334 research outputs found
A Comparison Between Coupled and Decoupled Vehicle Motion Controllers Based on Prediction Models
In this work, a comparative study is carried out with two different predictive controllers that consider the longitudinal jerk and steering rate change as additional parameters, as additional parameters, so that comfort constraints can be included. Furthermore, the approaches are designed so that the effect of longitudinal and lateral motion control coupling can be analyzed. This way, the first controller is a longitudinal and lateral coupled MPC approach based on a kinematic model of the vehicle, while the second is a decoupled strategy based on a triple integrator model based on MPC for the longitudinal control and a double proportional curvature control for the lateral motion control. The control architecture and motion planning are exhaustively explained. The comparative study is carried out using a test vehicle, whose dynamics and low-level controllers have been simulated using the realistic simulation environment Dynacar. The performed tests demonstrate the effectiveness of both approaches in speeds higher than 30 km/h, and demonstrate that the coupled strategy provides better performance than the decoupled one. The relevance of this work relies in the contribution of vehicle motion controllers considering the comfort and its advantage over decoupled alternatives for future implementation in real vehicles.This work has been conducted within the ENABLE-S3 project that has
received funding from the ECSEL Joint Undertaking under Grant Agreement
No 692455. This work was developed at Tecnalia Research & Innovation
facilities supporting this research
Longitudinal Model Predictive Control with comfortable speed planner
Guaranteeing simplicity and safety is a real challenge of Advanced Driver Assistance Systems (ADAS), being these aspects necessary for the development of decision and control stages in highly automated vehicles. Considering that a human-centered design is generally pursued, exploring comfort boundaries in passenger vehicles has a significant importance. This work aims to implement a simple Model Predictive Control (MPC) for longitudinal maneuvers, considering a bare speed planner based on the curvature of a predefined geometrical path. The speed profiles are constrained with a maximum value at any time, in such way that total accelerations are lower than specified constraint limits. A double proportional with curvature bias control was employed as a simple algorithm for lateral maneuvers. The tests were performed within a realistic simulation environment with a virtual vehicle model based on a multi-body formulation. The results of this investigation permits to determine the capabilities of simplified control algorithms in real scenarios, and comprehend how to improve them to be more efficient.Authors want to acknowledge their organization. This project
has received funding from the Electronic Component Systems
for European Leadership Joint Undertaking under grant agreement
No 737469 (AutoDrive Project). This Joint Undertaking
receives support from the European Unions Horizon 2020
research and innovation programme and Germany, Austria, Spain, Italy, Latvia, Belgium, Netherlands, Sweden, Finland,
Lithuania, Czech Republic, Romania, Norway. This work
was developed at Tecnalia Research & Innovation facilities
supporting this research
First principles quasiparticle damping rates in bulk lead
First principles calculations of the damping rates (inverse inelastic
lifetimes) of low energy quasiparticles in bulk Pb are presented. Damping rates
are obtained both for excited electrons and holes with energies up to 8 eV on a
set of k vectors throughout the Brillouin zone (BZ). Strong localization
effects in the calculated lifetimes are found. Averaged over the BZ inelastic
lifetimes versus quasiparticle energy are reported as well. In addition, the
effect of the spin-orbit induced splitting in the band structure on the
calculated lifetimes in Pb is investigated.Comment: 10 pages, 8 figures, 5 table
Machine Learning Based Fall Detector with a Sensorized Tip
Fall detection has become an area of interest in recent years, as quick response to these events is critical to reduce the morbidity and mortality rate. In order to ensure proper fall detection, several technologies have been developed, including vision system, environmental detection systems, and wearable sensor based systems. However, in elderly or impaired people, it has been shown that the implementation of sensors in Assistive Devices for Walking, such as crutches or canes, can also be a promising alternative. In this work, a Support Vector Machine (SVM) based Fall Detection system is proposed, which uses the data provided by a Sensorized Tip which can be attached to different Assistive Devices for Walking (ADW). Unlike other approaches, the developed one is able to differentiate the fall of the ADW from the fall of the user. For that purpose, the developed Fall Detector uses two modules connected in series. The first one detects all falls, while the second differentiates between user and ADW falls. The proposed approach is validated in a set of experimental tests carried out by healthy volunteers that have simulated different falls. In addition, a comparative analysis is carried out by comparing the performance of the Sensorized Tip based Fall Detector and a state-of-the-art commercial accelerometer system. Results demonstrate that the proposed approach provides high Fall Detection Ratios (over 90%), similar or higher to wearable-sensor based approaches
Differences in branch characteristics of Scots pine (Pinus sylvestris L.) genetic entries grown at different spacing
• We studied the differences in branch characteristics along the stems of six different
genetic entries of 20 year old Scots pines (Pinus sylvestris L.) grown at
different spacing (current stand density range 2000–4000 trees ha−1) in central
Finland. Furthermore, we studied the phenotypic correlations between yield, wood density
traits and branch characteristics. All the genetic entries had Kanerva pine (plus tree
S1101) as a father tree, whereas the mother tree represented Finnish plus trees from
southern, central and northern Finland.
• Spacing affected all yield traits, wood density and living branch characteristics such
as relative average branch diameter and relative cumulative branch area
(p < 0.05). As a comparison, genetic entry affected height,
while origin group (southern, central and northern ones) affected most of the studied
traits. Regardless of spacing, the northern origin had, on average, the largest stem
diameter and highest wood density, while the central one was the tallest one. Furthermore,
average branch diameter along the stem was affected by branch age, origin group and
spacing, while average branch angle was affected by branch age and genetic entry
(p < 0.05).
• In general the average branch size could be decreased especially in lower tree canopy
by denser spacing during the early phase of the rotation, but only at the expense of tree
growth. Correspondingly differences between origins are mainly related to their
differences in stem growth
Lateral-Acceleration-Based Vehicle-Models-Blending for Automated Driving Controllers
Model-based trajectory tracking has become a widely used technique for automated driving system applications. A critical design decision is the proper selection of a vehicle model that achieves the best trade-off between real-time capability and robustness. Blending different types of vehicle models is a recent practice to increase the operating range of model-based trajectory tracking control applications. However, current approaches focus on the use of longitudinal speed as the blending parameter, with a formal procedure to tune and select its parameters still lacking. This work presents a novel approach based on lateral accelerations, along with a formal procedure and criteria to tune and select blending parameters, for its use on model-based predictive controllers for autonomous driving. An electric passenger bus traveling at different speeds over urban routes is proposed as a case study. Results demonstrate that the lateral acceleration, which is proportional to the lateral forces that differentiate kinematic and dynamic models, is a more appropriate model-switching enabler than the currently used longitudinal velocity. Moreover, the advanced procedure to define blending parameters is shown to be effective. Finally, a smooth blending method offers better tracking results versus sudden model switching ones and non-blending techniquesThis research was funded by AUTODRIVE within the Electronic Components and Systems for European Leadership Joint Undertaking (ECSEL JU) in collaboration with the European Union’s H2020 Framework Program (H2020/2014-2020) and National Authorities, under Grant No. 73746
Exchange interaction and its tuning in magnetic binary chalcogenides
Using a first-principles Green's function approach we study magnetic
properties of the magnetic binary chalcogenides Bi2Te3, Bi2Se3, and Sb2Te3. The
magnetic coupling between transition-metal impurities is long-range, extends
beyond a quintuple layer, and decreases with increasing number of d electrons
per 3d atom. We find two main mechanisms for the magnetic interaction in these
materials: the indirect exchange interaction mediated by free carriers and the
indirect interaction between magnetic moments via chalcogen atoms. The
calculated Curie temperatures of these systems are in good agreement with
available experimental data. Our results provide deep insight into magnetic
interactions in magnetic binary chalcogenides and open a way to design new
materials for promising applications
Enhancement of tribological behavior of rolling bearings by applying a multilayer ZrN/ZrCN coating
This paper focuses on the tribological behaviour of ZrN/ZrCN coating on bearing steel substrates DIN 17230, 100Cr6/1.3505. Coatings are applied at room temperature processes by means of Cathodic Arc Evaporation (CAE), a kind of Physical Vapor Deposition (PVD) technique. In order to achieve a satisfactory compromise between coating-substrate adhesion and the surface roughness requirement of the bearing rings, a polish post-processing is proposed. Different polish post-processing times and conditions are applied. The coated and polished bearing rings are tested under real friction torque test protocols. These tests show that the application of the coating does not entail a significant improvement in friction performance of the bearing. However, fatigue tests in real test bench are pending to evaluate the possible improvement in bearing life time
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