Search Results

This paper investigates the FPGA resources for the implementation of in-cycle closed-loop combustion control algorithms. Closed-loop combustion control obtains feedback from fast in-cylinder pressure measurements for accurate and reliable information about the combustion progress, synchronized with the flywheel encoder. In-cycle combustion control requires accurate and fast computations for their real-time execution. A compromise between accuracy and computation complexity must be selected for an effective combustion control. The requirements on the signal processing (evaluation rate and digital resolution) are investigated. A common practice for the combustion supervision is to monitor the heat release rate. For its calculation, different methods for the computation of the cylinder volume and heat capacity ratio are compared. Combustion feedback requires of virtual sensors for the misfire detection, burnt fuel mass and pressure prediction.

Yearly 3.3 million premature deaths occur worldwide due to air pollution and NOx pollution counts for nearly one seventh of those [1]. This makes exhaust after-treatment a very important research and has caused the permitted emission levels for NOx to decrease to very low levels, for EURO 6 only 0.4 g/kWh. Recently new legislation on ammonia slip with a limit of 10 ppm NH3 has been added [2], which makes the SCR-technology more challenging. This technology injects small droplets of an aqueous Urea solution into the stream of exhaust gases and through a catalytic reaction within the SCR-catalyst, NOx is converted into Nitrogen and Water. To enable the catalytic reaction the water content in the Urea solution needs to be evaporated and the ammonia molecules need to have sufficient time to mix with the gases prior to the catalyst.

Model-based analysis of in-cylinder pressure sensor signals has been a key component for internal combustion engine research, diagnostics and controller development during the past decades. This analysis is often based on simple thermodynamic models of the in-cylinder processes. In order for the analysis to give accurate results, the models need to be sufficiently calibrated. This paper investigates the use of the extended Kalman filter and the particle filter for the purpose of online estimation of top-dead-center offset, a convective heat-transfer coefficient and cylinder-wall temperature in a Gatowski heat-release model. Simulation results show that the filters are consistent in estimating the true parameters, that the assumed model uncertainty and heat-release noise density works as filter tuning parameters. The filters were found to be sensitive to errors on pressure-sensor offset and the cylinder compression ratio.

The aim of this paper is to compile the state of the art of engine control and develop scenarios for improvements in a number of applications of engine control where the pace of technology change is at its most marked. The first application is control of downsized engines with enhancement of combustion using direct injection, variable valve actuation and turbo charging. The second application is electrification of the powertrain with its impact on engine control. Various architectures are explored such as micro, mild, full hybrid and range extenders. The third application is exhaust gas after-treatment, with a focus on the trade-off between engine and after-treatment control. The fourth application is implementation of powertrain control systems, hardware, software, methods, and tools. The paper summarizes several examples where the performance depends on the availability of control systems for automotive applications.