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In a gasoline engine, the unswept in-cylinder residual gas and introduction of external EGR is one of the important means of controlling engine raw NOx emissions and improving part load fuel economy via reduction of pumping losses. Since the trapped in-cylinder Residual Gas Fraction (RGF, comprised of both internal, and external) significantly affects the combustion process, on-line diagnosis and monitoring of in-cylinder RGF is very important to the understanding of the in-cylinder dilution condition. This is critical during the combustion system development testing and calibration processes. However, on-line measurement of in-cylinder RGF is difficult and requires an expensive exhaust gas analyzer, making it impractical for every application. Other existing methods, based on measured intake and exhaust pressures (steady state or dynamic traces) to calculate gas mass flowrate across the cylinder ports, provide a fast and economical solution to this problem.

This paper reports on DaimlerChrysler's participation in the Ad Hoc Diesel Fuels Test Program. This program was initiated by the U.S. Department of Energy and included major U.S. auto makers, major U.S. oil companies, and the Department of Energy. The purpose of this program was to identify diesel fuels and fuel properties that could facilitate the successful use of compression ignition engines in passenger cars and light-duty trucks in the United States at Tier 2 and LEV II tailpipe emissions standards. This portion of the program focused on minimizing engine-out particulates and NOx by using selected fuels, (not a matrix of fuel properties,) in steady state dynamometer tests on a modern, direct injection, common rail diesel engine.

An electro-mechanical infinitely variable transmission (eVT), comprising a pair of planetary trains interconnected with two electric machines and clutches, has been proposed. The transmission leverages the advantages of an output power-split configuration for low-speed operation and a compound power-split configuration for high-speed operation. It is capable of being operated in a number of operating modes including an eVT only mode and a hybrid mode when equipped with on-board energy storage devices. The transmission provides a compact, highly efficient and potentially low cost driveline solution for both conventional vehicles and hybrid electric vehicles. A virtual transmission prototype was built in EASY51. A base vehicle model was also constructed in EASY5 environment with Ricardo Powertrain Library components.

An electro-mechanical variable speed transmission (eVT) is proposed for hybrid electric vehicles. The transmission is comprised of a pair of planetary gear trains interconnected with two electric machines and clutches. With on-board energy storage devices, the transmission combines, in a compact unit, independent speed-ratio control and power regulation between the engine and drive wheels. It offers a highly integrated, efficient and low cost solution to hybrid electric vehicles. Operating principles of the transmission were outlined. Virtual transmission and vehicle prototypes were built with EASY5. Simulations were conducted to evaluate its performance in context of a hybrid electric vehicle. Comparisons were made against non-hybrid vehicles equipped respectively with eVT and four-speed automatic transmission, and against the production hybrid vehicle Prius. Results showed superior performance of the proposed eVT in hybrid vehicle.

Variable Valve Actuation (VVA) technology provides high potential in achieving high performance, low fuel consumption and pollutant reduction. However, more degrees of freedom impose a big challenge for engine characterization and calibration. In this study, a simulation based approach and optimization framework is proposed to optimize the setpoints of multiple independent control variables. Since solving an optimization problem typically requires hundreds of function evaluations, a direct use of the high-fidelity simulation tool leads to the unbearably long computational time. Hence, the Artificial Neural Networks (ANN) are trained with high-fidelity simulation results and used as surrogate models, representing engine's response to different control variable combinations with greatly reduced computational time. To demonstrate the proposed methodology, the cam-phasing strategy at Wide Open Throttle (WOT) is optimized for a dual-independent Variable Valve Timing (VVT) engine.

Cam-phasing is increasingly considered as a feasible Variable Valve Timing (VVT) technology for production engines. Additional independent control variables in a dual-independent VVT engine increase the complexity of the system, and achieving its full benefit depends critically on devising an optimum control strategy. A traditional approach relying on hardware experiments to generate set-point maps for all independent control variables leads to an exponential increase in the number of required tests and prohibitive cost. Instead, this work formulates the task of defining actuator set-points as an optimization problem. In our previous study, an optimization framework was developed and demonstrated with the objective of maximizing torque at full load. This study extends the technique and uses the optimization framework to minimize fuel consumption of a VVT engine at part load.

Current engine development processes typically involve extensive steady-state and simple transient testing in order to characterize the engine's fuel consumption, emissions, and performance based on several controllable inputs such as throttle, spark advance, and EGR. Steady-state and simple transient testing using idealistic load conditions alone, however, is no longer sufficient to meet powertrain development schedule requirements. Mapping and calibration of an engine under transient operation has become critically important. And, independent engine development utilizing accelerated techniques is becoming more attractive. In order to thoroughly calibrate new engines in accelerated fashion and under realistic transient conditions, more advanced testing is necessary.

The base design of commercial vehicle wheel end systems has changed very little over the past 50 years. Current bearings for R-drive and trailer wheel end systems were designed between the 1920's and the 1960's and designs have essentially remained the same. Over the same period of time, considerable gains have been made in bearing design, manufacturing capabilities and materials science. These gains allow for the opportunity to significantly increase bearing load capacity and improve efficiency. Government emissions regulations and the need for fuel efficiency improvements in truck fleets are driving the opportunity for redesigned wheel end systems. The EPA and NHTSA standard requires up to 23% reduction in emissions and fuel consumption by 2017 relative to the 2010 baseline for heavy-duty tractor combinations.

A predictive automatic gear shift system is currently under development. The system optimizes the gear shift process, taking the conditions of the road ahead into account, such that the fuel consumption is minimized. An essential part of the system is a module that predicts the vehicle speed dynamics: This calculates a speed trajectory, i.e. the most probable vehicle speed the driver will desire for the upcoming section of the route. In the paper the theoretical background for predicting the vehicle speed, and simulation results of the predictive shift algorithm are presented.