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Author

Federico Baronti

Bio: Federico Baronti is an academic researcher from University of Pisa. The author has contributed to research in topics: Battery (electricity) & State of charge. The author has an hindex of 22, co-authored 123 publications receiving 2297 citations.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a battery management system (BMS) for the smart grid and electric vehicles (EVs) has been proposed to improve the performance of Li-ion batteries.
Abstract: With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.

721 citations

Journal ArticleDOI
TL;DR: The moving window least squares parameter-identification technique was validated by both data obtained from a simulated battery model and experimental data and the necessity of updating the parameters is evaluated using observers with updating and nonupdating parameters.
Abstract: Real-time estimation of the state of charge (SOC) of the battery is a crucial need in the growing fields of plug-in hybrid electric vehicles and smart grid applications. The accuracy of the estimation algorithm directly depends on the accuracy of the model used to describe the characteristics of the battery. Considering a resistance-capacitance (RC)-equivalent circuit to model the battery dynamics, we use a piecewise linear approximation with varying coefficients to describe the inherently nonlinear relationship between the open-circuit voltage (VOC) and the SOC of the battery. Several experimental test results on lithium (Li)-polymer batteries show that not only do the VOC-SOC relationship coefficients vary with the SOC and charging/discharging rates but also the RC parameters vary with them as well. The moving window least squares parameter-identification technique was validated by both data obtained from a simulated battery model and experimental data. The necessity of updating the parameters is evaluated using observers with updating and nonupdating parameters. Finally, the SOC coestimation method is compared with the existing well-known SOC estimation approaches in terms of performance and accuracy of estimation.

337 citations

Journal ArticleDOI
TL;DR: In this paper, a simple but effective analysis to calculate the performances achievable by a balancing circuit for series-connected lithium-ion batteries (i.e., the time required to equalise the battery and the energy lost during this process) is described.

156 citations

Proceedings ArticleDOI
12 Mar 2012
TL;DR: A general and flexible architecture for battery management implementation and the main techniques for state-of-charge estimation and charge balancing are reported and an innovative BMS is described, which incorporates an almost fully-integrated active charge equalizer.
Abstract: The battery is a fundamental component of electric vehicles, which represent a step forward towards sustainable mobility. Lithium chemistry is now acknowledged as the technology of choice for energy storage in electric vehicles. However, several research points are still open. They include the best choice of the cell materials and the development of electronic circuits and algorithms for a more effective battery utilization. This paper initially reviews the most interesting modeling approaches for predicting the battery performance and discusses the demanding requirements and standards that apply to ICs and systems for battery management. Then, a general and flexible architecture for battery management implementation and the main techniques for state-of-charge estimation and charge balancing are reported. Finally, we describe the design and implementation of an innovative BMS, which incorporates an almost fully-integrated active charge equalizer.

148 citations

Journal ArticleDOI
TL;DR: An innovative lithium-battery cell-to-cell active equalizer capable of moving charge between series-connected cells using a super-capacitor as an energy tank and its very high efficiency, which is over 90%.
Abstract: The charge stored in series-connected lithium batteries needs to be well equalized between the elements of the series. We present here an innovative lithium-battery cell-to-cell active equalizer capable of moving charge between series-connected cells using a super-capacitor as an energy tank. The system temporarily stores the charge drawn from a cell in the super-capacitor, then the charge is moved into another cell without wasting energy as it happens in passive equalization. The architecture of the system which employs a digitally-controlled switching converter is compared with the state of the art, then fully investigated, together with the methodology used in its design. The performance of the system is described by presenting and discussing the experimental results of laboratory tests. The most innovative and attractive aspect of the proposed system is its very high efficiency, which is over 90%.

108 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, a battery management system (BMS) for the smart grid and electric vehicles (EVs) has been proposed to improve the performance of Li-ion batteries.
Abstract: With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.

721 citations

Journal ArticleDOI
TL;DR: In this paper, the authors comprehensively review technologies of ESSs, its classifications, characteristics, constructions, electricity conversion, and evaluation processes with advantages and disadvantages for EV applications.
Abstract: The electric vehicle (EV) technology addresses the issue of the reduction of carbon and greenhouse gas emissions. The concept of EVs focuses on the utilization of alternative energy resources. However, EV systems currently face challenges in energy storage systems (ESSs) with regard to their safety, size, cost, and overall management issues. In addition, hybridization of ESSs with advanced power electronic technologies has a significant influence on optimal power utilization to lead advanced EV technologies. This paper comprehensively reviews technologies of ESSs, its classifications, characteristics, constructions, electricity conversion, and evaluation processes with advantages and disadvantages for EV applications. Moreover, this paper discusses various classifications of ESS according to their energy formations, composition materials, and techniques on average power delivery over its capacity and overall efficiencies exhibited within their life expectancies. The rigorous review indicates that existing technologies for ESS can be used for EVs, but the optimum use of ESSs for efficient EV energy storage applications has not yet been achieved. This review highlights many factors, challenges, and problems for sustainable development of ESS technologies in next-generation EV applications. Thus, this review will widen the effort toward the development of economic and efficient ESSs with a longer lifetime for future EV uses.

614 citations

Journal ArticleDOI
TL;DR: In this paper, the authors reviewed and discussed various battery modelling approaches, including mathematical models, electrochemical models and electrical equivalent circuit models, and concluded that the state-of-the-art in battery modelling is not sufficient for this chemistry, and new modelling approaches are needed.
Abstract: Accurate prediction of range of an electric vehicle (EV) is a significant issue and a key market qualifier. EV range forecasting can be made practicable through the application of advanced modelling and estimation techniques. Battery modelling and state-of-charge estimation methods play a vital role in this area. In addition, battery modelling is essential for safe charging/discharging and optimal usage of batteries. Much existing work has been carried out on incumbent Lithium-ion (Li-ion) technologies, but these are reaching their theoretical limits and modern research is also exploring promising next-generation technologies such as Lithium–Sulphur (Li–S). This study reviews and discusses various battery modelling approaches including mathematical models, electrochemical models and electrical equivalent circuit models. After a general survey, the study explores the specific application of battery models in EV battery management systems, where models may have low fidelity to be fast enough to run in real-time applications. Two main categories are considered: reduced-order electrochemical models and equivalent circuit models. The particular challenges associated with Li–S batteries are explored, and it is concluded that the state-of-the-art in battery modelling is not sufficient for this chemistry, and new modelling approaches are needed.

541 citations

Journal ArticleDOI
TL;DR: In this article, the effects of temperature on the battery performance from three aspects: low temperature, high temperature and differential temperature are discussed with the main emphasis on battery modeling methods and thermal management strategies.

517 citations

Journal ArticleDOI
TL;DR: In this article, a systematic review of the most commonly used battery modeling and state estimation approaches for BMSs is presented, including the physics-based electrochemical models, the integral and fractional order equivalent circuit models, and data-driven models.
Abstract: With the rapid development of new energy electric vehicles and smart grids, the demand for batteries is increasing. The battery management system (BMS) plays a crucial role in the battery-powered energy storage system. This paper presents a systematic review of the most commonly used battery modeling and state estimation approaches for BMSs. The models include the physics-based electrochemical models, the integral and fractional order equivalent circuit models, and data-driven models. The state estimation approaches are analyzed from the perspectives of remaining capacity and energy estimation, power capability prediction, lifespan and health prognoses, and other crucial indexes in BMS. This present paper, through the analysis of literature, includes almost all states in the BMS. The estimation approaches of state-of-charge (SOC), state-of-energy (SOE), state-of-power (SOP), state-of-function (SOF), state-of-health (SOH), remaining useful life (RUL), remaining discharge time (RDT), state-of-balance (SOB), and state-of-temperature (SOT) are reviewed and discussed in a systematical way. Moreover, the challenges and outlooks of the research on future battery management are disclosed, in the hope of providing some inspirations to the development and design of the next-generation BMSs.

494 citations