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In Motorsports the understanding of the real engine performance within a complete circuit lap is a crucial topic. On the basis of the telemetry data the engineers are able to monitor this performance and try to adapt the engine to the vehicle's and race track's characteristics and driver's needs. However, quite often the telemetry is the sole analysis instrument for the Engine-Vehicle-Driver (EVD) system and it has no prediction capability. The engine optimization for best lap-time or best fuel economy is therefore a topic which is not trivial to solve, without the aid of suitable, reliable and predictive engineering tools. A complete EVD model was therefore built in a GT-SUITE™ environment for a Motorsport racing car (STCC-VW-Scirocco) equipped with a Compressed Natural Gas (CNG) turbocharged S.I. engine and calibrated on the basis of telemetry and test bench data.

Minimizing the lap time for a given race track is the main target in racecar development. In order to achieve the highest possible performance of the vehicle configuration the mutual interaction at the level of assemblies and components requires a balance between the advantages and disadvantages for each design decision. Especially the major shift in the focus of racecar powerunit development to high efficiency powertrains is driving a development of lean boosted and rightsized engines. In terms of dynamic engine behavior the time delay from requested to provided torque could influence the lap time performance. Therefore, solely maximizing the full load behavior objective is insufficient to achieve minimal lap time. By means of continuous predictive virtual methods throughout the whole development process, the influence on lap time by dynamic power lags, e.g. caused by the boost system, can be recognized efficiently even in the early concept phase.

The main objective of the FVV-project “Cylinder Module” was the development of a profoundly modular designed concept for object-oriented modeling of in-cylinder processes of internal combustion engines. It was designed in such a way, that it can either be used as a stand-alone real working-process calculation tool or in tools for whole vehicle simulations. It is possible to run the “Cylinder Module”-code inside the FVV-“GPA”-software for transient vehicle and driving cycle simulations and it is possible to use the graphical user interface “ATMOS” of the “GPA”-project. The code can also be used as a user-subroutine in 1-D-flow simulation codes. Much effort was spent on the requirements of flexibility and expandability in order to be well prepared to cope with the diversity of both today's and future tasks. The code is freely available for members of the German Research Association for Combustion Engines (FVV).

Turbocharged SI-DI-engines in combination with a reduction of engine displacement (“Downsizing”) offer the possibility to remarkably reduce the overall fuel consumption. In charged mode it is possible to scavenge fresh unburnt air into the exhaust system if a positive slope during the overlap phase of the gas exchange occurs. The matching of the turbo system in SI-engines always causes a trade-off between low-end torque and high power output. The higher mass flow at low engine speeds of an engine using scavenging allows a partial solution of this trade-off. Thus, higher downsizing grades and fuel consumption reduction potential can be obtained. Through scavenging the global fuel to air ratio deviates from the local in-cylinder fuel to air ratio. It is possible to use a rich in-cylinder fuel to air ratio, whereas the global fuel to air ratio remains stochiometrical. This could be very beneficial to reduce the effect of catalytic aging on the one hand and engine knock on the other hand.

The hybrid power train technology offers various prospects to optimize the engine efficiency in order to minimize the CO₂ emissions of an internal-combustion-engine-powered vehicle. Today different types of hybrid architectures like parallel, serial, power split or through-the-road concepts are commonly known. To achieve lowest fuel consumption the following hybrid electric vehicle drive modes can be used: Start/Stop, pure electric/thermal driving, recuperation of brake energy and the hybrid mode. The high complexity of the interaction between those power sources requires an extensive investigation to determine the optimal configuration of a natural-gas-powered SI engine within a parallel hybrid power train. Therefore, a turbocharged 1.0-liter 3-cylinder CNG engine was analyzed on the test bench. Using an optimized combustion strategy, the engine was operated at stoichiometric and lean air/fuel ratio applying both high- and low-pressure EGR.

In this paper, a serial/parallel hybrid electric vehicle with a 17 kWh battery and 400 V voltage level is simulated. The vehicle is a C-segment vehicle, which has optimized driving resistances. It also has an external recharge possibility, which enables fully electric driving. The vehicle uses an Otto-engine concept as well as two electric motors. One motor is a permanent magnet synchronous motor and can be used as traction motor or generator, the other one is an induction motor used as main traction motor for the vehicle. The vehicle uses a 2-speed gearbox, where the electric motors are mounted in P2-configuration. To reach optimal results for the fuel consumption, an operating strategy based on the Equivalent Consumption Minimization Strategy (ECMS) is introduced and implemented in the vehicle simulation.