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Waste Heat Recovery (WHR) is one of the most viable opportunities to reduce fuel consumption and CO2 emissions from internal combustion engines in the transportation sector. Hybrid thermal and electrical propulsion systems appear particularly interesting because of the presence of an electric battery that simplifies the management of the electrical energy produced by the recovery system. The different technologies proposed for WHR can be categorized into direct and indirect ones, if the working fluid operating inside the recovery system is the exhaust gas itself or a different one whose sequence of transformations follows a thermodynamic cycle. In this paper, a turbocharged diesel engine (F1C Iveco) equipped with a Variable Geometry Turbine (VGT) has been tested to assess the energy recoverable from the exhaust gases both for direct and indirect recovery.

The demand of game-changing technologies to improve efficiency and abate emissions of heavy-duty trucks and off-road vehicles promoted the development of novel engine concepts. The Recuperated Split-Cycle (R-SC) engine allows to recover the exhaust gases energy into the air intake by separating the compression and combustion stages into two different but connected cylinders: the compressor and expander, respectively. The result is a potential increase of the engine thermal efficiency. Accordingly, the 3D-computational fluid dynamics (CFD) modelling of the gas exchange process and the combustion evolution inside the expander becomes essential to control and optimize the R-SC engine concept. This work aims to address the most challenging numerical aspects encountered in a 3D numerical simulation of an R-SC engine.

The requirements for modern drivetrains are increasing across all industries. Even mobile working machines such as agricultural and construction machinery are subject to increasingly higher demands in terms of efficiency and CO2 emissions. To verify these requirements and drive further development, it is necessary for testing processes to comprehensively evaluate the machine and its operational processes. For this purpose, the MOBiL testing approach was developed at the Institute of Mobile Machines. This approach incorporates parallel drivetrains, information flow and the environment of the driving and working task. To implement this approach in a complete vehicle testbench, a framework was developed that enables fully individual driving and working tasks of a mobile working machine to be replicated on a test bench. The basis for this framework is the Robot Operating System (ROS), which runs various nodes.

This article presents a novel approach for predicting fuel consumption in vehicles through a recurrent neural network (RNN) that uses only speed, acceleration, and road slope as input data. The model has been developed for real-time vehicle monitoring, route planning optimization, cost and emissions reduction and it is suitable for fleet-management purposes. To train and test the RNN, chosen after addressing several structures, experimental data have been measured on-board of a heavy-duty truck representative of a heavy-duty transportation company. Data have been acquired during typical daily missions, making use of an advanced connectivity platform, which features CANbus vehicle connection, GPS tracking, 4G/LTE - 5G connectivity, along with on-board data processing. The experimental data used for RNN train and test have been treated starting from on-board acquired raw data (e.g., speed, acceleration, fuel consumption, etc.) along with road slope downloaded from map providers.

To accurately evaluate the energy consumption benefits provided by connected and automated vehicles (CAV), it is necessary to establish a reasonable baseline virtual driver, against which the improvements are quantified before field testing. Virtual driver models have been developed that mimic the real-world driver, predicting a longitudinal vehicle speed profile based on the route information and the presence of a lead vehicle. The Intelligent Driver Model (IDM) is a well-known virtual driver model which is also used in the microscopic traffic simulator, SUMO. The Enhanced Driver Model (EDM) has emerged as a notable improvement of the IDM. The EDM has been shown to accurately forecast the driver response of a passenger vehicle to urban and highway driving conditions, including the special case of approaching a signalized intersection with varying signal phases and timing. However, most of the efforts in the literature to calibrate driver models have focused on passenger vehicles.

Natural gas is an attractive fuel for heavy-duty internal combustion engines as it has the potential to reduce CO2, particulate, and NOx emissions. This study reports optical investigations on the effect of methane stratification at lean combustion conditions in a heavy-duty optical diesel engine converted to spark-ignition operation. The combination of the direct injector (DI) and port-fuel injectors (PFI) fueling allows different levels of in-cylinder fuel stratification. The engine was operated in skip-firing mode, and high-speed natural combustion luminosity color images were recorded using a high-speed color camera from the bottom view, along with in-cylinder pressure measurements. The results from methane combustion based on port-fuel injections indicate the lean burn limit at λ = 1.4. To improve the lean limit of methane combustion, fuel stratification is introduced into the mixture using direct injections.

To reduce carbon dioxide (CO2) emissions from heavy-duty diesel engines down to zero until 2050, alternative powertrain strategies have been proposed in lieu of the improvements in internal combustion engines (ICEs). However, total amount of renewable electricity could be limited for the constructing infrastructure, the production of new battery and/or fuel cell vehicles and the operation of them compared with the growing demand of transportation in the future. Therefore, drastic improvement in transport efficiency with suppressing the increase of total CO2 emissions is essential. From these points of view, extremely high efficiency ICEs, combined or at least compatible with carbon neutral or renewable fuels having the capability of drop-in into the conventional fuels, should be attracted attention. Nevertheless, there have been few studies on the effects of fuel properties for further improving fuel consumption of diesel ICEs.

Synthetic fuels can significantly improve the combustion and emission characteristics of heavy-duty diesel engines toward decarbonizing heavy-duty propulsion systems. This work analyzes the effects of engine operating conditions and synthetic fuel properties on spray, combustion, and emissions (soot, NOx) using a supercharging single-cylinder engine experiment and KIVA-4 code combined with CHEMKIN-II and in-house phenomenological soot model. The blended fuel ratio is fixed at 80% diesel and 20% n-paraffin by volume (hereafter DP). Diesel, DP1 (diesel with n-pentane C5H12), DP2 (diesel with n-hexane C6H14), and DP3 (diesel with n-heptane C7H16) are used in engine-like-condition constant volume chamber (CVC) and engine experiments. Boosted engine experiments (1080 rpm, common-rail injection pressure 160 MPa, multi-pulse injection) are performed using the same DP fuel groups under various main injection timings, pulse-injection intervals, and EGR = 0-40%.

The transportation industry has been scrutinized for its contribution towards the global greenhouse gas emissions over the years. While the automotive sector has been regulated by strict emission legislation globally, the emissions from marine transportation have been largely neglected. However, during the past decade, the international maritime organization focused on ways to lower the emission intensity of the marine sector by introducing several legislations. This sets limits on the emissions of different oxides of carbon, nitrogen and sulphur, which are emitted in large amounts from heavy fuel oil (HFO) combustion (the primary fuel for the marine sector). A 40% and 70% reduction per transport work compared to the levels of 2008 is set as target for CO2 emission for 2030 and 2050, respectively. To meet these targets, commonly, methanol, as a low-carbon fuel, and ammonia, as a zero-carbon fuel, are considered.

The transportation sector, and commercial vehicles in particular, play an important role in global CO2 emissions. For this reason, the EU recently decided to reduce CO2 emissions from commercial vehicles by 30% until 2030. One alternative to conventional diesel propulsion is the usage of stoichiometric natural gas combustion. Due to the lowered C/H ratio and the cost effective exhaust after treatment (EAT) in form of a three way catalyst (TWC), less CO2 is emitted and it is possible to comply even with most stringent NOX legislations. However, the stoichiometric combustion of natural gas has also disadvantages. In particular, the throttling and retarded 50 % mass fuel burned (MFB50) positions due to knocking lead to efficiency losses. One way to minimize these is the usage of exhaust gas re-circulation (EGR), Miller cycle and water injection. The reduced knocking tendency allows the geometric compression ratio to be increased further, which leads to an additional efficiency advantage.

With the increase of heavy-duty transportation, more fuel efficient technologies and services have become of great importance due to their environmental and economical impacts for the fleet managers. In this paper, we first develop a new analytical model of the heavy-truck for its dynamics and its fuel consumption, and valid the model with experimental measurements. Then, we propose a bi-level optimization approach to reduce the fuel consumption, thus the CO2 emissions, while ensuring several safety constraints in real-time. Numerical results show that important reduction of the fuel consumption can be achieved, while satisfying imposed safety constraints.

In more or less all aspects of life and in all sectors, there is a generalized global demand to reduce greenhouse gas (GHG) emissions, leading to the tightening and expansion of existing emissions regulations. Currently, non-road engines manufacturers are facing updates such as, among others, US Tier 5 (2028), European Stage V (2019/2020), and China Non-Road Stage IV (in phases between 2023 and 2026). For on-road applications, updates of Euro VII (2025), China VI (2021), and California Low NOx Program (2024) are planned. These new laws demand significant reductions in nitrogen oxides (NOx) and particulate matter (PM) emissions from heavy-duty vehicles. When equipped with an appropriate exhaust aftertreatment system, natural gas engines are a promising technology to meet the new emission standards.

Increasing concern for air pollution together with the introduction of new types of fuels pose new challenges to the exhaust aftertreatment system for heavy-duty (HD) vehicles. For diesel-powered engines, emissions of particulate matter (PM) is one of the main drawbacks due to its effect on health. To mitigate the tailpipe emissions of PM, heavy-duty vehicles are since Euro V equipped with a diesel particulate filter (DPF). The accumulation of particles causes flow restriction resulting in fuel penalties and decreased vehicle performance. Understanding the properties of PM produced during engine operation is important for the development and optimized control of the DPF. This study has focused on assessing the reactivity of the PM by measuring the oxidation kinetics of the carbonaceous fraction. PM was sampled from two different heavy-duty engines during various test cycles.

This publication outlines FEV’s engineering approach and the associated process steps for efficiency optimization of the entire powertrain definition for various commercial applications, from light-duty vehicles to heavy long-haul trucks, with particular emphasis on the most important use cases. A focus is on the crucial trade-off between attractive transient drivetrain performance and the pursuit of ultra-low, near zero tailpipe pollutant emissions. The applied measures, ranging from minimized mechanical friction and reduced losses to on-demand support by different boosting technologies, different types of H2 injection and mixture formation (external and internal), and different exhaust gas aftertreatment layouts, are thoroughly evaluated and investigated using FEV’s dedicated H2-ICE simulation tool chain. This enables the specification of satisfactory H2-ICE based powertrain solutions for a wide range of use cases in the commercial vehicle sector.

The current political push for e-mobility marked a major decline in the R&D interest to internal combustion engine (ICE). Following this global trend, Ford is committed to going 100% electric by 2030 for passenger cars and 2035 for light commercial vehicles. At the same time, many researchers admit that, due to many objective factors, vehicles powered by ICE will remain in operation for decades to come. Development of alternative carbon-neutral fuels can bring a renaissance in the ICE development as practical limitations of electric-only approach get exposed. Since a significant part of energy losses in the ICE comes from friction, engine tribology has been an important research topic over the past two decades and a significant progress in improving the engine efficiency was achieved.

This study explores the potential benefits of combining a wave-shaped piston geometry with post injection strategy in diesel engines. The wave piston design features evenly spaced protrusions around the piston bowl, which improve fuel-air mixing and combustion efficiency. The 'waves' direct the flames towards the bowl center, recirculating them and utilizing the momentum in the flame jets for more complete combustion. Post injection strategy, which involves a short injection after the main injection, is commonly used to reduce emissions and improve fuel efficiency. By combining post injections with the wave piston design, additional fuel injection can increase the momentum utilized by the flame jets, potentially further improving combustion efficiency. To understand the effects and potential of the wave piston design with post injection strategy, a single-cylinder heavy-duty compression-ignition optical engine with a quartz piston is used.

Decades ago, like the 1990s automobile industry, the off-highway industry was purely recognized as a mechanical entity. In the mechanical system, accuracy and troubleshooting of faults were significant concerns. Additionally, the continuous stringent emission norms by the government call for the adaptation of the aftertreatment and DeNOx led to more complexity and challenges. To meet the government emission regulation and product performance, thorough functionality testing of manufactured units was crucial. For this purpose, EOL/diagnostics testers are developed. Diagnostic protocol CAN establish the connection between ECU and tester due to its robustness and data handling capabilities. This paper aims to develop and test the end-of-line (EOL) tester for off-highway diesel engines. The communication between the tester and ECU will be over UDSonCAN, conforming to standard ISO14229.

The Environmental Protection Agency (EPA), in partnership with Research Triangle Institute (RTI International) and Auto Research Center (ARC-Indy), have created digital geometries of commercially available heavy-duty tractor-trailers. The goal of this effort was to improve the agency’s understanding of aerodynamic modeling of modern trucks and to provide opportunities for more consistent engagement on computational fluid dynamics (CFD) analyses. Sleeper and day cab tractors with aerodynamic features and a 53-foot box trailer with aerodynamic technology options were scanned to create high-resolution geometries. The scanning process consisted of a combination of physical scanning with a handheld device, along with digital post-processing. The completed truck geometries are compatible with most commercial CFD software and are publicly available for modeling and analyses.

This work aimed to analyze the behavior of the rear structure region of an electric bus in a rear collision situation and to create mechanisms capable of absorbing the energy generated by the impact, to guarantee the integrity of the batteries. These, when damaged in a collision, can release different types of flammable electrolytes, and even start a fire, creating a great risk to passengers and other people near to the vehicle. For this purpose, an impact absorber was developed to protect the batteries. Studies were carried out on rectangular cross-section profiles for programmed deformation, known as crash boxes (which aim to convert kinetic energy into deformation energy). Proposals were created based on concepts obtained in the literature and numerically evaluated through explicit numerical simulations based on other similar articles. From these studies it was possible to obtain higher values of energy absorption when compared to a square tube of the same cross-section.

Improvements in component/system design is a daily challenge these days, always looking for high performance, reduced mass and low costs. The source for the best fit between these factors, coupled with adequate durability performance, is crucial to the success of a given product and this is what motivates engineering teams around the world. The demand for efficient projects with short deadlines for validation and certification is huge and simulation tools focused on accelerated durability and virtual validation are increasingly being used. When developing a new spring for commercial vehicles, lessons learned from the actual loads applied to the suspension are the “key” to a successful project. The loads/stresses from the ground (vertical loads, lateral loads, longitudinal and braking loads) are quite high and, consequently, relevant to the proper definition of the design of the suspension components.