Abstract
Further improvements of hybrid electric vehicle (HEV) with advanced, next generation powertrain design require design optimization using advanced computer powertrain modeling tools. This work explores new hybrid powertrain architectures using advanced multi-physics modeling tools, and vehicle performance simulation based design optimization. The optimization problem is formulated using fuel consumption minimization as design objective, and battery SOC and driving cycle as functional constraints. The multi-physics and hybrid vehicle modeling tools from Dymola are used to model and simulate the vehicle performance and fuel consumption of a template commercial hybrid electric vehicle with similar powertrain structure as the 2008 GM Chevrolet Tahoe Hybrid SUV. The optimization tool box in Dymola is used to carry out the preliminary control strategy optimization. This study provides guidelines for introducing more advanced hybrid powertrain architectures and control algorithms for HEVs.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.