Hybridizing vehicles is one of the paths followed by OEM to reduce their vehicle consumption and emissions, especially in premium segment. Indeed, this segment is facing severe problems in reaching European environmental exhaust targets when running on fossil fuel only, not the least due to the considerable vehicle weight. The European funded project ADVICE targeted this issue by aiming at increasing the market penetration of hybrid vehicles by cost reduction and by technology improvement.Simulation models are a cost-efficient approach to evaluate the impact of a technology on a variety of driving conditions or to virtually evaluate the impacts of potential improvements such as driving resistance, weight reduction or energy management strategy on vehicle fuel consumption. This paper presents a methodology to generate a reliable hybrid vehicle model exclusively from experimental data and validate it with objective KPIs. The methods we present permit to obtain sufficient components and strategy characterization accuracy from dynamic vehicle-level test such as WLTP or RDE. The advantage of this methodology is its capability to maximize the outcome of the regular vehicle-level testing activities to generate a predictive vehicle consumption model without the need of specific component or stabilized condition testing, being a cost-efficient first approach to build a model representing the observed vehicle use. Nonetheless, if required by the application, this model can be enriched with additional specific testing (components level, high demand testing, stabilized conditions…) to guarantee its predictivity in a wider set of conditions. Specific correlation KPIs were applied in order to guarantee adequate correlation between various signals acquired in the experimental activities and simulated signals. This methodology, guarantees the accuracy and the predictivity of the model, allowing consistent trade-off studies or new system assessment. The resulting predictive models were used to calculate the impact of improvements on weight, drag, auxiliary loads and strategy in consumption. The data for performing this activity is extracted from the European funded project ADVICE. The paper shows the application of the methodology, the correlation result and how the validated vehicle model is used to analyse the energy management and evaluate the potential impact of vehicle improvements on fuel consumption.

Mr. Pablo Cano, Applus IDIADA, SPAIN Mrs. Marina Roche, Applus IDIADA, FRANCE Mr. Albert Hernández, Applus IDIADA, SPAIN Mr. Dídac Sabrià, Applus IDIADA, SPAIN Dr. Eng. Marco Mammetti, Applus IDIADA, ITALY