Battery Aging-Aware Online Optimal Control: An Energy Management System for Hybrid Electric Vehicles Supported by a Bio-Inspired Velocity Prediction

In this manuscript, we address the problem of online optimal control for torque splitting in hybrid electric vehicles that minimises fuel consumption and preserves battery life. We divide the problem into the prediction of the future velocity profile (i.e. driver intention estimation) and the online optimal control of the hybrid powertrain following a Model Predictive Control (MPC) scheme. The velocity prediction is based on a bio-inspired driver model, which is compared on various datasets with two alternative prediction algorithms adopted in the literature. The online optimal control problem addresses both the fuel consumption and the preservation of the battery life using an equivalent cost given the estimated speed profile (i.e. guaranteeing the desired performance). The battery degradation is evaluated by means of a state-of-the-art electrochemical model. Both the predictor and the Energy Management System (EMS) are evaluated in simulation using real driving data divided into 30 driving cycles from 10 drivers characterised by different driving styles. A comparison of the EMS performances is carried out on two different benchmarks based on an offline optimization, in one case on the entire dataset length and in the second on an ideal prediction using two different receding horizon lengths. The proposed online system, composed of the velocity prediction algorithm and the optimal control MPC scheme, shows comparable performances with the previous ideal benchmarks in terms of fuel consumption and battery life preservation. The simulations show that the online approach is able to significantly reduce the capacity loss of the battery, while preserving the fuel saving performances

Performance Evaluation of end-to-end security protocols in an Internet of Things

Wireless Sensor Networks are destined to play a fundamental role in the next-generation Internet, which will be characterized by the Machine-to-Machine paradigm, according to which, embedded devices will actively exchange information, thus enabling the development of innovative applications. It will contribute to assert the concept of Internet of Things, where end-to-end security represents a key issue. In such context, it is very important to understand which protocols are able to provide the right level of security without burdening the limited resources of constrained networks. This paper presents a performance comparison between two of the most widely used security protocols: IPSec and DTLS. We provide the analysis of their impact on the resources of embedded devices. For this purpose, we have modified existing implementations of both protocols to make them properly run on our hardware platforms, and we have performed an extensive experimental evaluation study. The achieved results are not a consequence of a classical simulation campaign, but they have been obtained in a real scenario that uses software and hardware typical of the current technological developments. Therefore, they can help network designers to identify the most appropriate secure mechanism for end-to-end IP communications involving constrained devices

High Risk of Secondary Infections Following Thrombotic Complications in Patients With COVID-19

Background. This study’s primary aim was to evaluate the impact of thrombotic complications on the development of secondary infections. The secondary aim was to compare the etiology of secondary infections in patients with and without thrombotic complications. Methods. This was a cohort study (NCT04318366) of coronavirus disease 2019 (COVID-19) patients hospitalized at IRCCS San Raffaele Hospital between February 25 and June 30, 2020. Incidence rates (IRs) were calculated by univariable Poisson regression as the number of cases per 1000 person-days of follow-up (PDFU) with 95% confidence intervals. The cumulative incidence functions of secondary infections according to thrombotic complications were compared with Gray’s method accounting for competing risk of death. A multivariable Fine-Gray model was applied to assess factors associated with risk of secondary infections. Results. Overall, 109/904 patients had 176 secondary infections (IR, 10.0; 95% CI, 8.8–11.5; per 1000-PDFU). The IRs of secondary infections among patients with or without thrombotic complications were 15.0 (95% CI, 10.7–21.0) and 9.3 (95% CI, 7.9–11.0) per 1000-PDFU, respectively (P = .017). At multivariable analysis, thrombotic complications were associated with the development of secondary infections (subdistribution hazard ratio, 1.788; 95% CI, 1.018–3.140; P = .043). The etiology of secondary infections was similar in patients with and without thrombotic complications. Conclusions. In patients with COVID-19, thrombotic complications were associated with a high risk of secondary infections

Performance Assessment in Fingerprinting and Multi Component Quantitative NMR Analyses

An interlaboratory comparison (ILC) was organized with the aim to set up quality control indicators suitable for multicomponent quantitative analysis by nuclear magnetic resonance (NMR) spectroscopy. A total of 36 NMR data sets (corresponding to 1260 NMR spectra) were produced by 30 participants using 34 NMR spectrometers. The calibration line method was chosen for the quantification of a five-component model mixture. Results show that quantitative NMR is a robust quantification tool and that 26 out of 36 data sets resulted in statistically equivalent calibration lines for all considered NMR signals. The performance of each laboratory was assessed by means of a new performance index (named Qp-score) which is related to the difference between the experimental and the consensus values of the slope of the calibration lines. Laboratories endowed with a Qp-score falling within the suitable acceptability range are qualified to produce NMR spectra that can be considered statistically equivalent in terms of relative intensities of the signals. In addition, the specific response of nuclei to the experimental excitation/relaxation conditions was addressed by means of the parameter named NR. NR is related to the difference between the theoretical and the consensus slopes of the calibration lines and is specific for each signal produced by a well-defined set of acquisition parameters

A kinematic observer with adaptive dead-zone for vehicles lateral velocity estimation

International audienceIn this paper we tailor the dead-zone based mechanism presented in [3] to the well-known kinematic observer for the estimation of vehicle lateral velocity. We extend the previous results on the dead-zone observer to linear parameter varying systems. The proposed mechanism maintains the structure of the kinematic observer but inserts an adaptive dead-zone at the output injection term. This dead-zone mechanism partially "cuts" the noise and increases the noise rejection performance allowing for the selection of a larger observer gain. We use this freedom to increase the observer gain to attenuate constant bias errors in the acceleration measurements. The proposed solution is easy to implement and requires only measurements acquired from standard on-board sensors. The adaptation parameters are selected solving a suitable Linear Matrix Inequality (LMI), and no manual tuning is required. We show the effectiveness of the proposed solution through numerical simulations

A Decoupling Scheme for Force Control in Cooperative Multi-Robot Manipulation Tasks

International audienceThe internal forces and torques arising in cooperative manipulators ensembles are the grasp forces/torques and it is obviously desirable to control them. We present a novel approach that describes the internal loading as the interaction forces/torques arising in a multi-body system formed by multiple manipulators that behave like a formation of robots. We show that these quantities belong to the null space of the grasp matrix, thus they do not affect the dynamics of the object. The main contribution of this paper is a decoupling control scheme for tracking the internal and the motion-inducing forces and torques in a physically consistent way. The scheme is based on a physically and mathematically consistent model of the dynamics of the constrained interaction

Load-Deflection Behavior of RF-MEMS Switches: FEA and Analytical Modeling for Prediction of Mechanical Properties

SixNy/a-Si/SixNy thin film RF-MEMS switches were fabricated by unconventional PECVD process using surface micromachining approach. The mechanical properties of tri-layer were measured by nanoindentation and wafer curvature method. Deflections of switches clamped on two opposite edges were measured by a profilometer applying increasing quasi-point pressure loads. Finite Element Analysis (FEA) was used to study the mechanical behavior of clamped-clamped switches. An analytical solution was developed and validated, numerically and experimentally, to describe the load-deflection response of perforated membranes to quasi-point loads. The proposed function was used to determine the internal stress of the investigated membranes; the relative error between the predicted and calculated stress values was in the range 2.1–8.5%

Approximate Mechanical Properties of Clamped–Clamped Perforated Membranes From In-Situ Deflection Measurements Using a Stylus Profiler

Surface micromachined membranes such as RF-MEMS switches are widely adopted in the field of telecommunication devices and represent nowadays the lowest loss devices for switching and routing RF signals. The knowledge of specific properties of structural materials is crucial for a reliable design of devices with optimized performance. Material properties, like Young's modulus and stress, strongly determine the mechanical behavior of MEMS devices. In this paper, Si x N y /a-Si/Si x N y thin film membranes, of different sizes and porosities, were fabricated by unconventional low temperature PECVD, using surface micromachining approach. The tri-layer was characterized by nanoindentation and stress measurements based on wafer curvature method. On the possibility to extract mechanical properties from deflection measurements, to the best of our knowledge, literature seems to lack of analytical solutions of the nonlinear large deflection problem of such membranes. Finite element analysis was used to model the load-deflection response of double-clamped membranes, in agreement with measured data. An approximate empirical function was proposed and validated, for describing the maximum deflection under quasi-point loads. The function was used to determine the stress of the investigated membranes; the relative error between predicted and calculated stress values was in the range 2.1%-8.5% for membranes with lower porosity