BMS Learn & Build Platform

The BMS Learn & Build Platform is a complete training and research solution designed to bridge the gap between classroom learning and real-world battery applications. As electric vehicles, renewable energy storage, and portable electronics continue to grow, the need for safe, efficient, and intelligent battery management has become essential. This platform empowers students, researchers, and developers to design, program, and validate Battery Management System (BMS) algorithms on real battery packs, providing both hands-on learning and research opportunities. At its core, the system is built on a modular architecture that integrates three subsystems: a BMS Learn & Build System for algorithm development, a Battery Cycler with Data Analytics for programmable charge-discharge cycles, and an Environmental Chamber Unit for temperature- and humidity-controlled testing. With a LabVIEW-based graphical interface and open-source firmware, users can configure experiments, simulate protection events, monitor performance in real-time, and refine their algorithms based on collected data. The result is a powerful, flexible, and scalable platform that prepares learners and innovators to address the challenges of modern battery technology.

Key Features

Battery Flexibility; Supports up to 23S5P packs with BYOB (Bring Your Own Battery) capability.
Chemistry Compatibility; Works with LiFePO₄, NMC, and other lithium chemistries.
Precision Monitoring; High-resolution measurement of voltage, current, and temperature at both cell and pack levels.
Safety First; Comprehensive protection against over-voltage, under-voltage, over-current, short circuit, thermal extremes, and more.
Smart Balancing; Experiment with passive, active, and dynamic balancing techniques in real-time.
SoC Estimation; Learn and compare Coulomb Counting, OCV, Kalman Filter, EKF, and custom algorithms.
SoH Insights; Track capacity fade and resistance growth for advanced battery health studies.
Open-Source Firmware; Modify protections, balancing logic, and estimation algorithms to suit research needs.
Interactive GUI; Real-time visualization, data logging, fault simulation, and debugging in a user-friendly interface.
Battery Cycler Integration; Run programmable charge/discharge experiments under constant current, voltage, or C-rate modes.
Thermal Testing; Validate packs under controlled temperatures and humidity with the Environmental Chamber.
Research-Ready; Supports studies in aging, fault tolerance, predictive balancing, and IoT-based smart BMS applications.
Education-Focused; Ideal for universities and R&D labs, supporting structured learning and open-ended research.

Learning Module

BMS Fundamentals & Protection

Learn basics of cell voltage, pack voltage, current, and temperature sensing.
Explore and compare passive, active, and dynamic balancing techniques.
Test BMS protection features by simulating faults such as over-voltage, under-voltage, over-current, short-circuit, and extreme temperature events.

State of Charge & Algorithm Development

Implement and compare SoC estimation methods: Coulomb Counting, OCV, Kalman Filter, EKF.
Customize algorithms using open-source firmware and the LabVIEW interface.
Study algorithm performance across different load profiles and temperatures.
Extend learning into SoH estimation with degradation and resistance growth analysis.

Advanced Validation & Research

Conduct charge-discharge cycles at programmable C-rates using the Battery Cycler.
Validate battery performance in environment-controlled testing with the Environmental Chamber.
Perform aging studies: cycle aging, calendar aging, and degradation tracking.
Investigate fault tolerance and safety responses under simulated abuse conditions.

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