A Sizing Procedure for the DC-Side Capacitor of a Three-Phase Modular Multilevel Converter

The integration of photovoltaic (PV) modules with a modular multilevel converter (MMC) is very interesting because it allows us to exploit the intrinsic advantages of that converter, such as modularity and high voltage quality, and to implement distributed maximum power point tracking algorithms. The latter can appropriately be performed through controlling the circulating currents. In the literature, some control strategies for both the AC and DC circulating currents were proposed to manage the power mismatch among the legs and between the arms of the MMC. In a previous work, the authors proposed a novel control strategy for the circulating current components and inserted a capacitor on the DC side of a three-phase MMC with integrated PV panels. In the present work, it is shown how the correct sizing of this capacitor is essential to optimize the AC circulating voltages and minimize converter losses. A sizing procedure is proposed, deeply analyzed, and validated through numerical simulations

simple control strategy for a pv battery system

Nowadays, energy storage systems, such as batteries, are spreading in many applications. Among the kinds of batteries, the lithium-ion technology is one of the most promising solutions. Considering the photovoltaic (PV) plants, it is very important to perform a correct sizing of the battery pack to both maximise the self-consumption and minimise the total costs. In general, PV plants need a dc–dc converter to maximise the electric power that can be extracted from PV panels and a dc–ac converter to connect them to the ac grid. The battery pack can be connected in three different ways: dc coupled and ac coupled using a dedicated converter or through a direct connection on the dc-link between the dc–dc and dc–ac converters. In the present study, the last solution, without any dedicated converters, is used and a simple control strategy to both maximise the power extracted from the PV panel and regulate the charging/discharging of the battery is proposed

Unified model of lithium-ion battery and electrochemical storage system

Nowadays, energy storage systems are of paramount importance in sectors such as renewable energy production and sustainable mobility because of the energy crisis and climate change issues. Although there are various types of energy storage systems, electrochemical devices such as electric double layer capacitors (EDLCs), lithium-ion capacitors (LiCs), and lithium-ion batteries (LiBs) are the most common because of their high efficiency and flexibility. In particular, LiBs are broadly employed in many applications and preferred in the mobility sector, where there is a need for high energy and high power. To ensure good operating conditions for a battery and limit its degradation, it is important to have a precise model of the device. The literature contains numerous equivalent circuit models capable of predicting the electrical behavior of an LiB in the time or frequency domain. In most of them, the battery impedance is in series with a voltage source modeling the open circuit voltage of the battery for simulation in the time domain. This study demonstrated that an extension of a model composed exclusively of passive elements from the literature for EDLCs and LiCs would also be suitable for LiBs, resulting in a unified model for these types of electrochemical storage systems. This model uses the finite space Warburg impedance, which, in addition to the diffusion process of lithium\lithium ions in the electrodes\electrolyte, makes it possible to consider the main capacitance of the battery. Finally, experimental tests were performed to validate the proposed model

Calendar Aging Effect on the Open Circuit Voltage of Lithium-Ion Battery

In recent years, lithium-ion batteries (LiBs) have gained a lot of importance due to the increasing use of renewable energy sources and electric vehicles. To ensure that batteries work properly and limit their degradation, the battery management system needs accurate battery models capable of precisely predicting their parameters. Among them, the state of charge (SOC) estimation is one of the most important, as it enables the prediction of the battery's available energy and prevents it from operating beyond its safety limits. A common method for SOC estimation involves utilizing the relationship between the state of charge and the open circuit voltage (OCV). On the other hand, the latter changes with battery aging. In a previous work, the authors studied a simple function to model the OCV curve, which was expressed as a function of the absolute state of discharge, q, instead of SOC. They also analyzed how the parameters of such a curve changed with the cycle aging. In the present work, a similar analysis was carried out considering the calendar aging effect. Three different LiB cells were stored at three different SOC levels (low, medium, and high levels) for around 1000 days, and an analysis of the change in the OCV-q curve model parameters with the calendar aging was performed

Lithium ion battery models and parameter identification techniques

Nowadays, battery storage systems are very important in both stationary and mobile applications. In particular, lithium ion batteries are a good and promising solution because of their high power and energy densities. The modeling of these devices is very crucial to correctly predict their state of charge (SoC) and state of health (SoH). The literature shows that numerous battery models and parameters estimation techniques have been developed and proposed. Moreover, surveys on their electric, thermal, and aging modeling are also reported. This paper presents a more complete overview of the different proposed battery models and estimation techniques. In particular, a method for classifying the proposed models based on their approaches is proposed. For this classification, the models are divided in three categories: mathematical models, physical models, and circuit models

Windowed PWM: a Configurable Modulation Scheme for Modular Multilevel Converter Based Traction Drives

This article introduces a modulation technique for modular multilevel converter (MMC) in variable speed traction drives for electrical transportation referred as windowed pulsewidth modulation (W-PWM). The windowed PWM (W-PWM) is derived by blending the principles of operation of conventional modulation schemes for MMC based on the nearest level control (NLC) and on PWM with the aim of combining their inherent strengths and offering a higher degree of flexibility. This can reduce switching losses compared to classical PWM schemes and lower the current harmonic distortion compared to NLC schemes. The window in which the PWM is applied can be seen as an additional degree of freedom that allows a dynamic optimization of the performance of the traction drive depending on its operating characteristics. The performance of the W-PWM technique is assessed in this article for several operating conditions and compared with conventional schemes based on NLC and on the phase opposition disposition PWM with both numerical simulation and experimental verification on a small-scale prototype. Results demonstrate the flexibility of the W-PWM and its potential for applications in electrical traction drives. © 1986-2012 IEEE.acceptedVersio

LCA of a Proton Exchange Membrane Fuel Cell Electric Vehicle Considering Different Power System Architectures

Fuel cell electric vehicles are a promising solution for reducing the environmental impacts of the automotive sector; however, there are still some key points to address in finding the most efficient and less impactful implementation of this technology. In this work, three electrical architectures of fuel cell electric vehicles were modeled and compared in terms of the environmental impacts of their manufacturing and use phases. The three architectures differ in terms of the number and position of the DC/DC converters connecting the battery and the fuel cell to the electric motor. The life cycle assessment methodology was employed to compute and compare the impacts of the three vehicles. A model of the production of the main components of vehicles and fuel cell stacks, as well as of the production of hydrogen fuel, was constructed, and the impacts were calculated using the program SimaPro. Eleven impact categories were considered when adopting the ReCiPe 2016 midpoint method, and the EF (adapted) method was exploited for a final comparison. The results highlighted the importance of the converters and their influence on fuel consumption, which was identified as the main factor in the comparison of the environmental impacts of the vehicle

Analysis, Design and Experimental Validation of Modified Simple Soft Switching DC-DC Boost Converter

This paper investigates a modified simple soft switching dc-dc converter for low power applications. This simple topology uses an auxiliary switch, an inductor and a capacitor to operate the converter without switching losses. The efficiency of the converter is improved by transferring the energy that would be dissipated during the switching to the load. The main switch turns-on with zero current switching (ZCS) and turns-off with zero voltage switching (ZVS), while the auxiliary switch turns-on and turns-off with zero voltage switching (ZVS). The detailed theoretical analysis and the design equations are described. In addition to that, the analysis of proposed converter is demonstrated by both simulation and experimental results for effectiveness of the study.Web of Science16433733

Social Cognition Individualized Activities Lab for Social Cognition Training and Narrative Enhancement in Patients With Schizophrenia: A Randomized Controlled Study to Assess Efficacy and Generalization to Real-Life Functioning (Prot. n°: NCT05130853)

Subjects affected by schizophrenia present significant deficits in various aspects of social cognition, such as emotion processing, social perception and theory of mind (ToM). These deficits have a greater impact than symptoms on occupational and social functioning. Therefore, social cognition represents an important therapeutic target in people with schizophrenia. Recent meta-analyses showed that social cognition training (SCT) is effective in improving social cognition in subjects with schizophrenia; however, real-life functioning is not always ameliorated. Integration of SCT with an intervention targeting metacognitive abilities might improve the integration of social cognitive skills to daily life functioning. Our research group has implemented a new individualized rehabilitation program: the Social Cognition Individualized Activities Lab, SoCIAL, which integrates SCT with a module for narrative enhancement, an intervention targeting metacognitive abilities. The present multi-center randomized controlled study will compare the efficacy of SoCIAL and treatment as usual (TAU) in subjects diagnosed with a schizophrenia-spectrum disorder. The primary outcome will be the improvement of social cognition and real-life functioning; while the secondary outcome will be the improvement of symptoms, functional capacity and neurocognition. The results of this study will add empirical evidence to the benefits and feasibility of SCT and narrative enhancement in people with schizophrenia-spectrum disorders