EV Drive Line Simulator

The EV Drive Line Simulator (EDLS) by Ecosense is a state-of-the-art educational and experimental platform designed to provide real-time simulation, analysis, and control of electric vehicle (EV) drivetrain systems. With integrated traction motors, dynamometer-based loading, and open-source software, EDLS allows students and researchers to deeply engage with every aspect of EV propulsion, control, and regenerative braking. It serves as a complete, lab-scale replica of an actual EV drivetrain, enabling practical learning, algorithm development, and system performance evaluation.

Key Features

Real EV Components for Real-Time Simulation
EDLS integrates actual EV hardware including a traction motor, motor controller, dynamometer, and battery pack, providing realistic system behavior and measurable outputs.
Modifiable Control Algorithms
Comes with open-source application software and an FPGA-based controller, allowing users to modify inverter control algorithms and simulate drive cycles with full customization.
Integrated and Standalone Learning Environment
Includes all essential EV drivetrain components in a single platform—no external equipment needed. Ideal for academic labs, skill centers, and R&D environments.
Regenerative Braking System
Supports complete study and analysis of regenerative braking behavior, including energy recovery patterns and battery charging during deceleration.
Drive Cycle Simulation
Capable of simulating standard and custom drive cycles such as Indian Drive Cycle (IDC) and NEDC, for comprehensive performance testing and emissions modeling.
Dynamic Loading with Electric Dynamometer
The system uses an electric dynamometer to apply variable loads and simulate real road conditions. Controlled manually or via software-defined drive profiles.
FPGA-Based Central Controller
Provides real-time signal processing and control through a robust, user-programmable FPGA system, ensuring precise motor behavior replication.

Learning Module

Control Systems and Algorithm Development

Design and implement inverter control algorithms using an FPGA-based controller.
Develop and test custom switching strategies for improving drive efficiency and responsiveness.
Simulate various drive cycles (IDC, NEDC) and observe system behavior under different conditions.
Program dynamic load profiles to simulate real road conditions via the electric dynamometer.

Performance Testing and Motor Analysis

Analyze motor torque-speed characteristics and dynamic response to load changes.
Record and evaluate parameters such as voltage vs. time, current vs. time, torque vs. RPM, and efficiency curves.
Measure active, reactive, and apparent power under various operating scenarios.
Characterize EV motor behavior across a range of speeds and loads.

Regenerative Braking, Energy Recovery, and Data Analysis

Study regenerative braking behavior and observe energy flow from the motor to the battery during deceleration.
Analyze energy recovery patterns and charging behavior during braking events.
Perform real-time data acquisition of speed, torque, voltage, and current.
Visualize and export system performance data using the GUI for further analysis and reporting.

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