With, the onset of the electrification of vehicles, battery life estimation has become a very important issue in the design and commercialization of vehicle electrification technologies. Designing and implementing algorithms to adequately predict battery life is essential for the wide-scale adoption of hybrid vehicles, i.e. both charge-sustaining electric vehicles (HEVs) and plug-in electric vehicles (PHEVs) and pure electric vehicles (EVs). In order to effectively design methods for predicting battery life, accurate and efficient modeling and simulation tools are required to support in the design, identification, and modeling of such methodologies and algorithms. In this paper, we will present a modeling and simulation tool that is intended to be used for battery life estimation in PHEV applications. The dynamic PHEV model is based on many years of development at The Ohio State University's Center for Automotive Research in Columbus OH. The focus of the paper is not so much on each individual vehicle component of the model, but on the design and implementation of the software model. In addition, we will present the design and implementation of parallelized Monte Carlo simulations completed on The Ohio Supercomputer Center using the software model. At the end of the paper, we will present some example results and metrics obtained from the simulation infrastructure that can be used for battery life estimation.
Battery life estimation in PHEV applications: A monte carlo simulation study
2012
8 Seiten, 14 Bilder, 3 Tabellen, 10 Quellen
Aufsatz (Konferenz)
Englisch
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