DrivePy (Data-Driven Powertrain Modelling in Python) is a cutting-edge framework for simulating and analyzing powertrain systems using advanced data-driven methodologies.
DrivePy leverages state-of-the-art machine learning techniques and robust numerical solvers to model a wide range of powertrain architectures, from internal combustion engines to fully electric and hybrid systems.
Key features include:
- Real-time simulation capabilities for vehicle drive cycles such as WLTP, NEDC, and custom routes.
- Modular design, enabling easy integration of components like engines, electric motors, transmissions, and control systems.
- Support for dynamic scenarios, including thermal interactions, transient effects, and energy management strategies.
- A library of pre-trained models for different powertrain configurations (ICE, HEV, BEV, PHEV, FCEV) and parameter sets.
- Functionality to simulate experimental conditions, such as torque-speed profiles, regenerative braking, and gearshift schedules.
DrivePy is designed for both researchers and engineers, offering an extensible platform to optimize performance, minimize emissions, and innovate in the rapidly evolving field of vehicle powertrain technologies.