Predictive operation strategy for hybrid vehicles
The hybrid electric vehicle (HEV) is considered to be one of the best solutions for the automobile industry, to cope with the diminishing oil resources and environmental problems, by achieving low emissions and fuel consumption. The HEV is powered by two sources, composed of an internal combustion engine (ICE) and its transmission as well as one or two electric machines (EM), battery pack and converters. The additional electric power system brings further degrees of freedom for powertrain arrangement and operation, which lead to a challenge the research and development. A number of publications [Radke13] [Schroeter13] [Albers13] [Ambühl09] [Stiegeler08] discussed predictive operation strategies with global optimization methods, e.g. dynamic programming. However, the computing and memory requirements of the global optimization method are significantly higher than those from a heuristic optimization method, thus rendering its complete application in onboard electronic control units (ECU) almost impossible. Some predictive operation strategies are combinations of global optimization and heuristic optimization method [Katsargyri09] [LaSch13]. In order to develop an online operation strategy for HEV by using the traffic context for semi-automated driving, a heuristic method is applied in this work and with consideration of longitudinal dynamics. Beside the fuel consumption the driving comfort and operation complexity are considered in this method to be optimized, which is lacked in many publications. This work presents the method and simulation results of this strategy. The details about real time capability will be done in the future work.
KeywordsCombustion Europe Lithium Torque Radar
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