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In the last years the automotive industry has been involved in the development and implementation of CO2 reducing concepts such as the engines downsizing, stop/start systems as well as more costly full hybrid solutions and, more recently, waste heat recovery technologies. These latter include ThermoElectric Generator (TEG), Rankine cycle and Electric Turbo Compound (ETC) that have been practically implemented on few heavy-duty application but have not been proved yet as effective and affordable solutions for the automotive industry. The paper deals with the analysis of opportunities and challenges of the Electric Turbo Compound for automotive light-duty engines. In the ETC concept the turbine-compressor shaft is connected to an electric machine, which can work either as generator or motor. In the former case the power can satisfy the vehicle electrical demand to drive the auxiliaries or stored in the batteries.

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.

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.

In the field of passenger car engines, recent research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting particularly stringent exhaust emissions limits. Knock and turbocharger control are two of the most critical factors that influence the achievement of maximum efficiency and satisfactory drivability, for this new generation of engines. The sound emitted from an engine encloses many information related to its operating condition. In particular, the turbocharger whistle and the knock clink are unmistakable sounds. This paper presents the development of real-time control functions, based on direct measurement of the engine acoustic emission, captured by an innovative and low cost acoustic sensor, implemented on a platform suitable for on-board application.

The emissions limits of CO2 for vehicles are becoming more stringent with the aim of reducing greenhouse gas emissions and improve fuel economy. The New European Driving Cycle (NEDC) is adopted to measure emissions for all new internal combustion engines in the European Union, and it is performed on cold vehicle, starting at a temperature of 22°C ± 2°C. Consequently, the cold-start efficiency of internal combustion engine is becoming of predominant interest. Since at cold start the lubricant oil viscosity is higher than at the target operating temperature, the consequently higher energy losses due to increased frictions can substantially affect the emission cycle results in terms of fuel consumption and CO2 emissions. A suitable thermal management system, such as an exhaust-to-oil heat exchanger, could help to raise the oil temperature more quickly.

Compression-ignited engines are still considered the most efficient and reliable technology for automotive applications. However, current and future emission regulations, which severely limit the production of NOx, particulate matter and CO2, hinder the use of diesel-like fuels. As a matter of fact, the spontaneous ignition of directly-injected Diesel leads to a combustion process that is heterogeneous by nature, therefore characterized by the simultaneous production of particulate matter and NOx. In this scenario, several innovative combustion techniques have been investigated over the past years, the goal being to benefit from the high thermal efficiency of compression-ignited engines, which results primarily from high Compression Ratio and lean and unthrottled operation, while simultaneously mitigating the amount of pollutant emissions.

Knock control systems based on engine block vibrations analysis are widely adopted in passenger car engines, but such approach shows its main limits at high engine speeds, since knock intensity measurement becomes less reliable due to the increased background mechanical noise. For small two wheelers engines, knock has not been historically considered a crucial issue, mainly due to small-sized combustion chambers and mixture enrichment. Due to more stringent emission regulations and in search of reduced CO2 emissions, an effective on-board knock controller acquires today greater importance also for motorcycle applications, since it could protect the engine when different fuel types are used, and it could significantly reduce fuel consumption (by avoiding lambda enrichment and/or allowing higher compression ratios to be adopted). These types of engines typically work at high rotational speeds and the reduced signal to noise ratio makes knock onset difficult to identify.

The next steps of the current European and US legislation, EURO 6c and LEV III, and the incoming new test cycles will impose more severe restrictions on pollutant emissions for Gasoline Direct Injection (GDI) engines. In particular, soot emission limits will represent a challenge for the development of this kind of engine concept, if injection and after-treatment systems costs are to be minimized at the same time. The paper illustrates the results obtained by means of a numerical and experimental approach, in terms of soot emissions and combustion stability assessment and control, especially during catalyst-heating conditions, where the main soot quantity in the test cycle is produced. A number of injector configurations has been designed by means of a CAD geometrical analysis, considering the main effects of the spray target on wall impingement.

Combustion phasing is crucial to achieve high performance and efficiency: for gasoline engines control variables such as Spark Advance (SA), Air-to-Fuel Ratio (AFR), Variable Valve Timing (VVT), Exhaust Gas Recirculation (EGR), Tumble Flaps (TF) can influence the way heat is released. The optimal control setting can be chosen taking into account performance indicators, such as Indicated Mean Effective Pressure (IMEP), Brake Specific Fuel Consumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature, or knock intensity. Given the high number of actuations, the calibration of control parameters is becoming challenging.

Measurement of particle number was introduced in the Euro 5/6 light duty vehicle emissions regulation. Due to the complex nature of combustion exhaust particles, and to transportation, transformation and deposition mechanisms, such type of measurement is particularly complex, and regression analysis is commonly used for the comparison of different measurement systems. This paper compares various commercial instruments, developing a correlation analysis focused on PN (Particle Number) measurement, and isolating the factors that mainly influence each measuring method. In particular, the experimental activity has been conducted to allow critical comparisons between measurement techniques that are imposed by current regulations and instruments that can be used also on the test cell. The paper presents the main results obtained by analyzing instruments based on different physical principles, and the effects of different sampling locations and different operating parameters.

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.

1 The Selective Catalytic reduction (SCR) using urea as reducing agent is currently regarded as the most promising after-treatment technology in order to comply with strict RDE targets for NOX and particulate in Diesel application. Model-based control strategies are promising to satisfy the demands of high NOX conversion efficiency and low tailpipe ammonia slip. This paper deals with the development of a control oriented model of a Cu-zeolite urea-SCR system for automotive Diesel engines. The model is intended to be used for the real-time urea-SCR management, depending on engine NOX emissions and ammonia storage. In order to ensure suitable computational demand for the on-board implementation, a reduced order one-state model of ammonia storage has been derived from a quasi-dimensional four-state model of the urea-SCR plant.

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.

This work focuses on the development and validation of a data-driven model capable of predicting the maximum in-cylinder pressure during the operation of an internal combustion engine, with the least possible computational effort. The model is based on two parameters, one that represents engine load and another one the combustion phase. Experimental data from four different gasoline engines, two turbocharged Gasoline Direct Injection Spark Ignition, a Naturally Aspirated SI and a Gasoline Compression Ignition engine, was used to calibrate and validate the model. Some of these engines were equipped with technologies such as Low-Pressure Exhaust Gas Recirculation and Water Injection or a compression ignition type of combustion in the case of the GCI engine. A vast amount of engine points were explored in order to cover as much as possible of the operating range when considering automotive applications and thus confirming the broad validity of the model.

The paper presents the main results obtained by developing and critically comparing different evaporative emissions leak detection diagnostic systems. Three different leak detection methods have been analyzed and developed by using a model-based approach: depressurization, air and fuel vapor compression, and natural vacuum pressure evolution. The methods have been developed to comply with the latest OBD II requirement for 0.5 mm leak detection. Detailed grey-box models of both the system (fuel tank, connecting pipes, canister module, engine intake system) and the components needed to perform the diagnostic test (air compressor or vacuum pump) have been used to analyze in a simulation environment the critical aspects of each of the three methods, and to develop “optimal” diagnostic model-based algorithms.

The paper presents the development and real-time implementation of a combustion control system based on optimal management of multiple spark discharge events, in order to increase combustion stability, reduce pollutant emissions and fuel consumption, and avoid partial or missing combustion cycles. The proposed approach has been developed as a cost-effective solution to several combustion-related issues that affect Gasoline Direct Injection (GDI) engines during cold start and part load operation. The problem of optimizing combustion efficiency and improving its stability during such operating modes is even more critical for high performance engines, which are designed to maximize charge efficiency especially at medium-high engine speeds.

During the development of an Internal Combustion Engine-based powertrain, traditional procedures for control strategies calibration and validation produce huge amount of data, that can be used to develop innovative data-driven applications, such as emission virtual sensing. One of the main criticalities is related to the data quality, that cannot be easily assessed for such a big amount of data. This work focuses on an emission modeling activity, using an enhanced Light Gradient Boosting Regressor and a dedicated data pre-processing pipeline to improve data quality. First thing, a software tool is developed to access a database containing data coming from emissions tests. The tool performs a data cleaning procedure to exclude corrupted data or invalid parts of the test. Moreover, it automatically tunes model hyperparameters, it chooses the best set of features, and it validates the procedure by comparing the estimation and the experimental measurement.

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.

Future regulations on pollutant emissions will impose a drastic cut on Diesel engines out-emissions. For this reason, the development of closed-loop combustion control algorithms has become a key factor in modern Diesel engine management systems. Diesel engines out-emissions can be reduced through a highly premixed combustion portion in low and medium load operating conditions. Since low-temperature premixed combustions are very sensitive to in-cylinder thermal conditions, the first aspect to be considered in newly developed Diesel engine control strategies is the control of the center of combustion. In order to achieve the target center of combustion, conventional combustion control algorithms correct the measured value varying main injection timing. A further reduction in engine-out emissions can be obtained applying an appropriate injection strategy.

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.