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High cycle-to-cycle variations (CTCV) in a Hydrogen-Fueled Internal Combustion Engine (H2-ICE), especially in the lean-burn condition, not only lower the engine’s efficiency but also increase emissions and torque variations. High CTCV are mainly due to the variations in: mixture motion within the cylinder at the time of spark, amount of air and fuel fed to the cylinder, and mixing of the fresh mixture and residual gases within the cylinder during each cycle. In this article, multiple cycle-based methodologies were compared and analyzed specifically for H2-ICEs based on systematic experimentation. The experimental test campaign was performed on a Port Fuel Injection (PFI) H2-ICE designed by PUNCH Torino and data is processed with MATLAB. A MATLAB code is also proposed as a tool for comparing multiple methodologies for the analysis of CTCV specifically for H2-ICE.

Alternative fuels, such as natural and bio-gas, are attractive options for reducing greenhouse gas emissions from combustion engines. However, the naturally occurring variation in gas composition poses a challenge and may significantly impact engine performance. The gas composition affects fundamental fuel properties such as flame propagation speed and heat release rate. Deviations from the gas composition for which the engine was calibrated result in changes in the combustion phase, reducing engine efficiency and increasing fuel consumption and emissions. However, the efficiency loss can be limited by estimating the combustion phase and adapting the spark timing, which could be implemented favorably using a closed-loop control approach. In this paper, we evaluate the efficiency loss resulting from varying gas compositions and the benefits of using a closed-loop controller to adapt the spark timing to retain the nominal combustion phase.

Predicting and preventing combustion anomalies leads to safe and efficient operation of the hydrogen internal combustion engine. This research presents the application of three machine learning (ML) models – K-Nearest Neighbors (KNN), Random Forest (RF) and Logistic Regression (LR) – for the prediction of combustion anomalies in a hydrogen internal combustion engine. A small experimental dataset was used to train the models and posterior experiments were used to evaluate their performance and predicting capabilities (both in operating points -speed and load- within the training dataset and operating points in other areas of the engine map). KNN and RF exhibit superior accuracy in classifying combustion anomalies in the training and testing data, particularly in minimizing false negatives, which could have detrimental effects on the engine.

The paper presents novel studies on the impact of different ignition control parameters on combustion stability and spark plug wear. First, experimental results from a 32.4-liter biogas fueled large bore single cylinder spark ignition engine are discussed. Two different ignition systems were considered in the experiment: a DC inductive and an AC capacitive. The spark plugs used in the experiment were of dual-iridium standard J-gap design of different electrode gaps. Test results show the importance of different degrees of freedom to control a spark. A robust ignition is found to be achieved by using a very short spark duration, which in turn reduces total energy discharge at the gap. Further observations reveal that once a stable and self-propagating flame kernel is developed, it becomes independent of the spark energy further added to the gap. Finally, results from the spark plug wear tests using a pressurized rig chamber are discussed.

Hydrogen Internal Combustion Engines (H2-ICEs) are subject to increased attention thanks to their extremely low criteria pollutant emission and near-zero CO2 tailpipe emissions. However, to further minimize exhaust emissions and increase the efficiency of a H2-ICE, it is important to carefully control the relative air-fuel ratio of operation, i.e. Lambda (λ), which will lead in turn to an optimal combustion process. The precise λ control mainly relies upon the methodology to calculate λ on board of the engine, where the availability of reliable sensors specifically-developed for hydrogen combustion is currently limited. In this article, a comparative analysis of different methodologies for the calculation of λ is performed, comparing four methodologies: exhaust gas analysis through a Spindt-Brettschneider approach (λEMI), raw Universal Exhaust Gas Oxygen (λR-UEGO), processed Universal Exhaust Gas Oxygen (λP-UEGO) and speed-density (λSD) outputs.

Increasingly stringent pollutant and CO2 emission standards require the car manufacturers to investigate innovative solutions to further improve the fuel economy and environmental impact of their fleets. Nowadays, NOx emissions standards are stringent for spark-ignition (SI) internal combustion engines (ICEs) and many techniques are investigated to limit these emissions. Among these, an extremely lean combustion has a large potential to simultaneously reduce the NOx raw emissions and the fuel consumption of SI ICEs. Engines with pre-chamber ignition system are promising solutions for realizing a high air-fuel ratio which is both ignitable and with an adequate combustion speed. In this work, the combustion characteristics of an active pre-chamber system are experimentally investigated using a single-cylinder research engine. The engine under exam is a large bore heavy-duty unit with an active pre-chamber fuelled with compressed natural gas.

De-fossilization is an increasingly important trend in the energy sector. In the transport sector the de-fossilization efforts have been centered in promoting the electrification of vehicles, nonetheless other pathways, like the use of carbon neutral or carbon-offsetting fuels under current vehicle fleets, are also worth considering. Low-carbon fuels (LCF) can be synthetized from sources that can take advantage of the carbon already present in the atmosphere (either by technologies like direct carbon capture or biological processes like photosynthesis in biofuels) and use energy from renewable sources for the necessary industrial processes. Although, LCFs can be compared to fossil fuels as energy sources for internal combustion engines, their composition is not the same and their properties can modify the engine combustion and emissions.

Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

This paper investigates the FPGA resources for the implementation of in-cycle closed-loop combustion control algorithms. Closed-loop combustion control obtains feedback from fast in-cylinder pressure measurements for accurate and reliable information about the combustion progress, synchronized with the flywheel encoder. In-cycle combustion control requires accurate and fast computations for their real-time execution. A compromise between accuracy and computation complexity must be selected for an effective combustion control. The requirements on the signal processing (evaluation rate and digital resolution) are investigated. A common practice for the combustion supervision is to monitor the heat release rate. For its calculation, different methods for the computation of the cylinder volume and heat capacity ratio are compared. Combustion feedback requires of virtual sensors for the misfire detection, burnt fuel mass and pressure prediction.

The constrained indicated efficiency optimization of the set-point reference for in-cycle closed-loop combustion regulators is investigated in this article. Closed-loop combustion control is able to reduce the stochastic cyclic variations of the combustion by the adjustment of multiple-injections, a pilot and main injection in this work. The set-point is determined by the demand on engine load, burned pilot mass reference and combustion timing. Two strategies were investigated, the regulation of the start of combustion (SOC) and the center of combustion (CA50). The novel approach taken in this investigation consists of including the effect of the controlled variables on the combustion dispersion, instead of using mean-value models, and solve the stochastic optimization problem. A stochastic heat release model is developed for simulation and calibrated with extensive data from a Scania D13 six-cylinder engine. A Monte Carlo approach is taken for the simulations.

Pilot injections are normally used for the reduction of diesel engine emissions and combustion noise. Nonetheless, with a penalty on the indicated thermal efficiency. The cost is reduced by the minimization of the pilot mass, which on its counterpart increases the risk of pilot misfire. Pilot misfire can have a higher penalty on the indicated efficiency if it is not compensated adequately. This paper investigates how in-cycle closed-loop combustion control techniques can reduce the effects of pilot misfire events. By closed-loop combustion control, pilot misfire can be detected and counteracted in-cycle. Two injection strategies are investigated. The first is the control of the main injection, the second includes an additional second pilot injection. Based on the in-cycle misfire diagnose, two architectures are investigated. The first uses a cycle-to-cycle controller to set the main injection under each scenario.

In recent years the research on Diesel engines has been increasingly shifting from performance and refinement to ultra-low emissions and efficiency. In fact, the last two attributes are key for the powertrain competitiveness in the propulsion electrified future, especially in the European market where 95gCO2/km fleet average and Euro6D RDE Step2 are phasing in at the same time. The present paper describes some of the most innovative research that GM and Istituto Motori Napoli are performing in the field, exploring how the steel-based additive manufacturing can be used to create innovative combustion bowl features that optimize the combustion process to a level that was not compatible with standard manufacturing technologies.

Gas engines (fuelled with CNG, LNG or Biogas) for generation of power and heat are, to this date, taking up larger shares of the market with respect to diesel engines. In order to meet the limit imposed by the TA-Luft regulations on stationary engines, lean combustion represents a viable solution for achieving lower emissions as well as efficiency levels comparable with diesel engines. Leaner mixtures however affect the combustion stability as the flame propagation velocity and consequently heat release rate are slowed down. As a strategy to deliver higher ignition energy, an active pre-chamber may be used. This work focuses on assessing the performance of a pre-chamber combustion configuration in a stationary heavy-duty engine for power generation, operating at different loads, air-to-fuel ratios and spark timings.

With demanding emissions legislations and the need for higher efficiency, new technologies for compression ignition engines are in development. One of them relies on reducing the heat losses of the engine during the combustion process as well as to devise injection strategies that reduce soot formation. Therefore, it is necessary a better comprehension about the turbulent kinetic energy (TKE) distribution inside the cylinder and how it is affected by the interaction between air flow motion and fuel spray. Furthermore, new diesel engines are characterized by massive decrease of NOx emissions. Therefore, considering the well-known NOx-soot trade-off, it is necessary a better comprehension and overall quantification of soot formation and how the different injection strategies can impact it.

Partially Premixed Combustion (PPC) has shown to be a promising advanced combustion mode for future engines in terms of efficiency and emission levels. The combustion timing should be suitably phased to realize high efficiency. However, a simple constant model based predictive controller is not sufficient for controlling the combustion during transient operation. This article proposed one learning based model predictive control (LBMPC) approach to achieve controllability and feasibility. A learning model was developed to capture combustion variation. Since PPC engines could have unacceptably high pressure-rise rates at different operation points, triple injection is applied as a solvent, with the use of two pilot fuel injections. The LBMPC controller utilizes the main injection timing to manage the combustion timing. The cylinder pressure is used as the combustion feedback. The method is validated in a multi-cylinder heavy-duty PPC engine for transient control.

For the reduction of emissions and combustion noise in an internal combustion diesel engine, multiple injections are normally used. A pilot injection reduces the ignition delay of the main injection and hence the combustion noise. However, normal variations of the operating conditions, component tolerances, and aging may result in the lack of combustion i.e. pilot misfire. The result is a lower indicated thermal efficiency, higher emissions, and louder combustion noise. Closed-loop combustion control techniques aim to monitor in real-time these variations and act accordingly to counteract their effect. To ensure the in-cycle controllability of the main injection, the misfire diagnosis must be performed before the start of the main injection. This paper focuses on the development and evaluation of in-cycle algorithms for the pilot misfire detection. Based on in-cylinder pressure measurements, different approaches to the design of the detectors are compared.

The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO2-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO2-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.

A large number of measurement techniques have been developed or adapted from other fields to measure various parameters of engine particulates. With the strict limits given by regulations on pollutant emissions, many advanced combustion strategies have been developed towards cleaner combustion. Exhaust gas recirculation (EGR) is widely applied to suppress nitrogen oxide (NOx) and reduce soot emissions. On the other hand, gasoline starts to be utilized in compression ignition engines due to great potential in soot reduction and high engine efficiency. New engine trends raise the need for good sensitivity and suitable accuracy of the PM measurement techniques to detect particulates with smaller size and low particulate mass emissions. In this work, we present a comparison between different measurement techniques for particulate matter (PM) emissions in a compression ignition engine running on gasoline fuel. A wide-range of EGR was used with lambda varied from 3 down to 1.

Diesel will continue to be an indispensable energy carrier for the car fleet CO2 emission targets in the short-term. This is particularly relevant for heavy-duty vehicles as for mid-size cars and SUVs. Looking at the latest technology achievements on the after-treatment systems, it can be stated that the concerning about the NOx emission gap between homologation test and real road use is basically solved, while the future challenge for diesel survival is to keep its competitiveness in the CO2 vs cost equation in comparison to other propulsion systems. The development of the combustion system design still represents an important leverage for further efficiency and emissions improvements while keeping the current excellent performance in terms of power density and low-end torque.

The combustion processes of three injection strategies in a light-duty (LD) diesel engine at a medium load point are captured with a high speed video camera. A double-pilot/main/single-post injection strategy representative of a LD Euro 6 calibration is considered as the reference. There is a modest temporal spacing (dwell) after the first pilot (P1) and second pilot (P2). A second strategy, “A,” adds a third pilot (P3). The dwell after both P2 and P3 are several times shorter than in the reference strategy. A third strategy, “B,” further reduces all dwells. Each injection has its own associated local peak in the heat release rate (HRR) following some ignition delay. Between these peaks lie local minima, or dips. In all three cases, the fuel from P1 combusts as a propagating premixed flame. For all strategies, the ignition of P2 primarily occurs at its interface with the existing combustion regions.