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An adaptative energy management strategy for series hybrid electric vehicles based on optimized maps and the SUMO (Simulation of Urban MObility) predictor is presented here. The first step of the investigation is the off line optimization of the control strategy parameters (already developed by the authors) over a series of reference mini driving cycles (duration of 60s) obtained from standard driving cycles (UDDS, EUDC, etc) and realistic driving cycles acquired on the ITAN500 HEV. The optimal variables related to each mini driving cycle are stored in maps that are then implemented on the ITAN500 vehicles. When the vehicle moves, a wireless card is used to exchange information with surrounding vehicle and infrastructure. These information are used by a local instance of the SUMO traffic prediction tool (run on board) to predict the driving conditions of the HEV in the future period of time T=60s.

In the present study, the influence of pressure waves propagating in the ducts of common rail injection systems on engine out emission has been investigated. The pressure waves originated by the closure of the injectors are characterized by an amplitude that can easily be greater than 10 MPa. When a multi injection strategy is adopted such fluctuations can strongly affect fuel delivery rate of subsequent injections and therefore emission levels and fuel consumption. The paper reports the results of an experimental investigation that has been carried out on a single cylinder engine equipped with a common rail electronically controlled high pressure injection system and an optical access, via endoscopes, for the visualization of soot and combustion process. The used injection strategy consisted of pilot and main injection. To allow the start of the main injection on a local pressure peak or valley without changing injection timing, injection system ducts of different length were used.