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The paper deals with the virtual and experimental analysis of two commercial Mechanical Brake Assist systems. They are described in detail, then modeled and experimentally evaluated through a Hardware-In-the-Loop test bench and road tests. Three different kinds of drivers are compared, from the point of view of the performance increase promised by Brake Assist during an emergency brake maneuver. The three driver types are based on the measurement of the behavior of real drivers, as it is presented in specific research activities in literature.

The clutch is that mechanical part located in an internal combustion engine vehicle which allows the torque transmission from the shaft to the wheels, permitting at the same time gear shifting and supporting engine revolutions while the car is idling. This component exploits friction as working principle, therefore heat generation is in its own nature. The comprehension of all the critical issues related to thermal emission, and also of the principal physical parameters driving the phenomena are a must in design phases. The subject of this paper is the elaboration of an accurate, but also easy to use and easily replicable, methodology to simulate thermal behavior of a clutch operating inside its usual environment. The present methodology allows to prevent corrective actions in the last phase of the projects (real testing), such as changes in gear ratios, that likely worsen CO2 emissions, permitting to achieve the wished thermal performance of the clutch avoiding late changes.

A method for estimating the vehicle mass in real time is presented. Traditional mass estimation methods suffer due a lack of knowledge of the vehicle parameters, the road surface conditions and most importantly the effect of the vehicle transmission. To resolve these issues, a method independent of a vehicle model is utilized in conjunction with a drivetrain output torque observer to obtain the estimate of the vehicle mass. Simulations and experimental track tests indicate that the method is able to accurately estimate the vehicle mass with a relatively fast rate of convergence compared to traditional methods.

Active Roll Control (ARC) is one of the most promising active systems to improve vehicle comfort and handling. This paper describes the simulation based procedure adopted to conceive a double-channel Active Roll Control system, characterized by the hydraulic actuation of the stabilizer bars of a sedan. The first part of the paper presents the vehicle model adopted for this activity. It is Base Model Simulator (BMS), the 14 Degrees-of-Freedom vehicle model by Politecnico di Torino. It was validated through road tests. Then the paper describes the development of the control algorithm adopted to improve the roll dynamics of the vehicle. The implemented control algorithm is characterized by a first subsystem, capable of obtaining the desired values of body roll angle as a function of lateral acceleration during semi-stationary maneuvers.

The term driveability describes the driver's complex subjective perception of the interactions with the vehicle. One of them is associated to longitudinal acceleration aspects. A relevant contribution to the driveability optimization process is, nowadays, realized by means of track tests during which a considerable amount of driveline parameters are tuned in order to obtain a good compromise of longitudinal acceleration response. Unfortunately, this process is carried out at a development stage when a design iteration becomes too expensive. In addition, the actual trend of downsizing and supercharging the engines leads to higher vibrations that are transmitted to the vehicle. A large effort is therefore dedicated to develop, test and implement ignition strategies addressed to minimize the torque irregularities. Such strategies could penalize the engine maximum performance, efficiency and emissions. The introduction of the dual mass flywheel is beneficial to this end.

The DEXA Cluster consisted of three closely interlinked projects. In 2003 the DEXA Cluster concluded by demonstrating the successful development of critical technologies for Diesel exhaust particulate after-treatment, without adverse effects on NOx emissions and maintaining the fuel economy advantages of the Diesel engine well beyond the EURO IV (2000) emission standards horizon. In the present paper the most important results of the DEXA Cluster projects in the demonstration of advanced particulate control technologies, the development of a simulation toolkit for the design of diesel exhaust after-treatment systems and the development of novel particulate characterization methodologies, are presented. The motivation for the DEXA Cluster research was to increase the market competitiveness of diesel engine powertrains for passenger cars worldwide, and to accelerate the adoption of particulate control technology.

In this paper a test bench for measuring the Static Transmission Error of two mating gears is presented and a comparison with the results obtained with the commercial software GeDy TrAss is shown. Static Transmission Error is considered as the main source of overloads and Noise, Vibration and Harshness issues in mechanical transmissions. It is defined as the difference between the theoretical angular position of two gears under load in quasi-static conditions and the real one. This parameter strictly depends on the applied torque and the tooth macro and micro-geometry. The test bench illustrated in this work is designed to evaluate the actual Static Transmission Error of two gears under load in quasi-static conditions. In particular, this testbed can be divided in two macro elements: the first one is the mechanism composed by weights and pulleys that generates a driving and a braking torque up to 500 Nm.

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.

Further improvement of the trade-off between CO2 and pollutant emissions is the main motivating factor for the development of new diesel engine concepts, from light-duty car applications via medium-duty commercial vehicles up to large long-haul trucks. The deactivation of one or more cylinders of a light-duty diesel engine during low load operation can be a sophisticated method to improve fuel economy and reduce especially NOx emissions at the same time. Dynamic Skip Fire (DSF) is an advanced cylinder deactivation technology, where the decision to fire or skip singular units of a multi-cylinder engine architecture is taken just prior to each firing opportunity, based on a balanced rankling of multiple input parameters.

Battery terminal voltage modelling is crucial for various applications, including electric vehicles, renewable energy systems, and portable electronics. Terminal voltage models are used to determine how a battery will respond under load and can be used to calculate run-time, power capability, and heat generation and as a component of state estimation approaches, such as for state of charge. Previous studies have shown better voltage modelling accuracy for long short-term memory (LSTM) recurrent neural networks than other traditional methods (e.g., equivalent circuit and electrochemical models). This study presents two new approaches – sequence training and data shuffling – to improve LSTM battery voltage models further, making them an even better candidate for the high-accuracy modelling of lithium-ion batteries. Because the LSTM memory captures information from past time steps, it must typically be trained using one series of continuous data.

This paper presents a methodology for the assessment of the NVH (noise vibration and harshness) performance of Dual Clutch Transmissions (DCTs) depending on some transmission design parameters, e.g. torsional backlash in the synchronizers or clutch disc moment of inertia, during low speed maneuvers. A 21-DOFs nonlinear dynamic model of a C-segment passenger car equipped with a DCT is used to simulate the torsional behavior of the driveline and to estimate the forces at the bearings. The impacts between the teeth of two engaging components, e.g. gears and synchronizers, generate impulses in the forces, thus loading the bearings with force time-history characterized by rich frequency content. A broadband excitation is therefore applied to the gearbox case, generating noise and vibration issues.

Vehicle dynamics is a fundamental part of vehicle performance. It combines functional requirements (i.e. road safety) with emotional content (“fun to drive”, “comfort”): this balance is what characterizes the car manufacturer (OEM) driving DNA. To reach the customer requirements on Ride & Handling, integration of CAE and testing is mandatory. Beside of cutting costs and time, simulation helps to break down vehicle requirements to component level. On chassis, the damper is the most important component, contributing to define the character of the vehicle, and it is defined late, during tuning, mainly by experienced drivers. Usually 1D lookup tables Force vs. Velocity, generated from tests like the standard VDA, are not able to describe the full behavior of the damper: different dampers display the same Force vs. Velocity curve but they can give different feeling to the driver.

This paper deals with the development of a Lap Time Simulator in order to carry out a first approximate evaluation of the potential benefits related to the adoption of the Kinetic Energy Recovery System (KERS). KERS will be introduced in the 2009 Formula 1 Season. This system will be able to store energy during braking and then use it in order to supply an extra acceleration during traction. Different technologies (e.g. electrical, hydraulic and mechanical) could be applied in order to achieve this target. The lap time simulator developed by the authors permits to investigate the advantages both in terms of fuel consumption reduction and the improvement of the lap time.

Several space agencies have announced plans to return humans to the Moon in the near future. The objectives of these missions include using the Moon as a stepping-stone towards crewed missions to Mars, to test advanced technology, and to further exploration of the Moon for scientific research and in-situ resource utilization. To meet these objectives, it will be necessary to establish and operate a lunar base. As a result, a wide variety of tasks that may pose a number of crew health and safety risks will need to be performed on the surface of the Moon. Therefore, to ensure sustainable human presence on the Moon and beyond, it is essential to anticipate potential risks, assess the impact of each risk, and devise mitigation strategies. To address this, a nine-week intensive investigation was performed by an international, interdisciplinary and intercultural team on how to maximize crew safety on the lunar surface through a symbiotic relationship between astronauts and robots.

Magneto-Rheological (MR) Fluid started to be used for industrial applications in the last 20 years, and, from that moment on, innovative uses have been evaluated for different applications to exploit its characteristic of changing yield stress as a function of the magnetic field applied. Because of the complexity of the behavior of the MR fluid, it is necessary to perform lots of simulations, combining multi-physical software capable of evaluating all the material’s characteristics. The paper proposes a strategy capable of quickly verifying the feasibility of an innovative MR system, considering a sufficient accuracy of the approximation, able to easily verify the principal criticalities of the innovative applications concerning the MR fluid main electromagnetic and fluid-dynamic capabilities.

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.

A fuel-cell-based system's performance is mainly identified in the overall efficiency, strongly depending on the amount of power losses due to auxiliary devices to supply. In such a situation, everything that causes either a decrease of the available power output or an increment of auxiliary losses would determine a sensible overall efficiency reduction.

The aim of this work is to analyze particle number and size distribution from a small displacement Euro 5 common rail automotive diesel engine, equipped with a close coupled aftertreatment system, featuring a DOC and a DPF integrated in a single canning. In particular the effects of different combustion processes on PM characteristics were investigated, by comparing measurements made both under normal operating condition and under DPF regeneration mode. Exhaust gas was sampled at engine outlet, at DOC outlet and at DPF outlet, in order to fully characterize PM emissions through the whole exhaust line. After a two stage dilution system, sampled gas was analyzed by means of a TSI 3080 SMPS, in the range from 6 to 240 nm. Particle number and size distribution were evaluated at part load operating conditions, representative of urban driving.

In the face of growing concerns about environmental sustainability and urban congestion, the integration of eco-driving strategies has emerged as a pivotal solution in the field of the urban transportation sector. This study explores the potential benefits of a CAV functioning as a virtual eco-driving controller in an urban traffic scenario with a group of following human-driven vehicles. A computationally inexpensive and realistic powertrain model and energy management system of the Chrysler Pacifica PHEV are developed with the field experiment data and integrated into a forward-looking vehicle simulator to implement and validate an eco-driving speed planning and energy management strategy assuming longitudinal automation. The eco-driving algorithm determines the optimal vehicle speed profile and energy management strategy.

Experimental Design methodologies have been applied in conjunction with objective functions for the optimization of the internal geometry of a rear muffler of a subcompact car equipped with a 1.4 liters displacement s.i. turbocharged engine. The muffler also features an innovative variable geometry design. The definition of an objective function summarising the silencing capability of the muffler has been driving the optimization process with the aim to reduce the tailpipe noise while maintaining acceptable pressure losses and complying with severe space constraints. Design of Experiments techniques for the reduction of experimental plans have been shown to be extremely effective to find out the optimum values of the design parameters, allowing a remarkable reduction of the time required by the design process in comparison with full factorial designs.