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This study presents a comparison of different approaches for the simulation of HEV fuel consumption. For this purpose a detailed 1D-CFD model within an HEV drivetrain is compared to a ‘traditional’ map-based combustion engine model as well as different types of simplified engine models which are able to reduce computing time significantly while keeping the model accuracy at a high level. First, a simplified air path model (fast running model) is coupled with a quasi dimensional, predictive combustion model. In a further step of reducing the computation time, an alternative way of modeling the in cylinder processes was evaluated, by replacing the combustion model with a mean value model. For this approach, the most important influencing factors of the 1D-CFD air path model (temperature, pressure, A/F-ratio) are used as input values into neural nets, while the corresponding outputs are in turn used as feedback for the air path model.