A comparative study of fuel efficiency and performance of an HEV powertrain was performed by a team from Maplesoft, ISKO Engineers AG and IPG Automotive. The powertrain model was developed in MapleSim, the multidomain modeling and simulation environment from Maplesoft. It was then converted into a Functional Mockup Unit (FMU) for integration with the test environment using IPG CarMaker®, an open integration and testing platform. The virtual vehicle, road and driver were set up using CarMaker, which then linked the entire virtual environment with Optimus®, a Process Integration and Design Optimization (PIDO) platform from Noesis, to perform comprehensive multi-objective optimization.
Overview of the process
The multidomain powertrain model was developed using components from MapleSim's electrical and mechanical libraries, as well as commercialized library components from MapleSim's Driveline Component Library and Battery Component Library. In order to meet the goal of a realistic HEV powertrain with a continuously variable transmission (CVT) where efficiency is maximized, a commercially-available powertrain example was selected as a reference model. The selected powertrain configuration is a Parallel HEV model with a CVT, inspired by the 2006 Honda Civic Integrated Motor Assist (IMA) powertrain.
Based on engine performance data for a 1.36L engine, the engine map for the model's internal combustion engine subsystem was implemented using MapleSim's Driveline engine components. The nickel metal hydride (NiMH) equivalent circuit battery model was selected from the MapleSim Battery Component Library, to represent the NiMH battery in the reference powertrain. It provides the electrical energy storage required for the HEV and an additional electrical charge to operate the auxiliary components that would normally operate the 12V electrical systems. The CVT component that allows the transmission ratio to be adjusted based on the specified gear ratio was selected from MapleSim's Driveline Component Library, and an energy management strategy was implemented, to determine the distribution of power between the electric motor, the internal combustion engine and the battery.
MapleSim powertrain model, prepared for FMU export
The completed powertrain model was then prepared for FMU export, using the MapleSim Connector for FMI. The Connector supports the FMI standards Model Exchange and Co-Simulation.
Through CarMaker's support for the FMI Co-Simulation Standalone standard, the powertrain FMU was imported and integrated into the test environment. CarMaker enables users to integrate their vehicle components â€“ from individual components all the way to interconnected systems - into a virtual vehicle prototype, and investigate the overall behavior and interactions between subsystems, under real-world driving conditions.
Powertrain FMU integration with CarMaker
The test environment provides a detailed matched interface to the full vehicle model, for easy integration of imported powertrain models. It consists of a parameterized vehicle model, which represents the vehicle dynamics and overall behavior of a real-world car. It is placed on a virtual road where traffic objects, traffic signs and lights, road markers and the environment can be defined, and is driven by an integrated driver model with maneuver control. By combining models that represent the vehicle, driver, traffic and the environment, with detailed powertrain models, CarMaker enables comprehensive analyses of powertrain systems.
Following the integration of the MapleSim-generated powertrain FMU into the CarMaker test environment, Optimus was used to take on the task of automatically starting the CarMaker simulations, analyzing the results, and performing required optimizations. Simulations were run for an aggressive driver and a defensive driver, and the results were used to perform multi-objective optimization of the powertrain FMU to meet pre-define performance goals.
This integrated design process, where models are shared easily between tools, provided engineers with a much richer understanding of how the HEV powertrain design will behave under different circumstances, and allowed them to then optimize performance, all at a fraction of the cost of traditional design methods.