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.
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