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The automotive industry is experiencing radical changes under the pressure of institutions that are increasingly reducing the limits on CO2 and pollutant emissions from road vehicles powered by internal combustion engines (ICEs). A way to decarbonize the transport sector without disrupting current automotive production is the adoption of alternative fuels for internal combustion engines (ICEs). Hydrogen is very attractive, thanks to the zero-carbon content and very high laminar flame speed, allowing for extending the lean burn limit. Other alternative fuels are methanol and ethanol. This work deals with the conversion of a small-sized passenger car powered by a three-cylinder spark ignition (SI) engine for the use of alternative fuels. In particular, the spark timing has been optimized to improve the fuel economy under every operating condition. The optimization procedure is based on the MATLAB/Simulink® R2024a-GT-Power co-simulation analysis and minimizes the fuel consumption by varying the spark timing independently for each cylinder. In particular, at full load, the algorithm reduces the spark timing only for the cylinder in which knock is detected, reducing fuel consumption by about 2% compared to the base calibration. This approach will be adopted in future activities to understand how the use of alternative fuels affects the ignition control strategy. [ABSTRACT FROM AUTHOR]

The thermal management of lithium-ion batteries in hybrid electric vehicles is a key issue, since operating temperatures can greatly affect their performance and life. A hybrid energy storage system, composed by the integration of a battery pack with a metal hydride-based hydrogen storage system, might be a promising solution, since it allows to efficiently exploit the endothermic desorption process of hydrogen in metal hydrides to perform the thermal management of the battery pack. In this work, starting from a battery electric scooter, a new fuel cell/battery hybrid powertrain is designed, based on the simulation results of a vehicle dynamic model that evaluates power and energy requirements on a standard driving cycle. Thus, the design of an original hybrid energy storage system for a plug-in fuel cell electric scooter is proposed, and its prototype development is presented. To this aim, the battery pack thermal power profile is retrieved from vehicle simulation, and the integrated metal hydride tank is sized in such a way to ensure a suitable thermal management. The conceived storage solution replaces the conventional battery pack of the vehicle. This leads to a significant enhancement of the on-board gravimetric and volumetric energy densities, with clear advantages on the achievable driving range. The working principle of the novel storage system and its integration within the powertrain of the vehicle are also discussed.

The H2-ICE project aims at developing, through numerical simulation, a new generation of hybrid powertrains featuring a hydrogen-fueled Internal Combustion Engine (ICE) suitable for 12 m urban buses in order to provide a reliable and cost-effective solution for the abatement of both CO2 and criteria pollutant emissions. The full exploitation of the potential of such a traction system requires a substantial enhancement of the state of the art since several issues have to be addressed. In particular, the choice of a more suitable fuel injection system and the control of the combustion process are extremely challenging. Firstly, a high-fidelity 3D-CFD model will be exploited to analyze the in-cylinder H2 fuel injection through supersonic flows. Then, after the optimization of the injection and combustion process, a 1D model of the whole engine system will be built and calibrated, allowing the identification of a "sweet spot" in the ultra-lean combustion region, characterized by extremely low NOx emissions and, at the same time, high combustion efficiencies. Moreover, to further enhance the engine efficiency well above 40%, different Waste Heat Recovery (WHR) systems will be carefully scrutinized, including both Organic Rankine Cycle (ORC)-based recovery units as well as electric turbo-compounding. A Selective Catalytic Reduction (SCR) aftertreatment system will be developed to further reduce NOx emissions to near-zero levels. Finally, a dedicated torque-based control strategy for the ICE coupled with the Energy Management Systems (EMSs) of the hybrid powertrain, both optimized by exploiting Vehicle-To-Everything (V2X) connection, allows targeting H2 consumption of 0.1 kg/km. Technologies developed in the H2-ICE project will enhance the know-how necessary to design and build engines and aftertreatment systems for the efficient exploitation of H2 as a fuel, as well as for their integration into hybrid powertrains. [ABSTRACT FROM AUTHOR]

In the last years, emissions standards for internal combustion engines are becoming more and more restrictive, particularly for NOx and soot emissions from Diesel engines. In order to comply with these requirements, OEMs have to face with innovative combustion concepts and/or sophisticate after-treatment devices. In both cases, the role of the Engine Management System (EMS) is increasingly essential, following the large number of actuators and sensors introduced and the need to meet customer expectations on performance and comfort. On the other hand, the large number of control variables to be tuned imposes a massive recourse to the experimental testing which is poorly sustainable in terms of time and money. In order to reduce the experimental effort and the time to market, the application of simulation models for EMS calibration has become fundamental. Predictive models, validated against a limited amount of experimental data, allow performing detailed analysis on the influence of engine control variables on pollutants, comfort and performance. In this paper, a simulation analysis on the impact of injection pattern and Exhaust Gas Recirculation (EGR) rate on fuel consumption, combustion noise, NO and soot emissions is presented for an automotive Common-Rail Diesel engine. Simulations are accomplished by means of a quasi-dimensional multi-zone model of in-cylinder processes. Furthermore a methodology for in-cylinder pressure processing is presented to estimate combustion noise contribution to radiated noise. Model validation is carried out by comparing simulated in-cylinder pressure traces and exhaust emissions with experimental data measured at the test bench in steady-state conditions. Effects of control variables on engine performance, noise and pollutants are analyzed by imposing significant deviation of EGR rate and injection pattern (i.e. rail pressure, start-of-injection, number of injections). The results evidence that quasi-dimensional in-cylinder models can be effective in supporting the engine control design toward the optimal tuning of EMS with significant saving of time and money.

In the last few years, car manufacturers are moving toward electrified powertrains, like Battery Electric Vehicles (BEV) and Hybrid Electric Vehicles (HEV), to reduce the levels of CO2 in the atmosphere. A promising alternative to BEVs to reduce CO2 emissions, while maintaining an existing and well-developed technology, could be the use of hydrogen for internal combustion engines (ICEs). Particularly, the zero-carbon content of hydrogen allows for guaranteeing very clean combustion and near-zero carbon footprint. Within this context, the present study aims to deeply investigate the effects of pure hydrogen fueling of Spark Ignition (SI) engines, especially on specific fuel consumption and NOx emissions. Particularly, the benefits of pure hydrogen fueling were assessed in a production small Direct Injection (DI) SI engine. The engine is intended to operate in steady state conditions as an Auxiliary Power Unit (APU) for a series hybrid powertrain. The effects of pure hydrogen fueling were investigated at two engine speeds, namely 2000 and 3000 rpm. All tests were carried out at unthrottled conditions and lean mixture. A 1-D engine model was developed within a commercial software. Combustion, heat transfer, and NOx emissions embedded sub-models were tuned based on the experimental data, to accurately reproduce the engine behavior in a wide range of operating conditions. Both experimental and simulation results demonstrated that hydrogen fueling, together with lean mixture operation, allow for significantly improving engine thermal efficiency. The results of 1-D model simulations supported the energy management strategies of the hybrid powertrain in selecting the most suitable ICE operating condition. Particularly, the best engine operating conditions in terms of fuel consumption are achieved at 2500 rpm, with λ = 2.0, while the lowest NOx emissions are reached when λ is increased up to 2.4. [ABSTRACT FROM AUTHOR]

During the last years, the sales of vehicles equipped with Spark-Ignition (SI) engines have increased, to the detriment of those powered by Compression-Ignition (CI) engines. However, SI engines provide lower efficiency than CI engines, due to the low compression ratio and stoichiometric mixture operation. A way to increase the efficiency of SI engines is lean combustion, as it allows to increase the specific heats ratio (γ) and reduces pumping losses at part loads. Nevertheless, the operation with extremely lean mixtures deals with ignition issues, promoting Cycle-to-Cycle Variability (CCV) and increasing the probability of misfire. The prechamber ignition concept, also known as Turbulent Jet Ignition (TJI), is a promising solution for enabling the implementation of lean combustion, without its drawback in SI engines. Such a concept can be implemented according to two approaches: In active TJI, there is an additional fuel supply system inside the prechamber, while in passive TJI there isn't. Therefore, the main advantage of passive TJI is its simplicity, as the prechamber can be installed into a conventional spark plug body, with obvious benefits in terms of packaging and costs. In this work, the benefits of passive TJI on combustion and performance are assessed by simulation analyses. Particularly, a 1-D engine model was developed to simulate the TJI combustion and was validated versus experimental data. Afterward, a 0-D method was applied to assess the impact of the relative air-fuel ratio on CCV. The analysis was carried out in a high speed and load operating condition, namely 4500 rpm and 13 bar of IMEP, under both stoichiometric and lean mixture. Experimental and numerical results demonstrate the effectiveness of the passive TJI concept in promoting faster and more stable combustion also in lean-burn conditions. [ABSTRACT FROM AUTHOR]

The emissions of diesel engines in terms of particulate matter are limited all over the world. One possible solution for reaching the target imposed by the various regulations could be the adoption of a catalytic diesel particulate filter (CDPF). Nevertheless, the effect of CDPFs on the particle size distributions (PSDs) during the regeneration process needs to be deeply investigated. Therefore, this research work is focused on a detailed PSD analysis during the active regeneration of a 30 %wt CuFe2O4 loaded CDPF at the exhaust of an L-D diesel engine to reach a more complete understanding of the filter behavior. The results of the experimental tests evidence that at the CDPF outlet, compared to a standard DPF: (i) during the start-up of the regeneration, the particle emissions are three orders of magnitude lower and remain two orders of magnitude lower for particle sizes larger than 50 nm; (ii) the PSDs measured in the time range of 200–450 s exhibit the bimodality observed during the accumulation phase, with a peak that is three orders of magnitude lower; (iii) at the end of the regeneration, the PN distribution exhibits reductions of two and three orders of magnitude for particle sizes of 5 nm and above 50 nm, respectively. [ABSTRACT FROM AUTHOR]

Well-designed energy management strategies are essential for the good operation of Hybrid Electric Vehicles (HEVs) in terms of fuel economy and pollutant emissions reduction, regardless of the specific powertrain architecture. The goal of this paper is to propose two innovative supervisory control strategies for HEVs derived from different optimization algorithms and to assess HEVs' fuel consumption reduction (compared to conventional vehicles). These approaches are derived from the literature and modified by the authors to present novel algorithms for the optimization problem. One is based on Dynamic Programming (DP), here referred to as the Forward Approach to Dynamic Programming (FADP) and introduces a different implementation of the DP to achieve computational and accuracy benefits. The other is based on the Equivalent Consumption Minimization Strategy (ECMS) approach, and it adapts to the latest driving conditions using information gathered in a finite-length backward-looking horizon. These techniques are used to achieve the optimal power share between the thermal engine and the battery of a parallel HEV. Their performances are compared and analysed in terms of achieved fuel economy and computational time with respect to conventional DP and Pontryagin's Minimum Principle (PMP) approaches. [ABSTRACT FROM AUTHOR]