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Ammonia/urea-SCR is a mature technology, applied worldwide for the control of NOx emissions in combustion exhausts from thermal power plants, cogeneration units, incinerators and stationary diesel engines and more recently also from mobile sources. However a greater DeNOx activity at low temperatures is desired in order to meet more and more restrictive legislations. In this paper we report transient and steady state data collected over commercial Fe-ZSM-5 and V₂O₅-WO₃/TiO₂ catalysts showing high NOx reduction efficiencies in the 200 - 350°C T-range when NO and ammonia react with nitrates, e.g., in the form of an aqueous solution of ammonium nitrate. Under such conditions a new reaction occurs, the so-called "Enhanced SCR" reaction, 2 NH₃ + 2 NO + NH₄NO₃ → 3 N₂ + 5 H₂O.

This paper presents a nonlinear control approach to achieve good performances in vehicle path following and collision avoidance when the vehicle is driving under cruise highway conditions. Nonlinear model predictive control (NLMPC) is adopted to achieve online trajectory control based on a simplified vehicle model. GMRES/Continuation algorithm is used to solve the online optimization problem. Simulations show that the proposed controller is capable of tracking the desired path as well as avoiding the obstacles.

The friction estimation at the tire-ground contact is crucial for the active safety of vehicles. Friction estimation is a key problem of vehicle dynamics and the ultimate solution is still unknown. However the proposed approach, based on a simple idea and on a simple hardware, provides an actual solution. The idea is to compare the tire characteristic at a given friction (nominal characteristic) with the actual characteristic that the tire has while running. The comparison among these two characteristics (the nominal one and the actual one) gives the desired friction coefficient. The friction coefficient is expressed in vector form and a number of running parameters are identified. The mentioned comparison is an efficient but complex algorithm based on a mathematical formulation of the tire characteristic. The actual tire characteristic is somehow measured in real time by a relatively simple smart wheel which is able to detect the three forces and the three moments acting at the hub.

The paper investigates the interaction between soil and tractor tires through a 2D numerical model. The tire is schematized as a rigid ring presenting a series of rigid tread bars on the external circumference. The outer profile of the tire is divided into a series of elements, each one able to exchange a normal and a tangential contact force with the ground. A 2D soil model was developed to compute the forces at the ground-tire interface: the normal force is determined on the basis of the compression of the soil generated by the sinking of the tire. The soil is modeled through a layer of springs characterized by two different stiffness for the loading (lower stiffness) and unloading (higher stiffness) condition. This scheme allows to introduce a memory effect on the soil which results stiffer and keeps a residual sinking after the passage of the tire. The normal contact force determines the maximum value of tangential force provided before the soil fails.

Highway and roadway surface measurement is a practice that has been ongoing for decades now. This sort of measurement is intended to ensure a safe level of road perturbances. The measurement may be conducted by a slow moving apparatus directly measuring the elevation of the road, at varying distance intervals, to obtain a road profile, with varying degrees of resolution. An alternate means is to measure the surface roughness at highway speeds using accelerometers coupled with high speed distance measurements, such as laser sensors. Vehicles out rigged with such a system are termed inertial profilers. This type of inertial measurement provides a sort of filtered roadway profile. Much research has been conducted on the analysis of highway roughness, and the associated metrics involved. In many instances, it is desirable to maintain an off-road course such that the course will provide sufficient challenges to a vehicle during durability testing.

In the last years the number of electronic controllers of vehicle dynamics applied to chassis components has increased dramatically. They use lookup table of the primary order vehicle global parameters as yaw rate, lateral acceleration, steering angle, car velocity, that define the ideal behavior of the vehicle. They are usually based on PID controllers which compare the actual behavior of every measured real vehicle data to the desired behavior, from look up table. The controller attempts to keep the measured quantities the same as the tabled quantities by using ESP, TC (brakes and throttle), CDC (control shocks absorbers), EDIFF(active differential) and 4WS (rear wheels active toe). The performances of these controls are good but not perfect. The improvement can be achieved by replacement of the lookup tables with a fast vehicle model running in parallel to the real vehicle.

This study examines the impact of slip in aero-thermal conditions of supercooled large droplets (SLD) produced in an Icing Wind Tunnel (IWT) on the ice accretion characteristics. The study identifies potential biases in the SLD model development based on IWT data and numerical predictions that assume the SLD to be in aerothermal equilibrium with the IWT airflow. To obtain realistic temperature and velocity data for each droplet size class in the test section of the Braunschweig Icing Wind Tunnel (BIWT), a Lagrangian droplet tracking solver was used within a Monte Carlo framework. Results showed that SLDs experience considerable slips in velocity and temperature due to their higher inertia and short residence time in the Braunschweig IWT. Large droplets were found to be warmer and slower than the flow in the test section, with larger droplets experiencing larger aerothermal slips.

Aim of this study is to analyze the benefits of the measures provided by smart tyres on tyre-road friction coefficient and vehicle sideslip angle estimation. In particular, a smart tyre constituted by 2 tri-axial accelerometers glued on the tyre inner liner is considered which is able to provide the measures of the tyre-road contact forces once per wheel turn. These measures are added to the ones usually present onboard vehicle (steer angle, lateral acceleration and yaw rate) and following included into an Extended Kalman Filter (EKF) based on a single-track vehicle model. Performance of the proposed observer is evaluated on a series of handling maneuvers and its robustness to road bank angle, tyre and vehicle parameters variation is discussed.

The Linear Time Varying (LTV) Model Predictive Control (MPC) is a linear model predictive control based on linearization of the nonlinear vehicle model. The linearization is carried out consideing each vehicle state. The developed model is able to steer to avoid obstacles and follow a given path. Once the optimal parameters are found, both in terms of trajectory following and real-time performances, the LTV-MPC is used for assessing the limit vehicle conditions as a function of the vehicle forward target speed, the obstacle shape as well as the road conditions (both dry and wet road conditions were taken into account). It is shown that, to avoid collisions, given performances of the vehicle brakes and of the mounted sensors are required.

For passenger cars, individual tyre model parameters, used in vehicle models able to simulate vehicle handling behavior, are traditionally derived from expensive component indoor laboratory tests as a result of an identification procedure minimizing the error with respect to force and slip measurements. Indoor experiments on agricultural tyres are instead more challenging and thus generally not performed due to tyre size and applied forces. However, the knowledge of their handling characteristics is becoming more and more important since in the next few years, all agricultural vehicles are expected to run on ordinary asphalt roads at a speed of 80km/h. The present paper presents a methodology to identify agricultural tyres' handling characteristics based only on the measurements carried out on board vehicle (vehicle sideslip angle, yaw rate, lateral acceleration, speed and steer angle) during standard handling maneuvers (step-steers, J-turns, etc.), instead than during indoor tests.

The aim of the paper is to provide simple and accurate analytical formulae describing the straight motion of a road vehicle. Such formulae can be used to compute either the steering torque or the additional rolling resistance induced by vehicle side-slip angle. The paper introduces a revised formulation of the Handling Diagram Theory to take into account tire ply-steer, conicity and road banking. Pacejka’s Handling Diagram Theory is based on a relatively simple fully non-linear single track model. We will refer to the linear part of the Handling Diagram, since straight motion will be considered only. Both the elastokinematics of suspension system and tire characteristics are taken into account. The validation of the analytical expressions has been performed both theoretically and after a subjective-objective test campaign. By means of the new and unreferenced analytical formulae, practical hints are given to set to zero the steering torque during straight running.

By analyzing the dynamic distortion in all body closure openings in a complete vehicle, a better understanding of the body characteristics can be achieved compared to traditional static load cases such as static torsional body stiffness. This is particularly relevant for non-traditional vehicle layouts and electric vehicle architectures. The body response is measured with the so-called Multi Stethoscope (MSS) when driving a vehicle on a rough pavé road (cobble stone). The MSS is measuring the distortion in each opening in two diagonals. During the virtual development, the distortion is described by the relative displacement in diagonal direction in time domain using a modal transient analysis. The results are shown as Opening Distortion Fingerprint ODF and used as assessment criteria within Solidity and Perceived Quality. By applying the Principal Component Analysis (PCA) on the time history of the distortion, a Dominant Distortion Pattern (DDP) can be identified.