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Fernanda Cristina Corrêa

Universidade Tecnológica Federal do Paraná

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Jony Javorski Eckert

Universidade Estadual de Campinas (UNICAMP)

Franco Giuseppe Dedini

Universidade Estadual de Campinas (UNICAMP)

Ludmila C. A. Silva

Universidade Estadual de Campinas (UNICAMP)

Fabio Mazzariol Santiciolli

Instituto Superior Politécnico Gaya

Hugo Valadares Siqueira

Universidade Tecnológica Federal do Paraná

Joelton Deonei Gotz

Universidade Tecnológica Federal do Paraná

Milton Borsato

Universidade Tecnológica Federal do Paraná

Eduardo dos Santos Costa

Universidade Estadual de Campinas (UNICAMP)

José Rodolfo Galvão

Universidade Tecnológica Federal do Paraná

Emilson Ribeiro Viana

Universidade Tecnológica Federal do Paraná

Cooperative Institutions

Universidade Tecnológica Federal do Paraná

Universidade Estadual de Ponta Grossa

Universidade Estadual de Campinas (UNICAMP)

Universidade Federal do Paraná

Universidade Estadual Paulista (Unesp)

Universidade Federal de Goiás

Universidade Federal de Santa Catarina

Hospital Israelita Albert Einstein

University of Minho

Universidade de São Paulo

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Random Forest-Based Grouping for Accurate SOH Estimation in Second-Life Batteries

Vehicles (2024)

Joelton Deonei Gotz José Rodolfo Galvão Fernanda Cristina Corrêa Alceu André Badin Hugo Valadares Siqueira

Retired batteries pose a significant current and future challenge for electric mobility due to their high cost and the need for a state of health (SOH) above 80% to supply energy efficiently. Recycling and alternative applications are the primary options for these batteries, with recycling still undergoing research as regards more efficient and cost-effective techniques. While advancements have been made, researchers are actively seeking improved methods. Repurposing retired batteries for lower-performance applications like stationary systems or low-speed vehicles is recommended. Second-life batteries (SLB) can be directly reused or reconstructed, with the latter involving the disassembly, measurement, and separation of cells based on their characteristics. The traditional measurement process, involving full charge and discharge cycles, is time-consuming. To address this, a Machine Learning (ML)-based SOH estimator is introduced in this work, offering the instant measurement and estimation of battery health without complete discharge. The results indicate that the model can accurately identify SOH within a nominal capacity range of 1400–2300 mAh, with a resolution near 45.70 mAh, in under five minutes of discharging. This innovative technique could be instrumental in selecting and assembling SLB packs.

State of health

Battery capacity

Repurposing

10.3390/vehicles6020038

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Citations (4)

Metaheuristics-Based Optimization of a Robust GAPID Adaptive Control Applied to a DC Motor-Driven Rotating Beam with Variable Load

Fábio Galvão Borges Márcio Guerreiro Paulo Eduardo Sampaio Sampaio Monteiro Frederic Conrad Janzen Fernanda Cristina Corrêa

This work aims to analyze two metaheuristics optimization techniques, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), with six variations each, and compare them regarding their convergence, quality, and dispersion of solutions. The optimization target is the Gaussian Adaptive PID control (GAPID) to find the best parameters to achieve enhanced performance and robustness to load variations related to the traditional PID. The adaptive rule of GAPID is based on a Gaussian function that has as adjustment parameters its concavity and the lower and upper bound of the gains. It is a smooth function with smooth derivatives. As a result, it helps avoid problems related to abrupt increases transition, commonly found in other adaptive methods. Because there is no mathematical methodology to set these parameters, this work used bio-inspired optimization algorithms. The test plant is a DC motor with a beam with a variable load. Results obtained by load and gain sweep tests prove the GAPID presents fast responses with very low overshoot and good robustness to load changes, with minimal variations, which is impossible to achieve when using the linear PID.

Robustness

Overshoot (microwave communication)

10.3390/s22166094

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Citations (3)

Intelligent Management for Second-Life Lithium-Ion Batteries with Backup Cells

Lecture notes in mechanical engineering (2023)

Joelton Deonei Gotz José Rodolfo Galvão Alexandre Moura da Silveira Emilson Ribeiro Viana Fernanda Cristina Corrêa

Energy density

10.1007/978-3-031-38165-2_116

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Citations (1)

Vehicle gear shifting strategy optimization with respect to performance and fuel consumption

Mechanics Based Design of Structures and Machines (2015)

Jony Javorski Eckert Fernanda Cristina Corrêa Fabio Mazzariol Santiciolli Eduardo dos Santos Costa Heron José Dionísio

Based on the movement resistance forces, the vehicle longitudinal dynamics is related to power demand for a specific route. The vehicle gear shifting influences significantly the acceleration performance and fuel consumption because it changes the engine operation point and the powertrain inertia. This paper presents a study based on the US06 velocity profile that involves high speed and high acceleration phases, where the vehicle performance is limited by both the engine power and the tire traction limit. For improving the vehicle performance without increasing fuel consumption, a genetic algorithm (GA) technique is used.

Powertrain

Engine power

Vehicle engineering

10.1080/15397734.2015.1094669

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Citations (37)

A random forest mechanism to identify the initial conditions of external short circuits in 18650 lithium-ion batteries

Joelton Deonei Gotz José Rodolfo Galvão Emilson Ribeiro Viana Milton Borsato Fernanda Cristina Corrêa

10.1007/s11581-025-06122-6

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Comparative Study of Intelligent and Classical MPPT Techniques Applied to Solar Battery Charger

Mario Henrique Bigai Larissa Freitas Matheus de Paula Eloi Agostini Fernanda Cristina Corrêa

Renewable solar energy is an excellent alternative to conventional energy sources and, recently, it has shown remarkable growth on electrical power grid in various countries around the world. Maximum power point tracking (MPPT) has critical importance in solar energy generation since it increases the system's efficiency in many scenarios. Photovoltaic modules (PV) are influenced by environmental factors such as temperature and solar irradiation density, changing the amount of energy generated throughout the day. In order to extract the maximum available power from a PV, its necessary to use the MPPT technique, which considers the systems nonlinearities. Maximum power tracking (MPP) is done by tuning the duty cycle of the DC-DC converter, so that the PV's terminal voltage is modulated to match the environmental conditions. This tuning, generally, is dependent on sensor readings. Normally, only the modules voltage and current sensors are used, due to the low cost and ease of acquisition of these signals. However, intelligent techniques demand the usage of temperature and irradiation sensors, increasing the complexity of the systems implementation. The use of intelligent control techniques applied to the energy generation system has had a notable presence in recent publications. The high efficiency obtained from its application demonstrates that the use of intelligent systems in the decision-making process is a useful tool in obtaining maximum generation power. The objective of the present study is the development and simulation via MATLAB/SIMULINK of a battery charging system with solar energy, which consists of a PV, a Buck converter, a 12V battery, and the MPPT controller. The intelligent fuzzy logic MPPT technique (FLS) and the classical incremental conductance technique (INC) will be compared, both techniques using only voltage and current measurements.

Duty cycle

Maximum power principle

Solar micro-inverter

10.55592/cilamce.v6i06.10180

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AN INFLUENCE STUDY OF PARALLEL HYBRID VEHICLE PROPULSION SYSTEM CONFIGURATIONS

Jony Javorski Eckert Fernanda Cristina Corrêa Fabio Mazzariol Santiciolli Eduardo dos Santos Costa Heron José Dionísio

The hybrid electric vehicle (HEV) became an alternative to reduce the fuel consumption. The HEV parallel configuration consists of two separated drive systems, such as the engine/powertrain system and an extra electric motors (EMs) system. The addition of an extra electrical power changes the engine operation point and consequently the fuel consumption. However, there are many ways to introduce this electrical power source as a secondary drive system. In this paper, two parallel HEV configurations are studied in a condition where the conventional engine/powertrain system, coupled to the vehicle front wheels, is the main power source and two different configurations of EMs drive system, coupled to the rear wheels, are auxiliary power sources. The first one consists of two in-wheel motors coupled directly to the vehicle rear wheels and the other one is an EM coupled to a differential system similar to the existent in the conventional vehicle powertrain. The aim of this paper is to simulate and compare the HEV behavior with the conventional vehicle behavior, both of them running in the Brazilian urban drive cycle NBR6601, evaluating differences in performance, fuel consumption and battery discharging when applicable.

Powertrain

Hybrid vehicle

Driving cycle

Battery electric vehicle

Hybrid power

Engine power

10.5151/engpro-simea2015-pap130

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Citations (2)

A Sub-Orbital Platform for Flight Tests of Small Space Capsules

IAF abstracts, 34th COSPAR Scientific Assembly (2002)

P. Moraes A. L. Pereira C. R. Silva D. J. Villas Bôas Fernanda Cristina Corrêa J. H. Miyoshi

Orbital mechanics

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Citations (0)

Scientific Production in Sustainable Supply Chains

Mauro Lizot Flávio Trojan Hugo Valadares Siqueira Fernanda Cristina Corrêa Paulo Afonso

Researchers need to know the trends of specific themes and how the main methods are applied to solve the existing gaps.The objective of this research is to apply a structured methodology to select articles of high scientific relevance in the area of sustainable supply chain.In methodological terms, bibliographical research was carried out, which followed several steps, such as: filtering of journals with stratum Q1, database selection, choice of keywords; reading of titles and abstracts; classification of the number of citations; full critical reading of all articles in the bibliographic portfolio.With regard to research results, it was possible to identify through the frequency analysis, the types of study found in the portfolio articles; sustainable supply chain aspects; and the percentage of journals in the bibliographic portfolio, with their respective JCRs with a high impact factor.In addition to an extensive systemic analysis, which allowed identifying research opportunities.

10.46254/eu6.20230351

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Retroactive Control Applied to a BLDC Motor

Mechanisms and machine science (2021)

Carlos da Conceição Castilho Neto Lenon Diniz Seixas Fernanda Cristina Corrêa

10.1007/978-3-030-60694-7_15

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