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Faced with one of the greatest challenges of humanity – climate change – the European Union has set out a strategy to achieve climate neutrality by 2050 as part of the European Green Deal. To date, extensive research has been conducted on the CO2 life cycle analysis of mobile propulsion systems. However, achieving absolute net-zero CO2 emissions requires the adjustment of the relevant key performance indicators for the development of mobile propulsion systems. In this context, research is presented that examines the ecological and economic sustainability impacts of a hydrogen-fueled mild hybrid vehicle, a hydrogen-fueled 48V hybrid vehicle, a methanol-fueled 400V hybrid vehicle, a methanol-to-gasoline-fueled plug-in hybrid vehicle, a battery electric vehicle, and a fuel cell electric vehicle. For this purpose, a combined Life-Cycle Assessment (LCA) and Life-Cycle Cost Assessment was performed for the different propulsion concepts.

The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation.

The societies around the world remain far from meeting the agreed primary goal outlined under the 2015 Paris Agreement on climate change: reducing greenhouse gas (GHG) emissions to keep global average temperature rise to well below 20°C by 2100 and making every effort to stay underneath of a 1.5°C elevation. Current emissions are rebounding from a brief decline during the economic downturn related to the Covid-19 pandemic. To get back on track to support the realization of the goal of the Paris Agreement, research suggests that GHG emissions should be roughly halved by 2030 on a trajectory to reach net zero by around mid-century.2 Although these are averaged global targets, every sector and country or market can and must contribute, especially higher-income and more developed countries bear the greater capacity to act. In 2020 direct tailpipe emissions from transport represented around 8 GtC02e, or nearly 15% of total emissions.

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.

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.

With the increasing focus on reducing CO2 emissions to combat global warming and climate change, the automotive industry is exploring near zero-emission alternative fuels to replace traditional fossil-based fuels like diesel, gasoline, and CNG. Methanol is a promising alternative fuel that is being evaluated in India due to its easy transportation and storage, as well as its production scalability and availability potential. This study focuses on the retro-fitment solution of M100 (pure methanol) SI port-fuel injection (PFI) mode of combustion. A heavy duty single-cylinder engine test setup was used to assess methanol SI combustion characteristic. Lean operation strategy has been investigated. At lean mixture conditions a significant drop in NOX and CO emissions was achieved. The fuel injection techniques and the impact of exhaust gas recirculation (EGR) on the conventional stoichiometric combustion process is highlighted.

Many Indian cities are amongst the most polluted cities in the world. Transport sector is identified as one of the major contributors to air pollution. Following the global trend, Government of India is also promoting near zero emission fuels with zero CO2 emissions as a way forward to solve the emission problems. With its policies like Green Hydrogen Mission, government of India plans to accelerate the adoption of Hydrogen as a fuel in the country. These initiatives have created a breakthrough in development of Hydrogen ICEs by the Indian OEM’s. Hydrogen ICE have only NOx emissions as the most prominent engine out emissions. NOx emission in Hydrogen engines is very sensitive to operating lambda, where in, after a certain threshold lambda the emissions rise significantly. Therefore, the air management system plays a very important role in the hydrogen engine performance & NOx emissions. This study evaluates various air management system options for a heavy-duty Hydrogen engine.

Most of the vehicles with internal combustion engines worldwide use fossil fuels. The widely used fuels available on the market are gasoline, diesel, and CNG. These fuels are getting costlier every year while at the same time generating pollutants through exhaust gases. Hence in the market, electric vehicles are effectively providing pollution-free solutions in the passenger car and lightweight carrier vehicle segments. However, the off-road, heavy-duty, and stationary applications with high load factors, are in general less favorable for battery electric scenarios since frequent charging will be mandatory and time-consuming. Hence, for these applications, the replacement of an internal combustion engine is quite difficult. There are various renewable fuels like ammonia, methanol, and biodiesel under research tests and study. As these are renewable fuels, the cost of these fuels can be lowered during mass production.

Climate change and global warming are one of the major challenges faced by the world today. A significant number of Indian cities rank among the most polluted globally, with vehicular emissions being the primary contributor. To address this issue, the Government of India is actively advocating for the adoption of zero-emission vehicles such as electric vehicles through policies and initiatives like FAME II [1], PMP and the National Mission for Transformative Mobility and Storage. The acceptance of electric vehicles is growing in the Indian market seeing more than 200% increase in sales in the year 2022 compared to 2021 with a large share of 2-wheelers, 3-wheelers and compact cars getting electrified. Further adoption of electrification on a much larger scale currently faces the major challenge of high overall vehicle cost compared to conventional vehicles, with the major contribution coming from the HV battery which is the costliest system on the electric vehicles.

Pre-ignition in a boosted spark-ignition engine can be triggered by several mechanisms, including oil-fuel droplets, deposits, overheated engine components and gas-phase autoignition of the fuel-air mixture. A high pre-ignition resistance of the fuel used mitigates the risk of engine damage, since pre-ignition can evolve into super-knock. This paper presents the pre-ignition propensities of 11 RON 89-100+ gasoline fuel blends in a single-cylinder research engine. Albeit the addition of two high-octane components (methanol and reformate) to a toluene primary reference fuel improved the pre-ignition resistance, one high-RON fuel experienced runaway pre-ignition at relatively low boost pressure levels. A comparison of RON 96 blends showed that the fuel composition can affect pre-ignition resistance at constant RON.

The challenge of industrial carbon footprint reduction is led by the engine manufacturers that are developing new technologies and fuels to lower CO2 emissions. Although the deployment of relevant investments for the development of battery electric vehicles, diesel, and gasoline cars are still widely used, especially for their longer operating range, faster refueling, and lower cost. For this reason, more efficient traditional internal combustion engines can guide the transition towards new propulsion systems. In this document, the innovative piston damage and exhaust gas temperature models previously developed by the authors are reversed and coupled to manage the combustion process, increasing the overall energy conversion efficiency. The instantaneous piston erosion and the exhaust gas temperature at the turbine inlet are evaluated according to the models’ estimation which manages both the spark advance, and the target lambda.

The increasing environmental concern is leading to the need for innovation in the field of internal combustion engines, in order to reduce the carbon footprint. In this context, hydrogen is a possible mid-term solution to be used both in conventional-like internal combustion engines and in fuel cells (for hybridization purposes), thus, hydrogen combustion characteristics must be considered. In particular, the flame of a hydrogen combustion is less subjected to the quenching effect caused by the engine walls in the combustion chamber. Thus, the significant heating up of the thin lubricant layer upon the cylinder liner may lead to its evaporation, possibly and negatively affecting the combustion process, soot production. The authors propose an analysis which aims to address the behavior of different typical engine oils, (SAE0W30, SAE5W30, SAE5W40) under engine thermo-physical conditions considering a large hydrogen-fuelled engine.

Nowadays, in the perspective of a full electric automotive scenario, internal combustion engines can still play a central role in the fulfilment of different needs if the efficiency will be improved, and the tailpipe emission will be further limited. Gasoline Compression Ignition engines can offer a favourable balance between NOx, particulate, operating range. Stable operations are ensured by ultra-high gasoline injection pressure and tailored injection patterns in order to design the most proper local fuel distribution. In this context, engine simulations by means of CFD codes can provide insights on the design of the injection parameters, and emphasis must be placed on the capture of spray-wall impingement behaviour under those non-conventional conditions. This paper aims to analyse the spray-wall impingement behaviour of ultra-high gasoline spray using a combined experimental-CFD approach.

The proposed Euro 7 emission standard foresees that the emission behaviour of Euro 7 vehicles is monitored via an on-board monitoring (OBM) system. In Euro 7 vehicles, OBM systems will monitor the emissions of nitrogen oxides (NOX), ammonia (NH3) and particulate matter (PM) for every trip through a combination of measured and modelled data. Sensors employed to support on-board diagnostics (OBD) in current vehicles may be used to support OBM. According to the Euro 7 OBM concept presented in this paper, OBM will serve a dual purpose: the first is to warn the user of a vehicle about the need to perform repairs on the engine or the pollution control systems when these are needed. If these repairs are not performed in a timely manner, the OBM system will be able to ultimately prevent engine restart, akin to the existing low-reagent driver warning system in some compression ignition vehicles. The second purpose of OBM is to monitor the compliance of vehicle types with the emission limits.

Powertrain electrification is becoming increasingly common in the transportation sector to address the challenges of global warming and deteriorating air quality. This paper introduces a novel “Build Your Hybrid” approach to experience and test various hybrid powertrain concepts. This approach is applied to the light commercial vehicles (LCV) segment due to the attractive combination of a Diesel engine and a partly electrified powertrain. For this purpose, a demonstrator vehicle has been set up with a flexible P02 hybrid topology and a prototype Hybrid Control Unit (HCU). Based on user input, the HCU software modifies the control functions and simulation models to emulate different sub-topologies and levels of hybridization in the demonstrator vehicle. Three powertrain concepts are considered for LCVs: HV P2, 48V P2 and 48V P0 hybrid. Dedicated hybrid control strategies are developed to take full advantage of the synergies of the electrical system and reduce CO2 and NOx emissions.

As the world strives toward the common goal of carbon neutrality by 2050, motorsport cannot be allowed to stand alone as an exception. A gradual energy transition is clearly underway in the automotive industry but has already begun in motorsport as well. Among other initiatives, the Dakar Rally and the FIA have created the T1 ultimate category for prototypes powered by low-carbon fuels, including hydrogen. The Dakar is the pinnacle of off-road endurance rally competitions. It offers a great opportunity to ORECA Magny-Cours and FEV to expose their jointly developed internal combustion engine (ICE), fuelled with hydrogen only, to extreme conditions. In addition, the racing environment imposes a unique pace of development which can serve as a catalyst for spurring the H2-ICE technology. Moreover, a hydrogen powered engine is an interesting fit for motorsports because it combines high power output, a relatively long driving range and driving pleasure with an excellent carbon footprint.

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.

The implementation of emission standards has brought significant reductions in vehicle emissions in the EU, but road transport is still a major source of air pollution. Future emission standards will aim at making road vehicles as clean as possible under a wide range of driving conditions and throughout their complete lifetime. The current paper presents the methodology followed by the Consortium for ultra LOw Vehicle Emissions (CLOVE) to support the preparation of the Euro 7 proposal. As a first step, the emission performance of the latest-technology vehicles under various driving conditions was evaluated. Towards this direction, an emissions database was developed, containing data from a wide range of tests, both within and beyond the current RDE boundaries.

In the past years, stringent emission regulations for Internal Combustion (IC) engines produced a large amount of research aimed at the development of innovative combustion methodologies suitable to simultaneously reduce fuel consumption and engine-out emissions. Previous research demonstrates that the goal can be obtained through the so-called Low Temperature Combustions (LTC), which combine the benefits of compression-ignited engines, such as high compression ratio and unthrottled lean operation, with a properly premixed air-fuel mixture, usually obtained injecting gasoline-like fuels with high volatility and longer ignition delay. Gasoline Partially Premixed Combustion (PPC) is a promising LTC technique, mainly characterized by the high-pressure direct-injection of gasoline and the spontaneous ignition of the premixed air-fuel mixture through compression, which showed a good potential for the simultaneous reduction of fuel consumption and emissions in CI engines.

E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Still, major challenges for large scale deployment remain. They include higher maturity with respect to performance (e.g., range, interaction with the grid), development efficiency (e.g., time-to-market), or production costs. Additionally, an important market transformation currently occurs with the co-development of automated driving functions, connectivity, mobility-as-a-service. New opportunities arise to customize road transportation systems toward application-driven, user-centric smart mobility solutions.