Battery Cycler with Data Analytics

The Battery Cycler with Data Analytics (BCDA) by Ecosense is a comprehensive educational and experimental platform designed to study and analyze electric vehicle (EV) battery systems. Combining real EV components with open-source software and a built-in environmental chamber, this system provides users with the tools to conduct hands-on experiments, simulate real-world conditions, and perform in-depth data analytics. BCDA is ideal for institutions and research labs aiming to deliver practical skills and foster innovation in battery technology and electric mobility.

Key Features

Integrated Experimental Platform with Real EV Components
Includes an actual lithium-based EV battery pack, smart BMS, and power electronics—all enclosed in a modular, scalable design that supports realistic battery cycling experiments.
Battery Cycler with Real-Time Data Logging
Supports programmable charge/discharge cycles using Constant Current (CC), Constant Voltage (CV), and Constant Power (CP) mode, C-Rate Mode and Battery Cycler mode. Monitors voltage, current, temperature, SoH, and SoC continuously with high-resolution data acquisition.
Environmental Chamber for Thermal Testing
Features an integrated environmental chamber capable of simulating ambient temperatures from –10°C to +60°C and humidity levels from 60%–90%, enabling the study of battery behavior under diverse environmental conditions.
Open-Source Control and Analytics Software
Users can configure tests, define control parameters, and modify algorithms using a PC-based software suite. The open-source nature of the system allows custom algorithm development for advanced research.
FPGA-Based Control Unit
A robust FPGA control board governs the cycler system, allowing precise, real-time regulation of testing parameters, ensuring high accuracy in all experiments.
Flexible Experimental Framework
Allows performance comparison of new and aged batteries, state-of-health (SoH) tracking, thermal response evaluation, and fuel economy benchmarking—all within a safe and controlled lab setting.
Designed for Indoor Use and Research
The enclosed, electrically safe design is ideal for indoor use in academic and industrial research labs. Includes full documentation and experiment protocols.

Learning Module

Battery Testing, Environmental Performance & Degradation

Conduct charge/discharge tests using Constant Current (CC), Constant Voltage (CV), Constant Power (CP), and C-rate modes.
Analyze battery behavior across different loads and cycling patterns.
Use the integrated environmental chamber to simulate temperatures from –10°C to +60°C and assess thermal effects on battery efficiency.
Monitor State of Health (SoH) and capacity fade by comparing new and aged battery packs over multiple cycles.

Regenerative Battery Cycling and Control

Operate the regenerative battery cycler to recover and reuse energy during discharge cycles.
Use the FPGA-based control system for precise charge/discharge regulation and experiment automation.
Configure programmable test cases and simulate real-world EV load conditions.
Evaluate cycle performance under different regeneration conditions and study energy recovery efficiency.

Data Analytics, Optimization & Decision-Making

Collect and analyze real-time data including voltage, current, temperature, SoC, and SoH.
Use the software interface for real-time plotting, storage, and export of test results.
Compare battery charging strategies (e.g., 0–100%, 30–100%, 50–100%) for performance and longevity.
Apply data analytics to optimize battery usage, assess energy density, and support EV system design decisions.

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