Model-based closed-loop control strategies for flex-fuel capability

Abstract

Meeting future limits for greenhouse gas (GHG) and pollutant emissions represents major challenges for the further development of internal combustion engines for light and heavy-duty applications. To comply with increasingly higher standards, the use of renewable fuels is an important option due to their great potential in terms of energy density, sustainability and low-pollution combustion. However, the increased fuel diversity associated with their use increases the complexity of the powertrain development and calibration process, resulting in an increase in development time and cost. To address these challenges, advanced model-based closed-loop control strategies are applied to optimize the fuel- and air-path settings and make best use of the properties of the different fuels. One such approach is Combustion Rate Shaping (CRS). This ensures a closed-loop control of combustion parameters such as the indicated mean effective pressure, the center of heat release, and the combustion noise excitation. In addition, a model-based closed-loop NOx control could simplify the control on the air-path side. Such a closed-loop approach can further be combined with an onboard fuel detection algorithm and learning functionalities that eventually allow switching to optimal setpoints based on the fuel properties. This publication presents an evaluation of CRS as control concept with flex-fuel operation. The control strategy is implemented on a demonstrator vehicle built up with a Rapid Control Prototyping (RCP) system. The results of emission test cycles with conventional diesel fuel and later with a blend with 1- Octanol, OME3–5 and a paraffinic renewable diesel fuel are presented to illustrate the potential of the novel control concept. The developed CRS concept shows a reduced combustion parameters and emissions dispersion. In particular, the results with OME3–5 blend shows up to 40% reduction in NOx emissions and up to 1 dB(A) lower average combustion noise in comparison to conventional open-loop control. Moreover, an onboard fuel detection and an adaptive control functionality are proposed and experimental validations are carried out to demonstrate the potential to optimize engine emissions.