Vehicle functional requirements, emission regulations, and thermal limits all have a direct impact on the design of a powertrain cooling airflow system. Given the expected increase in emission-related heat rejection, suppliers and vehicle manufacturers must work together as partners in the design, selection, and packaging of cooling system components. The goal of this two-day course is to introduce engineers and managers to the basic principles of cooling airflow systems for commercial and off-road vehicles.
The recent and future trends of energy for heavy-duty vehicles are considered e-fuel, H2, and electricity, and the Selective Catalytic Reduction (SCR) system is necessary for achieving the goals of zero-emission internal combustion engines that use e-fuel and H2 as a fuel. The Japanese automotive industry uses a Cu-zeolite based SCR catalyst since Vanadium is designated as a specific chemical substance, which the Ministry of Environment prohibits its release into the atmosphere. This study attempted purification rate improvement by controlling the NH3 supply with a mini-reactor and by simulated exhaust gas. Specifically, the experiment was done by examining the effect of the pulse amplitude, frequency, and duty ratio on the purification rate by supplying the NH3 pulse injection to the test piece Cu-chabazite catalyst. Additionally, the results of the reactor experiment were validated by numerical simulation considering the detailed surface reaction processes on the catalyst.
Traditional CACC systems utilize inter-vehicle wireless communication to maintain minimal yet safe inter-vehicle distances, thereby improving traffic efficiency. However, introducing communication delays generates system uncertainties that jeopardize string stability, a crucial requirement for robust CACC performance. To address these issues, we introduce a decentralized Model Predictive Control (MPC) approach that incorporates Kalman Filters and state predictors to counteract the uncertainties posed by noise and communication delays. We validate our approach through MATLAB Simulink simulations, using stochastic and mathematical models to capture vehicular dynamics, Wi-Fi communication errors, and sensor noises. In addition, we explore the application of a Reinforcement Learning (RL)-based algorithm to compare its merits and limitations against our decentralized MPC controller, considering factors like feasibility and reliability.
The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly validated and calibrated through many iterations to function effectively and meet the regulation standards. Their development and design process are more complex when prototype hardware is not available and therefore virtual testing is a prominent solution, including Software-in-the-loop (SiL) and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing relying on real-time simulation models is necessary to design and test new era’s OBD systems quickly and in scale. The new fuel cell powertrain involves new and preciously unexplored fail modes. To make the system robust, simulations are required to be carried out to identify different fails.
Reducing CO2 emissions in on-the-road transport is important to limit global warming and follow a green transition towards net zero Carbon by 2050. In a long-term scenario, electrification will be the future of transportation. However, in the mid-term, the priority should be given more strongly to other technological alternatives (e.g., decarbonization of the electrical energy and battery recharging time). In the short- to mid-term, the technological and environmental reinforcement of ICEs could participate in the effort of decarbonization, also matching the need to reduce harmful pollutant emissions, mainly during traveling in urban areas. Engine thermal management represents a viable solution considering its potential benefits and limited implementation costs compared to other technologies. A variable flow coolant pump actuated independently from the crankshaft represents the critical component of a thermal management system.
The objective of this study is to investigate the potential of a sustainable fuel composed of ethanol and lignin for marine engines. Lignin is the second most abundant biomass after cellulose, produced i.e. from the pulp-and-paper industries. Lignin has a higher heating value (HHV) of 23.2 – 25.6 MJ/kg but is difficult to exploit efficiently because it is a stable solid material and often ends up as waste. combining lignin and alcohol to a liquid fuel has a huge interest, and is mainly for marine engines as they are designed to tolerate a wide range of fuels. In this study, lignin-fuel with 44 wt% lignin and 50 wt% of ethanol was experimentally evaluated by using an extensively modified small-bore compression ignition (CI) engine. The technical challenges and approach to applying this kind of lignin-fuel to engines are presented.
In the effort to achieve the goal of a climate-neutral transportation system, the use of hydrogen and other synthetic fuels plays a key role. As Battery Electric Vehicles (BEVs) become more widespread, e-fuels could be used to defossilize the hard-to-electrify transportation sectors and to store energy produced from renewable and non-continuous energy sources. Among e-fuels, hydrogen and ammonia are attractive because they are carbon-neutral and their oxidation does not lead to any CO2 emissions. Furthermore, hydrogen/ammonia blends overcome the issues that arise as each of the two fuels is used separately. As a matter of fact, hydrogen/ammonia mixtures can be liquified at a lower pressure than hydrogen and are more reactive than ammonia. In the automotive sector, the use of hydrogen and ammonia or their blends requires a characterization of such mixtures under engine-like conditions, that is, at high pressures and temperatures.
Ammonia has emerged as a promising carbon-free alternative fuel for internal combustion engines (ICE), particularly in large-bore engine applications. However, integrating ammonia into conventional engines presents challenges, prompting the exploration of innovative combustion strategies like dual-fuel combustion. Nitrous oxide (N2O) emissions have emerged as a significant obstacle to the widespread adoption of ammonia in ICE. Various studies suggest that combining exhaust gas recirculation (EGR) with adjustments in inlet temperature and diesel injection timing can effectively mitigate nitrogen oxides (NOx) emissions across diverse operating conditions in dual-fuel diesel engines.
Climate change and the decarbonization process are challenges for our times. In this context, the transportation sector is undergoing significant changes and new scenarios in the future mobility are open. For light duty vehicles, electrification represents the most immediate and spreading solution; however, to promote the e-mobility expansion, technological improvements mainly related to the charging infrastructures are needed. This work aims at investigating the possibility to use a spark ignition engine fueled with bio-ethanol for off-grid electric vehicle charging station. The engine is a 8.7 liter turbocharged spark ignition engine, single point injection and develops a maximum rated power of about 230 kW at 1500 rpm. A 1-D numerical model was developed to evaluate the main performance in terms of brake power, efficiency, specific fuel consumption and NOx emissions at different spark advances and air-fuel ratio.
Heavy duty truck engines are quite difficult to electrify, due to the large amount of energy required on-board, in order to achieve a range comparable to that of diesels. This paper considers a commercial 6-cylinder engine with a displacement of 12.8 L, developed in two different versions. As a standard diesel, the engine is able to deliver more than 420 kW at 1800 rpm, whereas in the CNG configuration the maximum power output is 330 kW at 1800 rpm. Maintaining the same combustion chamber design of the last version, a theoretical study is carried out in order to run the engine on Hydrogen, compressed at 700 bar. The study is based on GT-Power simulations, adopting a predictive combustion model, calibrated with experimental results. The study shows that the implementation of a combustion system running on lean mixtures of Hydrogen, permits to cancel the emissions of CO2, while maintaining the same power output of the CNG engine.
Water management in PEMFC power generation systems is a key point to guarantee optimal performances and durability. It is known that a poor water management has a direct impact on PEMFC voltage, both in drying and flooding conditions: furthermore, water management entails phenomena from micro-scale, i.e., formation and water transport within membrane, to meso-scale, i.e., water capillary transport inside the GDL, up to the macro-scale, i.e., water droplet formation and removal from the GFC. Water transport mechanisms through the membrane are well known in literature, but typically a high computational burden is requested for their proper simulation. To deal with this issue, the authors have developed an analytical model for the water membrane content simulation as function of stack temperature and current density, for fast on-board monitoring and control purposes, with good fit with literature data.