Search Results

The OBD II and EOBD legislation have significantly increased the number of system components that have to be monitored in order to avoid emissions degradation. Consequently, the algorithm design and the related calibration effort is becoming more and more challenging. Because of decreasing OBD thresholds, the monitoring strategy accuracy, which is tightly related with the components tolerances and the calibration quality, has to be improved. A model-based offline simulation of the monitoring strategies allows consideration of component and sensor tolerances as well as a first calibration optimization in the early development phase. AVL applied and improved a methodology that takes into account this information, which would require a big effort using testbed or vehicle measurements. In many cases a component influence analysis is possible before hardware is available for testbed measurements.

Worldwide OBD legislation has and will be tightened drastically. In the US, OBD II for PC and the introduction of HD OBD for HD vehicles in 2010 will be the next steps. Further challenges have come up with the introduction of active exhaust gas aftertreatment components to meet the lower future emission standards, especially with the implementation of combined DPF-De-NOx-systems for PC and HD engines. Following such an increase in complexity, more comprehensive algorithms and software have to be developed to cope with the legislative requirements for exhaust gas aftertreatment devices. The calibration has to assure the proper functionality of OBD under all driving situations and ambient conditions. The increased complexity can only be mastered when new and efficient tools and methodologies are applied for both algorithm design and calibration. Consequently, OBD requirements have to be taken into account right from the start of engine development.

Wet Clutches are used in automotive powertrains to enable compact designs and efficient gear shifting. During the slip phase of engagement, significant flash temperatures arise at the friction disc to separator interface because of dissipative frictional losses. An important aspect of the design process is to ensure the interface temperature does not exceed the material temperature threshold at which accelerated wear behavior and/or thermal degradation occurs. During the early stages of a design process, it is advantageous to evaluate numerous system and component design iterations exposed to plethora of possible drive cycles. A simulation tool is needed which can determine the critical operational conditions the system must survive for performance and durability to be assured. This paper describes a time-efficient multiphysics model developed to predict clutch disc temperatures with a runtime in the order of minutes.

The relationship of the airbag fire-distribution as a function of impact velocity to the airbag fire-time is studied through the use of an optimization procedure. The study is conducted by abstracting the sensor algorithm and its associated constraints into a simple mathematical formulation. An airbag fire objective function is constructed that integrates the fire-rate and fire-time requirements. The function requires the input of a single acceleration time history; it produces an output depending on the airbag fire condition. Numerical search of the optimal fire threshold curve is achieved through parameterizing this curve and applying a modified simplex search optimization algorithm that determines the optimal threshold function parameters without computing the complete objective function in the parameter space. Numerical results are given to show the effectiveness and potential difficulties with the automatic search scheme.

This paper describes the approximation of the engine torque of an SI-engine using recurrent neural networks. As modern engine control units today are based on engine torque management, there is a need for an accurate determination of the produced engine torque. Since direct measurements of this value are not possible in series applications due to resulting high costs, a fast and accurate algorithm for the approximation of these values from other sensor signals has to be found. Dynamic neural networks are a promising method to fulfill these requirements.

Future emission regulations and customer needs require revolutionary new approaches to engine management systems. In the EC part-funded AENEAS program the partners Ricardo, Kistler and DaimlerChrysler formed a consortium to investigate the application of a new combustion pressure sensor concept and innovative algorithms for engine management systems. This paper describes the general scope and the basic concepts of the system.

For the development of complex control algorithms and strategies the engine and powertrain test bed offers a number of advantages over the development in the prototype vehicle. The paper discusses how state-of-the-art simulation techniques can contribute to a continuous development process, which is based upon offline simulation using hardware in the loop, the utilization of modern test bed technology up to vehicle adjustment. The integration of hardware-in-the-loop testing together with vehicle and transmission simulation on the testbed allows to speed up the optimization of fuel consumption, emissions and driveability in an early stage in the development process. The available software tools are presented and application examples are given.