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An innovative 0D predictive combustion model for the simulation of the HRR (heat release rate) in DI diesel engines was assessed and implemented in a 1D fluid-dynamic commercial code for the simulation of a Fiat heavy duty diesel engine equipped with a Variable Geometry Turbocharger system, in the frame of the CORE (CO2 reduction for long distance transport) Collaborative Project of the European Community, VII FP. The 0D combustion approach starts from the calculation of the injection rate profile on the basis of the injected fuel quantities and on the injection parameters, such as the start of injection and the energizing time, taking the injector opening and closure delays into account. The injection rate profile in turn allows the released chemical energy to be estimated. The approach assumes that HRR is proportional to the energy associated with the accumulated fuel mass in the combustion chamber.

The potential of internal EGR (iEGR) and external EGR (eEGR) in reducing the engine-out NOx emissions in a heavy-duty diesel engine has been investigated by means of a refined 1D fluid-dynamic engine model developed in the GT-Power environment. The engine is equipped with Variable Valve Actuation (VVA) and Variable Geometry Turbocharger (VGT) systems. The activity was carried out in the frame of the CORE Collaborative Project of the European Community, VII FP. The engine model integrates an innovative 0D predictive combustion algorithm for the simulation of the HRR (heat release rate) based on the accumulated fuel mass approach and a multi-zone thermodynamic model for the simulation of the in-cylinder temperatures. NOx emissions are calculated by means of the Zeldovich thermal and prompt mechanisms.

A model-based approach to control BMEP (Brake Mean Effective Pressure) and NOx emissions has been developed and assessed on a FPT F1C 3.0L Euro VI diesel engine for heavy-duty applications. The controller is based on a zero-dimensional real-time combustion model, which is capable of simulating the HRR (heat release rate), in-cylinder pressure, BMEP and NOx engine-out levels. The real-time combustion model has been realized by integrating and improving previously developed simulation tools. A new discretization scheme has been developed for the model equations, in order to reduce the accuracy loss when the computational step is increased. This has allowed the required computational time to be reduced to a great extent.

This paper presents a study related to an Articulated Amphibious All-Terrain Tracked Vehicle (ATV) characterized by a modular architecture. The ATV is composed by two modules: the first one hosts mainly the vehicle engine and powertrain components, meanwhile the second one can be used for goods transportation, personnel carrier, crane and so on. The engine torque is transmitted to the front axle sprocket wheel of each module and finally distributed on the ground through a track mechanism. The two modules are connected through a multiaxial joint designed to guarantee four relative degrees of freedom. To steer the ATV, an Electro Hydraulic Power System (EHPS) is adopted, thus letting the vehicle steerable on any kind of terrain without a differential tracks speed. The paper aims to analyze the steady-state lateral behavior of the ATV on a flat road, through a non-linear mathematical vehicle model built in Matlab/Simulink environment.

In automotive market, today more than in the past, it is very important to reduce time to market and, mostly, developing costs before the final production start. Ideally, bench and on-road tests can be replaced by multi-body studies because virtual approach guarantees test conditions very close to reality and it is able to exactly replicate the standard procedures. Therefore, today, it is essential to create very reliable models, able to forecast the vehicle behavior on every road condition (including uneven surfaces). The aim of this study is to build an accurate multi-body model of a heavy-duty truck, check its handling performance, and correlate experimental and numerical data related to comfort tests for model tuning and validation purposes. Experimental results are recorded during tests carried out at different speeds and loading conditions on a Belgian blocks track. Simulation data are obtained reproducing the on-road test conditions in multi-body environment.

Hybrid and electric powertrains are experiencing a consistent growth in the automotive field demonstrating their effectiveness in reducing pollutant emissions especially in urban areas. Recently these technologies started to be investigated in the field of work machineries as possible solution to meet increasingly stricter regulations on pollutant emissions. The construction field was the first to recognize the benefits of a partial or total electrification of a work machinery. Nowadays, the consolidation of the technology allowed for its consistent diffusion in the more conservative agricultural field where manufacturers are struggling to meet emissions regulations without losing in terms of work performance. Tractors manufacturers are the most affected actors because of the difficulty to integrate bulky gas aftertreatment systems on board of their vehicle.

The concept of autonomous driving is becoming increasingly familiar in the automotive and “in-door” automation systems fields. Furthermore, the industrial development is focusing its efforts on industry 4.0, whose some main features are data transfer, programming, systems interconnection and automation. The agricultural sector just recently has experienced the first examples of autonomous agricultural vehicles, although agricultural mechanization has reached a good level of automation. Indeed, many examples of automatic machineries are already present in the market such as little robots for the execution of some operations. This work focuses on modelling and simulation of a self-driving orchard tractor. The main goal was to reproduce the behaviour of the specialized vehicle, moving in an orchard or a vineyard and conducting automatic or semi-automatic operations.

The paper addresses some aspects of an ongoing research on a commercial compact excavator. The interest is focused on the analysis and modelling of the whole hydraulic circuit that, beside a load sensing variable displacement pump, features a stack of nine proportional directional control valves modules of which seven are of the load sensing type. Loads being sensed are the boom swing, boom, stick and bucket, right and left track motors and work tools; instead, the blade and the turret swing users do not contribute to the load sensing signal. Of specific interest are the peculiarities that were observed in the stack. In fact, to develop an accurate AMESim modelling, the stack was dismantled and all modules analysed and represented in a CAD environment as 3D parts. The load sensing flow generation unit was replaced on the vehicle by another one whose analysis and modelling have been developed using available design and experimental data.

In the last few years, the number of Advanced Driver Assistance Systems (ADAS) on road vehicles has been increased with the aim of dramatically reducing road accidents. Therefore, the OEMs need to integrate and test these systems, to comply with the safety regulations. To lower the development cost, instead of experimental testing, many virtual simulation scenarios need to be tested for ADAS validation. The classic multibody vehicle approach, normally used to design and optimize vehicle dynamics performance, is not always suitable to cope with these new tasks; therefore, real-time lumped-parameter vehicle models implementation becomes more and more necessary. This paper aims at providing a methodology to convert experimentally validated light commercial vehicles (LCV) multibody models (MBM) into real-time lumped-parameter models (RTM).

The Vehicle Energy Consumption calculation Tool (VECTO) is used in Europe for calculating standardised energy consumption and CO2 emissions from Heavy-Duty Trucks (HDTs) for certification purposes. The tool requires detailed vehicle technical specifications and a series of component efficiency maps, which are difficult to retrieve for those that are outside of the manufacturing industry. In the context of quantifying HDT CO2 emissions, the Joint Research Centre (JRC) of the European Commission received VECTO simulation data of the 2016 vehicle fleet from the vehicle manufacturers. In previous work, this simulation data has been normalised to compensate for differences and issues in the quality of the input data used to run the simulations. This work, which is a continuation of the previous exercise, focuses on the deeper meaning of the data received to understand the factors contributing to energy and fuel consumption.

Since vehicles are comprised of thousands of components, it is essential to reduce the Life Cycle Inventory (LCI) modelling workload. This study aims to compare different LCI modeling workload-reducing scenarios to provide a trade-off between the workload efforts and result accuracy. To achieve the optimal balance between computational effort and data specification requirements, the driver seat is used as a case study, instead of the entire vehicle. When all the components of a conventional light-duty commercial vehicle are sorted by mass descending order, seats are among the first five. In addition, unlike the other components, seats are comprised of metals as well as a wide range of plastics and textiles, making them a representative test case for a general problem formulation. In this way, methodology and outcomes can be reasonably extended to the entire vehicle.

Fuel cell electrified powertrains are currently a promising technology towards decarbonizing the heavy-duty transportation sector. In this context, extensive research is required to thoroughly assess the hydrogen economy potential of fuel cell heavy-duty electrification. This paper proposes a real-time capable energy management strategy (EMS) that can achieve improved hydrogen economy for a fuel cell electrified heavy-duty truck. The considered heavy-duty truck is modelled first in Simulink® environment. A baseline heuristic map-based controller is then retained that can instantaneously control the electrical power split between fuel cell system and the high-voltage battery pack of the heavy-duty truck. Particle swarm optimization (PSO) is consequently implemented to optimally tune the parameters of the considered EMS.

Aim of this work is the development of a lumped parameters simulation model of single-vane vacuum pumps for pneumatically actuated brake boosters. Kinematic and fluid-dynamic models are integrated in a simulation environment to create a tool aimed at evaluating the vacuum pump performance and at guiding the designer during the prototype development. The paper describes extensively the mathematical model, the time domain simulation and experimental analyses performed on a camshaft mounted unit. Great emphasis is placed on the evaluation of the geometric quantities of the control volumes into which the vacuum pump has been divided. For each control volume the mass and energy conservation equations lead to the determination of the instantaneous pressure. The volume of each variable chamber and the respective angular derivative are calculated as function of the shaft position starting from the stator track profile supplied as a generic closed polyline.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

Nowadays, green hydrogen can play a crucial role in a successful clean energy transition, thus reaching net zero emissions in the transport sector. Moreover, hydrogen exploitation in internal combustion engines is favoured by its suitable combustion properties and quasi-zero harmful emissions. High flame speeds enable a lean combustion approach, which provides high efficiency and reduces NOx emissions. However, high air flow rates are required to achieve the load levels typical of heavy-duty applications. In this framework, the present study aims to investigate the required boosting system of a 6-cylinder, 13-liter heavy-duty spark ignition engine through 1D numerical simulation. A comparison among various architectures of the turbocharging system and the size of each component is presented, thus highlighting limitations and potentialities of each architecture and providing important insights for the selection of the best turbocharging system.

In the last decades, the locomotion of wheeled and tracked vehicles on soft soils has been widely investigated due to the large interest in planetary, agricultural, and military applications. The development of a tire-soft soil contact model which accurately represents the micro and macro-scale interactions plays a crucial role for the performance assessment in off-road conditions since vehicle traction and handling are strongly influenced by the soil characteristics. In this framework, the analysis of realistic operative conditions turns out to be a challenging research target. In this research work, a semi-empirical model describing the interaction between a tire and homogeneous and fine-grained soils is developed in Matlab/Simulink. The stress distribution and the resulting forces at the contact patch are based on well-known terramechanics theories, such as pressure-sinkage Bekker’s approach and Mohr-Coulomb’s failure criterion.