STATE OF CHARGE BALANCING DROOP CONTROL

This thesis presents a load sharing method applied in a distributed micro grid system. The goal of this method is to balance the state-of-charge (SoC) of each parallel connected battery and make it possible to detect the average SoC of the system by measuring bus voltage for all connected modules. In this method the reference voltage for each battery converter is adjusted by adding a proportional SoC factor. Under such setting the battery with a higher SoC will output more power, whereas the one with lower SoC gives out less. Therefore the higher SoC battery will use its energy faster than the lower ones, and eventually the SoC and output power of each battery will converge. And because the reference voltage is related to SoC status, the information of the average SoC in this system could be shared for all modules by measuring bus voltage. The SoC balancing speed is related to the SoC droop factors. This SoC-based load sharing control system is analyzed in feasibility and stability. Simulations in MATLAB/Simulink are presented, which indicate that this control scheme could balance the battery SoCs as predicted. The observation of SoC sharing through bus voltage was validated in both software simulation and hardware experiments. It could be of use to non-communicated distributed power system in load shedding and power planning.

A NOVEL MODELING AND STATE OF CHARGE ESTIMATION SCHEME FOR LITHIUM-ION BATTERIES

Lithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.

Analisi energetica al variare dello state of charge di propulsori ibridi e plug-in operanti nel ciclo WLTP con propulsore termico a punto fisso stechiometrico

Il presente lavoro propone la stesura di un codice in ambiente MATLAB per l'analisi energetica di powertrain ibridi operanti nel ciclo WLTP con il particolare funzionamento del motore termico benzina a punto fisso stechiometrico. Nello specifico, il codice prende dei dati in input tramite un'interfaccia grafica ed avvia una simulazione, i cui risultati principali corrispondono ad emissioni di anidride carbonica per chilometro percorso ed ai chilometri percorsi con un litro di carburante. Queste sono le due grandezze che questo lavoro si prefigge di ottimizzare, dalle quali proviene la scelta del particolare funzionamento del motore termico. Sono state implementate due differenti strategie di controllo, una generale ed una più particolare. La simulazione con la strategia generale è stata applicata a tre differenti scenari reali, con le caratteristiche tecniche di tre veicoli realmente esistenti che vengono inserite nell'interfaccia grafica. I risultati provenienti da queste simulazioni sono stati poi analizzati e discussi nel dettaglio, anche con l'ausilio di grafici a supporto della spiegazione. La strategia di controllo particolare non è stata applicata a scenari reali ma ha portato alla definizione di una ipotetica architettura di powertrain ibrido, alla quale la sopracitata strategia si adatta al meglio. Dopo aver proposto miglioramenti e possibili ulteriori sviluppi di questo lavoro, sono state tratte le conclusioni generali, allargando il tutto al contesto più ampio in cui si va ad inserire.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

STATE OF CHARGE BASED DROOP SURFACE FOR OPTIMAL CONTROL OF DC MICROGRIDS

For a microgrid with a high penetration level of renewable energy, energy storage use becomes more integral to the system performance due to the stochastic nature of most renewable energy sources. This thesis examines the use of droop control of an energy storage source in dc microgrids in order to optimize a global cost function. The approach involves using a multidimensional surface to determine the optimal droop parameters based on load and state of charge. The optimal surface is determined using knowledge of the system architecture and can be implemented with fully decentralized source controllers. The optimal surface control of the system is presented. Derivations of a cost function along with the implementation of the optimal control are included. Results were verified using a hardware-in-the-loop system.

Determination of the thermal parameters of high-power batteries by local heat

A new approach to the determination of the thermal parameters of high-power batteries is introduced here. Application of local heat flux measurement with a gradient heat flux sensor (GHFS) allows determination of the cell thermal parameters in di_erent surface points of the cell. The suggested methodology is not cell destructive as it does not require deep discharge of the cell or application of any charge/discharge cycles during measurements of the thermal parameters of the cell. The complete procedure is demonstrated on a high-power Li-ion pouch cell, and it is verified on a sample with well-known thermal parameters. A comparison of the experimental results with conventional thermal characterization methods shows an acceptably low error. The dependence of the cell thermal parameters on state of charge (SoC) and measurement points on the surface was studied by the proposed measurement approach.

Impact of driver behaviour on availability of electric vehicle stored energy for STOR

As take up of low carbon vehicles increase, there is interest in using the energy stored in the vehicles to help maintain system frequency through ancillary services on the electricity grid system. Research into this area is generally classed as vehicle-to-grid research. In theory, the energy available from electric vehicles could be directly correlated to the vehicle's state of charge (SoC) and battery capacity during the time the car is parked and plugged in. However, not all the energy in the vehicle may be used, as some capacity is required by the driver for their next journey. As such, this paper uses data captured as part of a large scale electric vehicle trial to investigate the effect of three different types of driver routine on vehicle-to-grid availability. Each driver's behaviour is analysed to assess the energy that is available for STOR, with follow on journey requirements also considered.

Performance assessment of vehicular connectivity in hybrid electric vehicles for fuel and emissions reduction

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.

Desenvolvimento de um Posto de Carregamento Lento com BMS e Interface com o Cockpit para o CEPIUM

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

Carregamento ótimo de veículos elétricos considerando as restrições das redes de distribuição de média tensão

Pós-graduação em Engenharia Elétrica - FEIS

Modelagem do consumo de energia de redes de sensores sem fio usando SystemC-AMS e stateflow

This work aims at modeling power consumption at the nodes of a Wireless Sensor Network (WSN). For doing so, a finite state machine was implemented by means of SystemC-AMS and Stateflow modeling and simulation tools. In order to achieve this goal, communication data in a WSN were collected. Based on the collected data, a simulation environment for power consumption characterization, which aimed at describing the network operation, was developed. Other than performing power consumption simulation, this environment also takes into account a discharging model as to analyze the battery charge level at any given moment. Such analysis result in a graph illustrating the battery voltage variations as well as its state of charge (SOC). Finally, a case study of the WSN power consumption aims to analyze the acquisition mode and network data communication. With this analysis, it is possible make adjustments in node-sensors to reduce the total power consumption of the network.

Spectroscopic, structural, and functional characterization of the alternative low-spin state of horse heart cytochrome c

The alternative low-spin states of Fe3+ and Fe2+ cytochrome c induced by SDS or AOT/hexane reverse micelles exhibited the heme group in a less rhombic symmetry and were characterized by electron paramagnetic resonance, UV-visible, CD, magnetic CD, fluorescence, and Raman resonance. Consistent with the replacement of Met 80 by another strong field ligand at the sixth heme iron coordination position, Fe3+ ALSScytc exhibited 1-nm Soret band blue shift and e enhancement accompanied by disappearance of the 695-nm charge transfer band. The Raman resonance, CD, and magnetic CD spectra of Fe3+ and Fe2+ ALSScytc exhibited significant changes suggestive of alterations in the heme iron microenvironment and conformation and should not be assigned to unfold because the Trp(59) fluorescence remained quenched by the neighboring heme group. ALSScytc was obtained with His(33) and His(26) carboxyethoxylated horse cytochrome c and with tuna cytochrome c (His(33) replaced by Asn) pointing out Lys(79) as the probable heme iron ligand. Fe3+ ALSScytc retained the capacity to cleave tert-butylhydroperoxide and to be reduced by dithiothreitol and diphenylacetaldehyde but not by ascorbate. Compatible with a more open heme crevice, ALSScytc exhibited a redox potential similar to 200 mV lower than the wild-type protein (1220 mV) and was more susceptible to the attack of free radicals.

Effect of Charge Asymmetry on Adsorption and Phase Separation of Polyampholytes on Silica and Cellulose Surfaces

The relation between the properties of polyampholytes in aqueous solution and their adsorption behaviors on silica and cellulose surfaces was investigated. Four polyampholytes carrying different charge densities but with the same nominal ratio of positive to negative segments and two structurally similar polyelectrolytes (a polyacid and a polybase) were investigated by using quartz crystal microgravimetry using silica-coated and cellulose-coated quartz resonators. Time-resolved mass and rigidity (or viscoelasticity) of the adsorbed layer was determined from the shifts in frequency (Delta f) and energy dissipation (Delta D) of the respective resonator. Therefore, elucidation of the dynamics and extent of adsorption, as well as the conformational changes of the adsorbed macromolecules, were possible. The charge properties of the solid Surface played a crucial role in the adsorption of the studied polyampholytes, which was explained by the capability of the surface to polarize the polyampholyte at the interface. Under the same experimental conditions, the polyampholytes had a higher nominal charge density phase-separated near the interface, producing a soft, dissipative, and loosely bound layer. In the case of cellulose substrates, where adsorption was limited, electrostatic and polarization effects were concluded to be less significant.

Modulation of charge-density waves by superlattice structures

We discuss the interplay between electronic correlations and an underlying superlattice structure in determining the period of charge density waves (CDW's), by considering a one-dimensional Hubbard model with a repeated (nonrandom) pattern of repulsive (U > 0) and free (U=0) sites. Density matrix renormalization group diagonalization of finite systems (up to 120 sites) is used to calculate the charge-density correlation function and structure factor in the ground state. The modulation period can still be predicted through effective Fermi wave vectors k(F)(*) and densities, and we have found that it is much more sensitive to electron (or hole) doping, both because of the narrow range of densities needed to go from q(*)=0 to pi, but also due to sharp 2k(F)(*)-4k(F)(*) transitions; these features render CDW's more versatile for actual applications in heterostructures than in homogeneous systems.