkey platform for full-spectrum BMS research without external equipment.
Real-Time Simulation and Data Logging
Enables accurate simulation of EV charging and discharging events while logging key data including voltage, current, SoC, and temperature for analysis and reporting.
Open-Source Control and Algorithm Development
Offers open software architecture with FPGA-based control, allowing users to implement and test their own BMS logic, SoC estimation models, and thermal strategies.
Environmental Chamber for Thermal Experiments
Allows testing of BMS cut-off behavior and thermal performance under controlled temperature conditions, simulating real-world operating environments.
Flexible SoC Estimation Techniques
Supports various methods including Coulomb Counting, Voltage-based SoC, Modified Coulomb Counting, and Kalman Filter, enabling experimentation and comparative analysis.
Advanced Battery Protection Testing
Evaluate responses to fault conditions such as overvoltage, undervoltage, overcurrent, short circuit, overcharging, and over-discharging to assess BMS reliability and safety compliance.

Learning Module

State of Charge Estimation and Cell Balancing

Implement and compare SoC estimation methods:
Coulomb Counting
Modified Coulomb Counting
Voltage-Based Estimation
Kalman Filter Method
Test and analyze passive vs. active cell balancing techniques.
Evaluate effectiveness of voltage equalization and its impact on battery life and performance.

Thermal Behavior and Battery Protection

Use the environmental chamber to test BMS response across –10°C to +60°C with humidity control.
Analyze thermal cutoff points, temperature-driven behavior, and protection logic.
Simulate and assess responses to fault conditions including:
Overvoltage / Undervoltage
Overcurrent / Short circuit
Overcharge / Over-discharge

Custom BMS Design and Simulation

Develop and modify BMS algorithms using open-source tools and FPGA-based control.
Simulate charging/discharging events and validate user-defined test scenarios.
Analyze system behavior in real-time, including SoC accuracy, thermal regulation, and safety logic.
Conduct end-to-end testing of BMS strategies for EV applications in a controlled lab environment.

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