Design Optimization of a Series Plug-in Hybrid Electric Vehicle for Real-World Driving Conditions

SAE 2010 World Congress & Exhibition
Authors Abstract
This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS). This is a finding of high relevance for forecasting technology diffusion, consumer acceptance, and impact of PHEVs on power grid. These differences increase progressively with desired AER due to increasing energy/mile usage of real world driving with distance.
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Patil, R., Adornato, B., and Filipi, Z., "Design Optimization of a Series Plug-in Hybrid Electric Vehicle for Real-World Driving Conditions," SAE Int. J. Engines 3(1):655-665, 2010,
Additional Details
Apr 12, 2010
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Journal Article