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The target of substantial CO₂ reductions in the spirit of the Kyoto Protocol as well as higher engine efficiency requirements has increased research efforts into hybridization of passenger cars. In the frame of this hybridization, there is a real need to develop small Internal Combustion Engines (ICE) with high power density. The two-stroke cycle can be a solution to reach these goals, allowing reductions of engine displacement, size and weight while maintaining good NVH, power and consumption levels. Reducing the number of cylinders, could also help reduce engine cost. Taking advantage of a strong interaction between the design office, 0D system simulations and 3D CFD computations, a specific methodology was set up in order to define a first optimized version of a two-stroke uniflow diesel engine. The main geometrical specifications (displacement, architecture) were chosen at the beginning of the study based on a bibliographic pre-study and the power target in terms.

The Hydrogen-Balance equation makes it possible to calculate the fuel economy or fuel consumption of hydrogen powered vehicles simply by analyzing exhaust emissions. While the benefits of such a method are apparent, it is important to discuss possible influencing factors that may decrease Hydrogen-Balance accuracy. Measuring vehicle exhaust emissions is done with a CVS (Constant Volume Sampling) system. While the CVS system has proven itself both robust and precise over the years, utilizing it for hydrogen applications requires extra caution to retain measurement accuracy. Consideration should be given to all testing equipment, as well as the vehicle being tested. Certain environmental factors may also play a role not just in Hydrogen-Balance accuracy, but as also in other low emission testing accuracy.

The results of previous Life Cycle Assessments indicate the ecological dominance of the vehicle's use phase compared to its production and recycling phase. Particularly the so-called weight-induced fuel saving coefficients point out the great spectrum (0.15 to 1.0 l/(100 kg · 100 km)) that affects the total result of the LCA significantly. The objective of this article, therefore, is to derive a physical based, i.e. scientific chargeable and practical approved, concept to determine the significant parameters of a vehicle's use phase for the Life Cycle Inventory. It turns out that - besides the aerodynamic and rolling resistance parameters and the efficiencies of the power train - the vehicle's weight, the rear axle's transmission ratio and the driven velocity profile have an important influence on a vehicle's fuel consumption.

The Energy and Environment Test Centre (EVZ) is a complex comprising three large climatic wind tunnels, two smaller test chambers, nine soak rooms and support infrastructure. The capabilities of the wind tunnels and chambers are varied, and as a whole give BMW the ability to test at practically all conditions experienced by their vehicles, worldwide. The three wind tunnels have been designed for differing test capabilities, but share the same air circuit design, which has been optimized for energy consumption yet is compact for its large, 8.4 m₂, nozzle cross-section. The wind tunnel test section was designed to meet demanding aerodynamic specifications, including a limit on the axial static pressure gradient and low frequency static pressure fluctuations - design parameters previously reserved for larger aerodynamic or aero-acoustic wind tunnels. The aerodynamic design was achieved, in-part, by use of computational fluid dynamics and a purpose-built model wind tunnel.

Engine downsizing is potentially one of the most effective strategies being explored to improve fuel economy. A main problem of downsizing using a turbocharger is the small range of stable functioning of the turbocharger centrifugal compressor at high boost pressures, and hence the measurement of the performance maps of both compressor and turbine. Automotive manufacturers use mainly numerical simulations for internal combustion engines simulations, hence the need of an accurate extrapolation model to get a complete turbine performance map. These complete maps are then used for internal combustion engines calibration. Automotive manufacturers use commercial softwares to extrapolate the turbine narrow performance maps, both mass flow characteristics and the efficiency curve.

A consortium of CONCAWE, EUCAR and the EU Commission's JRC carried out a Well-to-Wheels analysis of a wide range of automotive fuels and powertrains. The study gives an assessment of the energy consumption and greenhouse gas emissions for each pathway. It also considers macroeconomic costs and the market potential of alternative fuels.

The reduction of fuel consumption in vehicles remains an important target in vehicle development to meet the carbon dioxide emission reduction target. One of the significant consumers of energy in a vehicle is the hydraulic power-assisted steering system (HPS) powered by the engine belt drive. To reduce the energy consumption an electric motor can be used to drive the pump (electro-hydraulic power steering or EHPS). In this work a simulation model was developed and validated to model the energy consumption of the whole steering system. This includes an advanced friction model for the steering rack, a physically modeled steering valve, the hydraulic pump and the electric motor with the control unit. The model is used to investigate the influence of various parameters on the energy consumption for different road situations. The results identified the important parameters influencing the power consumption and showed the potential to reduce the power consumption of the system.

Multicore-based ECUs are increasingly used in embedded automotive software systems to allow more demanding automotive applications at moderate cost and energy consumption. Using a high number of parallel processors together with a high number of executed software components results in a practically unmanageable number of deployment alternatives to choose from. However correct deployment is one important step for reaching timing goals and acceptable latency, both also a must to reach safety goals of safety-relevant automotive applications. In this paper we focus at reducing the complexity of deployment decisions during the phases of allocation and scheduling. We tackle this complexity of deployment decisions by a mixed constructive and analytic approach.