Recommended System for Optimizing Battery Energy Management with Floating Car Data

Atualmente, os veículos pesados que transportam mercadoria sensível à temperatura utilizam sistemas de refrigeração ruidosos e com elevado consumo de combustível. Para combater estas desvantagens, está a ser instalado um sistema capaz de recuperar e produzir energia elétrica durante as travagens e a partir de painéis fotovoltaicos. Esta energia é armazenada num conjunto de baterias para, posteriormente, alimentar o sistema frigorífico em modo elétrico. Adicionalmente, estão a ser recolhidos dados em tempo real sobre o comportamento do veículo e do sistema.Tendo em conta que toda a energia disponível durante a condução está condicionada por diversas variáveis de operação, é fulcral extrair conhecimento a partir da análise dos dados recolhidos, identificando padrões que possam otimizar a produção e gestão da energia preditivamente. Este processo de extração de conhecimento inclui seleção e avaliação dos dados a recolher, construção do modelo preditivo do sistema e estudo da sua aplicação. Assim sendo, num dado momento, tendo em conta não só as métricas recolhidas da viagem atual, mas também de dados históricos de um dado percurso, será possível ao sistema de gestão de energia instalado no camião decidir qual a melhor ação a tomar de forma a otimizar a energia produzida sem causar stress ao sistema.Nowadays, heavy vehicles that transport temperature-sensitive goods, generally use a fuel-needy dedicated diesel engine. Towards solving this problem, an energy management system (EMS) capable of producing energy on-board of the vehicle is being developed. This recovery is possible due to the regenerative braking (RB) functionality, which consists in converting kinetic energy to electrical energy during a slowdown. The recovered energy is then stored in a set of batteries that supplies the refrigeration system when needed, allowing it to run in electrical mode. Using data retrieved from the vehicle's operation and this management system, an opportunity towards intelligently using the regenerative braking functionality emerges. By introducing an intelligence layer on the energy management system, a decision on applying the RB functionality could be made based on the trip's energetic potential. This decision will optimize the battery usage and reduce the load and wear on the EMS components.In order to calculate the energetic potential of a certain route, an estimation of the road is needed. This document presents context information and different approaches towards this end. In the modeling approach recommended and implemented, a route is divided in several spatial segments and each segment is categorized among three pre-defined classes. A classification model is used to predict traffic historical data as input. By using this modeling approach based on travel times, information on traffic flow and intersection queues are incorporated and by calculating the most likely sequence of states, a estimation of the road ahead is made.Using the information of the modeled path, when the RB systems detects a situation where the functionality can be applied, a decision will be made by weighting the energetic potential of the path ahead and the energy need. When the algorithm sees fit, a higher torque may be applied to the generator, which will result in a larger quantity of energy recovered. Since this causes stress to the system, this functionality needs a robust intelligence layer

Synchronization and information transmission in networks

The amount of information produced by a network may be measured by the mutual information rate. This measure, the Kolmogorov-Sinai entropy and the synchronization interval are expressed in terms of the transversal Lyapunov exponents. Thus, these concepts are related and we proved that the larger the synchronization is, the larger the rate with which information is exchanged between nodes in the network. In fact, as the coupling parameter increases, the mutual information rate increases to a maximum at the synchronization interval and then decreases. Moreover, the Kolmogorov-Sinai entropy decreases until reaching a minimum at the synchronization interval and then increases. We present some numerical simulations considering two different versions of coupling two maps, a complete network and a lattice, which confirmed our theoretical results

Dynamical analysis in growth models: Blumberg’s equation

We present a new dynamical approach to the Blumberg's equation, a family of unimodal maps. These maps are proportional to Beta(p, q) probability densities functions. Using the symmetry of the Beta(p, q) distribution and symbolic dynamics techniques, a new concept of mirror symmetry is defined for this family of maps. The kneading theory is used to analyze the effect of such symmetry in the presented models. The main result proves that two mirror symmetric unimodal maps have the same topological entropy. Different population dynamics regimes are identified, when the intrinsic growth rate is modified: extinctions, stabilities, bifurcations, chaos and Allee effect. To illustrate our results, we present a numerical analysis, where are demonstrated: monotonicity of the topological entropy with the variation of the intrinsic growth rate, existence of isentropic sets in the parameters space and mirror symmetry

An Extension of Gompertzian Growth Dynamics Weibull and Frechet Models

In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus

Modeling Allee Effect from Beta(p, 2) Densities

In this work we develop and investigate generalized populational growth models, adjusted from Beta(p, 2) densities, with Allee effect. The use of a positive parameter leads the presented generalization, which yields some more flexible models with variable extinction rates. An Allee limit is incorporated so that the models under study have strong Allee effect

Synchronization in Von Bertalanffy’s models

Many data have been useful to describe the growth of marine mammals, invertebrates and reptiles, seabirds, sea turtles and fishes, using the logistic, the Gom-pertz and von Bertalanffy's growth models. A generalized family of von Bertalanffy's maps, which is proportional to the right hand side of von Bertalanffy's growth equation, is studied and its dynamical approach is proposed. The system complexity is measured using Lyapunov exponents, which depend on two biological parameters: von Bertalanffy's growth rate constant and the asymptotic weight. Applications of synchronization in real world is of current interest. The behavior of birds ocks, schools of fish and other animals is an important phenomenon characterized by synchronized motion of individuals. In this work, we consider networks having in each node a von Bertalanffy's model and we study the synchronization interval of these networks, as a function of those two biological parameters. Numerical simulation are also presented to support our approaches

Toplological Entropy in the Syncronization of Piecewise Linear and Monotone Maps. Coupled Duffing Oscillators

In this paper is presented a relationship between the synchronization and the topological entropy. We obtain the values for the coupling parameter, in terms of the topological entropy, to achieve synchronization of two unidirectional and bidirectional coupled piecewise linear maps. In addition, we prove a result that relates the synchronizability of two m-modal maps with the synchronizability of two conjugated piecewise linear maps. An application to the unidirectional and bidirectional coupled identical chaotic Duffing equations is given. We discuss the complete synchronization of two identical double-well Duffing oscillators, from the point of view of symbolic dynamics. Working with Poincare cross-sections and the return maps associated, the synchronization of the two oscillators, in terms of the coupling strength, is characterized

An extended isogeometric boundary element formulation for three-dimensional linear elastic fracture mechanics

This paper presents a novel extended isogeometric boundary element formulation (XIGABEM) for three-dimensional linear elastic fracture mechanics. The formulation utilises the Dual BEM to accommodate coincident geometries for opposing crack surfaces, and inherits the well-known advantages of the NURBS basis as other isogeometric implementations. The originality herein involves the extension of the above-mentioned scheme to 3D using enrichment functions derived from asymptotic solutions for near-field crack tip displacements, in which Williams’ expansions are used on the crack surfaces and on the boundaries crossed by the crack front. Besides, Heaviside functions enrich external boundaries and allow the displacement discontinuity modelling. As with most enriched formulations, additional degrees of freedom are introduced; novel strategies are presented for the generation of auxiliary equations to recover a square system. Another key element of the proposed scheme is that the stress intensity factors are recovered directly from the solution vector and no post processing is required. Four applications demonstrate the formulation robustness, with results of models having comparatively few degrees of freedom comparing well against classical and other published results

Dynamical behaviour on the parameter space: new populational growth models proportional to beta densities

We present new populational growth models, generalized logistic models which are proportional to beta densities with shape parameters p and 2, where p > 1, with Malthusian parameter r. The complex dynamical behaviour of these models is investigated in the parameter space (r, p), in terms of topological entropy, using explicit methods, when the Malthusian parameter r increases. This parameter space is split into different regions, according to the chaotic behaviour of the models