Energy management system optimization based on an LSTM deep learning model using vehicle speed prediction

The energy management of a Hybrid Electric Vehicle (HEV) is a global optimization problem, and its optimal solution inevitably entails knowing the entire mission profile. The exploitation of Vehicle-to-Everything (V2X) connectivity can pave the way for reliable short-term vehicle speed predictions. As a result, the capabilities of conventional energy management strategies can be enhanced by integrating the predicted vehicle speed into the powertrain control strategy. Therefore, in this paper, an innovative Adaptation algorithm uses the predicted speed profile for an Equivalent Consumption Minimization Strategy (A-V2X-ECMS). Driving pattern identification is employed to adapt the equivalence factor of the ECMS when a change in the driving patterns occurs, or when the State of Charge (SoC) experiences a high deviation from the target value. A Principal Component Analysis (PCA) was performed on several energetic indices to select the ones that predominate in characterizing the different driving patterns. Long Short-Term Memory (LSTM) deep neural networks were trained to choose the optimal value of the equivalence factor for a specific sequence of data (i.e., speed, acceleration, power, and initial SoC). The potentialities of the innovative A-V2X-ECMS were assessed, through numerical simulation, on a diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. A virtual test rig of the investigated vehicle was built in the GT-SUITE software environment and validated against a wide database of experimental data. The simulations proved that the proposed approach achieves results much closer to optimal than the conventional energy management strategies taken as a reference

A hydrodynamic model arising in the context of granular media

AbstractIn this note, we propose a formal argument identifying the hydrodynamic limit of a Fokker-Planck model for granular media appearing in [1]. More precisely, in the limit of large background temperature and vanishing friction, this hydrodynamic limit is described by the classical system of isentropic gas dynamics with a nonstandard pressure law (specifically, the pressure is proportional to the cube root of the density). Finally, some qualitative properties of the hydrodynamic model are studied

The nonlinear diffusion limit for generalized Carleman models: the initial-boundary value problem

Consider the initial-boundary value problem for the 2-speed Carleman model of the Boltzmann equation of the kinetic theory of gases set in some bounded interval with boundary conditions prescribing the density of particles entering the interval. Under the usual parabolic scaling, a nonlinear diffusion limit is established for this problem. In fact, the techniques presented here allow treating generalizations of the Carleman system where the collision frequency is proportional to some power of the macroscopic density, with exponent in [-1,1]

Life Cycle Assessment of a Lithium-Ion Battery Pack Unit Made of Cylindrical Cells

Saving energy is a fundamental topic considering the growing energy requirements with respect to energy availability. Many studies have been devoted to this question, and life cycle assessment (LCA) is increasingly acquiring importance in several fields as an effective way to evaluate the energy demand and the emissions associated with products’ life cycles. In this work, an LCA analysis of an existent lithium-ion battery pack (BP) unit is presented with the aim to increase awareness about its consumption and offering alternative production solutions that are less energy intensive. Exploiting the literature data about cradle-to-grave and cradle-to-gate investigations, and after establishing reasonable approximations, the main BP sub-elements were considered for this study, such as the plastic cells support, the Li-ion cells brick, the PCBs for a battery management system (BMS), the liquid-based battery thermal management system (BTMS) and the BP container. For each of these components, the impacts of the extraction, processing, assembly, and transportation of raw materials are estimated and the partial and total values of the energy demand (ED) and global warming potential (GWP) are determined. The final interpretation of the results allows one to understand the important role played by LCA evaluations and presents other possible ways of reducing the energy consumption and (Formula presented.) emissions

A Methodology for the Reverse Engineering of the Energy Management Strategy of a Plug -In Hybrid Electric Vehicle for Virtual Test Rig Development

Nowadays, the need for more sustainable mobility is fostering powertrain electrification as a way of reducing the carbon footprint of conventional vehicles. On the other side, the presence of multiple energy sources significantly increases the powertrain complexity and requires the development of a suitable Energy Management System (EMS) whose performance can strongly affect the fuel economy potential of the vehicle. In such a framework, this article proposes a novel methodology to reverse engineer the control strategy of a test case P2 Plug-in Hybrid Electric Vehicle (PHEV) through the analysis of experimental data acquired in a wide range of driving conditions. In particular, a combination of data obtained from On-Board Diagnostic system (OBD), Controller Area Network (CAN)-bus protocol, and additional sensors installed on the High Voltage (HV) electric net of the vehicle is used to point out any dependency of the EMS decisions on the powertrain main operating variables. Furthermore, the impact that Vehicle-to-Infrastructure (V2I) connections have on the control law is assessed on several tests performing the same real-world route with the vehicle navigation system alternatively switched on and off. Finally, a virtual test rig of the tested vehicle, developed in the GT- SUITE environment, is used to validate the set of extracted rules against the experimental data. An error of about 1-2% on the prediction of the vehicle CO2 emissions and good matching of the State of Charge (SoC) profile in both Charge Depleting (CD) and Charge Sustaining (CS) phases prove the effectiveness of the proposed methodology

Integrating physical and topographic information into a fuzzy scheme to map flooded area by SAR

A flood mapping procedure based on a fuzzy sets theory has been developed. The method is based on the integration of Synthetic Aperture Radar (SAR) measurements with additional data on the inundated area, such as a land cover map and a digital elevation model (DEM). The information on land cover has allowed us to account for both specular reflection, typical of open water, and double bounce backscattering, typical of forested and urban areas. DEM has been exploited to include simple hydraulic considerations on the dependence of inundation probability on surface characteristics. Contextual information has been taken into account too. The proposed algorithm has been tested on a flood occurred in Italy on November 1994. A pair of ERS-1 images, collected before and after (three days later) the flood, has been used. The results have been compared with the data provided by a ground survey carried out when the flood reached its maximum extension. Despite the temporal mismatch between the survey and the post-inundation SAR image, the comparison has yielded encouraging results, with the 87% of the pixels correctly classified as inundated

Appropriate lung management in patients with primary antibody deficiencies

Introduction: Human primary immunodeficiency diseases (PIDs) include a broad spectrum of more than 350 disorders, involving different branches of the immune system and classified as 'rare diseases.' Predominantly antibody deficiencies (PADs) represent more than half of the PIDs diagnosed in Europe and are often diagnosed in the adulthood. Areas covered: Although PAD could first present with autoimmune or neoplastic features, respiratory infections are frequent and respiratory disease represents a relevant cause of morbidity and mortality. Pulmonary complications may be classified as infection-related (acute and chronic), immune-mediated, and neoplastic. Expert opinion: At present, no consensus guidelines are available on how to monitor and manage lung complications in PAD patients. In this review, we will discuss the available diagnostic, prognostic and therapeutic instruments and we will suggest an appropriate and evidence-based approach to lung diseases in primary antibody deficiencies. We will also highlight the possible role of promising new tools and strategies in the management of pulmonary complications. However, future studies are needed to reduce of diagnostic delay of PAD and to better understand lung diseases mechanisms, with the final aim to ameliorate therapeutic options that will have a strong impact on Quality of Life and long-term prognosis of PAD patients

2-D constrained Navier-Stokes equation and intermediate asymptotics

We introduce a modified version of the two-dimensional Navier-Stokes equation, preserving energy and momentum of inertia, which is motivated by the occurrence of different dissipation time scales and related to the gradient flow structure of the 2-D Navier-Stokes equation. The hope is to understand intermediate asymptotics. The analysis we present here is purely formal. A rigorous study of this equation will be done in a forthcoming paper

Identification of the K*± resonance decay by topological cuts and multivariate discrimination methods

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