Search Results

The Selective Catalytic Reduction (SCR) system installed on the exhaust line is currently widely used on Diesel heavy-duty trucks and it is considered a promising technique for light and medium duty trucks, large passenger cars and off-highway vehicles, to fulfill future emission legislation. Some vehicles of these last categories, equipped with SCR, have been already put on the market, not only in the US, where the emission legislation on Diesel vehicles is more restrictive, but also in Europe, demonstrating to be already compliant with the upcoming Euro 6. Moreover, new and more stringent emission regulations and homologation cycles are being proposed all over the world, with a consequent rapidly increasing interest for this technology. As a matter of fact, a physical model of the Diesel Exhaust Fluid (DEF) supply system is very useful, not only during the product development phase, but also for the implementation of the on-board real-time controller.

New gasoline engine design is highly influenced by CO2 and emission limits defined by legislations, the demand for real conditions fuel economy, higher torque, higher specific power and lower cost. To reach the requirements coming from the end-users and legislations, especially for SI engines, several technologies are available, such as downsizing, including turbocharging in combination with direct injection. These technologies allow to solve the main issues of gasoline engines in terms of efficiency and performance which are knocking, part-load losses, and thermal stress at high power conditions. Moreover, other possibilities are under evaluation to allow further steps of enhancement for the even more challenging requirements. However, the benefits and costs given by the mix of these technologies must be accurately evaluated by means of objective tools and procedures in order to choose among the best alternatives.

The continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at combustion control improvement. Nowadays, performing an efficient combustion control is crucial for drivability improvement, efficiency increase and pollutant emissions reduction. These aspects are even more crucial when innovative combustions (such as LTC or RCCI) are performed, due to the high instability and the high sensitivity with respect to the injection parameters that are associated to this kind of combustion. Aging of all the components involved in the mixture preparation and combustion processes is another aspect particularly challenging, since not all the calibrations developed in the setup phase of a combustion control system may still be valid during engine life.

The purpose of this paper is to present some innovative techniques developed for an unconventional utilization of currently standard exhaust sensors, such as HEGO, UEGO, and NOx probes. In order to comply with always more stringent legislation about pollutant emissions, intake-exhaust systems are becoming even more complex and sophisticated, especially for CI engines, often including one or two UEGO sensors and a NOx sensor, and potentially equipped with both short-route and long-route EGR. Within this context, the effort to carry out novel methods for measuring the main exhaust gas dynamic properties exploiting sensors installed for different purposes, could be useful both for control applications, such as EGR rates estimation, or cost reduction, minimizing the on-board devices number. In this work, a gray-box model for measuring the gas mass flow rate, based on standard NOx sensor operating parameters of its heating circuit, is analyzed.

Automotive engines and control systems are more and more sophisticated due to increasingly restrictive environmental regulations. Particularly in both diesel and SI lean-burn engines NOx emissions are the key pollutants to deal with and sophisticated Engine Management System (EMS) strategies and after-treatment devices have to be applied. In this context, the in-cylinder oxygen mass fraction plays a key-role due its direct influence on the NOx formation mechanism. Real-time estimation of the intake O₂ charge enhances the NOx prediction during engine transients, suitable for both dynamic adjustments of EMS strategies and management of aftertreatment devices. The paper focuses on the development and experimental validation of a real-time estimator of O₂ concentration in the intake manifold of an automotive common-rail diesel engine, equipped with turbocharger and EGR system.

This work focuses on the effects of cooled Low Pressure EGR and Water Injection observed by conducting experimental tests consisting mainly of Spark Advance sweeps at different cooled LP-EGR and WI rates. The implications on combustion and main engine performance indexes are then analysed and modelled with a control-oriented approach, showing that combustion duration and phase and exhaust gas temperature are the main affected parameters. Results show that cooled LP-EGR and WI have similar effects, being the associated combustion speed decrease the main cause of exhaust gas temperature reduction. Experimental data is used to identify control-oriented polynomial models able to capture the effects of LP-EGR and WI on both these aspects. The limitations of LP-EGR are also explored, identifying maximum compressor volumetric flow and combustion stability as the main ones.

This paper deals with modeling and analysis of the integration of ThermoElectric generators (TEG) into a conventional vehicle, specifically aimed at recovering waste heat from exhaust gases. The model is based on existing and commercial thermoelectric materials, specifically Bi2Te3, having ZTs not exceeding 1 and efficiency below 5%, but a trade-off between cost and performance that would be acceptable for automotive applications. TEGs operate on the principle of thermoelectric energy conversion via Seebeck effect, utilizing thermal gradients to generate electric current, with exhaust gases at the hot side and coolant at the cold side. In the simulated configuration the TEG converters are interfaced with the battery/alternator supporting the operation of the vehicle, reducing the energy consumption due to electrical accessories and HVAC.

Multi-jet injection strategies open significant opportunities for the combustion management of the modern diesel engine. Splitting up the injection process into 5 steps facilitates the proper design of the combustion phase in order to obtain the desired torque level, whilst attempting a reduction in emissions, particularly in terms of NOx. Complex 3-D models are needed in the design stage, where components such as the injector or combustion chamber shape have to be determined. Alternatively, zero-dimensional approaches are more useful when fast interpretation of experimental data is needed and an optimization of the combustion process should be obtained based on actual data. For example, zero-dimensional models allow a quick choice of optimum control settings for each engine operating condition, avoiding the need to test all the possible combinations of engine control parameters.

Theoretical models are useful tools in the design of engine control systems, with applications that range from the design of engine layout, the definition of optimised management systems, to hardware-in-the-loop testing (HiL) and to model-based control strategies. To define theoretical models for control-oriented applications, an original library has been built up at the University of Parma for the simulation of the intake and exhaust systems of automotive turbocharged engines. Starting from this library, a Mean Value Model (MVM) of a Diesel engine, with variable-geometry turbocharger (VGT), EGR and throttle valve, has been developed for a small automotive application. In the paper the matching of the engine model with a detailed model of the exhaust system (developed by Magneti Marelli Powertrain) is presented.

Regarding automotive applications, Internal Combustion Engines (ICE) have become very complex plants to comply with present and future requirements in reduction of fuel consumption, pollutant emissions and performance improvement. As a consequence, the development of engine control and diagnostic system is a key aspect in the powertrain design. Mathematical models are useful tools in this direction, with applications that range from the definition of optimised management systems, to Hardware- and Software-in-the-Loop testing (HiL and SiL) and to modelbased control strategies. To this extent an original library has been developed by the authors for the simulation of last generation automotive engines. Library blocks were used to assembly a sub-model of the typical intake and exhaust system of a turbocharged engine (with VGT, intercooler, EGR circuit with cooler and throttle).

Nowadays requirements towards a reduction in fuel consumption and pollutant emissions of Internal Combustion Engines (ICE) keep on pushing manufacturers to improve engines performance through the enhancement of existing subsystems (e.g.: electronic fuel injection, air systems) and the introduction of specific devices (e.g.: exhaust gas recirculation systems, SCR, …). Modern systems require a combined design and application of different after-treatment devices. Mathematical models are useful tools to investigate the complexity of different system layouts, to design and to validate (HIL/SIL testing) control strategies for the after-treatment management. This study presents a mean value model of an exhaust system with SCR; it has been coupled with a common rail diesel engine combustion black box model (Neural Network based). So, dedicated models for exhaust pipes, oxidation catalyst, diesel particulate filter and selective catalytic converter are developed.

In the last decades, worldwide automotive regulations induced the industry to dramatically increase the application of electronics in the control of the engine and of the pollutant emissions reduction systems. Besides the need of engine control, suitable fault diagnosis tools had also to be developed, in order to fulfil OBD-II and E-OBD requirements. At present, one of the problems in the development of Diesel engines is represented by the achievement of an ever more sharp control on the systems used for the pollutant emission reduction. In particular, as far as NOx gas is concerned, EGR systems are mature and widely used, but an ever higher efficiency in terms of emissions abatement, requires to determine as better as possible the actual oxygen content in the charge at the engine intake manifold, also in dynamic conditions, i.e. in transient engine operation.

The paper focuses on the experimental identification and validation of different neural networks for virtual sensing of NOx emissions in combustion compression ignition engines (CI). A comparison of several neural network architectures (NN, TDNN and RNN) has been carried out in order to evaluate precision and generalization in dynamic prediction of NOx formation. Furthermore the model complexity (number and types of inputs, neuron and layer number, etc.) has been considered to allow a future ECU implementation and on line training. Suited training procedures and experimental tests are proposed to improve the models. Several measurements of NOx emissions have been performed through different devices applied to the outlet of a EURO 5 Common Rail diesel engine with EGR. The accuracy of the developed models is assessed by comparing simulated and experimental trajectories for a wide range of operating conditions.

Modern internal combustion engine control systems require on-board evaluation of a large number of quantities, in order to perform an efficient combustion control. The importance of optimal combustion control is mainly related to the requests for pollutant emissions reduction, but it is also crucial for noise, vibrations and harshness reduction. Engine system aging can cause significant differences between each cylinder combustion process and, consequently, an increase in vibrations and pollutant emissions. Another aspect worth mentioning is that newly developed low temperature combustion strategies (such as HCCI combustion) deliver the advantage of low engine-out NOx emissions, however, they show a high cylinder-to-cylinder variation. For these reasons, non uniformity in torque produced by the cylinders in an internal combustion engine is a very important parameter to be evaluated on board.

It is well known that in automotive applications problems related to control and management are nowadays of paramount importance to improve engine performance and to reduce fuel consumption and pollutant emissions. In the design of control and diagnostics systems, the use of theoretical models proved to be very promising, also to reduce development time and costs, as widely documented in the open literature. From this point of view, the complexity of actual engines due both to the continuous enhancement of existing subsystems (e.g., turbochargers, exhaust gas recirculation systems, aftertreatment components, etc.) and to the introduction of specific devices (e.g., Variable Valve Actuation systems) give rise to challenging issues in modeling development and applications. The paper describes a theoretical model of an automotive engine built up starting from the original library developed in Simulink® by the authors for the simulation of last generation automotive engines.

In modern turbocharged downsized GDI engines the achievement of maximum thermal efficiency is precluded by the occurrence of knock. In-cylinder pressure sensors give the best performance in terms of abnormal combustion detection, but they are affected by long term reliability issues and still constitute a considerable part of the entire engine management system cost. To overcome these problems, knock control strategies based on engine block vibrations or ionization current signals have been developed and are widely used in production control units. Furthermore, previous works have shown that engine sound emissions can be real-time processed to provide the engine management system with control-related information such as turbocharger rotational speed and knock intensity, demonstrating the possibility of using a multi-function device to replace several sensors.

The continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at complying with upcoming increasingly stringent regulations throughout the world. Performing an efficient combustion control is crucial for efficiency increase and pollutant emissions reduction. These aspects are even more crucial for innovative Low Temperature Combustions (such as RCCI), mainly due to the high instability and the high sensitivity to slight variations of the injection parameters that characterize this kind of combustion. Optimal combustion control can be achieved through a proper closed-loop control of the injection parameters. The most important feedback quantities used for combustion control are engine load (Indicated Mean Effective Pressure or Torque delivered by the engine) and center of combustion (CA50), i.e. the angular position in which 50% of fuel burned within the engine cycle is reached.

New and upcoming exhaust emissions regulations and fuel consumption reduction requirements are forcing the development of innovative and particularly complex intake-engine-exhaust layouts. Especially in the case of Compression Ignition (CI) engines, the HC-CO-NOx-PM after-treatment system is becoming extremely expensive and sophisticated, and the necessity to further reduce engine-out emission levels, without significantly penalizing fuel consumption figures, may lead to the adoption of intricate and challenging intake-exhaust systems configurations. The adoption of both long- and short-route Exhaust Gas Recirculation (EGR) systems is one example of such situation, and the need to precisely measure (or estimate) mass flow rates in the various elements of the gas exchange circuit is one of the consequences.

The increase in the fuel price and more stringent regulations on greenhouse gases (CO2) make the engine compression ignition technology even more attractive in the context of internal combustion engines. This is because the modern turbocharged direct injection engines, with the common rail fuel system, are characterized by high combustion efficiency and power density, that make them particularly suitable both for applications on and off road. On the other hand, the compression ignition engines are subject to a heavy technological developments to meet the more stringent regulations on emissions of exhaust pollutants, especially PM and NOx. The adopted technologies have two main approaches, on the combustion and on the exhaust gas aftertreatment. The measures applied for combustion can reduce emissions, but with the risk of penalizing the other engine performances, such as noise, power output and fuel consumption.

The paper describes suited methodologies for developing Recurrent Neural Networks (RNN) aimed at estimating NOx emissions at the exhaust of automotive Diesel engines. The proposed methodologies particularly aim at meeting the conflicting needs of feasible on-board implementation of advanced virtual sensors, such as neural network, and satisfactory prediction accuracy. Suited identification procedures and experimental tests were developed to improve RNN precision and generalization in predicting engine NOx emissions during transient operation. NOx measurements were accomplished by a fast response analyzer on a production automotive Diesel engine at the test bench. Proper post-processing of available experiments was performed to provide the identification procedure with the most exhaustive information content. The comparison between experimental results and predicted NOx values on several engine transients, exhibits high level of accuracy.