Modelling and Optimization of Energy Management Strategies for Hybrid Vehicles

In the last decades the automotive sector has seen a technological revolution, due mainly to the more restrictive regulation, the newly introduced technologies and, as last, to the poor resources of fossil fuels remaining on Earth. Promising solution in vehicles’ propulsion are represented by alternative architectures and energy sources, for example fuel-cells and pure electric vehicles. The automotive transition to new and green vehicles is passing through the development of hybrid vehicles, that usually combine positive aspects of each technology. To fully exploit the powerful of hybrid vehicles, however, it is important to manage the powertrain’s degrees of freedom in the smartest way possible, otherwise hybridization would be worthless. To this aim, this dissertation is focused on the development of energy management strategies and predictive control functions. Such algorithms have the goal of increasing the powertrain overall efficiency and contextually increasing the driver safety. Such control algorithms have been applied to an axle-split Plug-in Hybrid Electric Vehicle with a complex architecture that allows more than one driving modes, including the pure electric one. The different energy management strategies investigated are mainly three: the vehicle baseline heuristic controller, in the following mentioned as rule-based controller, a sub-optimal controller that can include also predictive functionalities, referred to as Equivalent Consumption Minimization Strategy, and a vehicle global optimum control technique, called Dynamic Programming, also including the high-voltage battery thermal management. During this project, different modelling approaches have been applied to the powertrain, including Hardware-in-the-loop, and diverse powertrain high-level controllers have been developed and implemented, increasing at each step their complexity. It has been proven the potential of using sophisticated powertrain control techniques, and that the gainable benefits in terms of fuel economy are largely influenced by the chose energy management strategy, even considering the powerful vehicle investigated.

Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of the global warming. In this context, the transportation sector plays a vital role, since it is responsible for a large part of carbon dioxide production. In order to address these issues, the present thesis deals with the development of advanced control strategies for the energy efficiency optimization of plug-in hybrid electric vehicles (PHEVs), supported by the prediction of future working conditions of the powertrain. In particular, a Dynamic Programming algorithm has been developed for the combined optimization of vehicle energy and battery thermal management. At this aim, the battery temperature and the battery cooling circuit control signal have been considered as an additional state and control variables, respectively. Moreover, an adaptive equivalent consumption minimization strategy (A-ECMS) has been modified to handle zero-emission zones, where engine propulsion is not allowed. Navigation data represent an essential element in the achievement of these tasks. With this aim, a novel simulation and testing environment has been developed during the PhD research activity, as an effective tool to retrieve routing information from map service providers via vehicle-to-everything connectivity. Comparisons between the developed and the reference strategies are made, as well, in order to assess their impact on the vehicle energy consumption. All the activities presented in this doctoral dissertation have been carried out at the Green Mobility Research Lab} (GMRL), a research center resulting from the partnership between the University of Bologna and FEV Italia s.r.l., which represents the industrial partner of the research project.

Study of materials and interphases for electrochemical energy storage from renewable sources

Batteries should be refined depending on their application for a future in which the sustainable energy demand increases. On the one hand, it is fundamental to improve their safety, prevent failures, increase energy density, and reduce production costs. On the other hand, new battery materials and architecture are required to satisfy the growing demand. This thesis explores different electrochemical energy storage systems and new methodologies to investigate complex and dynamic processes. Lithium-ion batteries are described in all their cell components. In these systems, this thesis investigates negative electrodes. Both the development of new sustainable materials and new in situ electrode characterization methods were explored. One strategy to achieve high-energy systems is employing lithium metal anodes. In this framework, ammonium hexafluorophosphate is demonstrated to be a suitable additive for stabilizing the interphase and preventing uncontrolled dendritic deposition. Deposition/stripping cycles, electrochemical impedance spectroscopy, in situ optical microscopy, and operando confocal Raman spectroscopy have been used to study lithium metal-electrolyte interphase in the presence of the additive. Redox Flow Batteries (RFBs) are proposed as a sustainable alternative for stationary applications. An all-copper aqueous RFB (CuRFB) has been studied in all its aspects. For the electrolyte optimization, spectro-electrochemical tests in diluted solution have been used to get information on the electrolyte’s electrochemical behaviour with different copper complexes distributions. In concentrated solutions, the effects of copper-to-ligand ratios, the concentration, and the counter-ion of the complexing agent were evaluated. Electrode thermal treatment was optimized, finding a compromise between the electrochemical performance and the carbon footprint. On the membrane side, a new method for permeability studies was designed using scanning electrochemical microscopy (SECM). The Cu(II) permeability of several membranes was tested, obtaining direct visualization of Cu(II) concentration in space. Also, two spectrophotometric approaches were designed for SoC monitoring systems for negative and positive half-cells.

Non-thermal phenomena in galaxy clusters: the LOFAR revolution

Turbulence introduced into the intra-cluster medium (ICM) through cluster merger events transfers energy to non-thermal components (relativistic particles and magnetic fields) and can trigger the formation of diffuse synchrotron radio sources. Owing to their steep synchrotron spectral index, such diffuse sources can be better studied at low radio frequencies. In this respect, the LOw Frequency ARray (LOFAR) is revolutionizing our knowledge thanks to its unprecedented resolution and sensitivity below 200 MHz. In this Thesis we focus on the study of radio halos (RHs) by using LOFAR data. In the first part of this work we analyzed the largest-ever sample of galaxy clusters observed at radio frequencies. This includes 309 Planck clusters from the Second Data Release of the LOFAR Two Metre Sky Survey (LoTSS-DR2), which span previously unexplored ranges of mass and redshift. We detected 83 RHs, half of which being new discoveries. In 140 clusters we lack a detected RH; for this sub-sample we developed new techniques to derive upper limits to their radio powers. By comparing detections and upper limits, we carried out the first statistical analysis of populations of clusters observed at low frequencies and tested theoretical formation models. In the second part of this Thesis we focused on ultra-steep spectrum radio halos. These sources are almost undetected at GHz frequencies, but are thought to be common at low frequencies. We presented LOFAR observations of two interesting clusters hosting ultra-steep spectrum radio halos. With complementary radio and X-ray observations we constrained the properties and origin of these targets.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

“Study of Electro-thermal Effects on PLA Materials Fed with AC Currents”

Given the rise in the emergence of new composite materials, their multifunctional properties, and possible applications in simple and complex structural components, there has been a need to unravel the characterization of these materials. The possibility of printing these conductive composite materials has opened a new area in the design of structural components which can conduct, transmit, and modulate electric signals with no limitation from complex geometry. Although several works have researched the behaviour of polymeric composites due to the immediate growth, however, the electrothermal behaviour of the material when subjected to varying AC applied voltage (Joule’s effect) has not been thoroughly researched. This study presents the characterization of the electrothermal behaviour of conductive composites of a polylactic acid matrix reinforced with conductive carbon black particles (CB-PLA). An understanding of this behaviour would contribute to the improved work in additive manufacturing of functional electro-mechanical conductive materials with potential application in energy systems, bioelectronics, etc. In this study, the electrothermal interplay is monitored under applied AC voltage, varying lengths, and filament printing orientations (longitudinal, oblique, and transverse). Each sample was printed using the fused deposition modeling technique such that each specimen has three different lengths (1L, 2L, 2.75L). To this end, deductions were made on properties that affect composite’s efficiency and life expectancy. The result of this study shows a great influence of printing orientation on material properties of 3D printed conductive composites of CB-PLA. The result also identifies the contribution of AC applied voltage to composites' stabilization time. This knowledge is important to provide experimental background for components' electrothermal interplay, estimate possible degradation and operating limits of composite structures when used in applications.

Beam-energy Dependence Of The Directed Flow Of Protons, Antiprotons, And Pions In Au+au Collisions.

Rapidity-odd directed flow (v1) measurements for charged pions, protons, and antiprotons near midrapidity (y=0) are reported in sNN=7.7, 11.5, 19.6, 27, 39, 62.4, and 200 GeV Au+Au collisions as recorded by the STAR detector at the Relativistic Heavy Ion Collider. At intermediate impact parameters, the proton and net-proton slope parameter dv1/dy|y=0 shows a minimum between 11.5 and 19.6 GeV. In addition, the net-proton dv1/dy|y=0 changes sign twice between 7.7 and 39 GeV. The proton and net-proton results qualitatively resemble predictions of a hydrodynamic model with a first-order phase transition from hadronic matter to deconfined matter, and differ from hadronic transport calculations.

Yellowing And Bleaching Of Grey Hair Caused By Photo And Thermal Degradation.

Yellowing is an undesirable phenomenon that is common in people with white and grey hair. Because white hair has no melanin, the pigment responsible for hair colour, the effects of photodegradation are more visible in this type of hair. The origin of yellowing and its relation to photodegradation processes are not properly established, and many questions remain open in this field. In this work, the photodegradation of grey hair was investigated as a function of the wavelength of incident radiation, and its ultrastructure was determined, always comparing the results obtained for the white and black fibres present in grey hair with the results of white wool. The results presented herein indicate that the photobehaviour of grey hair irradiated with a mercury lamp or with solar radiation is dependent on the wavelength range of the incident radiation and on the initial shade of yellow in the sample. Two types of grey hair were used: (1) blended grey hair (more yellow) and (2) grey hair from a single-donor (less yellow). After exposure to a full-spectrum mercury lamp for 200 h, the blended white hair turned less yellow (the yellow-blue difference, Db(*) becomes negative, Db(*)=-6), whereas the white hair from the single-donor turned slightly yellower (Db(*)=2). In contrast, VIS+IR irradiation resulted in bleaching in both types of hair, whereas a thermal treatment (at 81 °C) caused yellowing of both types of hair, resulting in a Db(*)=3 for blended white hair and Db(*)=9 for single-donor hair. The identity of the yellow chromophores was investigated by UV-Vis spectroscopy. The results obtained with this technique were contradictory, however, and it was not possible to obtain a simple correlation between the sample shade of yellow and the absorption spectra. In addition, the results are discussed in terms of the morphology differences between the pigmented and non-pigmented parts of grey hair, the yellowing and bleaching effects of grey hair, and the occurrence of dark-follow reactions.

Hypothalamic Inflammation And The Central Nervous System Control Of Energy Homeostasis.

The control of energy homeostasis relies on robust neuronal circuits that regulate food intake and energy expenditure. Although the physiology of these circuits is well understood, the molecular and cellular response of this program to chronic diseases is still largely unclear. Hypothalamic inflammation has emerged as a major driver of energy homeostasis dysfunction in both obesity and anorexia. Importantly, this inflammation disrupts the action of metabolic signals promoting anabolism or supporting catabolism. In this review, we address the evidence that favors hypothalamic inflammation as a factor that resets energy homeostasis in pathological states.

Beam-energy Dependence Of Charge Separation Along The Magnetic Field In Au+au Collisions At Rhic.

Local parity-odd domains are theorized to form inside a quark-gluon plasma which has been produced in high-energy heavy-ion collisions. The local parity-odd domains manifest themselves as charge separation along the magnetic field axis via the chiral magnetic effect. The experimental observation of charge separation has previously been reported for heavy-ion collisions at the top RHIC energies. In this Letter, we present the results of the beam-energy dependence of the charge correlations in Au+Au collisions at midrapidity for center-of-mass energies of 7.7, 11.5, 19.6, 27, 39, and 62.4 GeV from the STAR experiment. After background subtraction, the signal gradually reduces with decreased beam energy and tends to vanish by 7.7 GeV. This implies the dominance of hadronic interactions over partonic ones at lower collision energies.

Rapidly Switching Multidirectional Defibrillation: Reversal Of Ventricular Fibrillation With Lower Energy Shocks.

Cardiac arrest after open surgery has an incidence of approximately 3%, of which more than 50% of the cases are due to ventricular fibrillation. Electrical defibrillation is the most effective therapy for terminating cardiac arrhythmias associated with unstable hemodynamics. The excitation threshold of myocardial microstructures is lower when external electrical fields are applied in the longitudinal direction with respect to the major axis of cells. However, in the heart, cell bundles are disposed in several directions. Improved myocardial excitation and defibrillation have been achieved by applying shocks in multiple directions via intracardiac leads, but the results are controversial when the electrodes are not located within the cardiac chambers. This study was designed to test whether rapidly switching shock delivery in 3 directions could increase the efficiency of direct defibrillation. A multidirectional defibrillator and paddles bearing 3 electrodes each were developed and used in vivo for the reversal of electrically induced ventricular fibrillation in an anesthetized open-chest swine model. Direct defibrillation was performed by unidirectional and multidirectional shocks applied in an alternating fashion. Survival analysis was used to estimate the relationship between the probability of defibrillation and the shock energy. Compared with shock delivery in a single direction in the same animal population, the shock energy required for multidirectional defibrillation was 20% to 30% lower (P < .05) within a wide range of success probabilities. Rapidly switching multidirectional shock delivery required lower shock energy for ventricular fibrillation termination and may be a safer alternative for restoring cardiac sinus rhythm.

Beam Energy Dependence Of Moments Of The Net-charge Multiplicity Distributions In Au+au Collisions At Rhic.

We report the first measurements of the moments--mean (M), variance (σ(2)), skewness (S), and kurtosis (κ)--of the net-charge multiplicity distributions at midrapidity in Au+Au collisions at seven energies, ranging from sqrt[sNN]=7.7 to 200 GeV, as a part of the Beam Energy Scan program at RHIC. The moments are related to the thermodynamic susceptibilities of net charge, and are sensitive to the location of the QCD critical point. We compare the products of the moments, σ(2)/M, Sσ, and κσ(2), with the expectations from Poisson and negative binomial distributions (NBDs). The Sσ values deviate from the Poisson baseline and are close to the NBD baseline, while the κσ(2) values tend to lie between the two. Within the present uncertainties, our data do not show nonmonotonic behavior as a function of collision energy. These measurements provide a valuable tool to extract the freeze-out parameters in heavy-ion collisions by comparing with theoretical models.

Remediation Of 17-α-ethinylestradiol Aqueous Solution By Photocatalysis And Electrochemically-assisted Photocatalysis Using Tio2 And Tio2/wo3 Electrodes Irradiated By A Solar Simulator.

TiO2 and TiO2/WO3 electrodes, irradiated by a solar simulator in configurations for heterogeneous photocatalysis (HP) and electrochemically-assisted HP (EHP), were used to remediate aqueous solutions containing 10 mg L(-1) (34 μmol L(-1)) of 17-α-ethinylestradiol (EE2), active component of most oral contraceptives. The photocatalysts consisted of 4.5 μm thick porous films of TiO2 and TiO2/WO3 (molar ratio W/Ti of 12%) deposited on transparent electrodes from aqueous suspensions of TiO2 particles and WO3 precursors, followed by thermal treatment at 450 (°)C. First, an energy diagram was organized with photoelectrochemical and UV-Vis absorption spectroscopy data and revealed that EE2 could be directly oxidized by the photogenerated holes at the semiconductor surfaces, considering the relative HOMO level for EE2 and the semiconductor valence band edges. Also, for the irradiated hybrid photocatalyst, electrons in TiO2 should be transferred to WO3 conduction band, while holes move toward TiO2 valence band, improving charge separation. The remediated EE2 solutions were analyzed by fluorescence, HPLC and total organic carbon measurements. As expected from the energy diagram, both photocatalysts promoted the EE2 oxidation in HP configuration; after 4 h, the EE2 concentration decayed to 6.2 mg L(-1) (35% of EE2 removal) with irradiated TiO2 while TiO2/WO3 electrode resulted in 45% EE2 removal. A higher performance was achieved in EHP systems, when a Pt wire was introduced as a counter-electrode and the photoelectrodes were biased at +0.7 V; then, the EE2 removal corresponded to 48 and 54% for the TiO2 and TiO2/WO3, respectively. The hybrid TiO2/WO3, when compared to TiO2 electrode, exhibited enhanced sunlight harvesting and improved separation of photogenerated charge carriers, resulting in higher performance for removing this contaminant of emerging concern from aqueous solution.

Hypothalamic S1p/s1pr1 Axis Controls Energy Homeostasis.

Sphingosine 1-phosphate receptor 1 (S1PR1) is a G-protein-coupled receptor for sphingosine-1-phosphate (S1P) that has a role in many physiological and pathophysiological processes. Here we show that the S1P/S1PR1 signalling pathway in hypothalamic neurons regulates energy homeostasis in rodents. We demonstrate that S1PR1 protein is highly enriched in hypothalamic POMC neurons of rats. Intracerebroventricular injections of the bioactive lipid, S1P, reduce food consumption and increase rat energy expenditure through persistent activation of STAT3 and the melanocortin system. Similarly, the selective disruption of hypothalamic S1PR1 increases food intake and reduces the respiratory exchange ratio. We further show that STAT3 controls S1PR1 expression in neurons via a positive feedback mechanism. Interestingly, several models of obesity and cancer anorexia display an imbalance of hypothalamic S1P/S1PR1/STAT3 axis, whereas pharmacological intervention ameliorates these phenotypes. Taken together, our data demonstrate that the neuronal S1P/S1PR1/STAT3 signalling axis plays a critical role in the control of energy homeostasis in rats.

Draft Genome Sequence Of Ft9, A Novel Bacillus Cereus Strain Isolated From A Brazilian Thermal Spring.

A Bacillus cereus strain, FT9, isolated from a hot spring in the midwest region of Brazil, had its entire genome sequenced.