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Technical Paper

A Computational Study of Hydrogen Direct Injection Using a Pre-Chamber in an Opposed-Piston Engine

Combustion characteristics of a hydrogen (H2) direct-injected (DI) pre-chamber (PC)-assisted opposed piston two-stroke (OP2S) engine are investigated by 3D computational fluid dynamics (CFD) simulations. The architecture of the OP2S engine has potential features for reducing wall heat losses, as the DI H2 jets are not directed towards the piston face. To overcome the high resistance to autoignition of H2, a PC technology was implemented in order to enhance the ignition of the mixture by the multiple hot reactive jets. To further investigate the interaction between the H2 plume and the chamber walls, three different piston bowl designs were evaluated and ranked based on a merit function. For the cases under study, the flat piston design was found to be most favorable (compared to the narrow and wide pistons) due to its reduced surface area for lower wall heat losses.
Journal Article

Developing Fuel Savings Performance Function Considering Various Truck Platooning Configurations

Abstract Truck platooning facilitates the operation of trucks in close proximity to one another, resulting in decreased air resistance and improved fuel efficiency. While previous research has mostly focused on the effects of intra-distance on fuel savings, this study aims to develop fuel savings performance functions considering various truck platooning configurations. This article comprehensively investigates the influence of different truck platoon configurations on fuel savings. This analysis focuses on examining the impacts of several variables including inter-vehicle distance, platoon speed, truck weight, number of trucks in the platoon, and the truck’s distinctive design characteristics. Data used in the analysis were collected from 10 different field experiments. Three machine learning techniques—artificial neural networks (ANN), extreme gradient boosting (XGBoost), and K-nearest neighbors (KNN)—alongside the negative binomial regression model were employed.
Technical Paper

Optimization of Hydroformed Exhaust Gas Recirculation Tube under Vibrational Load by Finite Element Analysis

This study emphasizes the importance of CAE approach in optimizing EGR tube under vibrational load. EGR tube is a weak link in the EGR system and chances of failure due to vibration and relative displacement of mating parts, i.e., overhang or improper support at exhaust manifold, intake manifold, or EGR system. Consideration of the mating parts for the EGR tube is very important to get the realistic resonance frequencies, otherwise it could have some different results in the CAE, which will deviate from the reality. So, it’s important to study the dynamic response on the EGR tube, which needs to be taken care during the design phase. This paper aims to optimize the EGR tube under vibrational load by using CAE techniques and the industry experience as a product expertise. some critical parameter such as damping is very important during the CAE, which can be generated by doing the rigorous testing and how it affects the stress and correspondingly FOS.
Technical Paper

Numerical Study of Application of Gas Foil Bearings in High-Speed Drivelines

The commitment to environmentally friendly transportation calls for efficient solutions with the evolution of automotive industry. Turbochargers are an important part of this development. The application of Gas or Air Foil Bearings (GFB) instead of traditional hydrodynamic bearings is recently very noticed, with which the fuel consumption, and emissions can be minimized as well as decreasing the maintenance costs and increasing the reliability. However, low viscosity of gas leads to lower dynamic stiffness and damping characteristics resulting in low load carrying capacity and instability at higher speeds. Gas bearings can be enhanced by adding a foil structure commonly known as gas foil bearings whose dynamic stiffness can be tailored by modifying the geometry and the material properties resulting in better stability and higher load carrying capacity.
Technical Paper

The Evolution of Conventional Vehicles’ Efficiency for Meeting Carbon Neutrality Ambition

In 2023, the European Union set more ambitious targets for reducing greenhouse gas emissions from passenger cars: the new fleet-wide average targets became 93.6 g/km for 2025, 49.5 g/km in 2030, going to 0 in 2035. One year away from the 2025 target, this study evaluates what contribution to CO2 reduction was achieved from new conventional vehicles and how to interpret forecasts for future efficiency gains. The European Commission’s vehicle efficiency cost-curves suggest that optimal technology adoption can guarantee up to 50% CO2 reduction by 2025 for conventional vehicles. Official registration data between 2013 and 2022, however, reveal only an average 14% increase in fuel efficiency in standard combustion vehicles, although reaching almost 23% for standard hybrids. The smallest gap between certified emissions and best-case scenarios is of 14 g/km, suggesting that some manufacturers’ declared values are approaching the optimum.
Technical Paper

Guided Port Injection of Hydrogen as an Approach for Reducing Cylinder-to-Cylinder Deviations in Spark-Ignited H2 Engines – A Numerical Investigation

The reduction of anthropogenic greenhouse gas emissions and ever stricter regulations on pollutant emissions in the transport sector require research and development of new, climate-friendly propulsion concepts. The use of renewable hydrogen as a fuel for internal combustion engines promises to provide a good solution especially for commercial vehicles. For optimum efficiency of the combustion process, hydrogen-specific engine components are required, which need to be tested on the test bench and analysed in simulation studies. This paper deals with the simulation-based investigation and optimisation of fuel injection in a 6-cylinder PFI commercial vehicle engine, which has been modified for hydrogen operation starting from a natural gas engine concept.
Technical Paper

Development of a Soft-Actor Critic Reinforcement Learning Algorithm for the Energy Management of a Hybrid Electric Vehicle

In recent years, the urgent need to fully exploit the fuel economy potential of Electrified Vehicles (xEVs) through the optimal design of their Energy Management System (EMS) has led to an increasing interest in Machine Learning (ML) techniques. Among them, Reinforcement Learning (RL) seems to be one of the most promising approaches thanks to its peculiar structure in which an agent learns the optimal control strategy by interacting directly with an environment, making decisions, and receiving feedback in the form of rewards. Therefore, in this study, a new Soft Actor-Critic (SAC) agent, which exploits a stochastic policy, was implemented on a digital twin of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The SAC agent was trained to enhance the fuel economy of the PHEV while guaranteeing its battery charge sustainability.
Technical Paper

Experimental Study of Lignin Fuels for CI Engines

This study explores the feasibility of using a sustainable lignin-based fuel, consisting of 44 % lignin, 50 % ethanol, and 6 % water, in conventional compression ignition (CI) marine engines. Through experimental evaluations on a modified small-bore CI engine, we identified the primary challenges associated with lignin-based fuel, including engine startup and shutdown issues due to solvent evaporation and lignin solidification inside the fuel system, and deposit formation on cylinder walls leading to piston ring seizure. To address these issues, we developed a fuel switching system transitioning from lignin-based fuel to cleaning fuel with 85 vol% of acetone, 10 vol% of water and 5 vol% of ignition improving additive, effectively preventing system clogs.