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Due to the new CO2 targets for vehicles, electrification of powertrains and operation strategies for electrified powertrains have drawn more attention. This article presents a predictive multi-objective operation strategy for hybrid electric vehicles (HEVs), which simultaneously minimizes the fuel consumption and the cycle aging of traction batteries. This proposed strategy shows better performance by using predictive information and high robustness to inaccuracy of predictive information. In this work, the benefits of the developed operation strategies are demonstrated in a strong hybrid electric vehicle (sHEV) with P2-configuration. For the cycle aging of a lithium-ion battery, an empirical model is built up with Gaussian processes based on experimental data.

New combustion principle concepts combined with enormous application efforts as well as rapid development of gasoline- and diesel injection systems, make high demands on the fuel consumption measuring system. Because of the high degree of automated test bed applications, challenging requirements to reliability and plausibility of measuring results at simultaneously shorter measuring times arise. The following paper describes a new fuel consumption measuring system by presenting specific application examples and shows how efficient utilisation of resources, regarding manpower and test bed capacity, can be reached and how a significant timesaving can be realised.