Search Results

A methodology for an efficient failure prediction of automotive steel wheels during fatigue experimental tests is proposed. The strategy joins the CDTire simulative package effectiveness to a specific wheel finite element model in order to deeply monitor the stress distribution among the component to predict damage. The numerical model acts as a Software-in-the-loop and it is calibrated with experimental data. The developed tool, called VirtualWheel, can be applied for the optimisation of design reducing prototyping and experimental test costs in the development phase. In the first section, the failure criterion is selected. In the second one, the conversion of hardware test-rig into virtual model is described in detail by focusing on critical aspects of finite element modelling. In conclusion, failure prediction is compared with experimental test results.

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.

The Atmospheric Revitalization System (ARS) provides carbon dioxide removal, trace contaminant control, and gas constituent analysis. In this field, the interest of RecycLAB [5], the TAS-I Advanced Live Support Research & Development laboratory is directed to trace gas contaminants removal and monitoring. During manned space mission, the decontamination of cabin or rack air after contingency events such as fire or pyrolysis is a priority for the crew safety. In this paper, basic zeolites, obtained by impregnation of common zeolites with a basic oxide, are used to remove acid gas contaminants from air stream. A multi-functional system, able to accommodate reactors of different shape, characteristics and set-up, is used at this purpose. This breadboard, called ZEUS (Zeolites for an Environmental-control Unit in Space), is made of AISI 316L stainless steel and consists of a closed loop, in which the inner volume is completely isolated from the external environment.

Thermo-structural analysis of components is usually carried out by means of two FE models, one that solves the thermal problem and one that, using the results of the thermal model, computes strains and stresses. The interaction between the two models is based on the superposition principle, but it means that the mutual effects and the non-linearities between the two physical problems are neglected. In this paper a multiphysics approach based on the Cell Method is proposed and it is applied to a time dependent thermo-mechanical case study represented by an exhaust manifold simulacrum: the coupled thermal and mechanical problems are solved in an unique run, giving the opportunity to take into account mutual effects. Comparing the results with the traditional FE analysis the advantages in terms of accuracy and computational time achieved through the proposed methodology are highlighted.

With electric vehicles becoming more and more popular, the classic “general purpose” vehicle concept is changing to a “dedicated vehicle” concept. Light trucks for goods delivery in cities are one of the examples. The European vehicle category L7e fits perfectly in the low power, low weight vehicle requirements for an electric light truck for goods delivery. However, the safety requirements of this vehicle category are very low and their occupants are highly exposed to injuries in the event of a collision. The European Commission co-funded project OPTIBODY (Optimized Structural components and add-ons to improve passive safety in new Electric Light Trucks and Vans) is developing a new structural concept based on a chassis, a cabin a several add-ons. The add-ons will provide improved protection in case of frontal, side and rear impact.

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 paper deals with the Hardware-In-the-Loop based methodology which was adopted to evaluate the dynamic characteristics of Electronic Stability Program (ESP) and Electro-Hydraulic Brake (EHB) components. Firstly, it permits the identification of the time delays due to the hardware of the actuation system. Secondly, the link between the hardware of the hydraulic unit and a vehicle model running in real time permits the objective evaluation of the performance induced by the single components of different hydraulic units in terms of vehicle dynamics. The paper suggests the main parameters and tests which can help the car manufacturer in evaluating ESP hydraulic units, without expensive road tests.

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.

The aim of this paper is to study in deep the peculiar test-rigs and experimental procedures adopted to the fulfilment of the principal requirements of automotive steel wheels, in particular regarding fatigue damaging. In the discussion, the standard requirements, the OEM specifications and the dimensional and geometric tolerances are approached. As result of an increasingly necessity to improve the performance of the components, innovative virtual test benches are presented. Differently from their traditional precursors, virtual test-rigs give an extended view of the physical behaviour of the component as the possibility to monitor stress-strain distribution in deep. In the first section, the state of the art and the specifications are listed. Secondly, the adopted hardware test-rigs as the experimental tests are described in detail. In the third one, proposed virtual test-rig is discussed.

This study assesses the capabilities of dynamic wireless power transfer with respect to range extension and payload capacity of heavy-duty trucks. Currently, a strong push towards tailpipe CO2 emissions abatement in the heavy-duty transport sector by policymakers is driving the development of battery electric trucks. Yet, battery-electric heavy-duty trucks require large battery packs which may reduce the payload capacity and increase dwell time at charging stations, negatively affecting their acceptance among fleet operators. By investigating various levels of development of wireless charging technology and exploring various deployment scenarios for an electrified highway lane, the potential for a more efficient and environmentally friendly battery sizing was explored.

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.

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.

Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.

This paper presents a numerical methodology to generate lookup tables that provide d- and q-axis stator current references for the control of electric motors. The main novelty with respect to other literature references is the introduction of the iron power losses in the equivalent-circuit electric motor model implemented in the optimization routine. The lookup tables generation algorithm discretizes the motor operating domain and, given proper constraints on maximum stator current and magnetic flux, solves a numerical optimization problem for each possible operating point to determine the combination of d- and q- axis stator currents that minimizes the imposed objective function while generating the desired torque. To demonstrate the versatility of the proposed approach, two different variants of this numerical interpretation of the motor control problem are proposed: Maximum Torque Per Ampere and Minimum Electromagnetic Power Loss.