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Controlled Auto Ignition combustion systems have a high potential for fuel consumption and emissions reduction for gasoline engines in part load operation. Controlled auto ignition is initiated by reaching thermal ignition conditions at the end of compression. Combustion of the CAI process is controlled essentially by chemical kinetics, and thus differs significantly from conventional premixed combustion. Consequently, the CAI combustion process is determined by the thermodynamic state, and can be controlled by a high amount of residual gas and stratification of air, residual gas and fuel. In this paper both fundamental and application relevant aspects are investigated in a combined approach. Fundamental knowledge about the auto-ignition process and its dependency on engine operating conditions are required to efficiently develop an application strategy for CAI combustion.

Due to today's demands to reduce cost and product time to market, engineering procedures are increasingly using more sophisticated simulation techniques, instead of validation testing. Early implementation of CAE methods yield higher quality products, even with first prototypes, reducing the design iterations required to reach production quality. The strategy is to conduct specific evaluations of a realistic representation of the product while focusing on the key boundary conditions necessary to extract fatigue effects. Discussed in this paper are adequate CAE methods for early identification, evaluation and removal of conceptual and local structural weaknesses. Possible solutions gained from a computational optimization process are discussed for highly loaded HSDI diesel cylinder heads as a representative example.

The requirements for diesel and gasoline engines are continuously increasing with respect to emissions, fuel consumption and durability. Besides the engine development process the quality of the production engine itself has to be ensured. This paper discusses alternative philosophies and approaches in terms of the quality management process. Based on a detailed analysis of the required equipment advanced solutions are presented. Modular containerized test cells are described being equipped exactly to the current testing task ready to use in low infrastructure. The testing capacity of the facility can be adjusted to the actual production volume by simply removing or adding modular test cells. Thus, at every facility the testing tasks can be executed successfully and the investment can be kept low.

Electric Motor and Drivetrain (Electric Mobility) Testing is a critical part of bringing any electric drivetrain into production. In this paper the requirements for an electric drivetrain test cell are discussed. The implementations of such test cells are described and examples of test results are provided. In particular, the energy and power requirements for PM brushless DC dynamometers and a PM brushless Unit Under Test (UUT) connected through a common dc bus are described. Simulation of the set-up is developed using MATLAB/Simulink and verified using empirical data from the test bench. The data used represents various steady state load conditions during durability test cycles. This “Smart Green Technology” concept not only reduces the energy requirement from the grid but also eliminates the inefficiencies related to putting energy back on the grid.