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BMS Learn & Build Platform 

The BMS Learn & Build Platform is a comprehensive learning, development, and validation solution designed for students, researchers, universities, and industry professionals working with battery technologies. It bridges the gap between theoretical education and practical implementation by providing a hands-on environment to design, program, test, and validate a BMS battery management system for real battery packs. Built for next-generation battery technologies, the platform enables users to develop and evaluate BMS for lithium-ion battery applications used in electric vehicles, renewable energy storage systems, robotics, drones, and industrial battery-powered equipment. Whether learning battery fundamentals or developing advanced control algorithms, this platform provides an industry-ready experience. The system combines a programmable BMS controller, intelligent battery monitoring system, battery cycler, data acquisition, and optional environmental testing chamber into a single integrated solution. With LabVIEW-based visualization and open-source firmware, users can configure battery parameters, perform BMS battery charging experiments, execute protection algorithms, and analyse battery performance in real time. Designed for education, research, and product development, the platform provides a scalable environment for developing modern EV BMS solutions while supporting practical experimentation with real lithium-ion battery packs. 

Key Features

  • Scalable BMS Battery Management System Architecture: Supports battery configurations up to 23 cells in series and 5 cells in parallel, while also allowing smaller battery packs for beginner-level experiments. The modular architecture makes it suitable for learning as well as advanced BMS battery management system development.
  • Bring Your Own Battery (BYOB): Connect custom lithium battery packs for practical testing and research. This flexibility allows users to validate different BMS for lithium-ion battery configurations without hardware limitations.
  • Intelligent Battery Monitoring System: The integrated battery monitoring system continuously measures individual cell voltage, bidirectional current, and multiple temperature points with high accuracy. Real-time monitoring enables precise battery diagnostics, safety analysis, and performance evaluation.
  • Advanced Protection Functions: The platform includes comprehensive battery protection features such as: Over-voltage protection, Under-voltage protection, Over-current protection, Short-circuit protection, Over-temperature protection, Under-temperature protection, Cell fault diagnostics, Pack-level protection logic. These features simulate real-world EV BMS safety functions used in commercial battery systems.
  • Multiple Cell Balancing Techniques: Compare and implement: Passive Cell Balancing, Active Cell Balancing, Dynamic Cell Balancing.Users can evaluate balancing efficiency while developing custom BMS battery management system algorithms.
  • State of Charge & State of Health Estimation: Supports multiple battery estimation techniques including:Coulomb Counting, Open Circuit Voltage (OCV), Kalman Filter, Extended Kalman Filter (EKF), User-defined estimation algorithms.Ideal for advanced BMS for lithium-ion battery research and algorithm validation.
  • Open-Source Firmware: The programmable controller allows users to develop custom protection logic, balancing methods, charging strategies, and estimation algorithms for EV BMS applications.
  • LabVIEW-Based User Interface: The intuitive graphical interface provides: Live battery visualization, Real-time data logging, Parameter configuration, Fault injection, Performance analysis, Battery diagnostics, Integrated Battery Cycler.
  • Supports programmable BMS battery charging and discharge profiles including: Constant Current (CC), Constant Voltage (CV), Constant Power (CP), C-Rate Testing, Charge–Discharge Cycling.This enables comprehensive battery validation under different operating conditions.
  • Environmental Testing Support: Optional integration with an environmental chamber enables testing of BMS for lithium-ion battery performance under varying temperature and humidity conditions, making it suitable for research laboratories and product validation.
Ecosense

Learning Module 

Ecosense

BMS Fundamentals & Battery Architecture

Learn the fundamentals of battery pack design, cell configurations, series and parallel connections, and the role of a modern BMS battery management system in ensuring battery safety, reliability, and performance.

Topics include:

  • Battery pack architecture
  • Cell interconnections
  • Battery chemistry fundamentals
  • BMS in battery concepts and terminology
  • Role of EV BMS in electric vehicles
  • Voltage, current, and temperature sensing
  • Hardware and software interaction

Battery Monitoring, Protection & Balancing

Understand how a battery monitoring system continuously supervises battery health while implementing advanced protection mechanisms.

Topics include:

  • Passive balancing
  • Active balancing
  • Dynamic balancing
  • Protection thresholds
  • Fault detection
  • Battery diagnostics
  • Safety algorithms
  • Comparative balancing analysis

Validation, Testing & Performance Analysis

Perform real-world battery experiments using programmable charge-discharge cycles and environmental testing.

Experiments include:

  • Controlled battery cycling
  • BMS battery charging validation
  • Thermal performance analysis
  • Long-term degradation studies
  • C-rate testing
  • Battery ageing analysis
  • Research data acquisition
  • Publication-ready data generation

How BMS Learn and Build Platform Works

The platform operates as a complete battery development and validation ecosystem for learning, research, and industrial prototyping.

  • Users begin by configuring battery parameters, balancing methods, protection thresholds, charging profiles, and control algorithms using the PC-based software interface.
  • These configurations are downloaded to the programmable controller, which acts as the central BMS battery management system for the connected battery pack.
  • The integrated battery monitoring system continuously measures individual cell voltages, battery current, and multiple temperature points using precision sensors.
  • The controller processes this information in real time to execute balancing algorithms, protection logic, and battery diagnostics.
  • The battery cycler performs programmable charging and discharging operations while supporting advanced BMS battery charging strategies for battery validation.
  • All battery parameters are recorded continuously for analysis, reporting, and research.
  • For advanced studies, the battery pack can be tested inside an environmental chamber to evaluate the effect of temperature and humidity on battery behaviour. This makes the platform ideal for EV BMS research, battery safety validation, and performance optimization.

The platform also introduces important BMS in battery concepts while providing a complete practical environment for understanding battery architecture, diagnostics, and intelligent battery management.

Applications

The BMS Learn & Build Platform is suitable for:

  • Engineering colleges and universities
  • Research laboratories
  • EV development centres
  • Battery manufacturers
  • Renewable energy system developers
  • Industrial R&D organisations
  • Academic training programmes
  • Battery algorithm research
  • Electric vehicle education
  • Product development and validation

Battery Management System (BMS) Setup Video Guide

Watch how to setup a Battery Management System (BMS) for EV Labs




Ecosense

Technical Specifications 

Ecosense

BMS Learn & Build System


ParametersSpecifications
Battery ConfigurationUp to 23S × 5P (BYOB)
Max Pack Voltage73.6 V
Current Measurement±30 A bidirectional
Temperature Sensors≥4 channels (NTC/RTD)
Balancing ModesPassive, Active, Dynamic

* specifications can be customized as per user's needs.

Battery Cycler & Analytics


ParametersSpecifications
Voltage Range2.5 – 90 V
Current Range0 – 30 A
Max Power2500 W
Operating ModesCC, CP, C-rate, Cycle
Data ExportCSV, image files

* specifications can be customized as per user's needs.

Control & User Interface


ParametersSpecifications
Controller32-bit ARM Cortex-M4
FirmwareOpen-source, user editable
GUILabVIEW-based
Data LoggingReal-time & historical
IntegrationEnvironmental chamber support

* specifications can be customized as per user's needs.

Real world impact across Campuses

Recent Installations

Ecosense Establishes Advanced Electric Vehicle Lab at IET Lucknow

Ecosense Establishes Advanced Electric Vehicle Lab at IET Lucknow

June 17, 2025

Hands on Learning Platform for Electric Mobility, Aligned with India's Clean Energy Future

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Frequently Asked Questions

The platform supports lithium-based battery chemistries such as LiFePO₄. It allows user-defined battery configurations up to 23 cells in series and 5 strings in parallel, enabling flexibility for academic experiments, EV battery studies, and research applications.

Yes. The system features open-source microcontroller firmware and a LabVIEW-based interface, allowing users to implement, modify, and validate custom algorithms for SoC estimation, cell balancing, and protection logic on real battery packs.

The platform incorporates comprehensive safety protections, including over-voltage, under-voltage, overcurrent, short-circuit, and temperature-based cut-offs at both cell and pack levels, ensuring safe operation during training and research.

The environmental chamber enables temperature- and humidity-controlled testing, allowing users to study battery performance, protection behaviour, and algorithm accuracy under real-world thermal stress conditions.

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