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We are the first to report about a micromachined flow sensor directly integrated in the Common Rail injection nozzle body between the double guidance and the tip of the nozzle. The thermal measurement principle is chosen, because it enables a very precise and fast detection of gaseous and liquid mass flows. Additionally, the velocity field in the nozzle is only slightly influenced by the integration of the sensor in the nozzle body due to the negligible height of the sensitive layer. For a hot film anemometer, a high pressure stable ceramic substrate can be used, fabricated in a low cost batch process. The technology, to fabricate the sensor, as well as the first flow measurements, carried out at a high pressure test set up, are presented.

In practical applications, failures in the components of the control system can lead to improper, or even unstable, operation of the control loop. These failures can be associated with the process (abrupt change in the process dynamics), the measuring and manipulating devices (sensors, actuators) or the controller itself. It is therefore desired to design control system capable of handling such events in the sense that stability is guaranteed and performance degradation is minimized. The proposed formulation of the reliable performance problem involves the simultaneous minimization of the performance index for all considered failure scenarios. Employing the fractional representation theory, the reliable performance problem is formulated as a quadratically constrained control problem. The solution to this problem is discussed in this paper and an illustrative example is presented.

Significant improvement of engine performance can be achieved by ushering in a micro-electronic system to control the execution of combustion - an exothermic process whose sole purpose is to generate pressure. Hence, the primary feedback for the controller is provided by a pressure transducer. The activators are piezo-electrically activated pintle valves of MEMS type. The task of the micro-electronic processor is to provide an accurate feed-forward signal for the actuators on the basis of the information obtained from the feedback signal, within a time interval between consecutive cycles. Furnished here for this purpose is an algorithm for an interface module between the pressure sensor and the governor. Concomitantly, the gains thus attainable in the reduction of fuel consumption and curtailment of pollutant formation are thereby assessed. The implementation of this method of approach is illustrated by application to a HCCI engine.

Combatting the modification of automotive control systems is a current and future challenge for OEMs and suppliers. ‘Chip-tuning’ is a manifestation of manipulation of a vehicle's original setup and calibration. With the increase in automotive functions implemented in software and corresponding business models, chip tuning will become a major concern. Recognizing and reporting of tuned control units in a vehicle is required for technical as well as legal reasons. This work approaches the problem by capturing the behavior of relevant control units within a machine learning system called a recognition module. The recognition module continuously monitors vehicle's sensor data. It comprises a set of classifiers that have been trained on the intended behavior of a control unit before the vehicle is delivered. When the vehicle is on the road, the recognition module uses the classifier together with current data to ascertain that the behavior of the vehicle is as intended.

The fact that, in our times, the execution of the exothermic process of combustion (‘heat release”) remains virtually uncontrolled is astonishing. Upon an attempt to rationalize this anomaly on historical grounds, technological means to rectify this astounding state of affairs are presented. They are based on the premise that, in the course of this process, the cylinder-piston enclosure is, in effect, a full-fledged chemical reactor. The salient feature of control is then active intervention into chemical reaction by turbulent jets. Principal elements of the control system are, as in any feedback mechanism, (1) sensors, (2) actuators and (3) a governor. The object of the first is to measure the profile of pressure - the useful output of the process. The second consists of a set of turbulent jet generators for injection of fuel and its mixing with air, as well as for ignition.

A microhygrometer has been developed at JPL's Microdevices Laboratory based on the principle of dewpoint/frostpoint detection. The surface acoustic wave device used in this instrument is approximately two orders of magnitude more sensitive to condensation than the optical sensor used in chilled-mirror hygrometers. In tests in the laboratory and on the NASA DC8, the SAW hygrometer has demonstrated more than an order of magnitude faster response than commercial chilled-mirror hygrometers, while showing comparable accuracy under steady-state conditions. Current development efforts are directed toward miniaturization and optimization of the microhygrometer electronics for flight validation experiments on a small radiosonde balloon.

Evaluating real-world hazards associated with perception subsystems is critical in enhancing the performance of autonomous vehicles. The reliability of autonomous vehicles perception subsystems are paramount for safe and efficient operation. While current studies employ different metrics to evaluate perception subsystem failures in autonomous vehicles, there still exists a gap in the development and emphasis on engineering requirements. To address this gap, this study proposes the establishment of engineering requirements that specifically target real-world hazards and resilience factors important to AV operation, using High-Definition Maps, Global Navigation Satellite System, and weather sensors. The findings include the need for engineering requirements to establish clear criteria for a high-definition maps functionality in the presence of erroneous perception subsystem inputs which enhances the overall safety and reliability of the autonomous vehicles.