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Internal combustion engines must be individually tested at the end of the manufacturing process. In recent years classical hot test stands, where the engine is run for several minutes, are being replaced by cold test alternatives. The latter allow fast testing cycles using an external motoring device without using any fuel. The absence of fuel and combustion lowers the health and safety requirements for the plant itself and subsequent engine transport, but this comes at the cost of additional difficulties for the verification of the correct assembly and operation of the combustion system hardware. This paper presents a cold test concept, which includes dedicated measurements and algorithms for the detection of common failures in the manufacturing process, including those of the combustion hardware.

Dual-fuel combustion engines have shown the potential to extend the operating range of Homogeneous Charge Compression Ignition (HCCI) by using several combustion modes, e.g. Reactivity Controlled Compression Ignition (RCCI) at low/medium load, and Partially Premixed Compression (PPC) at high load. In order to optimize the combustion mode operation, the respective sensitivity to the control inputs must be addressed. To this end, in this work the extremum seeking algorithm has been investigated. By definition, this technique allows to detect the control input authority over the system by perturbing its value by a known periodic signal. By analyzing the system response and calculating its gradient, the control input can be adjusted to reach optimal operation. This method has been applied to a dual-fuel engine under fully, highly and partially premixed conditions where the feedback information was provided by in-cylinder pressure and NOx sensors.

Fuel-to-air ratio stimulation, also called λ cycling or λ modulation, is a natural consequence of controlling fuel-to-air ratio in closed-loop with a switch-type λ-sensor. Nowadays, wideband λ-sensors are broadly extended and fuel-to-air ratio stimulation is an additional option that can or not be implemented in the control strategies to improve TWC conversion efficiency through the increase of the catalyst activity. The present work focus on the suitability of applying fuel-to-air ratio stimulation in a turbocharged GDI engine equipped with a close-coupled TWC. In particular, the influence of the main parameters such as stimulation amplitude and frequency on tailpipe emissions at steady-state conditions is assessed. The potential of λ cycling in order to reduce pollutant emissions in the face of fuel-to-air ratio disturbances has also been evaluated. Results show how a proper λ modulation decreases NOx emissions at lean conditions.

The development of one cycle resolution control strategies and the research at HCCI engines demands an accurate estimation of the trapped mass. In contrast to current methods for determining the mass flow, which are only able to determine averaged values of the flow entering the cylinders, the present paper proposes a methodology based on the in-cylinder pressure resonance. The determination of such frequency allows inferring the cylinder mass with one cycle resolution. In addition, the method permits determining error metrics based on the mass conservation principle. Validation results for a reactivity controlled compression ignition (RCCI) engine equipped with electrohydraulic variable valve timing (VVT) are presented to illustrate the performance of the method.

Boosting technologies have been key enablers for automotive engines development through downsizing and downspeeding. In this situation, numerous multistage boosting systems have appeared in the last decade. The complexity arising from multistage architectures requires an efficient matching methodology to obtain the best overall powertrain performance. The paper presents a model aimed to choose the best 2-stage boosting system architecture able to meet required criteria on boosting pressure, EGR ratios for both short and long route loops while respecting the engine thermo-mechanical limits such as in-cylinder pressure, compressor outlet temperature and exhaust manifold temperature. The model includes filling-and-emptying 0D elements together with mean value. The engine model is set in a way that, for given requirements and boosting system layout, calculates in seconds if the requirements will be achieved and the position of variable geometry, waste-gate, EGR and by-pass valves.

Pre-turbo aftertreatment systems benefit from an increase of the temperature across the monolith reducing the time up to DOC light-off and reaching better conditions for passive regeneration in the DPF. The engine performance is also improved by reducing the specific fuel consumption. The pumping work diminishes because of the lower aftertreatment pressure drop due to the higher gas density. Additionally, the aftertreatment pressure drop is not multiplied by the turbine expansion ratio to set the engine back-pressure, which becomes lower. It also makes the DPF pressure drop less dependent on the soot mass loading. In this context, the traditional ratio between engine displacement and DOC & DPF volume in post-turbo aftertreatment placement needs to be reviewed in pre-turbo applications as a way to optimize savings in fuel consumption and aftertreatment manufacturing cost.

This paper shows the potential of a multicalibration approach for reducing fuel consumption while keeping pollutant immissions. The paper demonstrates that the current engine control approach with a single fixed calibration involves important fuel penalties in areas with low vehicle densities where local pollution is not an issue, while the NOx emissions in urban areas are usually too high to fulfill air quality standards. The proposed strategy is based on using information about the vehicle location and the NOx concentrations in the ambient to choose a suitable calibration amongst a set of possibilities. To assess the potential of such a strategy experimental tests have been done with a state-of-art turbocharged Diesel engine. First, a design of experiments is used to obtain three different calibrations.

Observers can be used for combining different information sources, as fast models with slow but accurate sensors. For that, a Kalman filter can be used for identifying the bias and cancelling its variation during time. However, normal calibration procedure is iterative and ad-hoc and this does not get optimal results. Furthermore, the lack of enough accurate references make difficult to estimate the best tuning, and more if the calibration pretends to be an online procedure. For solving this, the paper presents a novel calibration method for Kalman filter based on a Monte Carlo analysis, simulating real conditions by means of statistical distributions. This makes possible to create actual references for estimating error metrics of the observer output. A previous sensitivity study is presented for understanding the performance of the algorithm under different conditions.

The increasingly stringent antipollution legislation and the necessity of a continuous control of the pollutant emissions lead to the development, among others, of NOx estimation models to be included in the engine control system and the on-board diagnostic system. Two elements are important for a good estimation of these pollutant emissions: the knowledge of the combustion process, which is available via the instantaneous pressure signal, and the flame temperature, which is estimated from the in-cylinder conditions (mainly from the air temperature and oxygen concentration). All these parameters could be nowadays available and even analyzed on the vehicle during normal engine operation. In this paper we intend to assess the NOx estimation sensitivity to inaccuracies in the input parameters to identify the critical parameters in this estimation. The NOx emissions model which has been developed and used for this purpose in the frame of this research is based on the Zeldovich mechanism.

The influence of turbine inlet gas temperature on turbocharger performance is a topic discussed recently by many authors. Some studies present results on adiabatic operation by insulating the turbocharger from ambient conditions and report significant differences in compressor isentropic efficiency. Other authors perform non-adiabatic tests and report a significant influence on compressor isentropic efficiency only at the lowest turbocharger speed. In present work two different levels of gas temperature at the inlet of a Variable Geometry Turbine (VGT) have been tested at two different vane positions and two different corrected turbine speeds. Temperatures have been measured in the outer cases of turbine and compressor in order to determine the radiated power and their relative importance with respect to different power definitions obtained from turbocharger operative variables. The obtained results show the influence on both compressor and turbine isentropic efficiency.

The present paper shows the use of a 1-D wave action model in the design process of a sequential parallel turbocharged engine. Even though little information was available at the beginning of the design process, a wave action model was used because of its capability of predicting the behaviour of the new engine. Main issues that were studied by means of simulations are: system architecture, turbochargers matching, prediction of the altitude effect on the turbocharging system, optimization of the transition between different modes, and control system design. The paper also summarises the limitations of the model, mainly concerning combustion process modelling, which were later identified once experimental information was available.

Measurement systems are becoming more complex and test beds are usually automated; high measurement accuracy is also required. However it is common that measurement failures are only detected in the post-processing, resulting in important time and economic loss. Due to the huge amount of sensor signals, the online validation of the data is very time-consuming and infeasible without computer aid. In this study a failure detection framework is used for data plausibility analysis. This failure detection methodology is able to deal with generic models relating different measure channels. The general approach incorporates model and sensor inaccuracies in the evaluation procedure. Additionally, a useful set of physical equations applicable for failure detection in engine test bends is presented. These equations are combined with data-driven models allowing satisfactory detection rates while maintaining a low rate of false alarms.

The objective of this work is to make an analysis of the behaviour of the venturi in real working conditions. The modelling of the venturi, as well as the experimental and modelled results obtained, will be described. Modelled and measured techniques have been used to realize this work. A new model of the venturi was developed and using this, it is possible to find important instantaneous variables of the venturi. In order to adjust the calculated model, it was necessary to characterise the steady flow test rig of the venturi. In addition, the information obtained from the engine tests has been essential to correctly adjust the model. Therefore, a combination of the information obtained from both the venturi test and from modelled work was necessary in order to understand the behaviour of the venturi installed in an engine. Different tests have been performed on each venturi.