Search Results

Abstract Minimizing vibration transmitted from the exhaust system to the vehicle’s passenger compartment is the primary goal of this article. With the introduction of regulatory norms on NVH behavior and emissions targets, it has become necessary to address these issues scientifically. Stringent emissions regulations increased the complexity of the exhaust system resulting in increased size and weight. Exhaust system vibration attenuation is essential not only from the vehicle NVH aspects but also for the optimized functionality of the subsystems installed on it. Based on earlier studies, this work adopts a more thorough strategy to reduce vehicle vibration caused by the exhaust system by adjusting it to actual operating conditions. To achieve this, a complete vehicle model of 22 DOF is considered, which consists of a powertrain, exhaust system, chassis frame, and suspension system. A method for evaluating static and dynamic vibration response is proposed.

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.

Fossil fuels such as natural gas used in engines still play an important role worldwide which however is also exacerbating climate change as a result of carbon dioxide emissions. Although natural gas engines show an overall low pollutant emissions level, methane slip due to incomplete combustion occurs, causing methane emissions with a more than 20 times higher global warming potential than CO2. Additionally, further tightening of emissions legislation is to be expected bringing methane emissions even more into focus making exhaust gas aftertreatment issues remain relevant. For lean gas applications, (Pd)-based catalysts turned out to convert CH4 most efficiently usually being supported by metal oxides such as aluminium oxide (Al2O3). Water (H2O) contained in the exhaust gas causes strong inhibition on Pd catalysts.

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.

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.

Many research centers and companies in general aviation have been devoting efforts to the electrification of propulsive plants to reduce environmental impact and/or increase safety. Even if the final goal is the total elimination of fossil fuels, the limitations of today's battery in terms of energy and power densities suggest the adoption of hybrid-electric solutions. These systems combine the advantages of conventional and electric propulsive systems, namely reduced fuel consumption, high peak power, and increased safety deriving from redundancy. Today, lithium-ion batteries are the best commercial option for the electrification of all means of transportation. However, lithium batteries are a family of technologies that presents a variety of specifications in terms of gravimetric and volumetric energy density, discharge and charge currents, safety, and cost.

Nowadays, the push for more ecological low-carbon propulsion systems is high in all mobility sectors, including the recreational or light-commercial boating, where propulsion is usually provided by internal combustion engines derived from road applications. In this work, the effects of replacing conventional fossil-derived B7 diesel with Hydrotreated Vegetable Oil (HVO) were experimentally investigated in a modern Medium-Duty Diesel Engine, using the advanced biofuel as ‘drop-in’ and testing according to the ISO 8178 marine standard. The compounded results showed significant benefits in terms of NOx, Particulate Matter, mass fuel consumption and especially Well-to-Wake (WtW) CO2 thanks to the inner properties of the aromatic-free, hydrogen-rich renewable fuel, with no impact on the engine power and minimal deterioration of the volumetric fuel economy.

Abstract The concern with global warming has led to the creation of legislation aimed at minimizing this phenomenon. As a result, the development of technologies to minimize vehicle emissions and reduce fuel consumption has gained market share. A promising alternative is the use of a belt starter generator (BSG): an electric machine to replace the vehicle’s alternator. This research analyzes the effects of introducing a 12 V BSG into a flex-fuel vehicle, specifically examining its impact on fuel economy and CO2 emissions when using both gasoline and ethanol. The utilization of a low-voltage BSG in a flex-fuel vehicle has not been previously studied. Numerical simulations and experimental fuel consumption and CO2 emissions tests were performed for the normal production flex-fuel baseline configuration and the vehicle with the 12 V BSG, following the standards ABNT NBR 6601 and ABNT NBR 7024.

Abstract In general, GDI engines operate with stratified mixtures at part-load conditions enabling increased fuel economy with high power output, however, with a compensation of increased soot emissions at part-load conditions. This is mainly due to improper in-cylinder mixing of air and fuel leading to a sharp decrease in gradient of reactant destruction term and heat release rate (HRR), resulting in flame quenching. The type of fuel injector and engine operating conditions play a significant role in the in-cylinder mixture formation. Therefore, in this study, a CFD analysis is utilized to compare the effect of stratified mixture combustion with multi-hole solid-cone and hollow-cone injectors on the performance and emission characteristics of a spray-guided GDI engine. The equivalence ratio (ϕ) from 0.6 to 0.8 with the constant engine speed of 2000 rev/min is considered. For both injectors, the fuel injection pressure of 200 bar is used with 60° spray-cone angles.