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The European Commission is going to publish the new Euro7 standard shortly, with the target of reducing the impact on pollutant emissions due to transportation systems. Besides forcing internal combustion engines to operate cleaner in a wider range of operating conditions, the incoming regulation will point out the role of On-Board Monitoring (OBM) as a key enabler to ensure limited emissions over the whole vehicle lifetime, necessarily taking into account the natural aging of involved systems and possible electronic/mechanical faults and malfunctions. In this scenario, this work aims to study the potential of data-driven approaches in detecting emission-relevant engine faults, supporting standard On-Board Diagnostics (OBD) in pinpointing faulty components, which is part of the main challenges introduced by Euro7 OBM requirements.

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.

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.

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.

To meet the requirements in relation to pollutants, CO2-emissions, performances, comfort and costs for 2025 timeframe, many technology options for the powertrain, that plays a key role in the vehicle, are possible. Beside the central aspect of reducing standard cycle consumption levels and emissions, consumer demands are also growing with respect to comfort and functionality. In addition, there is also the challenge of finding cost efficient ways of integrating technologies into a broad range of vehicles with different levels of hybridization. High degrees of electrification simultaneously provide opportunities to reduce the technology content of the internal combustion engines (ICE), resulting in a cost balancing compromise between combustion engine and hybrid technology. The design and optimization of powertrain topologies, functionalities, and components require a complex development process.

Modern turbo-charged downsized engines reach high values of specific power, causing a significant increase of the exhaust gas temperature. Such parameter plays a key role in the overall powertrain environmental impact because it strongly affects both the catalyst efficiency and the turbine durability. In fact, common techniques to properly manage the turbine inlet gas temperature are based on mixture enrichment, which causes both a steep increase in specific fuel consumption and a decrease of catalyst efficiency. At the test bench, exhaust gas temperature is typically measured using thermocouples that are not available for on-board application, and such information is processed to calibrate open-loop look-up-tables. A real-time, reliable, and accurate exhaust temperature model would then represent a strategic tool for improving the performance of the engine control system.

A control oriented model of a Dual Clutch Transmission was developed for real time Hardware In the Loop (HIL) applications. The model is an innovative attempt to reproduce the fast dynamics of the actuation system maintaining a step size large enough for real time applications. The model comprehends a detailed physical description of hydraulic circuit, clutches, synchronizers and gears, and simplified vehicle and internal combustion engine sub-models; a stable real time simulation is achieved with a simplification of the model without losing physical validity. After an offline validation, the model was implemented in a HIL system and connected to the TCU (Transmission Control Unit) via two input-output boards, and to a load plate which comprehends all the actuators.

Turbocharged (TC) engines work at high Indicated Mean Effective Pressure (IMEP), resulting in high in-cylinder pressures and temperatures, improving thermal efficiency, but at the same time increasing the possibility of abnormal combustion events like knock and pre-ignition. To mitigate knocking conditions, engine control systems typically apply spark retard and/or mixture enrichment, which decrease indicated work and increase specific fuel consumption. Many recent studies have advocated Water Injection (WI) as an approach to replace or supplement existing knock mitigation techniques. Water reduces temperatures in the end gas zone due to its high latent heat of vaporization. Furthermore, water vapor acts as diluent in the combustion process. In this paper, the development of a novel closed-loop, model-based WI controller is discussed and critically analyzed.

Due to the ever increasingly stringent emission regulations for passenger vehicles, the efficiency and performance increase of Spark Ignition (SI) engines have been under the focus of the engine manufacturers. The quest for efficiency and performance increase has led to the development of increasingly complex powertrains and control strategies. The development process requires novel methods that feature a smooth transition between the real and the virtual prototypes. Furthermore, to reduce the development time and cost, developing an engine simulator with a low computational effort and good accuracy, which predicts the engine behavior on the entire operating range, plays a crucial role. This work proposes an Artificial Intelligence-based engine simulator for a Spark Ignition engine. The simulator relies on Neural Networks for the calculation of the main combustion metrics. In the first part of this paper, the data acquired at the engine test cell are analyzed.

Due to the recent anti-pollution policies, the performance increase in Spark Ignition (SI) engines is currently under the focus of automotive manufacturers. This trend drives control systems designers to investigate accurate solutions and build more sophisticated algorithms to increase the efficiency of this kind of engines. The development of a control strategy is composed of several phases and steps, and the first part of such process is typically spent in defining and investigating the logic of the strategy. During this phase it is often useful to have a light engine simulator, which allows to have robust synthetic combustion data with a low calibration and computational effort. In the first part of this paper, a description of the control-oriented ANalytical Engine SIMulator (ANESIM) is carried out.

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.

Over the past years, policies affecting pollutant emissions control for Diesel engines have become more and more restrictive. In order to meet such requirements, innovative combustion control methods have currently become a key factor. Several studies demonstrate that the desired pollutant emission reduction can be achieved through a closed-loop combustion control based on in-cylinder pressure processing. Nevertheless, despite the fact that cylinder pressure sensors for on-board application have been recently developed, large scale deployment of such systems is currently hindered by unsatisfactory long term reliability and high costs. Whereas both the accuracy and the reliability of pressure measurement could be improved in future years, pressure sensors would still be a considerable part of the cost of the entire engine management system.

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.

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 need for strategies that allow managing combustion in an adaptive way has recently widely increased. Especially Diesel engines aimed for clean combustion require a precise control of the combustion outputs. Acoustic emission of internal combustion engines contains a lot of information related to engine behavior and working conditions. Mechanical noise and combustion noise are usually the main contributions to the noise produced by an engine. Combustion noise in particular can be used as an indicator of the combustion that is taking place inside the combustion chamber and therefore as a reference for the control strategy. This work discusses the correlations existing between in cylinder combustion and the acoustic emission radiated by the engine and presents a possible approach to use this signal in the engine management system for control purposes.

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.