학술논문

Comparison of Various Hybrid Electric Powertrains for Non-Road Mobile Machinery Using Real-Time Multibody Simulation
Document Type
Periodical
Source
IEEE Access Access, IEEE. 10:107631-107648 2022
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Mechanical power transmission
Biological system modeling
Vehicle dynamics
Load modeling
Engines
Hybrid electric vehicles
Power transmission
Hybrid electric vehicle
power transmission
tractor model
multibody dynamics
driveline simulation
Language
ISSN
2169-3536
Abstract
Electrification of non-road mobile machinery holds immense potential for reducing the high emissions and fuel consumption of such industrial machinery. Detailed real-time physics-based simulation models capable of comparing energy efficiencies of hybrid powertrains in realistic working conditions can aid the development of efficient mobile machinery. In this study, four system-level hybrid electric powertrain models have been developed and coupled with a detailed multibody dynamics-based tractor model in a co-simulation environment. The four models, differentiated by their topology and transmission design, are simulated in a virtual environment under the dynamic load conditions of a ploughing work cycle of the Deutsche Landwirtschafts-Gesellschaft powermix. The simulation results show that improvements of 9.7% and 9.2% in total energy consumption can be achieved by the two studied power-split configurations in the simulated work cycle compared to an automated manual transmission-based series powertrain. The double planetary gear-based power-split model achieved the highest energy recovery and lowest energy loss compared to the other models. The developed models are real-time capable, allowing a human operator to simulate customizable work cycles.